National Library of Energy BETA

Sample records for model based predictive

  1. An approach to model validation and model-based prediction -- polyurethane foam case study.

    SciTech Connect (OSTI)

    Dowding, Kevin J.; Rutherford, Brian Milne

    2003-07-01

    Enhanced software methodology and improved computing hardware have advanced the state of simulation technology to a point where large physics-based codes can be a major contributor in many systems analyses. This shift toward the use of computational methods has brought with it new research challenges in a number of areas including characterization of uncertainty, model validation, and the analysis of computer output. It is these challenges that have motivated the work described in this report. Approaches to and methods for model validation and (model-based) prediction have been developed recently in the engineering, mathematics and statistical literatures. In this report we have provided a fairly detailed account of one approach to model validation and prediction applied to an analysis investigating thermal decomposition of polyurethane foam. A model simulates the evolution of the foam in a high temperature environment as it transforms from a solid to a gas phase. The available modeling and experimental results serve as data for a case study focusing our model validation and prediction developmental efforts on this specific thermal application. We discuss several elements of the ''philosophy'' behind the validation and prediction approach: (1) We view the validation process as an activity applying to the use of a specific computational model for a specific application. We do acknowledge, however, that an important part of the overall development of a computational simulation initiative is the feedback provided to model developers and analysts associated with the application. (2) We utilize information obtained for the calibration of model parameters to estimate the parameters and quantify uncertainty in the estimates. We rely, however, on validation data (or data from similar analyses) to measure the variability that contributes to the uncertainty in predictions for specific systems or units (unit-to-unit variability). (3) We perform statistical analyses and

  2. QMC Simulations DataBase for Predictive Theory and Modeling | Argonne

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Leadership Computing Facility CO monoxide adsorbs on the Pt (111) surface CO monoxide adsorbs on the Pt (111) surface. One application of the QMC Simulations Database for the Predictive Modeling and Theory project is to model this important surface reaction which is poorly modeled by methods with static treatment of electron-electron interaction. Credit: William Parker, ALCF QMC Simulations DataBase for Predictive Theory and Modeling PI Name: David Ceperley PI Email: ceperley@illinois.ed

  3. Simulation of complex glazing products; from optical data measurements to model based predictive controls

    SciTech Connect (OSTI)

    Kohler, Christian

    2012-08-01

    Complex glazing systems such as venetian blinds, fritted glass and woven shades require more detailed optical and thermal input data for their components than specular non light-redirecting glazing systems. Various methods for measuring these data sets are described in this paper. These data sets are used in multiple simulation tools to model the thermal and optical properties of complex glazing systems. The output from these tools can be used to generate simplified rating values or as an input to other simulation tools such as whole building annual energy programs, or lighting analysis tools. I also describe some of the challenges of creating a rating system for these products and which factors affect this rating. A potential future direction of simulation and building operations is model based predictive controls, where detailed computer models are run in real-time, receiving data for an actual building and providing control input to building elements such as shades.

  4. Battery Life Predictive Model

    Energy Science and Technology Software Center (OSTI)

    2009-12-31

    The Software consists of a model used to predict battery capacity fade and resistance growth for arbitrary cycling and temperature profiles. It allows the user to extrapolate from experimental data to predict actual life cycle.

  5. In silico prediction of toxicity of non-congeneric industrial chemicals using ensemble learning based modeling approaches

    SciTech Connect (OSTI)

    Singh, Kunwar P. Gupta, Shikha

    2014-03-15

    Ensemble learning approach based decision treeboost (DTB) and decision tree forest (DTF) models are introduced in order to establish quantitative structuretoxicity relationship (QSTR) for the prediction of toxicity of 1450 diverse chemicals. Eight non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals was evaluated using Tanimoto similarity index. Stochastic gradient boosting and bagging algorithms supplemented DTB and DTF models were constructed for classification and function optimization problems using the toxicity end-point in T. pyriformis. Special attention was drawn to prediction ability and robustness of the models, investigated both in external and 10-fold cross validation processes. In complete data, optimal DTB and DTF models rendered accuracies of 98.90%, 98.83% in two-category and 98.14%, 98.14% in four-category toxicity classifications. Both the models further yielded classification accuracies of 100% in external toxicity data of T. pyriformis. The constructed regression models (DTB and DTF) using five descriptors yielded correlation coefficients (R{sup 2}) of 0.945, 0.944 between the measured and predicted toxicities with mean squared errors (MSEs) of 0.059, and 0.064 in complete T. pyriformis data. The T. pyriformis regression models (DTB and DTF) applied to the external toxicity data sets yielded R{sup 2} and MSE values of 0.637, 0.655; 0.534, 0.507 (marine bacteria) and 0.741, 0.691; 0.155, 0.173 (algae). The results suggest for wide applicability of the inter-species models in predicting toxicity of new chemicals for regulatory purposes. These approaches provide useful strategy and robust tools in the screening of ecotoxicological risk or environmental hazard potential of chemicals. - Graphical abstract: Importance of input variables in DTB and DTF classification models for (a) two-category, and (b) four-category toxicity intervals in T. pyriformis data. Generalization and predictive abilities of the

  6. A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory.

    SciTech Connect (OSTI)

    Johnson, J. D.; Oberkampf, William Louis; Helton, Jon Craig (Arizona State University, Tempe, AZ); Storlie, Curtis B. (North Carolina State University, Raleigh, NC)

    2006-10-01

    Evidence theory provides an alternative to probability theory for the representation of epistemic uncertainty in model predictions that derives from epistemic uncertainty in model inputs, where the descriptor epistemic is used to indicate uncertainty that derives from a lack of knowledge with respect to the appropriate values to use for various inputs to the model. The potential benefit, and hence appeal, of evidence theory is that it allows a less restrictive specification of uncertainty than is possible within the axiomatic structure on which probability theory is based. Unfortunately, the propagation of an evidence theory representation for uncertainty through a model is more computationally demanding than the propagation of a probabilistic representation for uncertainty, with this difficulty constituting a serious obstacle to the use of evidence theory in the representation of uncertainty in predictions obtained from computationally intensive models. This presentation describes and illustrates a sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory. Preliminary trials indicate that the presented strategy can be used to propagate uncertainty representations based on evidence theory in analysis situations where naive sampling-based (i.e., unsophisticated Monte Carlo) procedures are impracticable due to computational cost.

  7. Model Predictive Control-based Optimal Coordination of Distributed Energy Resources

    SciTech Connect (OSTI)

    Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming; Elizondo, Marcelo A.

    2013-01-07

    Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive control (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.

  8. Model Predictive Control-based Optimal Coordination of Distributed Energy Resources

    SciTech Connect (OSTI)

    Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming; Elizondo, Marcelo A.

    2013-04-03

    Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive control (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.

  9. Prediction of Lumen Output and Chromaticity Shift in LEDs Using Kalman Filter and Extended Kalman Filter Based Models

    SciTech Connect (OSTI)

    Lall, Pradeep; Wei, Junchao; Davis, J Lynn

    2014-06-24

    Abstract— Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based models have

  10. Midtemperature solar systems test facility predictions for thermal performance based on test data. Polisolar Model POL solar collector with glass reflector surface

    SciTech Connect (OSTI)

    Harrison, T.D.

    1981-05-01

    Thermal performance predictions based on test data are presented for the Polisolar Model POL solar collector, with glass reflector surfaces, for three output temperatures at five cities in the United States.

  11. SIMPLIFIED PREDICTIVE MODELS FOR CO₂ SEQUESTRATION PERFORMANCE ASSESSMENT RESEARCH TOPICAL REPORT ON TASK #3 STATISTICAL LEARNING BASED MODELS

    SciTech Connect (OSTI)

    Mishra, Srikanta; Schuetter, Jared

    2014-11-01

    We compare two approaches for building a statistical proxy model (metamodel) for CO₂ geologic sequestration from the results of full-physics compositional simulations. The first approach involves a classical Box-Behnken or Augmented Pairs experimental design with a quadratic polynomial response surface. The second approach used a space-filling maxmin Latin Hypercube sampling or maximum entropy design with the choice of five different meta-modeling techniques: quadratic polynomial, kriging with constant and quadratic trend terms, multivariate adaptive regression spline (MARS) and additivity and variance stabilization (AVAS). Simulations results for CO₂ injection into a reservoir-caprock system with 9 design variables (and 97 samples) were used to generate the data for developing the proxy models. The fitted models were validated with using an independent data set and a cross-validation approach for three different performance metrics: total storage efficiency, CO₂ plume radius and average reservoir pressure. The Box-Behnken–quadratic polynomial metamodel performed the best, followed closely by the maximin LHS–kriging metamodel.

  12. Elevated carbon dioxide is predicted to promote coexistence among competing species in a trait-based model

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Ali, Ashehad A.; Medlyn, Belinda E.; Aubier, Thomas G.; Crous, Kristine Y.; Reich, Peter B.

    2015-10-06

    Differential species responses to atmospheric CO2 concentration (Ca) could lead to quantitative changes in competition among species and community composition, with flow-on effects for ecosystem function. However, there has been little theoretical analysis of how elevated Ca (eCa) will affect plant competition, or how composition of plant communities might change. Such theoretical analysis is needed for developing testable hypotheses to frame experimental research. Here, we investigated theoretically how plant competition might change under eCa by implementing two alternative competition theories, resource use theory and resource capture theory, in a plant carbon and nitrogen cycling model. The model makes several novelmore » predictions for the impact of eCa on plant community composition. Using resource use theory, the model predicts that eCa is unlikely to change species dominance in competition, but is likely to increase coexistence among species. Using resource capture theory, the model predicts that eCa may increase community evenness. Collectively, both theories suggest that eCa will favor coexistence and hence that species diversity should increase with eCa. Our theoretical analysis leads to a novel hypothesis for the impact of eCa on plant community composition. In this study, the hypothesis has potential to help guide the design and interpretation of eCa experiments.« less

  13. predictive modeling | National Nuclear Security Administration

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Apply for Our Jobs Our Jobs Working at NNSA Blog Home predictive modeling predictive modeling Fukushima: Five Years Later After the March 11, 2011, Japan earthquake, tsunami, and ...

  14. Elevated carbon dioxide is predicted to promote coexistence among competing species in a trait-based model

    SciTech Connect (OSTI)

    Ali, Ashehad A.; Medlyn, Belinda E.; Aubier, Thomas G.; Crous, Kristine Y.; Reich, Peter B.

    2015-10-06

    Differential species responses to atmospheric CO2 concentration (Ca) could lead to quantitative changes in competition among species and community composition, with flow-on effects for ecosystem function. However, there has been little theoretical analysis of how elevated Ca (eCa) will affect plant competition, or how composition of plant communities might change. Such theoretical analysis is needed for developing testable hypotheses to frame experimental research. Here, we investigated theoretically how plant competition might change under eCa by implementing two alternative competition theories, resource use theory and resource capture theory, in a plant carbon and nitrogen cycling model. The model makes several novel predictions for the impact of eCa on plant community composition. Using resource use theory, the model predicts that eCa is unlikely to change species dominance in competition, but is likely to increase coexistence among species. Using resource capture theory, the model predicts that eCa may increase community evenness. Collectively, both theories suggest that eCa will favor coexistence and hence that species diversity should increase with eCa. Our theoretical analysis leads to a novel hypothesis for the impact of eCa on plant community composition. In this study, the hypothesis has potential to help guide the design and interpretation of eCa experiments.

  15. predictive-models | netl.doe.gov

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    predictive-models DOE/BC-88/1/SP. EOR Predictive Models: Handbook for Personal Computer Versions of Enhanced Oil Recovery Predictive Models. BPO Staff. February 1988. 76 pp. NTIS Order No. DE89001204. FORTRAN source code and executable programs for the five EOR Predictive Models shown below are available. The five recovery processes modeled are Steamflood, In-Situ Combustion, Polymer, Chemical Flooding, and CO2 Miscible Flooding. The models are available individually. Min Req.: IBM PC/XT, PS-2,

  16. Prediction of pure water stress corrosion cracking (PWSCC) in nickel base alloys using crack growth rate models

    SciTech Connect (OSTI)

    Thompson, C.D.; Krasodomski, H.T.; Lewis, N.; Makar, G.L.

    1995-02-22

    The Ford/Andresen slip dissolution SCC model, originally developed for stainless steel components in BWR environments, has been applied to Alloy 600 and Alloy X-750 tested in deaerated pure water chemistry. A method is described whereby the crack growth rates measured in compact tension specimens can be used to estimate crack growth in a component. Good agreement was found between model prediction and measured SCC in X-750 threaded fasteners over a wide range of temperatures, stresses, and material condition. Most data support the basic assumption of this model that cracks initiate early in life. The evidence supporting a particular SCC mechanism is mixed. Electrochemical repassivation data and estimates of oxide fracture strain indicate that the slip dissolution model can account for the observed crack growth rates, provided primary rather than secondary creep rates are used. However, approximately 100 cross-sectional TEM foils of SCC cracks including crack tips reveal no evidence of enhanced plasticity or unique dislocation patterns at the crack tip or along the crack to support a classic slip dissolution mechanism. No voids, hydrides, or microcracks are found in the vicinity of the crack tips creating doubt about classic hydrogen related mechanisms. The bulk oxide films exhibit a surface oxide which is often different than the oxides found within a crack. Although bulk chromium concentration affects the rate of SCC, analytical data indicates the mechanism does not result from chromium depletion at the grain boundaries. The overall findings support a corrosion/dissolution mechanism but not one necessarily related to slip at the crack tip.

  17. TH-E-BRF-05: Comparison of Survival-Time Prediction Models After Radiotherapy for High-Grade Glioma Patients Based On Clinical and DVH Features

    SciTech Connect (OSTI)

    Magome, T; Haga, A; Igaki, H; Sekiya, N; Masutani, Y; Sakumi, A; Mukasa, A; Nakagawa, K

    2014-06-15

    Purpose: Although many outcome prediction models based on dose-volume information have been proposed, it is well known that the prognosis may be affected also by multiple clinical factors. The purpose of this study is to predict the survival time after radiotherapy for high-grade glioma patients based on features including clinical and dose-volume histogram (DVH) information. Methods: A total of 35 patients with high-grade glioma (oligodendroglioma: 2, anaplastic astrocytoma: 3, glioblastoma: 30) were selected in this study. All patients were treated with prescribed dose of 30–80 Gy after surgical resection or biopsy from 2006 to 2013 at The University of Tokyo Hospital. All cases were randomly separated into training dataset (30 cases) and test dataset (5 cases). The survival time after radiotherapy was predicted based on a multiple linear regression analysis and artificial neural network (ANN) by using 204 candidate features. The candidate features included the 12 clinical features (tumor location, extent of surgical resection, treatment duration of radiotherapy, etc.), and the 192 DVH features (maximum dose, minimum dose, D95, V60, etc.). The effective features for the prediction were selected according to a step-wise method by using 30 training cases. The prediction accuracy was evaluated by a coefficient of determination (R{sup 2}) between the predicted and actual survival time for the training and test dataset. Results: In the multiple regression analysis, the value of R{sup 2} between the predicted and actual survival time was 0.460 for the training dataset and 0.375 for the test dataset. On the other hand, in the ANN analysis, the value of R{sup 2} was 0.806 for the training dataset and 0.811 for the test dataset. Conclusion: Although a large number of patients would be needed for more accurate and robust prediction, our preliminary Result showed the potential to predict the outcome in the patients with high-grade glioma. This work was partly supported by

  18. WE-E-17A-02: Predictive Modeling of Outcome Following SABR for NSCLC Based On Radiomics of FDG-PET Images

    SciTech Connect (OSTI)

    Li, R; Aguilera, T; Shultz, D; Rubin, D; Diehn, M; Loo, B

    2014-06-15

    Purpose: This study aims to develop predictive models of patient outcome by extracting advanced imaging features (i.e., Radiomics) from FDG-PET images. Methods: We acquired pre-treatment PET scans for 51 stage I NSCLC patients treated with SABR. We calculated 139 quantitative features from each patient PET image, including 5 morphological features, 8 statistical features, 27 texture features, and 100 features from the intensity-volume histogram. Based on the imaging features, we aim to distinguish between 2 risk groups of patients: those with regional failure or distant metastasis versus those without. We investigated 3 pattern classification algorithms: linear discriminant analysis (LDA), naive Bayes (NB), and logistic regression (LR). To avoid the curse of dimensionality, we performed feature selection by first removing redundant features and then applying sequential forward selection using the wrapper approach. To evaluate the predictive performance, we performed 10-fold cross validation with 1000 random splits of the data and calculated the area under the ROC curve (AUC). Results: Feature selection identified 2 texture features (homogeneity and/or wavelet decompositions) for NB and LR, while for LDA SUVmax and one texture feature (correlation) were identified. All 3 classifiers achieved statistically significant improvements over conventional PET imaging metrics such as tumor volume (AUC = 0.668) and SUVmax (AUC = 0.737). Overall, NB achieved the best predictive performance (AUC = 0.806). This also compares favorably with MTV using the best threshold at an SUV of 11.6 (AUC = 0.746). At a sensitivity of 80%, NB achieved 69% specificity, while SUVmax and tumor volume only had 36% and 47% specificity. Conclusion: Through a systematic analysis of advanced PET imaging features, we are able to build models with improved predictive value over conventional imaging metrics. If validated in a large independent cohort, the proposed techniques could potentially aid in

  19. Midtemperature Solar Systems Test Facility predictions for thermal performance based on test data. Alpha Solarco Model 104 solar collector with 0. 125-inch Schott low-iron glass reflector surface

    SciTech Connect (OSTI)

    Harrison, T.D.

    1981-04-01

    Thermal performance predictions based on test data are presented for the Alpha Solarco Model 104 solar collector, with 0.125-inch Schott low-iron glass reflector surface, for three output temperatures at five cities in the United States.

  20. Progress towards a PETN Lifetime Prediction Model

    SciTech Connect (OSTI)

    Burnham, A K; Overturf III, G E; Gee, R; Lewis, P; Qiu, R; Phillips, D; Weeks, B; Pitchimani, R; Maiti, A; Zepeda-Ruiz, L; Hrousis, C

    2006-09-11

    Dinegar (1) showed that decreases in PETN surface area causes EBW detonator function times to increase. Thermal aging causes PETN to agglomerate, shrink, and densify indicating a ''sintering'' process. It has long been a concern that the formation of a gap between the PETN and the bridgewire may lead to EBW detonator failure. These concerns have led us to develop a model to predict the rate of coarsening that occurs with age for thermally driven PETN powder (50% TMD). To understand PETN contributions to detonator aging we need three things: (1) Curves describing function time dependence on specific surface area, density, and gap. (2) A measurement of the critical gap distance for no fire as a function of density and surface area for various wire configurations. (3) A model describing how specific surface area, density and gap change with time and temperature. We've had good success modeling high temperature surface area reduction and function time increase using a phenomenological deceleratory kinetic model based on a distribution of parallel nth-order reactions having evenly spaced activation energies where weighing factors of the reactions follows a Gaussian distribution about the reaction with the mean activation energy (Figure 1). Unfortunately, the mean activation energy derived from this approach is high (typically {approx}75 kcal/mol) so that negligible sintering is predicted for temperatures below 40 C. To make more reliable predictions, we've established a three-part effort to understand PETN mobility. First, we've measured the rates of step movement and pit nucleation as a function of temperature from 30 to 50 C for single crystals. Second, we've measured the evaporation rate from single crystals and powders from 105 to 135 C to obtain an activation energy for evaporation. Third, we've pursued mechanistic kinetic modeling of surface mobility, evaporation, and ripening.

  1. Predictive Capability Maturity Model for computational modeling and simulation.

    SciTech Connect (OSTI)

    Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.

    2007-10-01

    The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronautics and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.

  2. Project Profile: Predictive Physico-Chemical Modeling of Intrinsic

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Degradation Mechanisms for Advanced Reflector Materials | Department of Energy Predictive Physico-Chemical Modeling of Intrinsic Degradation Mechanisms for Advanced Reflector Materials Project Profile: Predictive Physico-Chemical Modeling of Intrinsic Degradation Mechanisms for Advanced Reflector Materials NREL logo NREL, under the Physics of Reliability: Evaluating Design Insights for Component Technologies in Solar (PREDICTS) Program will be developing a physics-based computational

  3. Standardized Software for Wind Load Forecast Error Analyses and Predictions Based on Wavelet-ARIMA Models - Applications at Multiple Geographically Distributed Wind Farms

    SciTech Connect (OSTI)

    Hou, Zhangshuan; Makarov, Yuri V.; Samaan, Nader A.; Etingov, Pavel V.

    2013-03-19

    Given the multi-scale variability and uncertainty of wind generation and forecast errors, it is a natural choice to use time-frequency representation (TFR) as a view of the corresponding time series represented over both time and frequency. Here we use wavelet transform (WT) to expand the signal in terms of wavelet functions which are localized in both time and frequency. Each WT component is more stationary and has consistent auto-correlation pattern. We combined wavelet analyses with time series forecast approaches such as ARIMA, and tested the approach at three different wind farms located far away from each other. The prediction capability is satisfactory -- the day-ahead prediction of errors match the original error values very well, including the patterns. The observations are well located within the predictive intervals. Integrating our wavelet-ARIMA (stochastic) model with the weather forecast model (deterministic) will improve our ability significantly to predict wind power generation and reduce predictive uncertainty.

  4. Simplified Predictive Models for CO2 Sequestration Performance Assessment: Research Topical Report on Task #4 - Reduced-Order Method (ROM) Based Models

    SciTech Connect (OSTI)

    Mishra, Srikanta; Jin, Larry; He, Jincong; Durlofsky, Louis

    2015-06-30

    Reduced-order models provide a means for greatly accelerating the detailed simulations that will be required to manage CO2 storage operations. In this work, we investigate the use of one such method, POD-TPWL, which has previously been shown to be effective in oil reservoir simulation problems. This method combines trajectory piecewise linearization (TPWL), in which the solution to a new (test) problem is represented through a linearization around the solution to a previously-simulated (training) problem, with proper orthogonal decomposition (POD), which enables solution states to be expressed in terms of a relatively small number of parameters. We describe the application of POD-TPWL for CO2-water systems simulated using a compositional procedure. Stanford’s Automatic Differentiation-based General Purpose Research Simulator (AD-GPRS) performs the full-order training simulations and provides the output (derivative matrices and system states) required by the POD-TPWL method. A new POD-TPWL capability introduced in this work is the use of horizontal injection wells that operate under rate (rather than bottom-hole pressure) control. Simulation results are presented for CO2 injection into a synthetic aquifer and into a simplified model of the Mount Simon formation. Test cases involve the use of time-varying well controls that differ from those used in training runs. Results of reasonable accuracy are consistently achieved for relevant well quantities. Runtime speedups of around a factor of 370 relative to full- order AD-GPRS simulations are achieved, though the preprocessing needed for POD-TPWL model construction corresponds to the computational requirements for about 2.3 full-order simulation runs. A preliminary treatment for POD-TPWL modeling in which test cases differ from training runs in terms of geological parameters (rather than well controls) is also presented. Results in this case involve only small differences between

  5. In silico modeling to predict drug-induced phospholipidosis

    SciTech Connect (OSTI)

    Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G. Sadrieh, Nakissa

    2013-06-01

    Drug-induced phospholipidosis (DIPL) is a preclinical finding during pharmaceutical drug development that has implications on the course of drug development and regulatory safety review. A principal characteristic of drugs inducing DIPL is known to be a cationic amphiphilic structure. This provides evidence for a structure-based explanation and opportunity to analyze properties and structures of drugs with the histopathologic findings for DIPL. In previous work from the FDA, in silico quantitative structureactivity relationship (QSAR) modeling using machine learning approaches has shown promise with a large dataset of drugs but included unconfirmed data as well. In this study, we report the construction and validation of a battery of complementary in silico QSAR models using the FDA's updated database on phospholipidosis, new algorithms and predictive technologies, and in particular, we address high performance with a high-confidence dataset. The results of our modeling for DIPL include rigorous external validation tests showing 8081% concordance. Furthermore, the predictive performance characteristics include models with high sensitivity and specificity, in most cases above ? 80% leading to desired high negative and positive predictivity. These models are intended to be utilized for regulatory toxicology applied science needs in screening new drugs for DIPL. - Highlights: New in silico models for predicting drug-induced phospholipidosis (DIPL) are described. The training set data in the models is derived from the FDA's phospholipidosis database. We find excellent predictivity values of the models based on external validation. The models can support drug screening and regulatory decision-making on DIPL.

  6. Satellite Collision Modeling with Physics-Based Hydrocodes: Debris Generation Predictions of the Iridium-Cosmos Collision Event and Other Impact Events

    SciTech Connect (OSTI)

    Springer, H K; Miller, W O; Levatin, J L; Pertica, A J; Olivier, S S

    2010-09-06

    Satellite collision debris poses risks to existing space assets and future space missions. Predictive models of debris generated from these hypervelocity collisions are critical for developing accurate space situational awareness tools and effective mitigation strategies. Hypervelocity collisions involve complex phenomenon that spans several time- and length-scales. We have developed a satellite collision debris modeling approach consisting of a Lagrangian hydrocode enriched with smooth particle hydrodynamics (SPH), advanced material failure models, detailed satellite mesh models, and massively parallel computers. These computational studies enable us to investigate the influence of satellite center-of-mass (CM) overlap and orientation, relative velocity, and material composition on the size, velocity, and material type distributions of collision debris. We have applied our debris modeling capability to the recent Iridium 33-Cosmos 2251 collision event. While the relative velocity was well understood in this event, the degree of satellite CM overlap and orientation was ill-defined. In our simulations, we varied the collision CM overlap and orientation of the satellites from nearly maximum overlap to partial overlap on the outermost extents of the satellites (i.e, solar panels and gravity boom). As expected, we found that with increased satellite overlap, the overall debris cloud mass and momentum (transfer) increases, the average debris size decreases, and the debris velocity increases. The largest predicted debris can also provide insight into which satellite components were further removed from the impact location. A significant fraction of the momentum transfer is imparted to the smallest debris (< 1-5mm, dependent on mesh resolution), especially in large CM overlap simulations. While the inclusion of the smallest debris is critical to enforcing mass and momentum conservation in hydrocode simulations, there seems to be relatively little interest in their

  7. Computational Tools for Predictive Modeling of Properties in...

    Office of Scientific and Technical Information (OSTI)

    Book: Computational Tools for Predictive Modeling of Properties in Complex Actinide Systems Citation Details In-Document Search Title: Computational Tools for Predictive Modeling ...

  8. Predictive Models for Target Response During Penetration (Technical...

    Office of Scientific and Technical Information (OSTI)

    Predictive Models for Target Response During Penetration Citation Details In-Document Search Title: Predictive Models for Target Response During Penetration You are accessing a...

  9. Simplified Protein Models: Predicting Folding Pathways and Structure...

    Office of Scientific and Technical Information (OSTI)

    Simplified Protein Models: Predicting Folding Pathways and Structure Using Amino Acid Sequences Title: Simplified Protein Models: Predicting Folding Pathways and Structure Using ...

  10. Comparison of Uncertainty of Two Precipitation Prediction Models...

    Office of Scientific and Technical Information (OSTI)

    Prediction Models at Los Alamos National Lab Technical Area 54 Citation Details In-Document Search Title: Comparison of Uncertainty of Two Precipitation Prediction Models ...

  11. A predictive standard model for heavy electron systems (Conference...

    Office of Scientific and Technical Information (OSTI)

    A predictive standard model for heavy electron systems Citation Details In-Document Search Title: A predictive standard model for heavy electron systems You are accessing a ...

  12. Predictive Models of Li-ion Battery Lifetime

    SciTech Connect (OSTI)

    Smith, Kandler; Wood, Eric; Santhanagopalan, Shriram; Kim, Gi-heon; Shi, Ying; Pesaran, Ahmad

    2015-06-15

    It remains an open question how best to predict real-world battery lifetime based on accelerated calendar and cycle aging data from the laboratory. Multiple degradation mechanisms due to (electro)chemical, thermal, and mechanical coupled phenomena influence Li-ion battery lifetime, each with different dependence on time, cycling and thermal environment. The standardization of life predictive models would benefit the industry by reducing test time and streamlining development of system controls.

  13. Testing model for predicting spillway cavitation damage

    SciTech Connect (OSTI)

    Lee, W.; Hoopes, J.A.

    1995-12-31

    Using fuzzy mathematics a comprehensive model has been developed to predict the time, location and level (intensity) of spillway cavitation damage. Five damage levels and four factors affecting damage are used. Membership functions express the degree that each factor effects damage, and weights express the relative importance of each factor. The model has been calibrated and tested with operating data and experience from the Glen Canyon Dam left tunnel spillway, which had major cavitation damage in 1983. An error analysis for the Glen Canyon Dam left tunnel spillway gave the best ranges for model weights. Prediction of damage at other spillways (4 tunnels, 3 chutes) with functions and parameters as for the Glen Canyon Dam left tunnel spillway gave reasonable predictions of damage intensity and location and poor estimates of occurrence time in the tunnels. Chute predictions were in poor agreement with observations, indicating need for different parameter values. Finally, two membership functions with constant or time varying parameters are compared with observed results from the Glen Canyon Dam left tunnel spillway.

  14. Predictive Models for Regional Hepatic Function Based on 99mTc-IDA SPECT and Local Radiation Dose for Physiologic Adaptive Radiation Therapy

    SciTech Connect (OSTI)

    Wang, Hesheng; Feng, Mary; Frey, Kirk A.; Ten Haken, Randall K.; Lawrence, Theodore S.; Cao, Yue

    2013-08-01

    Purpose: High-dose radiation therapy (RT) for intrahepatic cancer is limited by the development of liver injury. This study investigated whether regional hepatic function assessed before and during the course of RT using 99mTc-labeled iminodiacetic acid (IDA) single photon emission computed tomography (SPECT) could predict regional liver function reserve after RT. Methods and Materials: Fourteen patients treated with RT for intrahepatic cancers underwent dynamic 99mTc-IDA SPECT scans before RT, during, and 1 month after completion of RT. Indocyanine green (ICG) tests, a measure of overall liver function, were performed within 1 day of each scan. Three-dimensional volumetric hepatic extraction fraction (HEF) images of the liver were estimated by deconvolution analysis. After coregistration of the CT/SPECT and the treatment planning CT, HEF dose–response functions during and after RT were generated. The volumetric mean of the HEFs in the whole liver was correlated with ICG clearance time. Three models, dose, priori, and adaptive models, were developed using multivariate linear regression to assess whether the regional HEFs measured before and during RT helped predict regional hepatic function after RT. Results: The mean of the volumetric liver HEFs was significantly correlated with ICG clearance half-life time (r=−0.80, P<.0001), for all time points. Linear correlations between local doses and regional HEFs 1 month after RT were significant in 12 patients. In the priori model, regional HEF after RT was predicted by the planned dose and regional HEF assessed before RT (R=0.71, P<.0001). In the adaptive model, regional HEF after RT was predicted by regional HEF reassessed during RT and the remaining planned local dose (R=0.83, P<.0001). Conclusions: 99mTc-IDA SPECT obtained during RT could be used to assess regional hepatic function and helped predict post-RT regional liver function reserve. This could support individualized adaptive radiation treatment strategies

  15. Streamflow effects on spawning, rearing, and outmigration of fall-run chinook salmon (Oncorhynchus tshawytscha) predicted by a spatial and individual-based model

    SciTech Connect (OSTI)

    Jager, H.I.; Sale, M.J.; Cardwell, H.E.; Deangelis, D.L.; Bevelhimer, M.J.; Coutant, C.C. )

    1994-06-01

    The thread posed to Pacific salmon by competing water demands is a great concern to regulators of the hydropower industry. Finding the balance between fish resource and economic objectives depends on our ability to quantify flow effects on salmon production. Because field experiments are impractical, simulation models are needed to predict the effects of minimum flows on chinook salmon during their freshwater residence. We have developed a model to simulate the survival and development of eggs and alevins in redds and the growth, survival, and movement of juvenile chinook in response to local stream conditions (flow, temperature, chinook and predator density). Model results suggest that smolt production during dry years can be increased by raising spring minimum flows.

  16. GIS-BASED PREDICTION OF HURRICANE FLOOD INUNDATION

    SciTech Connect (OSTI)

    JUDI, DAVID; KALYANAPU, ALFRED; MCPHERSON, TIMOTHY; BERSCHEID, ALAN

    2007-01-17

    A simulation environment is being developed for the prediction and analysis of the inundation consequences for infrastructure systems from extreme flood events. This decision support architecture includes a GIS-based environment for model input development, simulation integration tools for meteorological, hydrologic, and infrastructure system models and damage assessment tools for infrastructure systems. The GIS-based environment processes digital elevation models (30-m from the USGS), land use/cover (30-m NLCD), stream networks from the National Hydrography Dataset (NHD) and soils data from the NRCS (STATSGO) to create stream network, subbasins, and cross-section shapefiles for drainage basins selected for analysis. Rainfall predictions are made by a numerical weather model and ingested in gridded format into the simulation environment. Runoff hydrographs are estimated using Green-Ampt infiltration excess runoff prediction and a 1D diffusive wave overland flow routing approach. The hydrographs are fed into the stream network and integrated in a dynamic wave routing module using the EPA's Storm Water Management Model (SWMM) to predict flood depth. The flood depths are then transformed into inundation maps and exported for damage assessment. Hydrologic/hydraulic results are presented for Tropical Storm Allison.

  17. Illustrating the future prediction of performance based on computer...

    Office of Scientific and Technical Information (OSTI)

    Illustrating the future prediction of performance based on computer code, physical ... Citation Details In-Document Search Title: Illustrating the future prediction of ...

  18. New model accurately predicts reformate composition

    SciTech Connect (OSTI)

    Ancheyta-Juarez, J.; Aguilar-Rodriguez, E. )

    1994-01-31

    Although naphtha reforming is a well-known process, the evolution of catalyst formulation, as well as new trends in gasoline specifications, have led to rapid evolution of the process, including: reactor design, regeneration mode, and operating conditions. Mathematical modeling of the reforming process is an increasingly important tool. It is fundamental to the proper design of new reactors and revamp of existing ones. Modeling can be used to optimize operating conditions, analyze the effects of process variables, and enhance unit performance. Instituto Mexicano del Petroleo has developed a model of the catalytic reforming process that accurately predicts reformate composition at the higher-severity conditions at which new reformers are being designed. The new AA model is more accurate than previous proposals because it takes into account the effects of temperature and pressure on the rate constants of each chemical reaction.

  19. Maximum likelihood Bayesian model averaging and its predictive analysis for groundwater reactive transport models

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Lu, Dan; Ye, Ming; Curtis, Gary P.

    2015-08-01

    While Bayesian model averaging (BMA) has been widely used in groundwater modeling, it is infrequently applied to groundwater reactive transport modeling because of multiple sources of uncertainty in the coupled hydrogeochemical processes and because of the long execution time of each model run. To resolve these problems, this study analyzed different levels of uncertainty in a hierarchical way, and used the maximum likelihood version of BMA, i.e., MLBMA, to improve the computational efficiency. Our study demonstrates the applicability of MLBMA to groundwater reactive transport modeling in a synthetic case in which twenty-seven reactive transport models were designed to predict themore » reactive transport of hexavalent uranium (U(VI)) based on observations at a former uranium mill site near Naturita, CO. Moreover, these reactive transport models contain three uncertain model components, i.e., parameterization of hydraulic conductivity, configuration of model boundary, and surface complexation reactions that simulate U(VI) adsorption. These uncertain model components were aggregated into the alternative models by integrating a hierarchical structure into MLBMA. The modeling results of the individual models and MLBMA were analyzed to investigate their predictive performance. The predictive logscore results show that MLBMA generally outperforms the best model, suggesting that using MLBMA is a sound strategy to achieve more robust model predictions relative to a single model. MLBMA works best when the alternative models are structurally distinct and have diverse model predictions. When correlation in model structure exists, two strategies were used to improve predictive performance by retaining structurally distinct models or assigning smaller prior model probabilities to correlated models. Since the synthetic models were designed using data from the Naturita site, the results of this study are expected to provide guidance for real-world modeling. Finally

  20. Maximum likelihood Bayesian model averaging and its predictive analysis for groundwater reactive transport models

    SciTech Connect (OSTI)

    Lu, Dan; Ye, Ming; Curtis, Gary P.

    2015-08-01

    While Bayesian model averaging (BMA) has been widely used in groundwater modeling, it is infrequently applied to groundwater reactive transport modeling because of multiple sources of uncertainty in the coupled hydrogeochemical processes and because of the long execution time of each model run. To resolve these problems, this study analyzed different levels of uncertainty in a hierarchical way, and used the maximum likelihood version of BMA, i.e., MLBMA, to improve the computational efficiency. Our study demonstrates the applicability of MLBMA to groundwater reactive transport modeling in a synthetic case in which twenty-seven reactive transport models were designed to predict the reactive transport of hexavalent uranium (U(VI)) based on observations at a former uranium mill site near Naturita, CO. Moreover, these reactive transport models contain three uncertain model components, i.e., parameterization of hydraulic conductivity, configuration of model boundary, and surface complexation reactions that simulate U(VI) adsorption. These uncertain model components were aggregated into the alternative models by integrating a hierarchical structure into MLBMA. The modeling results of the individual models and MLBMA were analyzed to investigate their predictive performance. The predictive logscore results show that MLBMA generally outperforms the best model, suggesting that using MLBMA is a sound strategy to achieve more robust model predictions relative to a single model. MLBMA works best when the alternative models are structurally distinct and have diverse model predictions. When correlation in model structure exists, two strategies were used to improve predictive performance by retaining structurally distinct models or assigning smaller prior model probabilities to correlated models. Since the synthetic models were designed using data from the Naturita site, the results of this study are expected to provide guidance for real-world modeling. Finally, limitations of

  1. An Anisotropic Hardening Model for Springback Prediction

    SciTech Connect (OSTI)

    Zeng, Danielle; Xia, Z. Cedric

    2005-08-05

    As more Advanced High-Strength Steels (AHSS) are heavily used for automotive body structures and closures panels, accurate springback prediction for these components becomes more challenging because of their rapid hardening characteristics and ability to sustain even higher stresses. In this paper, a modified Mroz hardening model is proposed to capture realistic Bauschinger effect at reverse loading, such as when material passes through die radii or drawbead during sheet metal forming process. This model accounts for material anisotropic yield surface and nonlinear isotropic/kinematic hardening behavior. Material tension/compression test data are used to accurately represent Bauschinger effect. The effectiveness of the model is demonstrated by comparison of numerical and experimental springback results for a DP600 straight U-channel test.

  2. Mathematical modeling to predict residential solid waste generation

    SciTech Connect (OSTI)

    Ojeda Benitez, Sara; Vega, Carolina Armijo de

    2008-07-01

    One of the challenges faced by waste management authorities is determining the amount of waste generated by households in order to establish waste management systems, as well as trying to charge rates compatible with the principle applied worldwide, and design a fair payment system for households according to the amount of residential solid waste (RSW) they generate. The goal of this research work was to establish mathematical models that correlate the generation of RSW per capita to the following variables: education, income per household, and number of residents. This work was based on data from a study on generation, quantification and composition of residential waste in a Mexican city in three stages. In order to define prediction models, five variables were identified and included in the model. For each waste sampling stage a different mathematical model was developed, in order to find the model that showed the best linear relation to predict residential solid waste generation. Later on, models to explore the combination of included variables and select those which showed a higher R{sup 2} were established. The tests applied were normality, multicolinearity and heteroskedasticity. Another model, formulated with four variables, was generated and the Durban-Watson test was applied to it. Finally, a general mathematical model is proposed to predict residential waste generation, which accounts for 51% of the total.

  3. Predictive RANS simulations via Bayesian Model-Scenario Averaging

    SciTech Connect (OSTI)

    Edeling, W.N.; Cinnella, P.; Dwight, R.P.

    2014-10-15

    The turbulence closure model is the dominant source of error in most Reynolds-Averaged Navier–Stokes simulations, yet no reliable estimators for this error component currently exist. Here we develop a stochastic, a posteriori error estimate, calibrated to specific classes of flow. It is based on variability in model closure coefficients across multiple flow scenarios, for multiple closure models. The variability is estimated using Bayesian calibration against experimental data for each scenario, and Bayesian Model-Scenario Averaging (BMSA) is used to collate the resulting posteriors, to obtain a stochastic estimate of a Quantity of Interest (QoI) in an unmeasured (prediction) scenario. The scenario probabilities in BMSA are chosen using a sensor which automatically weights those scenarios in the calibration set which are similar to the prediction scenario. The methodology is applied to the class of turbulent boundary-layers subject to various pressure gradients. For all considered prediction scenarios the standard-deviation of the stochastic estimate is consistent with the measurement ground truth. Furthermore, the mean of the estimate is more consistently accurate than the individual model predictions.

  4. New climate model predicts likelihood of Greenland ice melt, sea level rise

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    and dangerous temperatures New climate model predicts likelihood of Greenland ice melt New climate model predicts likelihood of Greenland ice melt, sea level rise and dangerous temperatures A new computer model of accumulated carbon emissions predicts the likelihood of crossing several dangerous climate change thresholds. November 20, 2015 Greenland ice loss. Greenland ice loss. Contact Kevin Roark Communications Office (505) 665-9202 Email "The model is based on idealized

  5. SU-E-J-257: A PCA Model to Predict Adaptive Changes for Head&neck Patients Based On Extraction of Geometric Features From Daily CBCT Datasets

    SciTech Connect (OSTI)

    Chetvertkov, M; Siddiqui, F; Chetty, I; Kim, J; Kumarasiri, A; Liu, C; Gordon, J

    2015-06-15

    Purpose: Using daily cone beam CTs (CBCTs) to develop principal component analysis (PCA) models of anatomical changes in head and neck (H&N) patients and to assess the possibility of using these prospectively in adaptive radiation therapy (ART). Methods: Planning CT (pCT) images of 4 H&N patients were deformed to model several different systematic changes in patient anatomy during the course of the radiation therapy (RT). A Pinnacle plugin was used to linearly interpolate the systematic change in patient for the 35 fraction RT course and to generate a set of 35 synthetic CBCTs. Each synthetic CBCT represents the systematic change in patient anatomy for each fraction. Deformation vector fields (DVFs) were acquired between the pCT and synthetic CBCTs with random fraction-to-fraction changes were superimposed on the DVFs. A patient-specific PCA model was built using these DVFs containing systematic plus random changes. It was hypothesized that resulting eigenDVFs (EDVFs) with largest eigenvalues represent the major anatomical deformations during the course of treatment. Results: For all 4 patients, the PCA model provided different results depending on the type and size of systematic change in patient’s body. PCA was more successful in capturing the systematic changes early in the treatment course when these were of a larger scale with respect to the random fraction-to-fraction changes in patient’s anatomy. For smaller scale systematic changes, random changes in patient could completely “hide” the systematic change. Conclusion: The leading EDVF from the patientspecific PCA models could tentatively be identified as a major systematic change during treatment if the systematic change is large enough with respect to random fraction-to-fraction changes. Otherwise, leading EDVF could not represent systematic changes reliably. This work is expected to facilitate development of population-based PCA models that can be used to prospectively identify significant

  6. Stimulation Prediction Models | Open Energy Information

    Open Energy Info (EERE)

    Predictive Simulator for Enhanced Geothermal Systems California Science Applications International Corporation Recovery Act: Enhanced Geothermal Systems Component Research and...

  7. Model Predictive Control for the Operation of Building Cooling Systems

    SciTech Connect (OSTI)

    Ma, Yudong; Borrelli, Francesco; Hencey, Brandon; Coffey, Brian; Bengea, Sorin; Haves, Philip

    2010-06-29

    A model-based predictive control (MPC) is designed for optimal thermal energy storage in building cooling systems. We focus on buildings equipped with a water tank used for actively storing cold water produced by a series of chillers. Typically the chillers are operated at night to recharge the storage tank in order to meet the building demands on the following day. In this paper, we build on our previous work, improve the building load model, and present experimental results. The experiments show that MPC can achieve reduction in the central plant electricity cost and improvement of its efficiency.

  8. Prediction of interest rate using CKLS model with stochastic parameters

    SciTech Connect (OSTI)

    Ying, Khor Chia; Hin, Pooi Ah

    2014-06-19

    The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ{sup (j)}, we assume that φ{sup (j)} depends on φ{sup (j−m)}, φ{sup (j−m+1)},…, φ{sup (j−1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.

  9. Roadmap Toward a Predictive Performance-based Commercial Energy Code

    SciTech Connect (OSTI)

    Rosenberg, Michael I.; Hart, Philip R.

    2014-10-01

    Energy codes have provided significant increases in building efficiency over the last 38 years, since the first national energy model code was published in late 1975. The most commonly used path in energy codes, the prescriptive path, appears to be reaching a point of diminishing returns. The current focus on prescriptive codes has limitations including significant variation in actual energy performance depending on which prescriptive options are chosen, a lack of flexibility for designers and developers, and the inability to handle control optimization that is specific to building type and use. This paper provides a high level review of different options for energy codes, including prescriptive, prescriptive packages, EUI Target, outcome-based, and predictive performance approaches. This paper also explores a next generation commercial energy code approach that places a greater emphasis on performance-based criteria. A vision is outlined to serve as a roadmap for future commercial code development. That vision is based on code development being led by a specific approach to predictive energy performance combined with building specific prescriptive packages that are designed to be both cost-effective and to achieve a desired level of performance. Compliance with this new approach can be achieved by either meeting the performance target as demonstrated by whole building energy modeling, or by choosing one of the prescriptive packages.

  10. Illustrating the future prediction of performance based on computer...

    Office of Scientific and Technical Information (OSTI)

    Illustrating the future prediction of performance based on computer code, physical experiments, and critical performance parameter samples Citation Details In-Document Search ...

  11. Predictive Models of Li-ion Battery Lifetime (Presentation) (Conference) |

    Office of Scientific and Technical Information (OSTI)

    SciTech Connect Predictive Models of Li-ion Battery Lifetime (Presentation) Citation Details In-Document Search Title: Predictive Models of Li-ion Battery Lifetime (Presentation) Predictive models of Li-ion battery reliability must consider a multiplicity of electrochemical, thermal and mechanical degradation modes experienced by batteries in application environments. Complicating matters, Li-ion batteries can experience several path dependent degradation trajectories dependent on storage

  12. Predictive Models of Li-ion Battery Lifetime (Presentation) Smith...

    Office of Scientific and Technical Information (OSTI)

    Predictive Models of Li-ion Battery Lifetime (Presentation) Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Shi, Y.; Pesaran, A. 25 ENERGY STORAGE; 33 ADVANCED PROPULSION...

  13. Project Profile: Predictive Physico-Chemical Modeling of Intrinsic...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    NREL logo NREL, under the Physics of Reliability: Evaluating Design Insights for Component Technologies in Solar (PREDICTS) Program will be developing a physics-based computational ...

  14. Model-based tomographic reconstruction

    DOE Patents [OSTI]

    Chambers, David H.; Lehman, Sean K.; Goodman, Dennis M.

    2012-06-26

    A model-based approach to estimating wall positions for a building is developed and tested using simulated data. It borrows two techniques from geophysical inversion problems, layer stripping and stacking, and combines them with a model-based estimation algorithm that minimizes the mean-square error between the predicted signal and the data. The technique is designed to process multiple looks from an ultra wideband radar array. The processed signal is time-gated and each section processed to detect the presence of a wall and estimate its position, thickness, and material parameters. The floor plan of a building is determined by moving the array around the outside of the building. In this paper we describe how the stacking and layer stripping algorithms are combined and show the results from a simple numerical example of three parallel walls.

  15. Demonstrating the improvement of predictive maturity of a computational model

    SciTech Connect (OSTI)

    Hemez, Francois M; Unal, Cetin; Atamturktur, Huriye S

    2010-01-01

    We demonstrate an improvement of predictive capability brought to a non-linear material model using a combination of test data, sensitivity analysis, uncertainty quantification, and calibration. A model that captures increasingly complicated phenomena, such as plasticity, temperature and strain rate effects, is analyzed. Predictive maturity is defined, here, as the accuracy of the model to predict multiple Hopkinson bar experiments. A statistical discrepancy quantifies the systematic disagreement (bias) between measurements and predictions. Our hypothesis is that improving the predictive capability of a model should translate into better agreement between measurements and predictions. This agreement, in turn, should lead to a smaller discrepancy. We have recently proposed to use discrepancy and coverage, that is, the extent to which the physical experiments used for calibration populate the regime of applicability of the model, as basis to define a Predictive Maturity Index (PMI). It was shown that predictive maturity could be improved when additional physical tests are made available to increase coverage of the regime of applicability. This contribution illustrates how the PMI changes as 'better' physics are implemented in the model. The application is the non-linear Preston-Tonks-Wallace (PTW) strength model applied to Beryllium metal. We demonstrate that our framework tracks the evolution of maturity of the PTW model. Robustness of the PMI with respect to the selection of coefficients needed in its definition is also studied.

  16. Predicting laser weld reliability with stochastic reduced-order models. Predicting laser weld reliability

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Emery, John M.; Field, Richard V.; Foulk, James W.; Karlson, Kyle N.; Grigoriu, Mircea D.

    2015-05-26

    Laser welds are prevalent in complex engineering systems and they frequently govern failure. The weld process often results in partial penetration of the base metals, leaving sharp crack-like features with a high degree of variability in the geometry and material properties of the welded structure. Furthermore, accurate finite element predictions of the structural reliability of components containing laser welds requires the analysis of a large number of finite element meshes with very fine spatial resolution, where each mesh has different geometry and/or material properties in the welded region to address variability. We found that traditional modeling approaches could not bemore » efficiently employed. Consequently, a method is presented for constructing a surrogate model, based on stochastic reduced-order models, and is proposed to represent the laser welds within the component. Here, the uncertainty in weld microstructure and geometry is captured by calibrating plasticity parameters to experimental observations of necking as, because of the ductility of the welds, necking – and thus peak load – plays the pivotal role in structural failure. The proposed method is exercised for a simplified verification problem and compared with the traditional Monte Carlo simulation with rather remarkable results.« less

  17. Predicting laser weld reliability with stochastic reduced-order models. Predicting laser weld reliability

    SciTech Connect (OSTI)

    Emery, John M.; Field, Richard V.; Foulk, James W.; Karlson, Kyle N.; Grigoriu, Mircea D.

    2015-05-26

    Laser welds are prevalent in complex engineering systems and they frequently govern failure. The weld process often results in partial penetration of the base metals, leaving sharp crack-like features with a high degree of variability in the geometry and material properties of the welded structure. Furthermore, accurate finite element predictions of the structural reliability of components containing laser welds requires the analysis of a large number of finite element meshes with very fine spatial resolution, where each mesh has different geometry and/or material properties in the welded region to address variability. We found that traditional modeling approaches could not be efficiently employed. Consequently, a method is presented for constructing a surrogate model, based on stochastic reduced-order models, and is proposed to represent the laser welds within the component. Here, the uncertainty in weld microstructure and geometry is captured by calibrating plasticity parameters to experimental observations of necking as, because of the ductility of the welds, necking – and thus peak load – plays the pivotal role in structural failure. The proposed method is exercised for a simplified verification problem and compared with the traditional Monte Carlo simulation with rather remarkable results.

  18. Development of a fourth generation predictive capability maturity model.

    SciTech Connect (OSTI)

    Hills, Richard Guy; Witkowski, Walter R.; Urbina, Angel; Rider, William J.; Trucano, Timothy Guy

    2013-09-01

    The Predictive Capability Maturity Model (PCMM) is an expert elicitation tool designed to characterize and communicate completeness of the approaches used for computational model definition, verification, validation, and uncertainty quantification associated for an intended application. The primary application of this tool at Sandia National Laboratories (SNL) has been for physics-based computational simulations in support of nuclear weapons applications. The two main goals of a PCMM evaluation are 1) the communication of computational simulation capability, accurately and transparently, and 2) the development of input for effective planning. As a result of the increasing importance of computational simulation to SNL's mission, the PCMM has evolved through multiple generations with the goal to provide more clarity, rigor, and completeness in its application. This report describes the approach used to develop the fourth generation of the PCMM.

  19. LHC diphoton Higgs signal predicted by little Higgs models

    SciTech Connect (OSTI)

    Wang Lei; Yang Jinmin

    2011-10-01

    Little Higgs theory naturally predicts a light Higgs boson whose most important discovery channel at the LHC is the diphoton signal pp{yields}h{yields}{gamma}{gamma}. In this work, we perform a comparative study for this signal in some typical little Higgs models, namely, the littlest Higgs model, two littlest Higgs models with T-parity (named LHT-I and LHT-II), and the simplest little Higgs models. We find that compared with the standard model prediction, the diphoton signal rate is always suppressed and the suppression extent can be quite different for different models. The suppression is mild (< or approx. 10%) in the littlest Higgs model but can be quite severe ({approx_equal}90%) in other three models. This means that discovering the light Higgs boson predicted by the little Higgs theory through the diphoton channel at the LHC will be more difficult than discovering the standard model Higgs boson.

  20. Practical model for predicting pressure in gas-storage reservoirs

    SciTech Connect (OSTI)

    Mollnard, J.E.; Le Bitoux, P.; Pelce, V. ); Tek, M.R. )

    1990-11-01

    Optional planning, design, and operation of gas fields in production or storage critically depends on reliable models for predicting pressures that are often based on sophisticated numerical and mathematical concepts. The pressure that prevails at a given time is a direct function of production/injection schedules, past history, and surface equipment as related to reserves and reservoir characteristics. Maintaining the pressure within prescribed limits is particularly important in underground storage to avoid pressures above a maximum for reasons of safety and migration and below a minimum for surface-equipment and contracted-deliverability considerations. This paper presents a way to calculate the convolution integral on which the pressure variations depend. The classic methods were long and costly to run and seldom used. The author's method, which identifies this convolution integral with a finite sum of exponential terms, is much quicker and has been implemented in a program called PREPRE, usable on microcomputers. Based on a production/pressure schedule, the model is capable of forecasting the evolution of pressures in main zones of interest, such as wellbores, gathering systems, and surface equipment. The data required for the model-past production/pressure history-are matched by a special algorithm that automatically calculates the main reservoir parameters used as bases for future projections.

  1. Dynamic model predicts well bore surge and swab pressures

    SciTech Connect (OSTI)

    Bing, Z.; Kaiji, Z.

    1996-12-30

    A dynamic well control model predicts surge and swab pressures more accurately than a steady-state model, thereby providing better estimates of pressure fluctuations when pipe is tripped. Pressure fluctuations from tripping pipe into a well can contribute to lost circulation, kicks,and well control problems. This dynamic method of predicting surge and swab pressures was verified in a full-scale test well in the Zhong Yuan oil field in China. Both the dynamic model and steady state model were verified through the test data. The test data showed the dynamic model can correctly predict downhole pressures from running or pulling pipe in a well; steady state models may result in relatively large prediction errors, especially in deeper wells.

  2. New model predicts once-mysterious chemical reactions

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    New model predicts once-mysterious chemical reactions New model predicts once-mysterious chemical reactions Results will also be used to understand basic questions about nature such as the cooling mechanisms of the early universe and the formation of planets and stars. June 28, 2016 Mark Zammit, of Los Alamos' Physics and Chemistry of Materials group, is part of a team that developed a theoretical model to forecast the fundamental chemical reactions involving molecular hydrogen. Photo credit

  3. A predictive ocean oil spill model

    SciTech Connect (OSTI)

    Sanderson, J.; Barnette, D.; Papodopoulos, P.; Schaudt, K.; Szabo, D.

    1996-07-01

    This is the final report of a two-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). Initially, the project focused on creating an ocean oil spill model and working with the major oil companies to compare their data with the Los Alamos global ocean model. As a result of this initial effort, Los Alamos worked closely with the Eddy Joint Industry Project (EJIP), a consortium oil and gas producing companies in the US. The central theme of the project was to use output produced from LANL`s global ocean model to look in detail at ocean currents in selected geographic areas of the world of interest to consortium members. Once ocean currents are well understood this information could be used to create oil spill models, improve offshore exploration and drilling equipment, and aid in the design of semi-permanent offshore production platforms.

  4. SimTable helps firefighters model and predict fire direction

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    SimTable models and predicts fire path SimTable helps firefighters model and predict fire direction In 2009, SimTable received $100,000 from the LANS Venture Acceleration Fund to improve the user interface and seed firefighting academies with customized set ups. April 3, 2012 Stephen Guerin (L) and Chip Garner (R) with SimTable Stephen Guerin (L), and Chip Garner (R), with SimTable, a Santa Fe company helping firefighters model and predict where a fire is most likely to spread, received support

  5. TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

    SciTech Connect (OSTI)

    Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A; Ge, Y

    2014-06-15

    Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH/NCI under grant

  6. Prediction of cloud droplet number in a general circulation model

    SciTech Connect (OSTI)

    Ghan, S.J.; Leung, L.R.

    1996-04-01

    We have applied the Colorado State University Regional Atmospheric Modeling System (RAMS) bulk cloud microphysics parameterization to the treatment of stratiform clouds in the National Center for Atmospheric Research Community Climate Model (CCM2). The RAMS predicts mass concentrations of cloud water, cloud ice, rain and snow, and number concnetration of ice. We have introduced the droplet number conservation equation to predict droplet number and it`s dependence on aerosols.

  7. Statistical thermodynamics model and empirical correlations for predicting

    Office of Scientific and Technical Information (OSTI)

    mixed hydrate phase equilibria (Journal Article) | SciTech Connect Statistical thermodynamics model and empirical correlations for predicting mixed hydrate phase equilibria Citation Details In-Document Search Title: Statistical thermodynamics model and empirical correlations for predicting mixed hydrate phase equilibria Authors: Garapati, Nagasree ; Anderson, Brian J Publication Date: 2014-07-01 OSTI Identifier: 1165558 Report Number(s): A-UNIV-PUB-100 Journal ID: ISSN 0378-3812 DOE Contract

  8. PV Module Intraconnect Thermomechanical Durability Damage Prediction Model

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    | Department of Energy Module Intraconnect Thermomechanical Durability Damage Prediction Model PV Module Intraconnect Thermomechanical Durability Damage Prediction Model Presented at the PV Module Reliability Workshop, February 26 - 27 2013, Golden, Colorado pvmrw13_ps2_dow_gaston.pdf (1.26 MB) More Documents & Publications FY2015 Status Report: CIRFT Testing of High-Burnup Used Nuclear Fuel Rods from Pressurized Water Reactor and BWR Environments 2014 Propulsion Materials R&D Annual

  9. Using a Simple Binomial Model to Assess Improvement in Predictive

    Office of Scientific and Technical Information (OSTI)

    Capability: Sequential Bayesian Inference, Hypothesis Testing, and Power Analysis (Technical Report) | SciTech Connect Technical Report: Using a Simple Binomial Model to Assess Improvement in Predictive Capability: Sequential Bayesian Inference, Hypothesis Testing, and Power Analysis Citation Details In-Document Search Title: Using a Simple Binomial Model to Assess Improvement in Predictive Capability: Sequential Bayesian Inference, Hypothesis Testing, and Power Analysis We present a

  10. A thermodynamic model to predict the aqueous solubility of hydrocarbon

    Office of Scientific and Technical Information (OSTI)

    mixtures at two-phase hydrate-liquid water equilibrium (Journal Article) | SciTech Connect Journal Article: A thermodynamic model to predict the aqueous solubility of hydrocarbon mixtures at two-phase hydrate-liquid water equilibrium Citation Details In-Document Search This content will become publicly available on March 30, 2018 Title: A thermodynamic model to predict the aqueous solubility of hydrocarbon mixtures at two-phase hydrate-liquid water equilibrium Authors: Velaga, Srinath C.

  11. Predictive models of circulating fluidized bed combustors

    SciTech Connect (OSTI)

    Gidaspow, D.

    1992-07-01

    Steady flows influenced by walls cannot be described by inviscid models. Flows in circulating fluidized beds have significant wall effects. Particles in the form of clusters or layers can be seen to run down the walls. Hence modeling of circulating fluidized beds (CFB) without a viscosity is not possible. However, in interpreting Equations (8-1) and (8-2) it must be kept in mind that CFB or most other two phase flows are never in a true steady state. Then the viscosity in Equations (8-1) and (8-2) may not be the true fluid viscosity to be discussed next, but an Eddy type viscosity caused by two phase flow oscillations usually referred to as turbulence. In view of the transient nature of two-phase flow, the drag and the boundary layer thickness may not be proportional to the square root of the intrinsic viscosity but depend upon it to a much smaller extent. As another example, liquid-solid flow and settling of colloidal particles in a lamella electrosettler the settling process is only moderately affected by viscosity. Inviscid flow with settling is a good first approximation to this electric field driven process. The physical meaning of the particulate phase viscosity is described in detail in the chapter on kinetic theory. Here the conventional derivation resented in single phase fluid mechanics is generalized to multiphase flow.

  12. LIFETIME PREDICTION FOR MODEL 9975 O-RINGS IN KAMS

    SciTech Connect (OSTI)

    Hoffman, E.; Skidmore, E.

    2009-11-24

    The Savannah River Site (SRS) is currently storing plutonium materials in the K-Area Materials Storage (KAMS) facility. The materials are packaged per the DOE 3013 Standard and transported and stored in KAMS in Model 9975 shipping packages, which include double containment vessels sealed with dual O-rings made of Parker Seals compound V0835-75 (based on Viton{reg_sign} GLT). The outer O-ring of each containment vessel is credited for leaktight containment per ANSI N14.5. O-ring service life depends on many factors, including the failure criterion, environmental conditions, overall design, fabrication quality and assembly practices. A preliminary life prediction model has been developed for the V0835-75 O-rings in KAMS. The conservative model is based primarily on long-term compression stress relaxation (CSR) experiments and Arrhenius accelerated-aging methodology. For model development purposes, seal lifetime is defined as a 90% loss of measurable sealing force. Thus far, CSR experiments have only reached this target level of degradation at temperatures {ge} 300 F. At lower temperatures, relaxation values are more tolerable. Using time-temperature superposition principles, the conservative model predicts a service life of approximately 20-25 years at a constant seal temperature of 175 F. This represents a maximum payload package at a constant ambient temperature of 104 F, the highest recorded in KAMS to date. This is considered a highly conservative value as such ambient temperatures are only reached on occasion and for short durations. The presence of fiberboard in the package minimizes the impact of such temperature swings, with many hours to several days required for seal temperatures to respond proportionately. At 85 F ambient, a more realistic but still conservative value, bounding seal temperatures are reduced to {approx}158 F, with an estimated seal lifetime of {approx}35-45 years. The actual service life for O-rings in a maximum wattage package likely lies

  13. The selection of turbulence models for prediction of room airflow

    SciTech Connect (OSTI)

    Nielsen, P.V.

    1998-10-01

    The airflow in buildings involves a combination of many different flow elements. It is, therefore, difficult to find an adequate, all-round turbulence model covering all aspects. Consequently, it is appropriate and economical to choose turbulence models according to the situation that is to be predicted. This paper discusses the use of different turbulence models and their advantages in given situations. As an example, it is shown that a simple zero-equation model can be used for the prediction of special situations as flow with a low level of turbulence. A zero-equation model with compensation for room dimensions and velocity level also is discussed. A {kappa}-{epsilon} model expanded by damping functions is used to improve the prediction of the flow in a room ventilated by displacement ventilation. The damping functions especially take into account the turbulence level and the vertical temperature gradient. Low Reynolds number models (LNR models) are used to improve the prediction of evaporation-controlled emissions from building material, which is shown by an example. Finally, large eddy simulation (LES) of room airflow is discussed and demonstrated.

  14. Estimating vehicle roadside encroachment frequency using accident prediction models

    SciTech Connect (OSTI)

    Miaou, S.-P.

    1996-07-01

    The existing data to support the development of roadside encroachment- based accident models are extremely limited and largely outdated. Under the sponsorship of the Federal Highway Administration and Transportation Research Board, several roadside safety projects have attempted to address this issue by providing rather comprehensive data collection plans and conducting pilot data collection efforts. It is clear from the results of these studies that the required field data collection efforts will be expensive. Furthermore, the validity of any field collected encroachment data may be questionable because of the technical difficulty to distinguish intentional from unintentional encroachments. This paper proposes an alternative method for estimating the basic roadside encroachment data without actually field collecting them. The method is developed by exploring the probabilistic relationships between a roadside encroachment event and a run-off-the-road event With some mild assumptions, the method is capable of providing a wide range of basic encroachment data from conventional accident prediction models. To illustrate the concept and use of such a method, some basic encroachment data are estimated for rural two-lane undivided roads. In addition, the estimated encroachment data are compared with the existing collected data. The illustration shows that the method described in this paper can be a viable approach to estimating basic encroachment data without actually collecting them which can be very costly.

  15. Sandia's ice sheet modeling of Greenland, Antarctica helps predict

    National Nuclear Security Administration (NNSA)

    sea-level rise | National Nuclear Security Administration | (NNSA) Sandia's ice sheet modeling of Greenland, Antarctica helps predict sea-level rise Wednesday, March 2, 2016 - 12:00am Sandia California researchers Irina Tezaur and Ray Tuminaro analyze a model of Antarctica. They are part of a Sandia team working to improve the reliability and efficiency of computational models that describe ice sheet behavior and dynamics. The Greenland and Antarctic ice sheets will make a dominant

  16. A comparison of Unified creep-plasticity and conventional creep models for rock salt based on predictions of creep behavior measured in several in situ and bench-scale experiments

    SciTech Connect (OSTI)

    Morgan, H.S.; Krieg, R.D.

    1988-04-01

    A unified creep-plasticity (UCP) model, a conventional elastic-secondary creep (ESC) model, and an elastic-secondary creep model with greatly reduced elastic moduli (RESC model) are used to compute creep responses for five experimental configurations in which rock salt is subjected to several different complex loadings. The UCP model is exercised with three sets of model parameters. Two sets are for salt from the site of the Waste Isolation Pilot Plant (WIPP) in southeastern New Mexico, and the third is for salt from Avery Island, Louisiana. The WIPP reference secondary creep parameters are used in both the EC and RESC models. The WIPP reference values for the elastic moduli are also used in the ESC model. These moduli are divided by 12.5 in the RESC model. The geometrical configurations include the South Drift at the WIPP site, a hypothetical shaft in rock salt, a large hollow cylinder of rock salt subjected to external pressure while still in the floor of a drift at Avery Island, Louisiana, a laboratory-scale hollow cylinder subjected to external pressure, and a model pillar of salt subjected to axial load. Measured creep responses are available for all of these experiments except the hypothetical shaft. In all cases, deformations computed with the UCP model are much larger than the ESC predictions and are in better agreement with the data. The RESC model also produces larger deformations than the ESC model, and for the South Drift, the RESC predictions agree well with measured closures. 46 refs., 19 figs., 2 tabs.

  17. Lepton Flavor Violation in Predictive SUSY-GUT Models

    SciTech Connect (OSTI)

    Albright, Carl H.; Chen, Mu-Chun; /UC, Irvine

    2008-02-01

    There have been many theoretical models constructed which aim to explain the neutrino masses and mixing patterns. While many of the models will be eliminated once more accurate determinations of the mixing parameters, especially sin{sup 2} 2{theta}{sub 13}, are obtained, charged lepton flavor violation (LFV) experiments are able to differentiate even further among the models. In this paper, they investigate various rare LFV processes, such as {ell}{sub i} {yields} {ell}{sub j} + {gamma} and {mu} - e conversion, in five predictive SUSY SO(10) models and their allowed soft SUSY breaking parameter space in the constrained minimal SUSY standard model (CMSSM). Utilizing the WMAP dark matter constraints, they obtain lower bounds on the branching ratios of these rare processes and find that at least three of the five models they consider give rise to predictions for {mu} {yields} e + {gamma} that will be tested by the MEG collaboration at PSI. in addition, the next generation {mu} - e conversion experiment has sensitivity to the predictions of all five models, making it an even more robust way to test these models. While generic studies have emphasized the dependence of the branching ratios of these rare processes on the reactor neutrino angle, {theta}{sub 13}, and the mass of the heaviest right-handed neutrino, M{sub 3}, they find very massive M{sub 3} is more significant than large {theta}{sub 13} in leading to branching ratios near to the present upper limits.

  18. Microsoft Word - NRAP-TRS-I-005-2014_Use of Science-Based Prediction...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Use of Science-Based Prediction to Characterize Reservoir Behavior as a Function of ... H.; Zhang, Y.; Guthrie, G. Use of Science-Based Prediction to Characterize ...

  19. Product component genealogy modeling and field-failure prediction

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    King, Caleb; Hong, Yili; Meeker, William Q.

    2016-04-13

    Many industrial products consist of multiple components that are necessary for system operation. There is an abundance of literature on modeling the lifetime of such components through competing risks models. During the life-cycle of a product, it is common for there to be incremental design changes to improve reliability, to reduce costs, or due to changes in availability of certain part numbers. These changes can affect product reliability but are often ignored in system lifetime modeling. By incorporating this information about changes in part numbers over time (information that is readily available in most production databases), better accuracy can bemore » achieved in predicting time to failure, thus yielding more accurate field-failure predictions. This paper presents methods for estimating parameters and predictions for this generational model and a comparison with existing methods through the use of simulation. Our results indicate that the generational model has important practical advantages and outperforms the existing methods in predicting field failures.« less

  20. The origins of computer weather prediction and climate modeling

    SciTech Connect (OSTI)

    Lynch, Peter [Meteorology and Climate Centre, School of Mathematical Sciences, University College Dublin, Belfield (Ireland)], E-mail: Peter.Lynch@ucd.ie

    2008-03-20

    Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.

  1. Principles of models based engineering

    SciTech Connect (OSTI)

    Dolin, R.M.; Hefele, J.

    1996-11-01

    This report describes a Models Based Engineering (MBE) philosophy and implementation strategy that has been developed at Los Alamos National Laboratory`s Center for Advanced Engineering Technology. A major theme in this discussion is that models based engineering is an information management technology enabling the development of information driven engineering. Unlike other information management technologies, models based engineering encompasses the breadth of engineering information, from design intent through product definition to consumer application.

  2. Mathematical approaches for complexity/predictivity trade-offs in complex system models : LDRD final report.

    SciTech Connect (OSTI)

    Goldsby, Michael E.; Mayo, Jackson R.; Bhattacharyya, Arnab; Armstrong, Robert C.; Vanderveen, Keith

    2008-09-01

    The goal of this research was to examine foundational methods, both computational and theoretical, that can improve the veracity of entity-based complex system models and increase confidence in their predictions for emergent behavior. The strategy was to seek insight and guidance from simplified yet realistic models, such as cellular automata and Boolean networks, whose properties can be generalized to production entity-based simulations. We have explored the usefulness of renormalization-group methods for finding reduced models of such idealized complex systems. We have prototyped representative models that are both tractable and relevant to Sandia mission applications, and quantified the effect of computational renormalization on the predictive accuracy of these models, finding good predictivity from renormalized versions of cellular automata and Boolean networks. Furthermore, we have theoretically analyzed the robustness properties of certain Boolean networks, relevant for characterizing organic behavior, and obtained precise mathematical constraints on systems that are robust to failures. In combination, our results provide important guidance for more rigorous construction of entity-based models, which currently are often devised in an ad-hoc manner. Our results can also help in designing complex systems with the goal of predictable behavior, e.g., for cybersecurity.

  3. Predictive Models of Li-ion Battery Lifetime (Presentation)

    SciTech Connect (OSTI)

    Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Shi, Y.; Pesaran, A.

    2014-09-01

    Predictive models of Li-ion battery reliability must consider a multiplicity of electrochemical, thermal and mechanical degradation modes experienced by batteries in application environments. Complicating matters, Li-ion batteries can experience several path dependent degradation trajectories dependent on storage and cycling history of the application environment. Rates of degradation are controlled by factors such as temperature history, electrochemical operating window, and charge/discharge rate. Lacking accurate models and tests, lifetime uncertainty must be absorbed by overdesign and warranty costs. Degradation models are needed that predict lifetime more accurately and with less test data. Models should also provide engineering feedback for next generation battery designs. This presentation reviews both multi-dimensional physical models and simpler, lumped surrogate models of battery electrochemical and mechanical degradation. Models are compared with cell- and pack-level aging data from commercial Li-ion chemistries. The analysis elucidates the relative importance of electrochemical and mechanical stress-induced degradation mechanisms in real-world operating environments. Opportunities for extending the lifetime of commercial battery systems are explored.

  4. Predictive Materials Modeling for Li-Air Battery Systems | Argonne

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Leadership Computing Facility electron density obtained from a density functional theory Shown here is the electron density obtained from a density functional theory (DFT) calculation of lithium oxide (Li2O) performed with the GPAW code. This visualization was the result of a simulation run on Intrepid, a supercomputer at the Argonne Leadership Computing Facility. Kah Chun Lau, Aaron Knoll and Larry A. Curtiss, Argonne National Laboratory Predictive Materials Modeling for Li-Air Battery

  5. Predictive Materials Modeling for Li-Air Battery Systems | Argonne

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Leadership Computing Facility Predictive Materials Modeling for Li-Air Battery Systems PI Name: Larry Curtiss PI Email: curtiss@anl.gov Institution: Argonne National Laboratory Allocation Program: INCITE Allocation Hours at ALCF: 50 Million Year: 2015 Research Domain: Materials Science A rechargeable lithium-air (Li-air) battery can potentially store five to ten times the energy of a lithium-ion (Li-ion) battery of the same weight. Realizing this enormous potential presents a challenging

  6. NREL: Transportation Research - NREL's Battery Life Predictive Model Helps

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Companies Take Charge NREL's Battery Life Predictive Model Helps Companies Take Charge October 26, 2015 A series of batteries hooked together next to a monitor. An example of a stationary, grid-connected battery is the NREL project from Erigo/EaglePicher Technologies, LLC Technologies. Inverters and nickel cadmium batteries inside of a utility scale 300 kW battery storage system will support Department of Defense micro-grids. Photo by Dennis Schroeder / NREL 32696 Companies that rely on

  7. Predictive based monitoring of nuclear plant component degradation using support vector regression

    SciTech Connect (OSTI)

    Agarwal, Vivek; Alamaniotis, Miltiadis; Tsoukalas, Lefteri H.

    2015-02-01

    Nuclear power plants (NPPs) are large installations comprised of many active and passive assets. Degradation monitoring of all these assets is expensive (labor cost) and highly demanding task. In this paper a framework based on Support Vector Regression (SVR) for online surveillance of critical parameter degradation of NPP components is proposed. In this case, on time replacement or maintenance of components will prevent potential plant malfunctions, and reduce the overall operational cost. In the current work, we apply SVR equipped with a Gaussian kernel function to monitor components. Monitoring includes the one-step-ahead prediction of the component’s respective operational quantity using the SVR model, while the SVR model is trained using a set of previous recorded degradation histories of similar components. Predictive capability of the model is evaluated upon arrival of a sensor measurement, which is compared to the component failure threshold. A maintenance decision is based on a fuzzy inference system that utilizes three parameters: (i) prediction evaluation in the previous steps, (ii) predicted value of the current step, (iii) and difference of current predicted value with components failure thresholds. The proposed framework will be tested on turbine blade degradation data.

  8. Knowledge-based prediction of plan quality metrics in intracranial stereotactic radiosurgery

    SciTech Connect (OSTI)

    Shiraishi, Satomi; Moore, Kevin L.; Tan, Jun; Olsen, Lindsey A.

    2015-02-15

    Purpose: The objective of this work was to develop a comprehensive knowledge-based methodology for predicting achievable dose–volume histograms (DVHs) and highly precise DVH-based quality metrics (QMs) in stereotactic radiosurgery/radiotherapy (SRS/SRT) plans. Accurate QM estimation can identify suboptimal treatment plans and provide target optimization objectives to standardize and improve treatment planning. Methods: Correlating observed dose as it relates to the geometric relationship of organs-at-risk (OARs) to planning target volumes (PTVs) yields mathematical models to predict achievable DVHs. In SRS, DVH-based QMs such as brain V{sub 10Gy} (volume receiving 10 Gy or more), gradient measure (GM), and conformity index (CI) are used to evaluate plan quality. This study encompasses 223 linear accelerator-based SRS/SRT treatment plans (SRS plans) using volumetric-modulated arc therapy (VMAT), representing 95% of the institution’s VMAT radiosurgery load from the past four and a half years. Unfiltered models that use all available plans for the model training were built for each category with a stratification scheme based on target and OAR characteristics determined emergently through initial modeling process. Model predictive accuracy is measured by the mean and standard deviation of the difference between clinical and predicted QMs, δQM = QM{sub clin} − QM{sub pred}, and a coefficient of determination, R{sup 2}. For categories with a large number of plans, refined models are constructed by automatic elimination of suspected suboptimal plans from the training set. Using the refined model as a presumed achievable standard, potentially suboptimal plans are identified. Predictions of QM improvement are validated via standardized replanning of 20 suspected suboptimal plans based on dosimetric predictions. The significance of the QM improvement is evaluated using the Wilcoxon signed rank test. Results: The most accurate predictions are obtained when plans are

  9. Model Predictive Control of Integrated Gasification Combined Cycle Power Plants

    SciTech Connect (OSTI)

    B. Wayne Bequette; Priyadarshi Mahapatra

    2010-08-31

    The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.

  10. QMC Simulations Database for Predictive Modeling and Theory | Argonne

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Leadership Computing Facility DMC spin densities for antiferromagnetic states AF1 (left) and AF3 (right) DMC spin densities for antiferromagnetic states AF1 (left) and AF3 (right). Shown only atoms with a non-null spin. The picture shows the localization of the spins in d-orbital. Blue is a spin down, while yellow is a spin up. Anouar Benali, Argonne National Laboratory QMC Simulations Database for Predictive Modeling and Theory PI Name: David Ceperley PI Email: ceperley@illinois.edu

  11. An Energy Based Fatigue Life Prediction Framework for In-Service Structural Components

    SciTech Connect (OSTI)

    H. Ozaltun; M. H.H. Shen; T. George; C. Cross

    2011-06-01

    An energy based fatigue life prediction framework has been developed for calculation of remaining fatigue life of in service gas turbine materials. The purpose of the life prediction framework is to account aging effect caused by cyclic loadings on fatigue strength of gas turbine engines structural components which are usually designed for very long life. Previous studies indicate the total strain energy dissipated during a monotonic fracture process and a cyclic process is a material property that can be determined by measuring the area underneath the monotonic true stress-strain curve and the sum of the area within each hysteresis loop in the cyclic process, respectively. The energy-based fatigue life prediction framework consists of the following entities: (1) development of a testing procedure to achieve plastic energy dissipation per life cycle and (2) incorporation of an energy-based fatigue life calculation scheme to determine the remaining fatigue life of in-service gas turbine materials. The accuracy of the remaining fatigue life prediction method was verified by comparison between model approximation and experimental results of Aluminum 6061-T6. The comparison shows promising agreement, thus validating the capability of the framework to produce accurate fatigue life prediction.

  12. Statistical model selection for better prediction and discovering science mechanisms that affect reliability

    SciTech Connect (OSTI)

    Anderson-Cook, Christine M.; Morzinski, Jerome; Blecker, Kenneth D.

    2015-08-19

    Understanding the impact of production, environmental exposure and age characteristics on the reliability of a population is frequently based on underlying science and empirical assessment. When there is incomplete science to prescribe which inputs should be included in a model of reliability to predict future trends, statistical model/variable selection techniques can be leveraged on a stockpile or population of units to improve reliability predictions as well as suggest new mechanisms affecting reliability to explore. We describe a five-step process for exploring relationships between available summaries of age, usage and environmental exposure and reliability. The process involves first identifying potential candidate inputs, then second organizing data for the analysis. Third, a variety of models with different combinations of the inputs are estimated, and fourth, flexible metrics are used to compare them. As a result, plots of the predicted relationships are examined to distill leading model contenders into a prioritized list for subject matter experts to understand and compare. The complexity of the model, quality of prediction and cost of future data collection are all factors to be considered by the subject matter experts when selecting a final model.

  13. Statistical model selection for better prediction and discovering science mechanisms that affect reliability

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Anderson-Cook, Christine M.; Morzinski, Jerome; Blecker, Kenneth D.

    2015-08-19

    Understanding the impact of production, environmental exposure and age characteristics on the reliability of a population is frequently based on underlying science and empirical assessment. When there is incomplete science to prescribe which inputs should be included in a model of reliability to predict future trends, statistical model/variable selection techniques can be leveraged on a stockpile or population of units to improve reliability predictions as well as suggest new mechanisms affecting reliability to explore. We describe a five-step process for exploring relationships between available summaries of age, usage and environmental exposure and reliability. The process involves first identifying potential candidatemore » inputs, then second organizing data for the analysis. Third, a variety of models with different combinations of the inputs are estimated, and fourth, flexible metrics are used to compare them. As a result, plots of the predicted relationships are examined to distill leading model contenders into a prioritized list for subject matter experts to understand and compare. The complexity of the model, quality of prediction and cost of future data collection are all factors to be considered by the subject matter experts when selecting a final model.« less

  14. GIS-Based Infrastructure Modeling

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    GIS-Based Infrastructure Modeling Hydrogen Scenario Meeting August 9-10, 2006 Keith Parks, NREL GIS-Based Infrastructure Modeling * Station Analysis - Selection Criteria - Los Angeles * By 2015 (10 & 20 Station Layouts) * By 2025 (100 & 600 Station Layouts) - NYC * Early Infrastructure (20 stations) Comparison * Station Layouts (SMR, Liquid, Pipeline) * Delivery Discussion Station Selection Criteria * Consumer strategy attributes rated good and above * Proximal to major civic airports *

  15. Predictive modeling of reactive wetting and metal joining.

    SciTech Connect (OSTI)

    van Swol, Frank B.

    2013-09-01

    The performance, reproducibility and reliability of metal joints are complex functions of the detailed history of physical processes involved in their creation. Prediction and control of these processes constitutes an intrinsically challenging multi-physics problem involving heating and melting a metal alloy and reactive wetting. Understanding this process requires coupling strong molecularscale chemistry at the interface with microscopic (diffusion) and macroscopic mass transport (flow) inside the liquid followed by subsequent cooling and solidification of the new metal mixture. The final joint displays compositional heterogeneity and its resulting microstructure largely determines the success or failure of the entire component. At present there exists no computational tool at Sandia that can predict the formation and success of a braze joint, as current capabilities lack the ability to capture surface/interface reactions and their effect on interface properties. This situation precludes us from implementing a proactive strategy to deal with joining problems. Here, we describe what is needed to arrive at a predictive modeling and simulation capability for multicomponent metals with complicated phase diagrams for melting and solidification, incorporating dissolutive and composition-dependent wetting.

  16. Mining Behavior Based Safety Data to Predict Safety Performance

    SciTech Connect (OSTI)

    Jeffrey C. Joe

    2010-06-01

    The Idaho National Laboratory (INL) operates a behavior based safety program called Safety Observations Achieve Results (SOAR). This peer-to-peer observation program encourages employees to perform in-field observations of each other's work practices and habits (i.e., behaviors). The underlying premise of conducting these observations is that more serious accidents are prevented from occurring because lower level “at risk” behaviors are identified and corrected before they can propagate into culturally accepted “unsafe” behaviors that result in injuries or fatalities. Although the approach increases employee involvement in safety, the premise of the program has not been subject to sufficient empirical evaluation. The INL now has a significant amount of SOAR data on these lower level “at risk” behaviors. This paper describes the use of data mining techniques to analyze these data to determine whether they can predict if and when a more serious accident will occur.

  17. Differential Angstrom model for predicting insolation from hours of sunshine

    SciTech Connect (OSTI)

    Yeboah-Amankwah, D.; Agyeman, K.

    1990-01-01

    The Angstrom model for predicting insolation is limited in scope because it gives equal weighting to sunshine hours recorded at any time of the day. The differential Angstrom model presented in this paper removes this limitation and relates insolation, q{sub j}, in the j{sup th} hour to the sunshine duration, n{sub j}, of the same period by the equation: q{sub j} = a{sub j} + b{sub j}. By regression analysis of monthly data, the set of constants a{sub j} and b{sub j} for each hour of each month of the year can be determined. Thus, using the appropriate set of a and b regression coefficients, any sunshine data can be transformed to insolation. The sum of the equation over a day gives the daily insolation from which monthly means can be calculated. The method has been applied to the 1986 and 1988 sunshine data recorded at the University of Papua New Guinea to predict the observed insolation to within 3.5%. The differential Angstrom method has applications in places which have much recorded data on hours of sunshine but have limited observed insolation data.

  18. Collaborative Research. Separating Forced and Unforced Decadal Predictability in Models and Observations

    SciTech Connect (OSTI)

    DelSole, Timothy

    2015-08-31

    The purpose of the proposed research was to identify unforced predictable components on decadal time scales, distinguish these components from forced predictable components, and to assess the reliability of model predictions of these components. The question of whether anthropogenic forcing changes decadal predictability, or gives rise to new forms of decadal predictability, also will be

  19. Adsorption of selected pharmaceuticals and an endocrine disrupting compound by granular activated carbon. 2. Model prediction

    SciTech Connect (OSTI)

    Yu, Z.; Peldszus, S.; Huck, P.M.

    2009-03-01

    The adsorption of two representative pharmaceutically active compounds (PhACs) naproxen and carbamazepine and one endocrine disrupting compound (EDC) nonylphenol was studied in pilot-scale granular activated carbon (GAC) adsorbers using post-sedimentation (PS) water from a full-scale drinking water treatment plant. The GAC adsorbents were coal-based Calgon Filtrasorb 400 and coconut shell-based PICA CTIF TE. Acidic naproxen broke through fastest while nonylphenol was removed best, which was consistent with the degree to which fouling affected compound removals. Model predictions and experimental data were generally in good agreement for all three compounds, which demonstrated the effectiveness and robustness of the pore and surface diffusion model (PSDM) used in combination with the time-variable parameter approach for predicting removals at environmentally relevant concentrations (i.e., ng/L range). Sensitivity analyses suggested that accurate determination of film diffusion coefficients was critical for predicting breakthrough for naproxen and carbamazepine, in particular when high removals are targeted. Model simulations demonstrated that GAC carbon usage rates (CURs) for naproxen were substantially influenced by the empty bed contact time (EBCT) at the investigated conditions. Model-based comparisons between GAC CURs and minimum CURs for powdered activated carbon (PAC) applications suggested that PAC would be most appropriate for achieving 90% removal of naproxen, whereas GAC would be more suitable for nonylphenol. 25 refs., 4 figs., 1 tab.

  20. Development of a land ice core for the Model for Prediction Across...

    Office of Scientific and Technical Information (OSTI)

    a land ice core for the Model for Prediction Across Scales (MPAS) Citation Details In-Document Search Title: Development of a land ice core for the Model for Prediction Across Scales ...

  1. Development of a land ice core for the Model for Prediction Across...

    Office of Scientific and Technical Information (OSTI)

    for the Model for Prediction Across Scales (MPAS) Citation Details In-Document Search Title: Development of a land ice core for the Model for Prediction Across Scales (MPAS) No ...

  2. Land-ice modeling for sea-level prediction (Technical Report...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Land-ice modeling for sea-level prediction Citation Details In-Document Search Title: Land-ice modeling for sea-level prediction Authors: Lipscomb, William H 1 ...

  3. RESIDUA UPGRADING EFFICIENCY IMPROVEMENT MODELS: COKE FORMATION PREDICTABILITY MAPS

    SciTech Connect (OSTI)

    John F. Schabron; A. Troy Pauli; Joseph F. Rovani Jr.

    2002-05-01

    The dispersed particle solution model of petroleum residua structure was used to develop predictors for pyrolytic coke formation. Coking Indexes were developed in prior years that measure how near a pyrolysis system is to coke formation during the coke formation induction period. These have been demonstrated to be universally applicable for residua regardless of the source of the material. Coking onset is coincidental with the destruction of the ordered structure and the formation of a multiphase system. The amount of coke initially formed appears to be a function of the free solvent volume of the original residua. In the current work, three-dimensional coke make predictability maps were developed at 400 C, 450 C, and 500 C (752 F, 842 F, and 932 F). These relate residence time and free solvent volume to the amount of coke formed at a particular pyrolysis temperature. Activation energies for two apparent types of zero-order coke formation reactions were estimated. The results provide a new tool for ranking residua, gauging proximity to coke formation, and predicting initial coke make tendencies.

  4. Optimal Control of Distributed Energy Resources using Model Predictive Control

    SciTech Connect (OSTI)

    Mayhorn, Ebony T.; Kalsi, Karanjit; Elizondo, Marcelo A.; Zhang, Wei; Lu, Shuai; Samaan, Nader A.; Butler-Purry, Karen

    2012-07-22

    In an isolated power system (rural microgrid), Distributed Energy Resources (DERs) such as renewable energy resources (wind, solar), energy storage and demand response can be used to complement fossil fueled generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation. The problem is formulated as a multi-objective optimization problem with the goals of minimizing fuel costs and changes in power output of diesel generators, minimizing costs associated with low battery life of energy storage and maintaining system frequency at the nominal operating value. Two control modes are considered for controlling the energy storage to compensate either net load variability or wind variability. Model predictive control (MPC) is used to solve the aforementioned problem and the performance is compared to an open-loop look-ahead dispatch problem. Simulation studies using high and low wind profiles, as well as, different MPC prediction horizons demonstrate the efficacy of the closed-loop MPC in compensating for uncertainties in wind and demand.

  5. Adaptive model predictive process control using neural networks

    DOE Patents [OSTI]

    Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.

    1997-01-01

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.

  6. Adaptive model predictive process control using neural networks

    DOE Patents [OSTI]

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  7. Aquatic pathways model to predict the fate of phenolic compounds

    SciTech Connect (OSTI)

    Aaberg, R.L.; Peloquin, R.A.; Strenge, D.L.; Mellinger, P.J.

    1983-04-01

    Organic materials released from energy-related activities could affect human health and the environment. To better assess possible impacts, we developed a model to predict the fate of spills or discharges of pollutants into flowing or static bodies of fresh water. A computer code, Aquatic Pathways Model (APM), was written to implement the model. The computer programs use compartmental analysis to simulate aquatic ecosystems. The APM estimates the concentrations of chemicals in fish tissue, water and sediment, and is therefore useful for assessing exposure to humans through aquatic pathways. The APM will consider any aquatic pathway for which the user has transport data. Additionally, APM will estimate transport rates from physical and chemical properties of chemicals between several key compartments. The major pathways considered are biodegradation, fish and sediment uptake, photolysis, and evaporation. The model has been implemented with parameters for distribution of phenols, an important class of compounds found in the water-soluble fractions of coal liquids. Current modeling efforts show that, in comparison with many pesticides and polyaromatic hydrocarbons (PAH), the lighter phenolics (the cresols) are not persistent in the environment. The properties of heavier molecular weight phenolics (indanols, naphthols) are not well enough understood at this time to make similar judgements. For the twelve phenolics studied, biodegradation appears to be the major pathway for elimination from aquatic environments. A pond system simulation (using APM) of a spill of solvent refined coal (SRC-II) materials indicates that phenol, cresols, and other single cyclic phenolics are degraded to 16 to 25 percent of their original concentrations within 30 hours. Adsorption of these compounds into sediments and accumulation by fish was minor.

  8. Results from baseline tests of the SPRE I and comparison with code model predictions

    SciTech Connect (OSTI)

    Cairelli, J.E.; Geng, S.M.; Skupinski, R.C.

    1994-09-01

    The Space Power Research Engine (SPRE), a free-piston Stirling engine with linear alternator, is being tested at the NASA Lewis Research Center as part of the Civil Space Technology Initiative (CSTI) as a candidate for high capacity space power. This paper presents results of base-line engine tests at design and off-design operating conditions. The test results are compared with code model predictions.

  9. Reliability analysis and prediction of mixed mode load using Markov Chain Model

    SciTech Connect (OSTI)

    Nikabdullah, N.; Singh, S. S. K.; Alebrahim, R.; Azizi, M. A.; K, Elwaleed A.; Noorani, M. S. M.

    2014-06-19

    The aim of this paper is to present the reliability analysis and prediction of mixed mode loading by using a simple two state Markov Chain Model for an automotive crankshaft. The reliability analysis and prediction for any automotive component or structure is important for analyzing and measuring the failure to increase the design life, eliminate or reduce the likelihood of failures and safety risk. The mechanical failures of the crankshaft are due of high bending and torsion stress concentration from high cycle and low rotating bending and torsional stress. The Markov Chain was used to model the two states based on the probability of failure due to bending and torsion stress. In most investigations it revealed that bending stress is much serve than torsional stress, therefore the probability criteria for the bending state would be higher compared to the torsion state. A statistical comparison between the developed Markov Chain Model and field data was done to observe the percentage of error. The reliability analysis and prediction was derived and illustrated from the Markov Chain Model were shown in the Weibull probability and cumulative distribution function, hazard rate and reliability curve and the bathtub curve. It can be concluded that Markov Chain Model has the ability to generate near similar data with minimal percentage of error and for a practical application; the proposed model provides a good accuracy in determining the reliability for the crankshaft under mixed mode loading.

  10. Predicting adenocarcinoma recurrence using computational texture models of nodule components in lung CT

    SciTech Connect (OSTI)

    Depeursinge, Adrien; Yanagawa, Masahiro; Leung, Ann N.; Rubin, Daniel L.

    2015-04-15

    Purpose: To investigate the importance of presurgical computed tomography (CT) intensity and texture information from ground-glass opacities (GGO) and solid nodule components for the prediction of adenocarcinoma recurrence. Methods: For this study, 101 patients with surgically resected stage I adenocarcinoma were selected. During the follow-up period, 17 patients had disease recurrence with six associated cancer-related deaths. GGO and solid tumor components were delineated on presurgical CT scans by a radiologist. Computational texture models of GGO and solid regions were built using linear combinations of steerable Riesz wavelets learned with linear support vector machines (SVMs). Unlike other traditional texture attributes, the proposed texture models are designed to encode local image scales and directions that are specific to GGO and solid tissue. The responses of the locally steered models were used as texture attributes and compared to the responses of unaligned Riesz wavelets. The texture attributes were combined with CT intensities to predict tumor recurrence and patient hazard according to disease-free survival (DFS) time. Two families of predictive models were compared: LASSO and SVMs, and their survival counterparts: Cox-LASSO and survival SVMs. Results: The best-performing predictive model of patient hazard was associated with a concordance index (C-index) of 0.81 ± 0.02 and was based on the combination of the steered models and CT intensities with survival SVMs. The same feature group and the LASSO model yielded the highest area under the receiver operating characteristic curve (AUC) of 0.8 ± 0.01 for predicting tumor recurrence, although no statistically significant difference was found when compared to using intensity features solely. For all models, the performance was found to be significantly higher when image attributes were based on the solid components solely versus using the entire tumors (p < 3.08 × 10{sup −5}). Conclusions: This study

  11. SIFTER search: a web server for accurate phylogeny-based protein function prediction

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

    2015-05-15

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access tomore » precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.« less

  12. SIFTER search: a web server for accurate phylogeny-based protein function prediction

    SciTech Connect (OSTI)

    Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

    2015-05-15

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access to precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.

  13. Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models

    SciTech Connect (OSTI)

    Xavier, MA; Trimboli, MS

    2015-07-01

    This paper introduces a novel application of model predictive control (MPC) to cell-level charging of a lithium-ion battery utilizing an equivalent circuit model of battery dynamics. The approach employs a modified form of the MPC algorithm that caters for direct feed-though signals in order to model near-instantaneous battery ohmic resistance. The implementation utilizes a 2nd-order equivalent circuit discrete-time state-space model based on actual cell parameters; the control methodology is used to compute a fast charging profile that respects input, output, and state constraints. Results show that MPC is well-suited to the dynamics of the battery control problem and further suggest significant performance improvements might be achieved by extending the result to electrochemical models. (C) 2015 Elsevier B.V. All rights reserved.

  14. Predictive model for ionic liquid extraction solvents for rare earth elements

    SciTech Connect (OSTI)

    Grabda, Mariusz; Oleszek, Sylwia; Panigrahi, Mrutyunjay; Kozak, Dmytro; Shibata, Etsuro; Nakamura, Takashi; Eckert, Franck

    2015-12-31

    The purpose of our study was to select the most effective ionic liquid extraction solvents for dysprosium (III) fluoride using a theoretical approach. Conductor-like Screening Model for Real Solvents (COSMO-RS), based on quantum chemistry and the statistical thermodynamics of predefined DyF{sub 3}-ionic liquid systems, was applied to reach the target. Chemical potentials of the salt were predicted in 4,400 different ionic liquids. On the base of these predictions set of ionic liquids’ ions, manifesting significant decrease of the chemical potentials, were selected. Considering the calculated physicochemical properties (hydrophobicity, viscosity) of the ionic liquids containing these specific ions, the most effective extraction solvents for liquid-liquid extraction of DyF{sub 3} were proposed. The obtained results indicate that the COSMO-RS approach can be applied to quickly screen the affinity of any rare earth element for a large number of ionic liquid systems, before extensive experimental tests.

  15. Model-based safety assessments

    SciTech Connect (OSTI)

    Carlson, D.D.; Jones, T.R.

    1998-04-01

    Sandia National Laboratories performs systems analysis of high risk, high consequence systems. In particular, Sandia is responsible for the engineering of nuclear weapons, exclusive of the explosive physics package. In meeting this responsibility, Sandia has developed fundamental approaches to safety and a process for evaluating safety based on modeling and simulation. These approaches provide confidence in the safety of our nuclear weapons. Similar concepts may be applied to improve the safety of other high consequence systems.

  16. Predicting individual action switching in covert and continuous interactive tasks using the fluid events model

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Radvansky, Gabriel A.; D’Mello, Sidney K.; Abbott, Robert G.; Bixler, Robert E.

    2016-01-27

    The Fluid Events Model is aimed at predicting changes in the actions people take on a moment-by-moment basis. In contrast with other research on action selection, this work does not investigate why some course of action was selected, but rather the likelihood of discontinuing the current course of action and selecting another in the near future. This is done using both task-based and experience-based factors. Prior work evaluated this model in the context of trial-by-trial, independent, interactive events, such as choosing how to copy a figure of a line drawing. In this paper, we extend this model to more covertmore » event experiences, such as reading narratives, as well as to continuous interactive events, such as playing a video game. To this end, the model was applied to existing data sets of reading time and event segmentation for written and picture stories. It was also applied to existing data sets of performance in a strategy board game, an aerial combat game, and a first person shooter game in which a participant’s current state was dependent on prior events. The results revealed that the model predicted behavior changes well, taking into account both the theoretically defined structure of the described events, as well as a person’s prior experience. Hence, theories of event cognition can benefit from efforts that take into account not only how events in the world are structured, but also how people experience those events.« less

  17. Stability of Ensemble Models Predicts Productivity of Enzymatic Systems

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Theisen, Matthew K.; Lafontaine Rivera, Jimmy G.; Liao, James C.

    2016-03-10

    Stability in a metabolic system may not be obtained if incorrect amounts of enzymes are used. Without stability, some metabolites may accumulate or deplete leading to the irreversible loss of the desired operating point. Even if initial enzyme amounts achieve a stable steady state, changes in enzyme amount due to stochastic variations or environmental changes may move the system to the unstable region and lose the steady-state or quasi-steady-state flux. This situation is distinct from the phenomenon characterized by typical sensitivity analysis, which focuses on the smooth change before loss of stability. Here we show that metabolic networks differ significantlymore » in their intrinsic ability to attain stability due to the network structure and kinetic forms, and that after achieving stability, some enzymes are prone to cause instability upon changes in enzyme amounts. We use Ensemble Modelling for Robustness Analysis (EMRA) to analyze stability in four cell-free enzymatic systems when enzyme amounts are changed. Loss of stability in continuous systems can lead to lower production even when the system is tested experimentally in batch experiments. The predictions of instability by EMRA are supported by the lower productivity in batch experimental tests. Finally, the EMRA method incorporates properties of network structure, including stoichiometry and kinetic form, but does not require specific parameter values of the enzymes.« less

  18. Eulerian CFD Models to Predict Thermophoretic Deposition of Soot...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    This paper describes an Eulerian axisymmetric method in Fluent(R) to predict the overall heat transfer reduction of a surrogate tube due to thermophoretic deposition of submicron ...

  19. DEFINING THE PLAYERS IN HIGHER-ORDER NETWORKS: PREDICTIVE MODELING FOR REVERSE ENGINEERING FUNCTIONAL INFLUENCE NETWORKS

    SciTech Connect (OSTI)

    McDermott, Jason E.; Costa, Michelle N.; Stevens, S.L.; Stenzel-Poore, Mary; Sanfilippo, Antonio P.

    2011-01-20

    A difficult problem that is currently growing rapidly due to the sharp increase in the amount of high-throughput data available for many systems is that of determining useful and informative causative influence networks. These networks can be used to predict behavior given observation of a small number of components, predict behavior at a future time point, or identify components that are critical to the functioning of the system under particular conditions. In these endeavors incorporating observations of systems from a wide variety of viewpoints can be particularly beneficial, but has often been undertaken with the objective of inferring networks that are generally applicable. The focus of the current work is to integrate both general observations and measurements taken for a particular pathology, that of ischemic stroke, to provide improved ability to produce useful predictions of systems behavior. A number of hybrid approaches have recently been proposed for network generation in which the Gene Ontology is used to filter or enrich network links inferred from gene expression data through reverse engineering methods. These approaches have been shown to improve the biological plausibility of the inferred relationships determined, but still treat knowledge-based and machine-learning inferences as incommensurable inputs. In this paper, we explore how further improvements may be achieved through a full integration of network inference insights achieved through application of the Gene Ontology and reverse engineering methods with specific reference to the construction of dynamic models of transcriptional regulatory networks. We show that integrating two approaches to network construction, one based on reverse-engineering from conditional transcriptional data, one based on reverse-engineering from in situ hybridization data, and another based on functional associations derived from Gene Ontology, using probabilities can improve results of clustering as evaluated by a

  20. Modelling hepatitis C therapy—predicting effects of treatment

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Perelson, Alan S.; Guedj, Jeremie

    2015-06-30

    Mathematically modelling changes in HCV RNA levels measured in patients who receive antiviral therapy has yielded many insights into the pathogenesis and effects of treatment on the virus. By determining how rapidly HCV is cleared when viral replication is interrupted by a therapy, one can deduce how rapidly the virus is produced in patients before treatment. This knowledge, coupled with estimates of the HCV mutation rate, enables one to estimate the frequency with which drug resistant variants arise. Modelling HCV also permits the deduction of the effectiveness of an antiviral agent at blocking HCV replication from the magnitude of themore » initial viral decline. One can also estimate the lifespan of an HCV-infected cell from the slope of the subsequent viral decline and determine the duration of therapy needed to cure infection. The original understanding of HCV RNA decline under interferon-based therapies obtained by modelling needed to be revised in order to interpret the HCV RNA decline kinetics seen when using direct-acting antiviral agents (DAAs). In addition, there also exist unresolved issues involving understanding therapies with combinations of DAAs, such as the presence of detectable HCV RNA at the end of therapy in patients who nonetheless have a sustained virologic response.« less

  1. Physics-based models of the plasmasphere

    SciTech Connect (OSTI)

    Jordanova, Vania K; Pierrard, Vivane; Goldstein, Jerry; Andr'e, Nicolas; Lemaire, Joseph F; Liemohn, Mike W; Matsui, H

    2008-01-01

    We describe recent progress in physics-based models of the plasmasphere using the Auid and the kinetic approaches. Global modeling of the dynamics and inAuence of the plasmasphere is presented. Results from global plasmasphere simulations are used to understand and quantify (i) the electric potential pattern and evolution during geomagnetic storms, and (ii) the inAuence of the plasmasphere on the excitation of electromagnetic ion cyclotron (ElvIIC) waves a.nd precipitation of energetic ions in the inner magnetosphere. The interactions of the plasmasphere with the ionosphere a.nd the other regions of the magnetosphere are pointed out. We show the results of simulations for the formation of the plasmapause and discuss the inAuence of plasmaspheric wind and of ultra low frequency (ULF) waves for transport of plasmaspheric material. Theoretical formulations used to model the electric field and plasma distribution in the plasmasphere are given. Model predictions are compared to recent CLUSTER and MAGE observations, but also to results of earlier models and satellite observations.

  2. Prediction of rodent carcinogenic potential of naturally occurring chemicals in the human diet using high-throughput QSAR predictive modeling

    SciTech Connect (OSTI)

    Valerio, Luis G. . E-mail: luis.valerio@FDA.HHS.gov; Arvidson, Kirk B.; Chanderbhan, Ronald F.; Contrera, Joseph F.

    2007-07-01

    Consistent with the U.S. Food and Drug Administration (FDA) Critical Path Initiative, predictive toxicology software programs employing quantitative structure-activity relationship (QSAR) models are currently under evaluation for regulatory risk assessment and scientific decision support for highly sensitive endpoints such as carcinogenicity, mutagenicity and reproductive toxicity. At the FDA's Center for Food Safety and Applied Nutrition's Office of Food Additive Safety and the Center for Drug Evaluation and Research's Informatics and Computational Safety Analysis Staff (ICSAS), the use of computational SAR tools for both qualitative and quantitative risk assessment applications are being developed and evaluated. One tool of current interest is MDL-QSAR predictive discriminant analysis modeling of rodent carcinogenicity, which has been previously evaluated for pharmaceutical applications by the FDA ICSAS. The study described in this paper aims to evaluate the utility of this software to estimate the carcinogenic potential of small, organic, naturally occurring chemicals found in the human diet. In addition, a group of 19 known synthetic dietary constituents that were positive in rodent carcinogenicity studies served as a control group. In the test group of naturally occurring chemicals, 101 were found to be suitable for predictive modeling using this software's discriminant analysis modeling approach. Predictions performed on these compounds were compared to published experimental evidence of each compound's carcinogenic potential. Experimental evidence included relevant toxicological studies such as rodent cancer bioassays, rodent anti-carcinogenicity studies, genotoxic studies, and the presence of chemical structural alerts. Statistical indices of predictive performance were calculated to assess the utility of the predictive modeling method. Results revealed good predictive performance using this software's rodent carcinogenicity module of over 1200 chemicals

  3. Impact of heterogeneous chemistry on model predictions of ozone changes

    SciTech Connect (OSTI)

    Granier, C.; Brasseur, G. )

    1992-11-20

    A two-dimensional chemical/transport model of the middle atmosphere is used to assess the importance of chemical heterogeneous processes in the polar regions (on polar stratospheric clouds (PSCs)) and at other latitudes (on sulfate aerosols). When conversion on type I and type II PSCs of N[sub 2]O[sub 5] into HNO[sub 3] and of CIONO[sub 2] into reactive forms of chlorine is taken into account, enhanced CIO concentrations lead to the formation of a springtime ozone hole over the Antarctic continent; no such major reduction in the ozone column is found in the Arctic region. When conversion of nitrogen and chlorine compounds is assumed to occur on sulfate particles in the lower stratosphere, significant perturbations in the chemistry are also found. For background aerosol conditions, the concentration of nitric acid is enhanced and agrees with observed values, while that of nitrogen oxides is reduced and agrees less than if heterogeneous processes are ignored in the calculations. The concentration of the OH radical is significantly increased. Ozone number density appears to become larger between 16 and 30 km but smaller below 16 km, especially at high latitudes. The ozone column is only slightly modified, except at high latitudes where it is substantially reduced if the CIONO[sub 2] conversion into reactive chlorine is considered. After a large volcanic eruption these changes are further exacerbated. The ozone budget in the lower stratrosphere becomes less affected by nitrogen oxides but is largely controlled by the CIO[sub x] and HO[sub x] chemistries. A substantial decrease in the ozone column is predicted as a result of the Pinatubo volcanic eruption, mostly in winter at middle and high latitudes. 62 refs., 18 figs., 3 tabs.

  4. In-Service Design & Performance Prediction of Advanced Fusion Material Systems by Computational Modeling and Simulation

    SciTech Connect (OSTI)

    G. R. Odette; G. E. Lucas

    2005-11-15

    This final report on "In-Service Design & Performance Prediction of Advanced Fusion Material Systems by Computational Modeling and Simulation" (DE-FG03-01ER54632) consists of a series of summaries of work that has been published, or presented at meetings, or both. It briefly describes results on the following topics: 1) A Transport and Fate Model for Helium and Helium Management; 2) Atomistic Studies of Point Defect Energetics, Dynamics and Interactions; 3) Multiscale Modeling of Fracture consisting of: 3a) A Micromechanical Model of the Master Curve (MC) Universal Fracture Toughness-Temperature Curve Relation, KJc(T - To), 3b) An Embrittlement DTo Prediction Model for the Irradiation Hardening Dominated Regime, 3c) Non-hardening Irradiation Assisted Thermal and Helium Embrittlement of 8Cr Tempered Martensitic Steels: Compilation and Analysis of Existing Data, 3d) A Model for the KJc(T) of a High Strength NFA MA957, 3e) Cracked Body Size and Geometry Effects of Measured and Effective Fracture Toughness-Model Based MC and To Evaluations of F82H and Eurofer 97, 3-f) Size and Geometry Effects on the Effective Toughness of Cracked Fusion Structures; 4) Modeling the Multiscale Mechanics of Flow Localization-Ductility Loss in Irradiation Damaged BCC Alloys; and 5) A Universal Relation Between Indentation Hardness and True Stress-Strain Constitutive Behavior. Further details can be found in the cited references or presentations that generally can be accessed on the internet, or provided upon request to the authors. Finally, it is noted that this effort was integrated with our base program in fusion materials, also funded by the DOE OFES.

  5. A Predictive Model of Fragmentation using Adaptive Mesh Refinement...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    A new arena for predictive simulations in high- powered laser systems "12 NIF" Or 96 ... Numerical simulations show how to mitigate damage from debris and shrapnel Damage prior to ...

  6. Mechanism-based classification of PAH mixtures to predict carcinogenic potential

    SciTech Connect (OSTI)

    Tilton, Susan C.; Siddens, Lisbeth K.; Krueger, Sharon K.; Larkin, Andrew J.; Löhr, Christiane V.; Williams, David E.; Baird, William M.; Waters, Katrina M.

    2015-04-22

    We have previously shown that relative potency factors and DNA adduct measurements are inadequate for predicting carcinogenicity of certain polycyclic aromatic hydrocarbons (PAHs) and PAH mixtures, particularly those that function through alternate pathways or exhibit greater promotional activity compared to benzo[a]pyrene (BaP). Therefore, we developed a pathway based approach for classification of tumor outcome after dermal exposure to PAH/mixtures. FVB/N mice were exposed to dibenzo[def,p]chrysene (DBC), BaP or environmental PAH mixtures (Mix 1-3) following a two-stage initiation/promotion skin tumor protocol. Resulting tumor incidence could be categorized by carcinogenic potency as DBC>>BaP=Mix2=Mix3>Mix1=Control, based on statistical significance. Gene expression profiles measured in skin of mice collected 12 h post-initiation were compared to tumor outcome for identification of short-term bioactivity profiles. A Bayesian integration model was utilized to identify biological pathways predictive of PAH carcinogenic potential during initiation. Integration of probability matrices from four enriched pathways (p<0.05) for DNA damage, apoptosis, response to chemical stimulus and interferon gamma signaling resulted in the highest classification accuracy with leave-one-out cross validation. This pathway-driven approach was successfully utilized to distinguish early regulatory events during initiation prognostic for tumor outcome and provides proof-of-concept for using short-term initiation studies to classify carcinogenic potential of environmental PAH mixtures. As a result, these data further provide a ‘source-to outcome’ model that could be used to predict PAH interactions during tumorigenesis and provide an example of how mode-of-action based risk assessment could be employed for environmental PAH mixtures.

  7. Mechanism-based classification of PAH mixtures to predict carcinogenic potential

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Tilton, Susan C.; Siddens, Lisbeth K.; Krueger, Sharon K.; Larkin, Andrew J.; Löhr, Christiane V.; Williams, David E.; Baird, William M.; Waters, Katrina M.

    2015-04-22

    We have previously shown that relative potency factors and DNA adduct measurements are inadequate for predicting carcinogenicity of certain polycyclic aromatic hydrocarbons (PAHs) and PAH mixtures, particularly those that function through alternate pathways or exhibit greater promotional activity compared to benzo[a]pyrene (BaP). Therefore, we developed a pathway based approach for classification of tumor outcome after dermal exposure to PAH/mixtures. FVB/N mice were exposed to dibenzo[def,p]chrysene (DBC), BaP or environmental PAH mixtures (Mix 1-3) following a two-stage initiation/promotion skin tumor protocol. Resulting tumor incidence could be categorized by carcinogenic potency as DBC>>BaP=Mix2=Mix3>Mix1=Control, based on statistical significance. Gene expression profiles measured inmore » skin of mice collected 12 h post-initiation were compared to tumor outcome for identification of short-term bioactivity profiles. A Bayesian integration model was utilized to identify biological pathways predictive of PAH carcinogenic potential during initiation. Integration of probability matrices from four enriched pathways (p<0.05) for DNA damage, apoptosis, response to chemical stimulus and interferon gamma signaling resulted in the highest classification accuracy with leave-one-out cross validation. This pathway-driven approach was successfully utilized to distinguish early regulatory events during initiation prognostic for tumor outcome and provides proof-of-concept for using short-term initiation studies to classify carcinogenic potential of environmental PAH mixtures. As a result, these data further provide a ‘source-to outcome’ model that could be used to predict PAH interactions during tumorigenesis and provide an example of how mode-of-action based risk assessment could be employed for environmental PAH mixtures.« less

  8. Mechanism-based classification of PAH mixtures to predict carcinogenic potential

    SciTech Connect (OSTI)

    Tilton, Susan C.; Siddens, Lisbeth K.; Krueger, Sharon K.; Larkin, Andrew J.; Lhr, Christiane V.; Williams, David E.; Baird, William M.; Waters, Katrina M.

    2015-04-22

    We have previously shown that relative potency factors and DNA adduct measurements are inadequate for predicting carcinogenicity of certain polycyclic aromatic hydrocarbons (PAHs) and PAH mixtures, particularly those that function through alternate pathways or exhibit greater promotional activity compared to benzo[a]pyrene (BaP). Therefore, we developed a pathway based approach for classification of tumor outcome after dermal exposure to PAH/mixtures. FVB/N mice were exposed to dibenzo[def,p]chrysene (DBC), BaP or environmental PAH mixtures (Mix 1-3) following a two-stage initiation/promotion skin tumor protocol. Resulting tumor incidence could be categorized by carcinogenic potency as DBC>>BaP=Mix2=Mix3>Mix1=Control, based on statistical significance. Gene expression profiles measured in skin of mice collected 12 h post-initiation were compared to tumor outcome for identification of short-term bioactivity profiles. A Bayesian integration model was utilized to identify biological pathways predictive of PAH carcinogenic potential during initiation. Integration of probability matrices from four enriched pathways (p<0.05) for DNA damage, apoptosis, response to chemical stimulus and interferon gamma signaling resulted in the highest classification accuracy with leave-one-out cross validation. This pathway-driven approach was successfully utilized to distinguish early regulatory events during initiation prognostic for tumor outcome and provides proof-of-concept for using short-term initiation studies to classify carcinogenic potential of environmental PAH mixtures. As a result, these data further provide a source-to outcome model that could be used to predict PAH interactions during tumorigenesis and provide an example of how mode-of-action based risk assessment could be employed for environmental PAH mixtures.

  9. Failure Predictions for VHTR Core Components using a Probabilistic Contiuum Damage Mechanics Model

    SciTech Connect (OSTI)

    Fok, Alex

    2013-10-30

    The proposed work addresses the key research need for the development of constitutive models and overall failure models for graphite and high temperature structural materials, with the long-term goal being to maximize the design life of the Next Generation Nuclear Plant (NGNP). To this end, the capability of a Continuum Damage Mechanics (CDM) model, which has been used successfully for modeling fracture of virgin graphite, will be extended as a predictive and design tool for the core components of the very high- temperature reactor (VHTR). Specifically, irradiation and environmental effects pertinent to the VHTR will be incorporated into the model to allow fracture of graphite and ceramic components under in-reactor conditions to be modeled explicitly using the finite element method. The model uses a combined stress-based and fracture mechanics-based failure criterion, so it can simulate both the initiation and propagation of cracks. Modern imaging techniques, such as x-ray computed tomography and digital image correlation, will be used during material testing to help define the baseline material damage parameters. Monte Carlo analysis will be performed to address inherent variations in material properties, the aim being to reduce the arbitrariness and uncertainties associated with the current statistical approach. The results can potentially contribute to the current development of American Society of Mechanical Engineers (ASME) codes for the design and construction of VHTR core components.

  10. Characterization and validation of an in silico toxicology model to predict the mutagenic potential of drug impurities*

    SciTech Connect (OSTI)

    Valerio, Luis G.; Cross, Kevin P.

    2012-05-01

    Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structureactivity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describe the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. -- Highlights: ? We characterize a new in silico model to predict mutagenicity of drug impurities. ? The model predicts Salmonella mutagenicity and will be useful for safety assessment. ? We examine toxicity fingerprints and toxicophores of this Ames assay model. ? We compare these attributes to those found in drug impurities known to FDA/CDER. ? We validate the model and find it has a desired predictive performance.

  11. Modeling the Number of Ignitions Following an Earthquake: Developing Prediction Limits for Overdispersed Count Data

    Broader source: Energy.gov [DOE]

    Modeling the Number of Ignitions Following an Earthquake: Developing Prediction Limits for Overdispersed Count Data Elizabeth J. Kelly and Raymond N. Tell

  12. Statistical surrogate models for prediction of high-consequence...

    Office of Scientific and Technical Information (OSTI)

    existing coupled atmospheric models due to the high computational cost of each simulation. ... CLIMATES; DIAGNOSIS; DISTRIBUTION; FORECASTING; GENERAL CIRCULATION MODELS; METRICS; ...

  13. Bulalo field, Philippines: Reservoir modeling for prediction of limits to sustainable generation

    SciTech Connect (OSTI)

    Strobel, Calvin J.

    1993-01-28

    The Bulalo geothermal field, located in Laguna province, Philippines, supplies 12% of the electricity on the island of Luzon. The first 110 MWe power plant was on line May 1979; current 330 MWe (gross) installed capacity was reached in 1984. Since then, the field has operated at an average plant factor of 76%. The National Power Corporation plans to add 40 MWe base load and 40 MWe standby in 1995. A numerical simulation model for the Bulalo field has been created that matches historic pressure changes, enthalpy and steam flash trends and cumulative steam production. Gravity modeling provided independent verification of mass balances and time rate of change of liquid desaturation in the rock matrix. Gravity modeling, in conjunction with reservoir simulation provides a means of predicting matrix dry out and the time to limiting conditions for sustainable levelized steam deliverability and power generation.

  14. Pharmacokinetic modeling: Prediction and evaluation of route dependent dosimetry of bisphenol A in monkeys with extrapolation to humans

    SciTech Connect (OSTI)

    Fisher, Jeffrey W. Twaddle, Nathan C.; Vanlandingham, Michelle; Doerge, Daniel R.

    2011-11-15

    A physiologically based pharmacokinetic (PBPK) model was developed for bisphenol A (BPA) in adult rhesus monkeys using intravenous (iv) and oral bolus doses of 100 {mu}g d6-BPA/kg (). This calibrated PBPK adult monkey model for BPA was then evaluated against published monkey kinetic studies with BPA. Using two versions of the adult monkey model based on monkey BPA kinetic data from and , the aglycone BPA pharmacokinetics were simulated for human oral ingestion of 5 mg d16-BPA per person (Voelkel et al., 2002). Voelkel et al. were unable to detect the aglycone BPA in plasma, but were able to detect BPA metabolites. These human model predictions of the aglycone BPA in plasma were then compared to previously published PBPK model predictions obtained by simulating the Voelkel et al. kinetic study. Our BPA human model, using two parameter sets reflecting two adult monkey studies, both predicted lower aglycone levels in human serum than the previous human BPA PBPK model predictions. BPA was metabolized at all ages of monkey (PND 5 to adult) by the gut wall and liver. However, the hepatic metabolism of BPA and systemic clearance of its phase II metabolites appear to be slower in younger monkeys than adults. The use of the current non-human primate BPA model parameters provides more confidence in predicting the aglycone BPA in serum levels in humans after oral ingestion of BPA. -- Highlights: Black-Right-Pointing-Pointer A bisphenol A (BPA) PBPK model for the infant and adult monkey was constructed. Black-Right-Pointing-Pointer The hepatic metabolic rate of BPA increased with age of the monkey. Black-Right-Pointing-Pointer The systemic clearance rate of metabolites increased with age of the monkey. Black-Right-Pointing-Pointer Gut wall metabolism of orally administered BPA was substantial across all ages of monkeys. Black-Right-Pointing-Pointer Aglycone BPA plasma concentrations were predicted in humans orally given oral doses of deuterated BPA.

  15. Prediction of global solar irradiance based on time series analysis: Application to solar thermal power plants energy production planning

    SciTech Connect (OSTI)

    Martin, Luis; Marchante, Ruth; Cony, Marco; Zarzalejo, Luis F.; Polo, Jesus; Navarro, Ana

    2010-10-15

    Due to strong increase of solar power generation, the predictions of incoming solar energy are acquiring more importance. Photovoltaic and solar thermal are the main sources of electricity generation from solar energy. In the case of solar thermal energy plants with storage energy system, its management and operation need reliable predictions of solar irradiance with the same temporal resolution as the temporal capacity of the back-up system. These plants can work like a conventional power plant and compete in the energy stock market avoiding intermittence in electricity production. This work presents a comparisons of statistical models based on time series applied to predict half daily values of global solar irradiance with a temporal horizon of 3 days. Half daily values consist of accumulated hourly global solar irradiance from solar raise to solar noon and from noon until dawn for each day. The dataset of ground solar radiation used belongs to stations of Spanish National Weather Service (AEMet). The models tested are autoregressive, neural networks and fuzzy logic models. Due to the fact that half daily solar irradiance time series is non-stationary, it has been necessary to transform it to two new stationary variables (clearness index and lost component) which are used as input of the predictive models. Improvement in terms of RMSD of the models essayed is compared against the model based on persistence. The validation process shows that all models essayed improve persistence. The best approach to forecast half daily values of solar irradiance is neural network models with lost component as input, except Lerida station where models based on clearness index have less uncertainty because this magnitude has a linear behaviour and it is easier to simulate by models. (author)

  16. Collaborative Research: Separating Forced and Unforced Decadal Predictability in Models and Observations

    SciTech Connect (OSTI)

    Tippett, Michael K.

    2014-04-09

    This report is a progress report of the accomplishments of the research grant “Collaborative Research: Separating Forced and Unforced Decadal Predictability in Models and Observa- tions” during the period 1 May 2011- 31 August 2013. This project is a collaborative one between Columbia University and George Mason University. George Mason University will submit a final technical report at the conclusion of their no-cost extension. The purpose of the proposed research is to identify unforced predictable components on decadal time scales, distinguish these components from forced predictable components, and to assess the reliability of model predictions of these components. Components of unforced decadal predictability will be isolated by maximizing the Average Predictability Time (APT) in long, multimodel control runs from state-of-the-art climate models. Components with decadal predictability have large APT, so maximizing APT ensures that components with decadal predictability will be detected. Optimal fingerprinting techniques, as used in detection and attribution analysis, will be used to separate variations due to natural and anthropogenic forcing from those due to unforced decadal predictability. This methodology will be applied to the decadal hindcasts generated by the CMIP5 project to assess the reliability of model projections. The question of whether anthropogenic forcing changes decadal predictability, or gives rise to new forms of decadal predictability, also will be investigated.

  17. PNNL: Mechanistic-Based Ductility Prediction for Complex Mg Castings...

    Broader source: Energy.gov (indexed) [DOE]

    and Vehicle Technologies Program Annual Merit Review and Peer Evaluation Meeting lm057sun2012o.pdf (3.7 MB) More Documents & Publications PNNL: Mechanistic-Based Ductility ...

  18. Agent-based Infrastructure Interdependency Model

    Energy Science and Technology Software Center (OSTI)

    2003-10-01

    The software is used to analyze infrastructure interdependencies. Agent-based modeling is used for the analysis.

  19. Using Models to Provide Predicted Ranges for Building-Human Interfaces: Preprint

    SciTech Connect (OSTI)

    Long, N.; Scheib, J.; Pless, S.; Schott, M.

    2013-09-01

    Most building energy consumption dashboards provide only a snapshot of building performance; whereas some provide more detailed historic data with which to compare current usage. This paper will discuss the Building Agent(tm) platform, which has been developed and deployed in a campus setting at the National Renewable Energy Laboratory as part of an effort to maintain the aggressive energyperformance achieved in newly constructed office buildings and laboratories. The Building Agent(tm) provides aggregated and coherent access to building data, including electric energy, thermal energy, temperatures, humidity, and lighting levels, and occupant feedback, which are displayed in various manners for visitors, building occupants, facility managers, and researchers. This paper focuseson the development of visualizations for facility managers, or an energy performance assurance role, where metered data are used to generate models that provide live predicted ranges of building performance by end use. These predicted ranges provide simple, visual context for displayed performance data without requiring users to also assess historical information or trends. Several energymodelling techniques were explored including static lookup-based performance targets, reduced-order models derived from historical data using main effect variables such as solar radiance for lighting performance, and integrated energy models using a whole-building energy simulation program.

  20. Performance of corrosion inhibiting admixtures for structural concrete -- assessment methods and predictive modeling

    SciTech Connect (OSTI)

    Yunovich, M.; Thompson, N.G.

    1998-12-31

    During the past fifteen years corrosion inhibiting admixtures (CIAs) have become increasingly popular for protection of reinforced components of highway bridges and other structures from damage induced by chlorides. However, there remains considerable debate about the benefits of CIAs in concrete. A variety of testing methods to assess the performance of CIA have been reported in the literature, ranging from tests in simulated pore solutions to long-term exposures of concrete slabs. The paper reviews the published techniques and recommends the methods which would make up a comprehensive CIA effectiveness testing program. The results of this set of tests would provide the data which can be used to rank the presently commercially available CIA and future candidate formulations utilizing a proposed predictive model. The model is based on relatively short-term laboratory testing and considers several phases of a service life of a structure (corrosion initiation, corrosion propagation without damage, and damage to the structure).

  1. SimTable helps firefighters model and predict fire direction

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    for modeling lung cancer. In other news December, 1 2015 - Novel therapy for stomach cancer; grand opening of Manhattan Project National Historical Park; 2015 Northern New...

  2. Kitaev models based on unitary quantum groupoids

    SciTech Connect (OSTI)

    Chang, Liang

    2014-04-15

    We establish a generalization of Kitaev models based on unitary quantum groupoids. In particular, when inputting a Kitaev-Kong quantum groupoid H{sub C}, we show that the ground state manifold of the generalized model is canonically isomorphic to that of the Levin-Wen model based on a unitary fusion category C. Therefore, the generalized Kitaev models provide realizations of the target space of the Turaev-Viro topological quantum field theory based on C.

  3. Simplified predictive models for CO2 sequestration performance assessment

    SciTech Connect (OSTI)

    Mishra, Srikanta; Ganesh, Priya; Schuetter, Jared; He, Jincong; Jin, Zhaoyang; Durlofsky, Louis J.

    2015-09-30

    Latin Hypercube sampling (LHS) based design with a multidimensional kriging metamodel fit. For roughly the same number of simulations, the LHS-based metamodel yields a more robust predictive model, as verified by a k-fold cross-validation approach (with data split into training and test sets) as well by validation with an independent dataset. In the third category, a reduced-order modeling procedure is utilized that combines proper orthogonal decomposition (POD) for reducing problem dimensionality with trajectory-piecewise linearization (TPWL) in order to represent system response at new control settings from a limited number of training runs. Significant savings in computational time are observed with reasonable accuracy from the PODTPWL reduced-order model for both vertical and horizontal well problems – which could be important in the context of history matching, uncertainty quantification and optimization problems. The simplified physics and statistical learning based models are also validated using an uncertainty analysis framework. Reference cumulative distribution functions of key model outcomes (i.e., plume radius and reservoir pressure buildup) generated using a 97-run full-physics simulation are successfully validated against the CDF from 10,000 sample probabilistic simulations using the simplified models. The main contribution of this research project is the development and validation of a portfolio of simplified modeling approaches that will enable rapid feasibility and risk assessment for CO2 sequestration in deep saline formations.

  4. Injection-Molded Long-Fiber Thermoplastic Composites: From Process Modeling to Prediction of Mechanical Properties

    SciTech Connect (OSTI)

    Nguyen, Ba Nghiep; Kunc, Vlastimil; Jin, Xiaoshi; Tucker III, Charles L.; Costa, Franco

    2013-12-18

    This article illustrates the predictive capabilities for long-fiber thermoplastic (LFT) composites that first simulate the injection molding of LFT structures by Autodesk Simulation Moldflow Insight (ASMI) to accurately predict fiber orientation and length distributions in these structures. After validating fiber orientation and length predictions against the experimental data, the predicted results are used by ASMI to compute distributions of elastic properties in the molded structures. In addition, local stress-strain responses and damage accumulation under tensile loading are predicted by an elastic-plastic damage model of EMTA-NLA, a nonlinear analysis tool implemented in ABAQUS via user-subroutines using an incremental Eshelby-Mori-Tanaka approach. Predicted stress-strain responses up to failure and damage accumulations are compared to the experimental results to validate the model.

  5. Vehicle Technologies Office Merit Review 2014: Mechanistic-based Ductility Prediction for Complex Mg Castings

    Broader source: Energy.gov [DOE]

    Presentation given by USAMP at 2014 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Office Annual Merit Review and Peer Evaluation Meeting about mechanistic-based ductility prediction...

  6. Prediction of hydrocarbon-bearing structures based on remote sensing

    SciTech Connect (OSTI)

    Smirnova, I.; Gololobov, Yu.; Rusanova, A. )

    1993-09-01

    The technology we developed is based on the use of remotely sensed data and has proved to be effective for identification of structures that appear promising for oil and gas, in particular, reefs in the hydrocarbon-bearing basin of central Asia (Turkmenistan and Uzbekistan). It implements the [open quotes]geoindication[close quotes] concept, the main idea being that landscape components (geoindicators) and subsurface geological features are correlated and depend on each other. Subsurface features (uplifts, depressions, faults, reefs, and other lithological and structural heterogeneities) cause physical and chemical alterations in overlying rocks up to the land surface; thus, they are reflected in distribution of landscape components and observed on airborne and satellite images as specific patterns. The following identified geoindicators are related to different subsurface geological features: definite formations, anticlines, and reefs (barrier, atoll, and bioherm). The geoindicators are extracted from images either visually or by using computer systems. Specially developed software is applied to analyze geoindicator distribution and calculate their characteristics. In the course of processing, it is possible to distinguish folds from reefs. Distribution of geoindicator characteristics is examined on the well studied reefs, and from the regularities, established promising areas with reefs are revealed. When applying the technology in central Asia, the results were successfully verified by field works, seismic methods, and drilling.

  7. Predictive Modeling of Terrestrial Radiation Exposure from Geologic Materials

    SciTech Connect (OSTI)

    Malchow, Russell L.; Haber, Daniel University of Nevada, Las Vegas; Burnley, Pamela; Marsac, Kara; Hausrath, Elisabeth; Adcock, Christopher

    2015-01-01

    Aerial gamma ray surveys are important for those working in nuclear security and industry for determining locations of both anthropogenic radiological sources and natural occurrences of radionuclides. During an aerial gamma ray survey, a low flying aircraft, such as a helicopter, flies in a linear pattern across the survey area while measuring the gamma emissions with a sodium iodide (NaI) detector. Currently, if a gamma ray survey is being flown in an area, the only way to correct for geologic sources of gamma rays is to have flown the area previously. This is prohibitively expensive and would require complete national coverage. This project’s goal is to model the geologic contribution to radiological backgrounds using published geochemical data, GIS software, remote sensing, calculations, and modeling software. K, U and Th are the three major gamma emitters in geologic material. U and Th are assumed to be in secular equilibrium with their daughter isotopes. If K, U, and Th abundance values are known for a given geologic unit the expected gamma ray exposure rate can be calculated using the Grasty equation or by modeling software. Monte Carlo N-Particle Transport software (MCNP), developed by Los Alamos National Laboratory, is modeling software designed to simulate particles and their interactions with matter. Using this software, models have been created that represent various lithologies. These simulations randomly generate gamma ray photons at energy levels expected from natural radiologic sources. The photons take a random path through the simulated geologic media and deposit their energy at the end of their track. A series of nested spheres have been created and filled with simulated atmosphere to record energy deposition. Energies deposited are binned in the same manner as the NaI detectors used during an aerial survey. These models are used in place of the simplistic Grasty equation as they take into account absorption properties of the lithology which the

  8. Prediction of turbulent buoyant flow using an RNG {kappa}-{epsilon} model

    SciTech Connect (OSTI)

    Gan, G.

    1998-02-06

    Buoyant flows occur in various engineering practices such as heating, ventilation, and air-conditioning of buildings. This phenomenon is particularly important in rooms with displacement ventilation, where supply air velocities are generally very low (< 0.2 m/s) so that the predominant indoor airflow is largely due to thermal buoyancy created by internal heat sources such as occupants and equipment. This type of ventilation system has been shown to be an effective means to remove excess heat and achieve good indoor air quality. Here, numerical predictions were carried out for turbulent natural convection in two tall air cavities. The standard and RNG {kappa}-{epsilon} turbulence models were used for the predictions. The predicted results were compared with experimental data from the literature, and good agreement between prediction and measurement was obtained. Improved prediction was achieved using the RNG {kappa}-{epsilon} model in comparison with the standard {kappa}-{epsilon} model. The principal parameters for the improvement were investigated.

  9. Model Predictive Control of HVAC Systems: Implementation and Testing at the University of California, Merced

    SciTech Connect (OSTI)

    Haves, Phillip; Hencey, Brandon; Borrell, Francesco; Elliot, John; Ma, Yudong; Coffey, Brian; Bengea, Sorin; Wetter, Michael

    2010-06-29

    A Model Predictive Control algorithm was developed for the UC Merced campus chilled water plant. Model predictive control (MPC) is an advanced control technology that has proven successful in the chemical process industry and other industries. The main goal of the research was to demonstrate the practical and commercial viability of MPC for optimization of building energy systems. The control algorithms were developed and implemented in MATLAB, allowing for rapid development, performance, and robustness assessment. The UC Merced chilled water plant includes three water-cooled chillers and a two million gallon chilled water storage tank. The tank is charged during the night to minimize on-peak electricity consumption and take advantage of the lower ambient wet bulb temperature. The control algorithms determined the optimal chilled water plant operation including chilled water supply (CHWS) temperature set-point, condenser water supply (CWS) temperature set-point and the charging start and stop times to minimize a cost function that includes energy consumption and peak electrical demand over a 3-day prediction horizon. A detailed model of the chilled water plant and simplified models of the buildings served by the plant were developed using the equation-based modeling language Modelica. Steady state models of the chillers, cooling towers and pumps were developed, based on manufacturers performance data, and calibrated using measured data collected and archived by the control system. A detailed dynamic model of the chilled water storage tank was also developed and calibrated. Simple, semi-empirical models were developed to predict the temperature and flow rate of the chilled water returning to the plant from the buildings. These models were then combined and simplified for use in a model predictive control algorithm that determines the optimal chiller start and stop times and set-points for the condenser water temperature and the chilled water supply temperature. The

  10. Incorporating Single-nucleotide Polymorphisms Into the Lyman Model to Improve Prediction of Radiation Pneumonitis

    SciTech Connect (OSTI)

    Tucker, Susan L., E-mail: sltucker@mdanderson.org [Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Li Minghuan [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China)] [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China); Xu Ting; Gomez, Daniel [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)] [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Yuan Xianglin [Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan (China)] [Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan (China); Yu Jinming [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China)] [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China); Liu Zhensheng; Yin Ming; Guan Xiaoxiang; Wang Lie; Wei Qingyi [Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)] [Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Mohan, Radhe [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)] [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Vinogradskiy, Yevgeniy [University of Colorado School of Medicine, Aurora, Colorado (United States)] [University of Colorado School of Medicine, Aurora, Colorado (United States); Martel, Mary [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)] [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Liao Zhongxing [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)] [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)

    2013-01-01

    Purpose: To determine whether single-nucleotide polymorphisms (SNPs) in genes associated with DNA repair, cell cycle, transforming growth factor-{beta}, tumor necrosis factor and receptor, folic acid metabolism, and angiogenesis can significantly improve the fit of the Lyman-Kutcher-Burman (LKB) normal-tissue complication probability (NTCP) model of radiation pneumonitis (RP) risk among patients with non-small cell lung cancer (NSCLC). Methods and Materials: Sixteen SNPs from 10 different genes (XRCC1, XRCC3, APEX1, MDM2, TGF{beta}, TNF{alpha}, TNFR, MTHFR, MTRR, and VEGF) were genotyped in 141 NSCLC patients treated with definitive radiation therapy, with or without chemotherapy. The LKB model was used to estimate the risk of severe (grade {>=}3) RP as a function of mean lung dose (MLD), with SNPs and patient smoking status incorporated into the model as dose-modifying factors. Multivariate analyses were performed by adding significant factors to the MLD model in a forward stepwise procedure, with significance assessed using the likelihood-ratio test. Bootstrap analyses were used to assess the reproducibility of results under variations in the data. Results: Five SNPs were selected for inclusion in the multivariate NTCP model based on MLD alone. SNPs associated with an increased risk of severe RP were in genes for TGF{beta}, VEGF, TNF{alpha}, XRCC1 and APEX1. With smoking status included in the multivariate model, the SNPs significantly associated with increased risk of RP were in genes for TGF{beta}, VEGF, and XRCC3. Bootstrap analyses selected a median of 4 SNPs per model fit, with the 6 genes listed above selected most often. Conclusions: This study provides evidence that SNPs can significantly improve the predictive ability of the Lyman MLD model. With a small number of SNPs, it was possible to distinguish cohorts with >50% risk vs <10% risk of RP when they were exposed to high MLDs.

  11. Project Profile: Physics-Based Reliability Models for Supercritical-CO2

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Turbomachinery Components | Department of Energy Physics-Based Reliability Models for Supercritical-CO2 Turbomachinery Components Project Profile: Physics-Based Reliability Models for Supercritical-CO2 Turbomachinery Components Abengoa logo GE, under the Physics of Reliability: Evaluating Design Insights for Component Technologies in Solar (PREDICTS) Program will be leveraging internally developed models to predict the reliability of hybrid gas bearing (HGB) and dry gas seal (DGS) components

  12. The effects of digital elevation model resolution on the calculation and predictions of topographic wetness indices.

    SciTech Connect (OSTI)

    Drover, Damion, Ryan

    2011-12-01

    One of the largest exports in the Southeast U.S. is forest products. Interest in biofuels using forest biomass has increased recently, leading to more research into better forest management BMPs. The USDA Forest Service, along with the Oak Ridge National Laboratory, University of Georgia and Oregon State University are researching the impacts of intensive forest management for biofuels on water quality and quantity at the Savannah River Site in South Carolina. Surface runoff of saturated areas, transporting excess nutrients and contaminants, is a potential water quality issue under investigation. Detailed maps of variable source areas and soil characteristics would therefore be helpful prior to treatment. The availability of remotely sensed and computed digital elevation models (DEMs) and spatial analysis tools make it easy to calculate terrain attributes. These terrain attributes can be used in models to predict saturated areas or other attributes in the landscape. With laser altimetry, an area can be flown to produce very high resolution data, and the resulting data can be resampled into any resolution of DEM desired. Additionally, there exist many maps that are in various resolutions of DEM, such as those acquired from the U.S. Geological Survey. Problems arise when using maps derived from different resolution DEMs. For example, saturated areas can be under or overestimated depending on the resolution used. The purpose of this study was to examine the effects of DEM resolution on the calculation of topographic wetness indices used to predict variable source areas of saturation, and to find the best resolutions to produce prediction maps of soil attributes like nitrogen, carbon, bulk density and soil texture for low-relief, humid-temperate forested hillslopes. Topographic wetness indices were calculated based on the derived terrain attributes, slope and specific catchment area, from five different DEM resolutions. The DEMs were resampled from LiDAR, which is a

  13. Method for quantifying the prediction uncertainties associated with water quality models

    SciTech Connect (OSTI)

    Summers, J.K.; Wilson, H.T.; Kou, J.

    1993-01-01

    Many environmental regulatory agencies depend on models to organize, understand, and utilize the information for regulatory decision making. A general analytical protocol was developed to quantify prediction error associated with commonly used surface water quality models. Its application is demonstrated by comparing water quality models configured to represent different levels of spatial, temporal, and mechanistic complexity. This comparison can be accomplished by fitting the models to a benchmark data set. Once the models are successfully fitted to the benchmark data, the prediction errors associated with each application can be quantified using the Monte Carlo simulation techniques.

  14. Evaluation of cloud prediction and determination of critical relative humidity for a mesoscale numerical weather prediction model

    SciTech Connect (OSTI)

    Seaman, N.L.; Guo, Z.; Ackerman, T.P.

    1996-04-01

    Predictions of cloud occurrence and vertical location from the Pennsylvannia State University/National Center for Atmospheric Research nonhydrostatic mesoscale model (MM5) were evaluated statistically using cloud observations obtained at Coffeyville, Kansas, as part of the Second International satellite Cloud Climatology Project Regional Experiment campaign. Seventeen cases were selected for simulation during a November-December 1991 field study. MM5 was used to produce two sets of 36-km simulations, one with and one without four-dimensional data assimilation (FDDA), and a set of 12-km simulations without FDDA, but nested within the 36-km FDDA runs.

  15. Maintenance personnel performance simulation (MAPPS): a model for predicting maintenance performance reliability in nuclear power plants

    SciTech Connect (OSTI)

    Knee, H.E.; Krois, P.A.; Haas, P.M.; Siegel, A.I.; Ryan, T.G.

    1983-01-01

    The NRC has developed a structured, quantitative, predictive methodology in the form of a computerized simulation model for assessing maintainer task performance. Objective of the overall program is to develop, validate, and disseminate a practical, useful, and acceptable methodology for the quantitative assessment of NPP maintenance personnel reliability. The program was organized into four phases: (1) scoping study, (2) model development, (3) model evaluation, and (4) model dissemination. The program is currently nearing completion of Phase 2 - Model Development.

  16. A Geometric Rendezvous-Based Domain Model

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    University of Wisconsin - Madison 1500 Engineering Dr. Madison, WI 53716 sslattery@wisc.edu March 20, 2013 1 A Geometric Rendezvous-Based Domain Model for Data Transfer...

  17. Predictive modeling of synergistic effects in nanoscale ion track formation

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Zarkadoula, Eva; Pakarinen, Olli H.; Xue, Haizhou; Zhang, Yanwen; Weber, William J.

    2015-08-05

    Molecular dynamics techniques and the inelastic thermal spike model are used to study the coupled effects of inelastic energy loss due to 21 MeV Ni ion irradiation and pre-existing defects in SrTiO3. We determine the dependence on pre-existing defect concentration of nanoscale track formation occurring from the synergy between the inelastic energy loss and the pre-existing atomic defects. We show that the nanoscale ion tracks’ size can be controlled by the concentration of pre-existing disorder. This work identifies a major gap in fundamental understanding concerning the role played by defects in electronic energy dissipation and electron–lattice coupling.

  18. Modeling predicts which counties could store more carbon in soil by growing

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    bioenergy crops | Argonne National Laboratory Modeling predicts which counties could store more carbon in soil by growing bioenergy crops By Katie Elyce Jones * July 13, 2016 Tweet EmailPrint To help stakeholders in government and business make smart decisions about the best types of land and local climates for planting bioenergy crops, researchers at the U.S. Department of Energy's (DOE's) Argonne National Laboratory are using computational modeling to predict which counties could see

  19. Model predictive control system and method for integrated gasification combined cycle power generation

    DOE Patents [OSTI]

    Kumar, Aditya; Shi, Ruijie; Kumar, Rajeeva; Dokucu, Mustafa

    2013-04-09

    Control system and method for controlling an integrated gasification combined cycle (IGCC) plant are provided. The system may include a controller coupled to a dynamic model of the plant to process a prediction of plant performance and determine a control strategy for the IGCC plant over a time horizon subject to plant constraints. The control strategy may include control functionality to meet a tracking objective and control functionality to meet an optimization objective. The control strategy may be configured to prioritize the tracking objective over the optimization objective based on a coordinate transformation, such as an orthogonal or quasi-orthogonal projection. A plurality of plant control knobs may be set in accordance with the control strategy to generate a sequence of coordinated multivariable control inputs to meet the tracking objective and the optimization objective subject to the prioritization resulting from the coordinate transformation.

  20. Models for prediction of temperature difference and ventilation effectiveness with displacement ventilation

    SciTech Connect (OSTI)

    Yuan, X.; Chen, Q.; Glicksman, L.R.

    1999-07-01

    Displacement ventilation may provide better indoor air quality than mixing ventilation. Proper design of displacement ventilation requires information concerning the air temperature difference between the head and foot level of a sedentary person and the ventilation effectiveness at the breathing level. This paper presents models to predict the air temperature difference and the ventilation effectiveness, based on a database of 56 cases with displacement ventilation. The database was generated by using a validated CFD program and covers four different types of US buildings: small offices, large offices with partitions, classrooms, and industrial workshops under different thermal and flow boundary conditions. Both the maximum cooling load that can be removed by displacement ventilation and the ventilation effectiveness are shown to depend on the heat source type and ventilation rate in a room.

  1. Rate-based degradation modeling of lithium-ion cells

    SciTech Connect (OSTI)

    E.V. Thomas; I. Bloom; J.P. Christophersen; V.S. Battaglia

    2012-05-01

    Accelerated degradation testing is commonly used as the basis to characterize battery cell performance over a range of stress conditions (e.g., temperatures). Performance is measured by some response that is assumed to be related to the state of health of the cell (e.g., discharge resistance). Often, the ultimate goal of such testing is to predict cell life at some reference stress condition, where cell life is defined to be the point in time where performance has degraded to some critical level. These predictions are based on a degradation model that expresses the expected performance level versus the time and conditions under which a cell has been aged. Usually, the degradation model relates the accumulated degradation to the time at a constant stress level. The purpose of this article is to present an alternative framework for constructing a degradation model that focuses on the degradation rate rather than the accumulated degradation. One benefit of this alternative approach is that prediction of cell life is greatly facilitated in situations where the temperature exposure is not isothermal. This alternative modeling framework is illustrated via a family of rate-based models and experimental data acquired during calendar-life testing of high-power lithium-ion cells.

  2. Predictive Maturity of Multi-Scale Simulation Models for Fuel Performance

    SciTech Connect (OSTI)

    Atamturktur, Sez; Unal, Cetin; Hemez, Francois; Williams, Brian; Tome, Carlos

    2015-03-16

    The project proposed to provide a Predictive Maturity Framework with its companion metrics that (1) introduce a formalized, quantitative means to communicate information between interested parties, (2) provide scientifically dependable means to claim completion of Validation and Uncertainty Quantification (VU) activities, and (3) guide the decision makers in the allocation of Nuclear Energy’s resources for code development and physical experiments. The project team proposed to develop this framework based on two complimentary criteria: (1) the extent of experimental evidence available for the calibration of simulation models and (2) the sophistication of the physics incorporated in simulation models. The proposed framework is capable of quantifying the interaction between the required number of physical experiments and degree of physics sophistication. The project team has developed this framework and implemented it with a multi-scale model for simulating creep of a core reactor cladding. The multi-scale model is composed of the viscoplastic self-consistent (VPSC) code at the meso-scale, which represents the visco-plastic behavior and changing properties of a highly anisotropic material and a Finite Element (FE) code at the macro-scale to represent the elastic behavior and apply the loading. The framework developed takes advantage of the transparency provided by partitioned analysis, where independent constituent codes are coupled in an iterative manner. This transparency allows model developers to better understand and remedy the source of biases and uncertainties, whether they stem from the constituents or the coupling interface by exploiting separate-effect experiments conducted within the constituent domain and integral-effect experiments conducted within the full-system domain. The project team has implemented this procedure with the multi- scale VPSC-FE model and demonstrated its ability to improve the predictive capability of the model. Within this

  3. A fugacity-based indoor residential pesticide fate model

    SciTech Connect (OSTI)

    Bennett, Deborah H.; Furtaw, Edward J.; McKone, Thomas E.

    2002-06-01

    Dermal and non-dietary pathways are potentially significant exposure pathways to pesticides used in residences. Exposure pathways include dermal contact with residues on surfaces, ingestion from hand- and object-to-mouth activities, and absorption of pesticides into food. A limited amount of data has been collected on pesticide concentrations in various residential compartments following an application. But models are needed to interpret this data and make predictions about other pesticides based on chemical properties. In this paper, we propose a mass-balance compartment model based on fugacity principles. We include air (both gas phase and aerosols), carpet, smooth flooring, and walls as model compartments. Pesticide concentrations on furniture and toys, and in food, are being added to the model as data becomes available. We determine the compartmental fugacity capacity and mass transfer-rate coefficient for wallboard as an example. We also present the framework and equations needed for a dynamic mass-balance model.

  4. Fragment-based {sup 13}C nuclear magnetic resonance chemical shift predictions in molecular crystals: An alternative to planewave methods

    SciTech Connect (OSTI)

    Hartman, Joshua D.; Beran, Gregory J. O.; Monaco, Stephen; Schatschneider, Bohdan

    2015-09-14

    We assess the quality of fragment-based ab initio isotropic {sup 13}C chemical shift predictions for a collection of 25 molecular crystals with eight different density functionals. We explore the relative performance of cluster, two-body fragment, combined cluster/fragment, and the planewave gauge-including projector augmented wave (GIPAW) models relative to experiment. When electrostatic embedding is employed to capture many-body polarization effects, the simple and computationally inexpensive two-body fragment model predicts both isotropic {sup 13}C chemical shifts and the chemical shielding tensors as well as both cluster models and the GIPAW approach. Unlike the GIPAW approach, hybrid density functionals can be used readily in a fragment model, and all four hybrid functionals tested here (PBE0, B3LYP, B3PW91, and B97-2) predict chemical shifts in noticeably better agreement with experiment than the four generalized gradient approximation (GGA) functionals considered (PBE, OPBE, BLYP, and BP86). A set of recommended linear regression parameters for mapping between calculated chemical shieldings and observed chemical shifts are provided based on these benchmark calculations. Statistical cross-validation procedures are used to demonstrate the robustness of these fits.

  5. Predicting carcinogenicity of diverse chemicals using probabilistic neural network modeling approaches

    SciTech Connect (OSTI)

    Singh, Kunwar P.; Gupta, Shikha; Rai, Premanjali

    2013-10-15

    Robust global models capable of discriminating positive and non-positive carcinogens; and predicting carcinogenic potency of chemicals in rodents were developed. The dataset of 834 structurally diverse chemicals extracted from Carcinogenic Potency Database (CPDB) was used which contained 466 positive and 368 non-positive carcinogens. Twelve non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals and nonlinearity in the data were evaluated using Tanimoto similarity index and BrockDechertScheinkman statistics. Probabilistic neural network (PNN) and generalized regression neural network (GRNN) models were constructed for classification and function optimization problems using the carcinogenicity end point in rat. Validation of the models was performed using the internal and external procedures employing a wide series of statistical checks. PNN constructed using five descriptors rendered classification accuracy of 92.09% in complete rat data. The PNN model rendered classification accuracies of 91.77%, 80.70% and 92.08% in mouse, hamster and pesticide data, respectively. The GRNN constructed with nine descriptors yielded correlation coefficient of 0.896 between the measured and predicted carcinogenic potency with mean squared error (MSE) of 0.44 in complete rat data. The rat carcinogenicity model (GRNN) applied to the mouse and hamster data yielded correlation coefficient and MSE of 0.758, 0.71 and 0.760, 0.46, respectively. The results suggest for wide applicability of the inter-species models in predicting carcinogenic potency of chemicals. Both the PNN and GRNN (inter-species) models constructed here can be useful tools in predicting the carcinogenicity of new chemicals for regulatory purposes. - Graphical abstract: Figure (a) shows classification accuracies (positive and non-positive carcinogens) in rat, mouse, hamster, and pesticide data yielded by optimal PNN model. Figure (b) shows generalization and predictive abilities

  6. Predictions of bubbly flows in vertical pipes using two-fluid models in CFDS-FLOW3D code

    SciTech Connect (OSTI)

    Banas, A.O.; Carver, M.B.; Unrau, D.

    1995-09-01

    This paper reports the results of a preliminary study exploring the performance of two sets of two-fluid closure relationships applied to the simulation of turbulent air-water bubbly upflows through vertical pipes. Predictions obtained with the default CFDS-FLOW3D model for dispersed flows were compared with the predictions of a new model (based on the work of Lee), and with the experimental data of Liu. The new model, implemented in the CFDS-FLOW3D code, included additional source terms in the {open_quotes}standard{close_quotes} {kappa}-{epsilon} transport equations for the liquid phase, as well as modified model coefficients and wall functions. All simulations were carried out in a 2-D axisymmetric format, collapsing the general multifluid framework of CFDS-FLOW3D to the two-fluid (air-water) case. The newly implemented model consistently improved predictions of radial-velocity profiles of both phases, but failed to accurately reproduce the experimental phase-distribution data. This shortcoming was traced to the neglect of anisotropic effects in the modelling of liquid-phase turbulence. In this sense, the present investigation should be considered as the first step toward the ultimate goal of developing a theoretically sound and universal CFD-type two-fluid model for bubbly flows in channels.

  7. Predictive modeling of synergistic effects in nanoscale ion track formation

    SciTech Connect (OSTI)

    Zarkadoula, Eva; Pakarinen, Olli H.; Xue, Haizhou; Zhang, Yanwen; Weber, William J.

    2015-08-05

    Molecular dynamics techniques and the inelastic thermal spike model are used to study the coupled effects of inelastic energy loss due to 21 MeV Ni ion irradiation and pre-existing defects in SrTiO3. We determine the dependence on pre-existing defect concentration of nanoscale track formation occurring from the synergy between the inelastic energy loss and the pre-existing atomic defects. We show that the nanoscale ion tracks’ size can be controlled by the concentration of pre-existing disorder. This work identifies a major gap in fundamental understanding concerning the role played by defects in electronic energy dissipation and electron–lattice coupling.

  8. Advanced Models and Controls for Prediction and Extension of Battery Lifetime (Presentation)

    SciTech Connect (OSTI)

    Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Pesaran, A.

    2014-02-01

    Predictive models of capacity and power fade must consider a multiplicity of degradation modes experienced by Li-ion batteries in the automotive environment. Lacking accurate models and tests, lifetime uncertainty must presently be absorbed by overdesign and excess warranty costs. To reduce these costs and extend life, degradation models are under development that predict lifetime more accurately and with less test data. The lifetime models provide engineering feedback for cell, pack and system designs and are being incorporated into real-time control strategies.

  9. Modeling uranium transport in acidic contaminated groundwater with base addition

    SciTech Connect (OSTI)

    Zhang, Fan; Luo, Wensui; Parker, Jack C.; Brooks, Scott C; Watson, David B; Jardine, Philip; Gu, Baohua

    2011-01-01

    This study investigates reactive transport modeling in a column of uranium(VI)-contaminated sediments with base additions in the circulating influent. The groundwater and sediment exhibit oxic conditions with low pH, high concentrations of NO{sub 3}{sup -}, SO{sub 4}{sup 2-}, U and various metal cations. Preliminary batch experiments indicate that additions of strong base induce rapid immobilization of U for this material. In the column experiment that is the focus of the present study, effluent groundwater was titrated with NaOH solution in an inflow reservoir before reinjection to gradually increase the solution pH in the column. An equilibrium hydrolysis, precipitation and ion exchange reaction model developed through simulation of the preliminary batch titration experiments predicted faster reduction of aqueous Al than observed in the column experiment. The model was therefore modified to consider reaction kinetics for the precipitation and dissolution processes which are the major mechanism for Al immobilization. The combined kinetic and equilibrium reaction model adequately described variations in pH, aqueous concentrations of metal cations (Al, Ca, Mg, Sr, Mn, Ni, Co), sulfate and U(VI). The experimental and modeling results indicate that U(VI) can be effectively sequestered with controlled base addition due to sorption by slowly precipitated Al with pH-dependent surface charge. The model may prove useful to predict field-scale U(VI) sequestration and remediation effectiveness.

  10. Modeling of fluidized-bed combustion of coal: Phase II, final reports. Volume III. Model predictions and results

    SciTech Connect (OSTI)

    Louis, J.F.; Tung, S.E.

    1980-10-01

    This document is the third of a seven volume series of our Phase II Final Report. This volume deals with parametric studies carried out using the FBC model. A comparison with available pilot plant data is included where such data are available. This volume in essence documents model performance; describing predictions on bubble growth, combustion characteristics, sulfur capture, heat transfer and related parameters. The model has approximately forty input variables which are at the disposal of the user. The user has the option to change a few or all of these input variables. In the parametric studies reported here, a large number of input variables whose variation is less critical to the predicted results, were maintained constant at the default values. On the other hand, those parameters whose selection is very important in design and operation of the FBC's were varied in suitable operating regions. The chief among such parameters are: bed temperature, coal feed size distribution (2 parameters), average bed-sorbent size, calcium to sulfur molar ratio, superficial velocity, excess air fraction, and bed weight (or bed height). The computations for obtaining the parametric relationships are based upon selection of a geometrical design for the combustor. Bed cross-section is 6' x 6', bed height is 4', and the freeboard height is 16'. The heat transfer tubes have 2'' OD, a pitch of 10'', and are located on an equilateral triangle pattern. The air distributor is a perforated plate with 0.1'' diameter holes on a rectangular grid with 0.75'' center-to-center spacing.

  11. Improving models to predict phenological responses to global change

    SciTech Connect (OSTI)

    Richardson, Andrew D.

    2015-11-25

    The term phenology describes both the seasonal rhythms of plants and animals, and the study of these rhythms. Plant phenological processes, including, for example, when leaves emerge in the spring and change color in the autumn, are highly responsive to variation in weather (e.g. a warm vs. cold spring) as well as longer-term changes in climate (e.g. warming trends and changes in the timing and amount of rainfall). We conducted a study to investigate the phenological response of northern peatland communities to global change. Field work was conducted at the SPRUCE experiment in northern Minnesota, where we installed 10 digital cameras. Imagery from the cameras is being used to track shifts in plant phenology driven by elevated carbon dioxide and elevated temperature in the different SPRUCE experimental treatments. Camera imagery and derived products (“greenness”) is being posted in near-real time on a publicly available web page (http://phenocam.sr.unh.edu/webcam/gallery/). The images will provide a permanent visual record of the progression of the experiment over the next 10 years. Integrated with other measurements collected as part of the SPRUCE program, this study is providing insight into the degree to which phenology may mediate future shifts in carbon uptake and storage by peatland ecosystems. In the future, these data will be used to develop improved models of vegetation phenology, which will be tested against ground observations collected by a local collaborator.

  12. Global warming and climate change - predictive models for temperate and tropical regions

    SciTech Connect (OSTI)

    Malini, B.H.

    1997-12-31

    Based on the assumption of 4{degree}C increase of global temperature by the turn of 21st century due to the accumulation of greenhouse gases an attempt is made to study the possible variations in different climatic regimes. The predictive climatic water balance model for Hokkaido island of Japan (a temperate zone) indicates the possible occurrence of water deficit for two to three months, which is a unknown phenomenon in this region at present. Similarly, India which represents tropical region also will experience much drier climates with increased water deficit conditions. As a consequence, the thermal region of Hokkaido which at present is mostly Tundra and Micro thermal will change into a Meso thermal category. Similarly, the moisture regime which at present supports per humid (A2, A3 and A4) and Humid (B4) climates can support A1, B4, B3, B2 and B1 climates indicating a shift towards drier side of the climatic spectrum. Further, the predictive modes of both the regions have indicated increased evapotranspiration rates. Although there is not much of change in the overall thermal characteristics of the Indian region the moisture regime indicates a clear shift towards the aridity in the country.

  13. Combining Traditional Cyber Security Audit Data with Psychosocial Data: Towards Predictive Modeling for Insider Threat Mitigation

    SciTech Connect (OSTI)

    Greitzer, Frank L.; Frincke, Deborah A.

    2010-09-01

    The purpose of this chapter is to motivate the combination of traditional cyber security audit data with psychosocial data, so as to move from an insider threat detection stance to one that enables prediction of potential insider presence. Two distinctive aspects of the approach are the objective of predicting or anticipating potential risks and the use of organizational data in addition to cyber data to support the analysis. The chapter describes the challenges of this endeavor and progress in defining a usable set of predictive indicators, developing a framework for integrating the analysis of organizational and cyber security data to yield predictions about possible insider exploits, and developing the knowledge base and reasoning capability of the system. We also outline the types of errors that one expects in a predictive system versus a detection system and discuss how those errors can affect the usefulness of the results.

  14. A Predictive Model of Fragmentation using Adaptive Mesh Refinement and a Hierarchical Material Model

    SciTech Connect (OSTI)

    Koniges, A E; Masters, N D; Fisher, A C; Anderson, R W; Eder, D C; Benson, D; Kaiser, T B; Gunney, B T; Wang, P; Maddox, B R; Hansen, J F; Kalantar, D H; Dixit, P; Jarmakani, H; Meyers, M A

    2009-03-03

    Fragmentation is a fundamental material process that naturally spans spatial scales from microscopic to macroscopic. We developed a mathematical framework using an innovative combination of hierarchical material modeling (HMM) and adaptive mesh refinement (AMR) to connect the continuum to microstructural regimes. This framework has been implemented in a new multi-physics, multi-scale, 3D simulation code, NIF ALE-AMR. New multi-material volume fraction and interface reconstruction algorithms were developed for this new code, which is leading the world effort in hydrodynamic simulations that combine AMR with ALE (Arbitrary Lagrangian-Eulerian) techniques. The interface reconstruction algorithm is also used to produce fragments following material failure. In general, the material strength and failure models have history vector components that must be advected along with other properties of the mesh during remap stage of the ALE hydrodynamics. The fragmentation models are validated against an electromagnetically driven expanding ring experiment and dedicated laser-based fragmentation experiments conducted at the Jupiter Laser Facility. As part of the exit plan, the NIF ALE-AMR code was applied to a number of fragmentation problems of interest to the National Ignition Facility (NIF). One example shows the added benefit of multi-material ALE-AMR that relaxes the requirement that material boundaries must be along mesh boundaries.

  15. Viscoplastic characterization and fatigue modeling of titanium based metal matrix composites. Master`s thesis

    SciTech Connect (OSTI)

    Foringer, M.A.

    1994-12-01

    Viscoplastic characterization and fatigue modeling of titanium-based metal matrix composites was accomplished by combining a unified viscoplastic theory, a nonlinear micromechanics model, and a linear damage accumulation model. First. Ti 15-3 was characterized using the Bodner-Partom viscoplastic theory. A micromechanics model was then employed in a linear damage accumulation fatigue model to predict the fatigue behavior of titanium based composites. The viscoplastic behavior predictions of the micromechanics model were used to eliminate separately defined time dependent terms in the fatigue model. Also, a new linear damage accumulation model was developed from the fatigue behavior of the composite constituents. Finally, it was found that the microstresses in the 0 degree ply could be used to accurately predict the fatigue behavior of a laminate containing these plies.

  16. Mechanism-based Representative Volume Elements (RVEs) for Predicting Property Degradations in Multiphase Materials

    SciTech Connect (OSTI)

    Xu, Wei; Sun, Xin; Li, Dongsheng; Ryu, Seun; Khaleel, Mohammad A.

    2013-02-01

    Quantitative understanding of the evolving thermal-mechanical properties of a multi-phase material hinges upon the availability of quantitative statistically representative microstructure descriptions. Questions then arise as to whether a two-dimensional (2D) or a three-dimensional (3D) representative volume element (RVE) should be considered as the statistically representative microstructure. Although 3D models are more representative than 2D models in general, they are usually computationally expensive and difficult to be reconstructed. In this paper, we evaluate the accuracy of a 2D RVE in predicting the property degradations induced by different degradation mechanisms with the multiphase solid oxide fuel cell (SOFC) anode material as an example. Both 2D and 3D microstructure RVEs of the anodes are adopted to quantify the effects of two different degradation mechanisms: humidity-induced electrochemical degradation and phosphorus poisoning induced structural degradation. The predictions of the 2D model are then compared with the available experimental measurements and the results from the 3D model. It is found that the 2D model, limited by its inability of reproducing the realistic electrical percolation, is unable to accurately predict the degradation of thermo-electrical properties. On the other hand, for the phosphorus poisoning induced structural degradation, both 2D and 3D microstructures yield similar results, indicating that the 2D model is capable of providing computationally efficient yet accurate results for studying the structural degradation within the anodes.

  17. Model-Based Design and Integration of Large Li-ion Battery Systems

    SciTech Connect (OSTI)

    Smith, Kandler; Kim, Gi-Heon; Santhanagopalan, Shriram; Shi, Ying; Pesaran, Ahmad; Mukherjee, Partha; Barai, Pallab; Maute, Kurt; Behrou, Reza; Patil, Chinmaya

    2015-11-17

    This presentation introduces physics-based models of batteries and software toolsets, including those developed by the U.S. Department of Energy's (DOE) Computer-Aided Engineering for Electric-Drive Vehicle Batteries Program (CAEBAT). The presentation highlights achievements and gaps in model-based tools for materials-to-systems design, lifetime prediction and control.

  18. the-schedule-based-transit-model

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    The Schedule-Based transit model of the Chicago Metropolitan Area Vadim Sokolov Transportation Research and Analysis Computing Center Argonne National Laboratory List of Authors ================ Vadim Sokolov Transportation Research and Analysis Computing Center Argonne National Laboratory 277 International Drive West Chicago, IL 60185 Abstract ========= Usually public transit systems are modeled using so called frequency based approach. In this case transit route times are defined in terms of

  19. Information system of rice planting calendar based on ten-day (Dasarian) rainfall prediction

    SciTech Connect (OSTI)

    Susandi, Armi; Tamamadin, Mamad; Djamal, Erizal; Las, Irsal

    2015-09-30

    This paper describes information system of rice planting calendar to help farmers in determining the time for rice planting. The information includes rainfall prediction in ten days (dasarian) scale overlaid to map of rice field to produce map of rice planting in village level. The rainfall prediction was produced by stochastic modeling using Fast Fourier Transform (FFT) and Non-Linier Least Squares methods to fit the curve of function to the rainfall data. In this research, the Fourier series has been modified become non-linear function to follow the recent characteristics of rainfall that is non stationary. The results have been also validated in 4 steps, including R-Square, RMSE, R-Skill, and comparison with field data. The development of information system (cyber extension) provides information such as rainfall prediction, prediction of the planting time, and interactive space for farmers to respond to the information submitted. Interfaces for interactive response will be critical to the improvement of prediction accuracy of information, both rainfall and planting time. The method used to get this information system includes mapping on rice planting prediction, converting the format file, developing database system, developing website, and posting website. Because of this map was overlaid with the Google map, the map files must be converted to the .kml file format.

  20. Development of a land ice core for the Model for Prediction Across Scales

    Office of Scientific and Technical Information (OSTI)

    (MPAS) (Conference) | SciTech Connect Development of a land ice core for the Model for Prediction Across Scales (MPAS) Citation Details In-Document Search Title: Development of a land ice core for the Model for Prediction Across Scales (MPAS) No abstract prepared. Authors: Hoffman, Matthew J [1] + Show Author Affiliations Los Alamos National Laboratory Publication Date: 2012-06-25 OSTI Identifier: 1044843 Report Number(s): LA-UR-12-22469 TRN: US201214%%525 DOE Contract Number: AC52-06NA25396

  1. Towards the Prediction of Decadal to Centennial Climate Processes in the Coupled Earth System Model

    SciTech Connect (OSTI)

    Liu, Zhengyu; Kutzbach, J.; Jacob, R.; Prentice, C.

    2011-12-05

    In this proposal, we have made major advances in the understanding of decadal and long term climate variability. (a) We performed a systematic study of multidecadal climate variability in FOAM-LPJ and CCSM-T31, and are starting exploring decadal variability in the IPCC AR4 models. (b) We develop several novel methods for the assessment of climate feedbacks in the observation. (c) We also developed a new initialization scheme DAI (Dynamical Analogue Initialization) for ensemble decadal prediction. (d) We also studied climate-vegetation feedback in the observation and models. (e) Finally, we started a pilot program using Ensemble Kalman Filter in CGCM for decadal climate prediction.

  2. Mass-transport models to predict toxicity of inhaled gases in the upper respiratory tract

    SciTech Connect (OSTI)

    Hubal, E.A.C.; Fedkiw, P.S.; Kimbell, J.S. [North Carolina State Univ., Raleigh, NC (United States)

    1996-04-01

    Mass-transport (the movement of a chemical species) plays an important role in determining toxic responses of the upper respiratory tract (URT) to inhaled chemicals. Mathematical dosimetry models incorporate physical characteristics of mass transport and are used to predict quantitative uptake (absorption rate) and distribution of inhaled gases and vapors in the respiratory tract. Because knowledge of dose is an essential component of quantitative risk assessment, dosimetry modeling plays an important role in extrapolation of animal study results to humans. A survey of existing mathematical dosimetry models for the URT is presented, limitations of current models are discussed, and adaptations of existing models to produce a generally applicable model are suggested. Reviewed URT dosimetry models are categorized as early, lumped-parameter, and distributed-parameter models. Specific examples of other relevant modeling work are also presented. 35 refs., 11 figs., 1 tab.

  3. Model-Predictive Cascade Mitigation in Electric Power Systems With Storage and Renewables-Part II: Case-Study

    SciTech Connect (OSTI)

    Almassalkhi, MR; Hiskens, IA

    2015-01-01

    The novel cascade-mitigation scheme developed in Part I of this paper is implemented within a receding-horizon model predictive control (MPC) scheme with a linear controller model. This present paper illustrates the MPC strategy with a case-study that is based on the IEEE RTS-96 network, though with energy storage and renewable generation added. It is shown that the MPC strategy alleviates temperature overloads on transmission lines by rescheduling generation, energy storage, and other network elements, while taking into account ramp-rate limits and network limitations. Resilient performance is achieved despite the use of a simplified linear controller model. The MPC scheme is compared against a base-case that seeks to emulate human operator behavior.

  4. Microstructure-based approach for predicting crack initiation and early growth in metals.

    SciTech Connect (OSTI)

    Cox, James V.; Emery, John M.; Brewer, Luke N.; Reedy, Earl David, Jr.; Puskar, Joseph David; Bartel, Timothy James; Dingreville, Remi P. M.; Foulk, James W., III; Battaile, Corbett Chandler; Boyce, Brad Lee

    2009-09-01

    Fatigue cracking in metals has been and is an area of great importance to the science and technology of structural materials for quite some time. The earliest stages of fatigue crack nucleation and growth are dominated by the microstructure and yet few models are able to predict the fatigue behavior during these stages because of a lack of microstructural physics in the models. This program has developed several new simulation tools to increase the microstructural physics available for fatigue prediction. In addition, this program has extended and developed microscale experimental methods to allow the validation of new microstructural models for deformation in metals. We have applied these developments to fatigue experiments in metals where the microstructure has been intentionally varied.

  5. Predicting ecological roles in the rhizosphere using metabolome and transportome modeling

    SciTech Connect (OSTI)

    Larsen, Peter E.; Collart, Frank R.; Dai, Yang; Blanchard, Jeffrey L.

    2015-09-02

    The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. New algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad’s ecological role in the rhizosphere: a biofilm, biocontrol agent, promoter of plant growth, or plant pathogen. Computational predictions of ecological niche were highly accurate overall with models trained on transportomic model output being the most accurate (Leave One Out Validation F-scores between 0.82 and 0.89). The strongest predictive molecular mechanism features for rhizosphere ecological niche overlap with many previously reported analyses of Pseudomonad interactions in the rhizosphere, suggesting that this approach successfully informs a system-scale level understanding of how Pseudomonads sense and interact with their environments. The observation that an organism’s transportome is highly predictive of its ecological niche is a novel discovery and may have implications in our understanding microbial ecology. The framework developed here can be generalized to the analysis of any bacteria across a wide range of environments and ecological niches making this approach a powerful tool for providing insights into functional predictions from bacterial genomic data.

  6. Subtask 2.4 - Integration and Synthesis in Climate Change Predictive Modeling

    SciTech Connect (OSTI)

    Jaroslav Solc

    2009-06-01

    The Energy & Environmental Research Center (EERC) completed a brief evaluation of the existing status of predictive modeling to assess options for integration of our previous paleohydrologic reconstructions and their synthesis with current global climate scenarios. Results of our research indicate that short-term data series available from modern instrumental records are not sufficient to reconstruct past hydrologic events or predict future ones. On the contrary, reconstruction of paleoclimate phenomena provided credible information on past climate cycles and confirmed their integration in the context of regional climate history is possible. Similarly to ice cores and other paleo proxies, acquired data represent an objective, credible tool for model calibration and validation of currently observed trends. It remains a subject of future research whether further refinement of our results and synthesis with regional and global climate observations could contribute to improvement and credibility of climate predictions on a regional and global scale.

  7. NEAR FIELD MODELING OF SPE1 EXPERIMENT AND PREDICTION OF THE...

    Office of Scientific and Technical Information (OSTI)

    provide a validated computation capability for the nuclear explosion monitoring community. ... needed for a science-based modeling capability for nuclearmore explosion monitoring. ...

  8. Long-Fiber Thermoplastic Injection Molded Composites: from Process Modeling to Property Prediction

    SciTech Connect (OSTI)

    Nguyen, Ba Nghiep; Holbery, Jim D.; Johnson, Kenneth I.; Smith, Mark T.

    2005-09-01

    Recently, long-fiber filled thermoplastics have become a great interest to the automotive industry since these materials offer much better property performance (e.g. elastic moduli, strength, durability) than their short-fiber analogues, and they can be processed through injection molding with some specific tool design. However, in order that long-fiber thermoplastic injection molded composites can be used efficiently for automotive applications, there is a tremendous need to develop process and constitutive models as well as computational tools to predict the microstructure of the as-formed composite, and its resulting properties and macroscopic responses from processing to the final product. The microstructure and properties of such a composite are governed by i) flow-induced fiber orientation, ii) fiber breakage during injection molding, and iii) processing conditions (e,g. pressure, mold and melt temperatures, mold geometries, injection speed, etc.). This paper highlights our efforts to address these challenging issues. The work is an integrated part of a research program supported by the US Department of Energy, which includes The development of process models for long-fiber filled thermoplastics, The construction of an interface between process modeling and property prediction as well as the development of new constitutive models to perform linear and nonlinear structural analyses, Experimental characterization of model parameters and verification of the model predictions.

  9. A comparison of simulation models for predicting soil water dynamics in bare and vegetated lysimeters

    SciTech Connect (OSTI)

    Link, S.O.; Kickert, R.N.; Fayer, M.J.; Gee, G.W.

    1993-06-01

    This report describes the results of simulation models used to predict soil water storage dynamics at the Field Lysimeter Test Facility (FLTF) weighing lysimeters. The objectives of this research is to develop the capability to predict soil water storage dynamics with plants in support of water infiltration control studies for the Hanford Permanent Isolation Barrier Development Program. It is important to gain confidence in one`s ability to simulate soil water dynamics over long time periods to assess the barrier`s ability to prevent drainage. Two models were compared for their ability to simulate soil water storage dynamics with and without plants in weighing lysimeters, the soil water infiltration and movement (SWIM) and the simulation of production and utilization of rangelands (SPUR-91) models. These models adequately simulated soil water storage dynamics for the weighing lysimeters. The range of root mean square error values for the two models was 7.0 to 19.8. This compares well with the range reported by Fayer et al. (1992) for the bare soil data sets of 8.1 to 22.1. Future research will test the predictive capability of these models for longer term lysimeter data sets and for historical data sets collected in various plant community types.

  10. Prediction of Liver Function by Using Magnetic Resonance-based Portal Venous Perfusion Imaging

    SciTech Connect (OSTI)

    Cao Yue; Wang Hesheng; Johnson, Timothy D.; Pan, Charlie; Hussain, Hero; Balter, James M.; Normolle, Daniel; Ben-Josef, Edgar; Ten Haken, Randall K.; Lawrence, Theodore S.; Feng, Mary

    2013-01-01

    Purpose: To evaluate whether liver function can be assessed globally and spatially by using volumetric dynamic contrast-enhanced magnetic resonance imaging MRI (DCE-MRI) to potentially aid in adaptive treatment planning. Methods and Materials: Seventeen patients with intrahepatic cancer undergoing focal radiation therapy (RT) were enrolled in institution review board-approved prospective studies to obtain DCE-MRI (to measure regional perfusion) and indocyanine green (ICG) clearance rates (to measure overall liver function) prior to, during, and at 1 and 2 months after treatment. The volumetric distribution of portal venous perfusion in the whole liver was estimated for each scan. We assessed the correlation between mean portal venous perfusion in the nontumor volume of the liver and overall liver function measured by ICG before, during, and after RT. The dose response for regional portal venous perfusion to RT was determined using a linear mixed effects model. Results: There was a significant correlation between the ICG clearance rate and mean portal venous perfusion in the functioning liver parenchyma, suggesting that portal venous perfusion could be used as a surrogate for function. Reduction in regional venous perfusion 1 month after RT was predicted by the locally accumulated biologically corrected dose at the end of RT (P<.0007). Regional portal venous perfusion measured during RT was a significant predictor for regional venous perfusion assessed 1 month after RT (P<.00001). Global hypovenous perfusion pre-RT was observed in 4 patients (3 patients with hepatocellular carcinoma and cirrhosis), 3 of whom had recovered from hypoperfusion, except in the highest dose regions, post-RT. In addition, 3 patients who had normal perfusion pre-RT had marked hypervenous perfusion or reperfusion in low-dose regions post-RT. Conclusions: This study suggests that MR-based volumetric hepatic perfusion imaging may be a biomarker for spatial distribution of liver function, which

  11. Model-Based Sampling and Inference

    U.S. Energy Information Administration (EIA) Indexed Site

    Model-Based Sampling, Inference and Imputation James R. Knaub, Jr., Energy Information Administration, EI-53.1 James.Knaub@eia.doe.gov Key Words: Survey statistics, Randomization, Conditionality, Random sampling, Cutoff sampling Abstract: Picking a sample through some randomization mechanism, such as random sampling within groups (stratified random sampling), or, say, sampling every fifth item (systematic random sampling), may be familiar to a lot of people. These are design-based samples.

  12. Rate-based process modeling study of CO{sub 2} capture with aqueous monoethanolamine solution

    SciTech Connect (OSTI)

    Zhang, Y.; Chen, H.; Chen, C.C.; Plaza, J.M.; Dugas, R.; Rochelle, G.T.

    2009-10-15

    Rate-based process modeling technology has matured and is increasingly gaining acceptance over traditional equilibrium-stage modeling approaches. Recently comprehensive pilot plant data for carbon dioxide (CO{sub 2}) capture with aqueous monoethanolamine (MEA) solution have become available from the University of Texas at Austin. The pilot plant data cover key process variables including CO{sub 2} concentration in the gas stream, CO{sub 2} loading in lean MEA solution, liquid to gas ratio, and packing type. In this study, we model the pilot plant operation with Aspen RateSep, a second generation rate-based multistage separation unit operation model in Aspen Plus. After a brief review of rate-based modeling, thermodynamic and kinetic models for CO{sub 2} absorption with the MEA solution, and transport property models, we show excellent match of the rate-based model predictions against the comprehensive pilot plant data and we validate the superiority of the rate-based models over the traditional equilibrium-stage models. We further examine the impacts of key rate-based modeling options, i.e., film discretization options and flow model options. The rate-based model provides excellent predictive capability, and it should be very useful for design and scale-up of CO{sub 2} capture processes.

  13. Monte Carlo and analytical model predictions of leakage neutron exposures from passively scattered proton therapy

    SciTech Connect (OSTI)

    Prez-Andjar, Anglica [Department of Radiation Physics, Unit 1202, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030 (United States)] [Department of Radiation Physics, Unit 1202, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030 (United States); Zhang, Rui; Newhauser, Wayne [Department of Radiation Physics, Unit 1202, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030 and The University of Texas Graduate School of Biomedical Sciences at Houston, 6767 Bertner Avenue, Houston, Texas 77030 (United States)] [Department of Radiation Physics, Unit 1202, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030 and The University of Texas Graduate School of Biomedical Sciences at Houston, 6767 Bertner Avenue, Houston, Texas 77030 (United States)

    2013-12-15

    Purpose: Stray neutron radiation is of concern after radiation therapy, especially in children, because of the high risk it might carry for secondary cancers. Several previous studies predicted the stray neutron exposure from proton therapy, mostly using Monte Carlo simulations. Promising attempts to develop analytical models have also been reported, but these were limited to only a few proton beam energies. The purpose of this study was to develop an analytical model to predict leakage neutron equivalent dose from passively scattered proton beams in the 100-250-MeV interval.Methods: To develop and validate the analytical model, the authors used values of equivalent dose per therapeutic absorbed dose (H/D) predicted with Monte Carlo simulations. The authors also characterized the behavior of the mean neutron radiation-weighting factor, w{sub R}, as a function of depth in a water phantom and distance from the beam central axis.Results: The simulated and analytical predictions agreed well. On average, the percentage difference between the analytical model and the Monte Carlo simulations was 10% for the energies and positions studied. The authors found that w{sub R} was highest at the shallowest depth and decreased with depth until around 10 cm, where it started to increase slowly with depth. This was consistent among all energies.Conclusion: Simple analytical methods are promising alternatives to complex and slow Monte Carlo simulations to predict H/D values. The authors' results also provide improved understanding of the behavior of w{sub R} which strongly depends on depth, but is nearly independent of lateral distance from the beam central axis.

  14. QMU as an approach to strengthening the predictive capabilities of complex models.

    SciTech Connect (OSTI)

    Gray, Genetha Anne; Boggs, Paul T.; Grace, Matthew D.

    2010-09-01

    Complex systems are made up of multiple interdependent parts, and the behavior of the entire system cannot always be directly inferred from the behavior of the individual parts. They are nonlinear and system responses are not necessarily additive. Examples of complex systems include energy, cyber and telecommunication infrastructures, human and animal social structures, and biological structures such as cells. To meet the goals of infrastructure development, maintenance, and protection for cyber-related complex systems, novel modeling and simulation technology is needed. Sandia has shown success using M&S in the nuclear weapons (NW) program. However, complex systems represent a significant challenge and relative departure from the classical M&S exercises, and many of the scientific and mathematical M&S processes must be re-envisioned. Specifically, in the NW program, requirements and acceptable margins for performance, resilience, and security are well-defined and given quantitatively from the start. The Quantification of Margins and Uncertainties (QMU) process helps to assess whether or not these safety, reliability and performance requirements have been met after a system has been developed. In this sense, QMU is used as a sort of check that requirements have been met once the development process is completed. In contrast, performance requirements and margins may not have been defined a priori for many complex systems, (i.e. the Internet, electrical distribution grids, etc.), particularly not in quantitative terms. This project addresses this fundamental difference by investigating the use of QMU at the start of the design process for complex systems. Three major tasks were completed. First, the characteristics of the cyber infrastructure problem were collected and considered in the context of QMU-based tools. Second, UQ methodologies for the quantification of model discrepancies were considered in the context of statistical models of cyber activity. Third

  15. A MULTISCALE, CELL-BASED FRAMEWORK FOR MODELING CANCER DEVELOPMENT

    SciTech Connect (OSTI)

    JIANG, YI

    2007-01-16

    Cancer remains to be one of the leading causes of death due to diseases. We use a systems approach that combines mathematical modeling, numerical simulation, in vivo and in vitro experiments, to develop a predictive model that medical researchers can use to study and treat cancerous tumors. The multiscale, cell-based model includes intracellular regulations, cellular level dynamics and intercellular interactions, and extracellular level chemical dynamics. The intracellular level protein regulations and signaling pathways are described by Boolean networks. The cellular level growth and division dynamics, cellular adhesion and interaction with the extracellular matrix is described by a lattice Monte Carlo model (the Cellular Potts Model). The extracellular dynamics of the signaling molecules and metabolites are described by a system of reaction-diffusion equations. All three levels of the model are integrated through a hybrid parallel scheme into a high-performance simulation tool. The simulation results reproduce experimental data in both avasular tumors and tumor angiogenesis. By combining the model with experimental data to construct biologically accurate simulations of tumors and their vascular systems, this model will enable medical researchers to gain a deeper understanding of the cellular and molecular interactions associated with cancer progression and treatment.

  16. A DISLOCATION-BASED CLEAVAGE INITIATION MODEL FOR PRESSURE VESSEL

    SciTech Connect (OSTI)

    Cochran, Kristine B; Erickson, Marjorie A; Williams, Paul T; Klasky, Hilda B; Bass, Bennett Richard

    2012-01-01

    Efforts are under way to develop a theoretical, multi-scale model for the prediction of fracture toughness of ferritic steels in the ductile-to-brittle transition temperature (DBTT) region that accounts for temperature, irradiation, strain rate, and material condition (chemistry and heat treatment) effects. This new model is intended to address difficulties associated with existing empirically-derived models of the DBTT region that cannot be extrapolated to conditions for which data are unavailable. Dislocation distribution equations, derived from the theories of Yokobori et al., are incorporated to account for the local stress state prior to and following initiation of a microcrack from a second-phase particle. The new model is the basis for the DISlocation-based FRACture (DISFRAC) computer code being developed at the Oak Ridge National Laboratory (ORNL). The purpose of this code is to permit fracture safety assessments of ferritic structures with only tensile properties required as input. The primary motivation for the code is to assist in the prediction of radiation effects on nuclear reactor pressure vessels, in parallel with the EURATOM PERFORM 60 project.

  17. Prediction of Regulation Reserve Requirements in California ISO Control Area based on BAAL Standard

    SciTech Connect (OSTI)

    Etingov, Pavel V.; Makarov, Yuri V.; Samaan, Nader A.; Ma, Jian; Loutan, Clyde

    2013-07-21

    This paper presents new methodologies developed at Pacific Northwest National Laboratory (PNNL) to estimate regulation capacity requirements in the California ISO control area. Two approaches have been developed: (1) an approach based on statistical analysis of actual historical area control error (ACE) and regulation data, and (2) an approach based on balancing authority ACE limit control performance standard. The approaches predict regulation reserve requirements on a day-ahead basis including upward and downward requirements, for each operating hour of a day. California ISO data has been used to test the performance of the proposed algorithms. Results show that software tool allows saving up to 30% on the regulation procurements cost .

  18. Comparison of a Recurrent Neural Network PV System Model with a Traditional Component-Based PV System Model

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    a Recurrent Neural Network PV System Model with a Traditional Component-Based PV System Model Daniel Riley, Sandia National Laboratories, Albuquerque, New Mexico, USA | Ganesh K. Venayagamoorthy, Missouri University of Science and Technology, Rolla, Missouri, USA Abstract Traditional PV system modeling approaches require system components to be tested in order to determine performance parameters. In some cases, system owners may wish to predict system performance, but lack the parameters

  19. Predicting ecological roles in the rhizosphere using metabolome and transportome modeling

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Larsen, Peter E.; Collart, Frank R.; Dai, Yang; Blanchard, Jeffrey L.

    2015-09-02

    The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. New algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad’s ecological role in the rhizosphere: a biofilm, biocontrol agent, promoter ofmore » plant growth, or plant pathogen. Computational predictions of ecological niche were highly accurate overall with models trained on transportomic model output being the most accurate (Leave One Out Validation F-scores between 0.82 and 0.89). The strongest predictive molecular mechanism features for rhizosphere ecological niche overlap with many previously reported analyses of Pseudomonad interactions in the rhizosphere, suggesting that this approach successfully informs a system-scale level understanding of how Pseudomonads sense and interact with their environments. The observation that an organism’s transportome is highly predictive of its ecological niche is a novel discovery and may have implications in our understanding microbial ecology. The framework developed here can be generalized to the analysis of any bacteria across a wide range of environments and ecological niches making this approach a powerful tool for providing insights into functional predictions from bacterial genomic data.« less

  20. An Elastic-Plastic and Strength Prediction Model for Injection-Molded Long-Fiber Thermoplastics

    SciTech Connect (OSTI)

    Nguyen, Ba Nghiep; Kunc, Vlastimil; Phelps, Jay; Tucker III, Charles L.; Bapanapalli, Satish K.

    2008-09-01

    This paper applies a recently developed model to predict the elastic-plastic stress/strain response and strength of injection-molded long-fiber thermoplastics (LFTs). The model combines a micro-macro constitutive modeling approach with experimental characterization and modeling of the composite microstructure to determine the composite stress/strain response and strength. Specifically, it accounts for elastic fibers embedded in a thermoplastic resin that exhibits the elastic-plastic behavior obeying the Ramberg-Osgood relation and J-2 deformation theory of plasticity. It also accounts for fiber length, orientation and volume fraction distributions in the composite formed by the injection-molding process. Injection-molded-long-glass-fiber/polypropylene (PP) specimens were prepared for mechanical characterization and testing. Fiber length, orientation, and volume fraction distributions were then measured at some selected locations for use in the computation. Fiber orientations in these specimens were also predicted using an anisotropic rotary diffusion model developed for LFTs. The stress-strain response of the as-formed composite was computed by an incremental procedure that uses the Eshelbys equivalent inclusion method, the Mori-Tanaka assumption and a fiber orientation averaging technique. The model has been validated against the experimental stress-strain results obtained for these long-glass-fiber/PP specimens.

  1. Project Profile: Physics-Based Reliability Models for Supercritical...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Physics-Based Reliability Models for Supercritical-CO2 Turbomachinery Components Project Profile: Physics-Based Reliability Models for Supercritical-CO2 Turbomachinery Components ...

  2. Physics-based statistical learning approach to mesoscopic model...

    Office of Scientific and Technical Information (OSTI)

    Physics-based statistical learning approach to mesoscopic model selection Citation Details ... Title: Physics-based statistical learning approach to mesoscopic model selection Authors: ...

  3. Predictive Theory and Modeling| U.S. DOE Office of Science (SC)

    Office of Science (SC) Website

    Predictive Theory and Modeling Basic Energy Sciences (BES) BES Home About Research Facilities Science Highlights Benefits of BES Funding Opportunities Closed Funding Opportunity Announcements (FOAs) Closed Lab Announcements Award Search / Public Abstracts Additional Requirements and Guidance for Digital Data Management Peer Review Policies EFRCs FOA Applications from Universities and Other Research Institutions Construction Review EPSCoR DOE Office of Science Graduate Fellowship (DOE SCGF)

  4. Controlling Bimetallic Nanostructures by the Microemulsion Method with Subnanometer Resolution Using a Prediction Model

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Buceta, D.; Tojo, C.; Vukmirovic, M.; Deepak, F. L.; Arturo Lopez-Quintela, M.

    2015-07-14

    We present a theoretical model to predict the atomic structure of Au/Pt nanoparticles synthesized in microemulsions. Excellent concordance with the experimental results shows that the structure of the nanoparticles can be controlled at sub-nanometer resolution simply by changing the reactants concentration. The results of this study not only offer a better understanding of the complex mechanisms governing reactions in microemulsions, but open up a simple new way to synthesize bimetallic nanoparticles with ad-hoc controlled nanostructures.

  5. A comparison of general circulation model predictions to sand drift and dune orientations

    SciTech Connect (OSTI)

    Blumberg, D.G.; Greeley, R.

    1996-12-01

    The growing concern over climate change and decertification stresses the importance of aeolian process prediction. In this paper the use of a general circulation model to predict current aeolian features is examined. A GCM developed at NASA/Goddard Space Flight Center was used in conjunction with White`s aeolian sand flux model to produce a global potential aeolian transport map. Surface wind shear stress predictions were used from the output of a GCM simulation that was performed as part of the Atmospheric Model Intercomparison Project on 1979 climate conditions. The spatial resolution of this study (as driven by the GCM) is 4{degrees} X 5{degrees}; instantaneous 6-hourly wind stress data were saved by the GCM and used in this report. A global map showing potential sand transport was compared to drift potential directions as inferred from Landsat images from the 1980s for several sand seas and a coastal dune field. Generally, results show a good correlation between the simulated sand drift direction and the drift direction inferred for dune forms. Discrepancies between the drift potential and the drift inferred from images were found in the North American deserts and the Arabian peninsula. An attempt to predict the type of dune that would be formed in specific regions was not successful. The model could probably be further improved by incorporating soil moisture, surface roughness, and vegetation information for a better assessment of sand threshold conditions. The correlation may permit use of a GCM to analyze {open_quotes}fossil{close_quotes} dunes or to forecast aeolian processes. 48 refs., 8 figs.

  6. Aquatic Pathways Model to predict the fate of phenolic compounds. Appendixes A through D

    SciTech Connect (OSTI)

    Aaberg, R.L.; Peloquin, R.A.; Strenge, D.L.; Mellinger, P.L.

    1983-04-01

    Organic materials released from energy-related activities could affect human health and the environment. We have developed a model to predict the fate of spills or discharges of pollutants into flowing or static bodies of fresh water. A computer code, Aquatic Pathways Model (APM), was written to implement the model. The APM estimates the concentrations of chemicals in fish tissue, water and sediment, and is therefore useful for assessing exposure to humans through aquatic pathways. The major pathways considered are biodegradation, fish and sediment uptake, photolysis, and evaporation. The model has been implemented with parameters for the distribution of phenols, an important class of compounds found in the water-soluble fractions of coal liquids. The model was developed to estimate the fate of liquids derived from coal. Current modeling efforts show that, in comparison with many pesticides and polyaromatic hydrocarbons (PAH), the lighter phenolics (the cresols) are not persistent in the environment. For the twelve phenolics studied, biodegradation appears to be the major pathway for elimination from aquatic environments. A pond system simulation of a spill of solvent-refined coal (SRC-II) materials indicates that phenol, cresols, and other single cyclic phenolics are degraded to 16 to 25 percent of their original concentrations within 30 hours. Adsorption of these compounds into sediments and accumulation by fish was minor. Results of a simulated spill of a coal liquid (SRC-II) into a pond show that APM predicted the allocation of 12 phenolic components among six compartments at 30 hours after a small spill. The simulation indicated that most of the introduced phenolic compounds were biodegraded. The phenolics remaining in the aquatic system partitioned according to their molecular weight and structure. A substantial amount was predicted to remain in the water, with less than 0.01% distributed in sediment or fish.

  7. Model-based Tomographic Reconstruction Literature Search

    SciTech Connect (OSTI)

    Chambers, D H; Lehman, S K

    2005-11-30

    In the process of preparing a proposal for internal research funding, a literature search was conducted on the subject of model-based tomographic reconstruction (MBTR). The purpose of the search was to ensure that the proposed research would not replicate any previous work. We found that the overwhelming majority of work on MBTR which used parameterized models of the object was theoretical in nature. Only three researchers had applied the technique to actual data. In this note, we summarize the findings of the literature search.

  8. Ductile Tearing of Thin Aluminum Plates Under Blast Loading. Predictions with Fully Coupled Models and Biaxial Material Response Characterization

    SciTech Connect (OSTI)

    Corona, Edmundo; Gullerud, Arne S.; Haulenbeek, Kimberly K.; Reu, Phillip L.

    2015-06-01

    The work presented in this report concerns the response and failure of thin 2024- T3 aluminum alloy circular plates to a blast load produced by the detonation of a nearby spherical charge. The plates were fully clamped around the circumference and the explosive charge was located centrally with respect to the plate. The principal objective was to conduct a numerical model validation study by comparing the results of predictions to experimental measurements of plate deformation and failure for charges with masses in the vicinity of the threshold between no tearing and tearing of the plates. Stereo digital image correlation data was acquired for all tests to measure the deflection and strains in the plates. The size of the virtual strain gage in the measurements, however, was relatively large, so the strain measurements have to be interpreted accordingly as lower bounds of the actual strains in the plate and of the severity of the strain gradients. A fully coupled interaction model between the blast and the deflection of the structure was considered. The results of the validation exercise indicated that the model predicted the deflection of the plates reasonably accurately as well as the distribution of strain on the plate. The estimation of the threshold charge based on a critical value of equivalent plastic strain measured in a bulge test, however, was not accurate. This in spite of efforts to determine the failure strain of the aluminum sheet under biaxial stress conditions. Further work is needed to be able to predict plate tearing with some degree of confidence. Given the current technology, at least one test under the actual blast conditions where the plate tears is needed to calibrate the value of equivalent plastic strain when failure occurs in the numerical model. Once that has been determined, the question of the explosive mass value at the threshold could be addressed with more confidence.

  9. Stem thrust prediction model for W-K-M double wedge parallel expanding gate valves

    SciTech Connect (OSTI)

    Eldiwany, B.; Alvarez, P.D.; Wolfe, K.

    1996-12-01

    An analytical model for determining the required valve stem thrust during opening and closing strokes of W-K-M parallel expanding gate valves was developed as part of the EPRI Motor-Operated Valve Performance Prediction Methodology (EPRI MOV PPM) Program. The model was validated against measured stem thrust data obtained from in-situ testing of three W-K-M valves. Model predictions show favorable, bounding agreement with the measured data for valves with Stellite 6 hardfacing on the disks and seat rings for water flow in the preferred flow direction (gate downstream). The maximum required thrust to open and to close the valve (excluding wedging and unwedging forces) occurs at a slightly open position and not at the fully closed position. In the nonpreferred flow direction, the model shows that premature wedging can occur during {Delta}P closure strokes even when the coefficients of friction at different sliding surfaces are within the typical range. This paper summarizes the model description and comparison against test data.

  10. Developing algorithms for predicting protein-protein interactions of homology modeled proteins.

    SciTech Connect (OSTI)

    Martin, Shawn Bryan; Sale, Kenneth L.; Faulon, Jean-Loup Michel; Roe, Diana C.

    2006-01-01

    The goal of this project was to examine the protein-protein docking problem, especially as it relates to homology-based structures, identify the key bottlenecks in current software tools, and evaluate and prototype new algorithms that may be developed to improve these bottlenecks. This report describes the current challenges in the protein-protein docking problem: correctly predicting the binding site for the protein-protein interaction and correctly placing the sidechains. Two different and complementary approaches are taken that can help with the protein-protein docking problem. The first approach is to predict interaction sites prior to docking, and uses bioinformatics studies of protein-protein interactions to predict theses interaction site. The second approach is to improve validation of predicted complexes after docking, and uses an improved scoring function for evaluating proposed docked poses, incorporating a solvation term. This scoring function demonstrates significant improvement over current state-of-the art functions. Initial studies on both these approaches are promising, and argue for full development of these algorithms.

  11. A Screening Model to Predict Microalgae Biomass Growth in Photobioreactors and Raceway Ponds

    SciTech Connect (OSTI)

    Huesemann, Michael H.; Van Wagenen, Jonathan M.; Miller, Tyler W.; Chavis, Aaron R.; Hobbs, Watts B.; Crowe, Braden J.

    2013-06-01

    A microalgae biomass growth model was developed for screening novel strains for their potential to exhibit high biomass productivities under nutrient-replete conditions in photobioreactors or outdoor ponds. Growth is modeled by first estimating the light attenuation by biomass according to Beer-Lamberts law, and then calculating the specific growth rate in discretized culture volume slices that receive declining light intensities due to attenuation. The model requires only two physical and two species-specific biological input parameters, all of which are relatively easy to determine: incident light intensity, culture depth, as well as the biomass light absorption coefficient and the specific growth rate as a function of light intensity. Roux bottle culture experiments were performed with Nannochloropsis salina at constant temperature (23 C) at six different incident light intensities (5, 10, 25, 50, 100, 250, and 850 ?mol/m2? sec) to determine both the specific growth rate under non-shading conditions and the biomass light absorption coefficient as a function of light intensity. The model was successful in predicting the biomass growth rate in these Roux bottle cultures during the light-limited linear phase at different incident light intensities. Model predictions were moderately sensitive to minor variations in the values of input parameters. The model was also successful in predicting the growth performance of Chlorella sp. cultured in LED-lighted 800 L raceway ponds operated at constant temperature (30 C) and constant light intensity (1650 ?mol/m2? sec). Measurements of oxygen concentrations as a function of time demonstrated that following exposure to darkness, it takes at least 5 seconds for cells to initiate dark respiration. As a result, biomass loss due to dark respiration in the aphotic zone of a culture is unlikely to occur in highly mixed small-scale photobioreactors where cells move rapidly in and out of the light. By contrast, as supported also by

  12. Lumped Parameter Modeling as a Predictive Tool for a Battery Status Monitor

    SciTech Connect (OSTI)

    Jon P. Christophersen; Chester G. Motloch; Chinh D. Ho; John L. Morrison; Ronald C. Fenton; Vincent S. Battaglia; Tien Q. Duong

    2003-10-01

    The Advanced Technology Development Program is currently evaluating the performance of the second generation of lithium-ion cells (i.e., Gen 2 cells). Both the Gen 2 Baseline and Variant C cells are tested in accordance with the cell-specific test plan, and are removed at roughly equal power fade increments and sent for destructive diagnostic analysis. The diagnostic laboratories did not need all test cells for analysis, and returned five spare cells to the Idaho National Engineering and Environmental Laboratory (INEEL). INEEL used these cells for special pulse testing at various duty cycles, amplitudes, and durations to investigate the usefulness of the lumped parameter model (LPM) as a predictive tool in a battery status monitor (BSM). The LPM is a simplified linear model that accurately predicts the voltage response during certain pulse conditions. A database of parameter trends should enable dynamic predictions of state-of-charge and state-of-health conditions during in-vehicle pulsing. This information could be used by the BSM to provide accurate information to the vehicle control system.

  13. Rolling Process Modeling Report: Finite-Element Prediction of Roll Separating Force and Rolling Defects

    SciTech Connect (OSTI)

    Soulami, Ayoub; Lavender, Curt A.; Paxton, Dean M.; Burkes, Douglas

    2014-04-23

    Pacific Northwest National Laboratory (PNNL) has been investigating manufacturing processes for the uranium-10% molybdenum (U-10Mo) alloy plate-type fuel for the U.S. high-performance research reactors. This work supports the Convert Program of the U.S. Department of Energy’s National Nuclear Security Administration (DOE/NNSA) Global Threat Reduction Initiative. This report documents modeling results of PNNL’s efforts to perform finite-element simulations to predict roll separating forces and rolling defects. Simulations were performed using a finite-element model developed using the commercial code LS-Dyna. Simulations of the hot rolling of U-10Mo coupons encapsulated in low-carbon steel have been conducted following two different schedules. Model predictions of the roll-separation force and roll-pack thicknesses at different stages of the rolling process were compared with experimental measurements. This report discusses various attributes of the rolled coupons revealed by the model (e.g., dog-boning and thickness non-uniformity).

  14. Depositional sequence analysis and sedimentologic modeling for improved prediction of Pennsylvanian reservoirs

    SciTech Connect (OSTI)

    Watney, W.L.

    1994-12-01

    Reservoirs in the Lansing-Kansas City limestone result from complex interactions among paleotopography (deposition, concurrent structural deformation), sea level, and diagenesis. Analysis of reservoirs and surface and near-surface analogs has led to developing a {open_quotes}strandline grainstone model{close_quotes} in which relative sea-level stabilized during regressions, resulting in accumulation of multiple grainstone buildups along depositional strike. Resulting stratigraphy in these carbonate units are generally predictable correlating to inferred topographic elevation along the shelf. This model is a valuable predictive tool for (1) locating favorable reservoirs for exploration, and (2) anticipating internal properties of the reservoir for field development. Reservoirs in the Lansing-Kansas City limestones are developed in both oolitic and bioclastic grainstones, however, re-analysis of oomoldic reservoirs provides the greatest opportunity for developing bypassed oil. A new technique, the {open_quotes}Super{close_quotes} Pickett crossplot (formation resistivity vs. porosity) and its use in an integrated petrophysical characterization, has been developed to evaluate extractable oil remaining in these reservoirs. The manual method in combination with 3-D visualization and modeling can help to target production limiting heterogeneities in these complex reservoirs and moreover compute critical parameters for the field such as bulk volume water. Application of this technique indicates that from 6-9 million barrels of Lansing-Kansas City oil remain behind pipe in the Victory-Northeast Lemon Fields. Petroleum geologists are challenged to quantify inferred processes to aid in developing rationale geologically consistent models of sedimentation so that acceptable levels of prediction can be obtained.

  15. Reduced-Order Model Based Feedback Control For Modified Hasegawa...

    Office of Scientific and Technical Information (OSTI)

    Reduced-Order Model Based Feedback Control For Modified Hasegawa-Wakatani Model Citation Details In-Document Search Title: Reduced-Order Model Based Feedback Control For Modified ...

  16. MM-Estimator and Adjusted Super Smoother based Simultaneous Prediction Confedenc

    Energy Science and Technology Software Center (OSTI)

    2002-07-19

    A Novel Application of Regression Analysis (MM-Estimator) with Simultaneous Prediction Confidence Intervals are proposed to detect up- or down-regulated genes, which are outliers in scatter plots based on log-transformed red (Cy5 fluorescent dye) versus green (Cy3 fluorescent Dye) intensities. Advantages of the application: 1) Robust and Resistant MM-Estimator is a Reliable Method to Build Linear Regression In the presence of Outliers, 2) Exploratory Data Analysis Tools (Boxplots, Averaged Shifted Histograms, Quantile-Quantile Normal Plots and Scattermore » Plots) are Unsed to Test Visually underlying assumptions of linearity and Contaminated Normality in Microarray data), 3) Simultaneous prediction confidence intervals (SPCIs) Guarantee a desired confidence level across the whole range of the data points used for the scatter plots. Results of the outlier detection procedure is a set of significantly differentially expressed genes extracted from the employed microarray data set. A scatter plot smoother (super smoother or locally weighted regression) is used to quantify heteroscendasticity is residual variance (Commonly takes place in lower and higher intensity areas). The set of differentially expressed genes is quantified using interval estimates for P-values as a probabilistic measure of being outlier by chance. Monte Carlo simultations are used to adjust super smoother-based SPCIs.her.« less

  17. Model based control of a coke battery

    SciTech Connect (OSTI)

    Stone, P.M.; Srour, J.M.; Zulli, P.; Cunningham, R.; Hockings, K.

    1997-12-31

    This paper describes a model-based strategy for coke battery control at BHP Steel`s operations in Pt Kembla, Australia. The strategy uses several models describing the battery thermal and coking behavior. A prototype controller has been installed on the Pt Kembla No. 6 Battery (PK6CO). In trials, the new controller has been well accepted by operators and has resulted in a clear improvement in battery thermal stability, with a halving of the standard deviation of average battery temperature. Along with other improvements to that battery`s operations, this implementation has contributed to a 10% decrease in specific battery energy consumption. A number of enhancements to the low level control systems on that battery are currently being undertaken in order to realize further benefits.

  18. Threshold Values for Identification of Contamination Predicted by Reduced-Order Models

    SciTech Connect (OSTI)

    Last, George V.; Murray, Christopher J.; Bott, Yi-Ju; Brown, Christopher F.

    2014-12-31

    The U.S. Department of Energys (DOEs) National Risk Assessment Partnership (NRAP) Project is developing reduced-order models to evaluate potential impacts on underground sources of drinking water (USDWs) if CO2 or brine leaks from deep CO2 storage reservoirs. Threshold values, below which there would be no predicted impacts, were determined for portions of two aquifer systems. These threshold values were calculated using an interwell approach for determining background groundwater concentrations that is an adaptation of methods described in the U.S. Environmental Protection Agencys Unified Guidance for Statistical Analysis of Groundwater Monitoring Data at RCRA Facilities.

  19. Controlling bimetallic nanostructures by the microemulsion method with subnanometer resolution using a prediction model

    SciTech Connect (OSTI)

    Buceta, David; Tojo, Concha; Vukmirovic, Miomir B.; Deepak, F. Leonard; Lopez-Quintela, M. Arturo

    2015-06-02

    In this study, we present a theoretical model to predict the atomic structure of Au/Pt nanoparticles synthesized in microemulsions. Excellent concordance with the experimental results shows that the structure of the nanoparticles can be controlled at sub-nanometer resolution simply by changing the reactants concentration. The results of this study not only offer a better understanding of the complex mechanisms governing reactions in microemulsions, but open up a simple new way to synthesize bimetallic nanoparticles with ad-hoc controlled nanostructures.

  20. Threshold Values for Identification of Contamination Predicted by Reduced-Order Models

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Last, George V.; Murray, Christopher J.; Bott, Yi-Ju; Brown, Christopher F.

    2014-12-31

    The U.S. Department of Energy’s (DOE’s) National Risk Assessment Partnership (NRAP) Project is developing reduced-order models to evaluate potential impacts on underground sources of drinking water (USDWs) if CO2 or brine leaks from deep CO2 storage reservoirs. Threshold values, below which there would be no predicted impacts, were determined for portions of two aquifer systems. These threshold values were calculated using an interwell approach for determining background groundwater concentrations that is an adaptation of methods described in the U.S. Environmental Protection Agency’s Unified Guidance for Statistical Analysis of Groundwater Monitoring Data at RCRA Facilities.

  1. Biologically based multistage modeling of radiation effects

    SciTech Connect (OSTI)

    William Hazelton; Suresh Moolgavkar; E. Georg Luebeck

    2005-08-30

    This past year we have made substantial progress in modeling the contribution of homeostatic regulation to low-dose radiation effects and carcinogenesis. We have worked to refine and apply our multistage carcinogenesis models to explicitly incorporate cell cycle states, simple and complex damage, checkpoint delay, slow and fast repair, differentiation, and apoptosis to study the effects of low-dose ionizing radiation in mouse intestinal crypts, as well as in other tissues. We have one paper accepted for publication in ''Advances in Space Research'', and another manuscript in preparation describing this work. I also wrote a chapter describing our combined cell-cycle and multistage carcinogenesis model that will be published in a book on stochastic carcinogenesis models edited by Wei-Yuan Tan. In addition, we organized and held a workshop on ''Biologically Based Modeling of Human Health Effects of Low dose Ionizing Radiation'', July 28-29, 2005 at Fred Hutchinson Cancer Research Center in Seattle, Washington. We had over 20 participants, including Mary Helen Barcellos-Hoff as keynote speaker, talks by most of the low-dose modelers in the DOE low-dose program, experimentalists including Les Redpath (and Mary Helen), Noelle Metting from DOE, and Tony Brooks. It appears that homeostatic regulation may be central to understanding low-dose radiation phenomena. The primary effects of ionizing radiation (IR) are cell killing, delayed cell cycling, and induction of mutations. However, homeostatic regulation causes cells that are killed or damaged by IR to eventually be replaced. Cells with an initiating mutation may have a replacement advantage, leading to clonal expansion of these initiated cells. Thus we have focused particularly on modeling effects that disturb homeostatic regulation as early steps in the carcinogenic process. There are two primary considerations that support our focus on homeostatic regulation. First, a number of epidemiologic studies using multistage

  2. NCAR Contribution to A U.S. National Multi-Model Ensemble (NMME) ISI Prediction System

    SciTech Connect (OSTI)

    Tribbia, Joseph

    2015-11-25

    NCAR brought the latest version of the Community Earth System Model (version 1, CESM1) into the mix of models in the NMME effort. This new version uses our newest atmospheric model CAM5 and produces a coupled climate and ENSO that are generally as good or better than those of the Community Climate System Model version 4 (CCSM4). Compared to CCSM4, the new coupled model has a superior climate response with respect to low clouds in both the subtropical stratus regimes and the Arctic. However, CESM1 has been run to date using a prognostic aerosol model that more than doubles its computational cost. We are currently evaluating a version of the new model using prescribed aerosols and expect it will be ready for integrations in summer 2012. Because of this NCAR has not been able to complete the hindcast integrations using the NCAR loosely-coupled ensemble Kalman filter assimilation method nor has it contributed to the current (Stage I) NMME operational utilization. The expectation is that this model will be included in the NMME in late 2012 or early 2013. The initialization method will utilize the Ensemble Kalman Filter Assimilation methods developed at NCAR using the Data Assimilation Research Testbed (DART) in conjunction with Jeff Anderson’s team in CISL. This methodology has been used in our decadal prediction contributions to CMIP5. During the course of this project, NCAR has setup and performed all the needed hindcast and forecast simulations and provide the requested fields to our collaborators. In addition, NCAR researchers have participated fully in research themes (i) and (ii). Specifically, i) we have begun to evaluate and optimize our system in hindcast mode, focusing on the optimal number of ensemble members, methodologies to recalibrate individual dynamical models, and accessing our forecasts across multiple time scales, i.e., beyond two weeks, and ii) we have begun investigation of the role of different ocean initial conditions in seasonal forecasts. The

  3. Bayesian probabilistic model for life prediction and fault mode classification of solid state luminaires

    SciTech Connect (OSTI)

    Lall, Pradeep; Wei, Junchao; Sakalaukus, Peter

    2014-06-22

    A new method has been developed for assessment of the onset of degradation in solid state luminaires to classify failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. Failure modes of the test population of the lamps have been studied to understand the failure mechanisms in 85°C/85%RH accelerated test. Results indicate that the dominant failure mechanism is the discoloration of the LED encapsulant inside the lamps which is the likely cause for the luminous flux degradation and the color shift. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identify luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. The α-λ plots have been used to evaluate the robustness of the proposed methodology. Results show that the predicted degradation for the lamps tracks the true degradation observed during 85°C/85%RH during accelerated life test fairly closely within the ±20% confidence bounds. Correlation of model prediction with experimental results indicates that the presented methodology allows the early identification of the onset of failure much prior to development of complete failure distributions and can be used for assessing the damage state of SSLs in fairly large deployments. It is expected that, the new prediction technique will allow the development of failure distributions without testing till L70 life for the manifestation of failure.

  4. Comparison of limited measurements of the OTEC-1 plume with analytical-model predictions

    SciTech Connect (OSTI)

    Paddock, R.A.; Ditmars, J.D.

    1981-07-01

    Ocean Thermal Energy Conversion (OTEC) requires significant amounts of warm surface waters and cold deep waters for power production. Because these waters are returned to the ocean as effluents, their behavior may affect plant operation and impact the environment. The OTEC-1 facility tested 1-MWe heat exchangers aboard the vessel Ocean Energy Converter moored off the island of Hawaii. The warm and cold waters used by the OTEC-1 facility were combined prior to discharge from the vessel to create a mixed discharge condition. A limited field survey of the mixed discharge plume using fluorescent dye as a tracer was conducted on April 11, 1981, as part of the environmental studies at OTEC-1 coordinated by the Marine Sciences Group at Lawrence Berkeley Laboratory. Results of that survey were compared with analytical model predictions of plume behavior. Although the predictions were in general agreement with the results of the plume survey, inherent limitations in the field measurements precluded complete description of the plume or detailed evaluation of the models.

  5. Mathematical model for predicting the probability of acute mortality in a human population exposed to accidentally released airborne radionuclides. Final report for Phase I

    SciTech Connect (OSTI)

    Filipy, R.E.; Borst, F.J.; Cross, F.T.; Park, J.F.; Moss, O.R.; Roswell, R.L.; Stevens, D.L.

    1980-05-01

    A mathematical model was constructed for the purpose of predicting the fraction of human population which would die within 1 year of an accidental exposure to airborne radionuclides. The model is based on data from laboratory experiments with rats, dogs and baboons, and from human epidemiological data. Doses from external, whole-body irradiation and from inhaled, alpha- and beta-emitting radionuclides are calculated for several organs. The probabilities of death from radiation pneumonitis and from bone marrow irradiation are predicted from doses accumulated within 30 days of exposure to the radioactive aerosol. The model is compared with existing similar models under hypothetical exposure conditions. Suggestions for further experiments with inhaled radionuclides are included. 25 refs., 16 figs., 13 tabs.

  6. Investigation of the effect of chemistry models on the numerical predictions of the supersonic combustion of hydrogen

    SciTech Connect (OSTI)

    Kumaran, K.; Babu, V.

    2009-04-15

    In this numerical study, the influence of chemistry models on the predictions of supersonic combustion in a model combustor is investigated. To this end, 3D, compressible, turbulent, reacting flow calculations with a detailed chemistry model (with 37 reactions and 9 species) and the Spalart-Allmaras turbulence model have been carried out. These results are compared with earlier results obtained using single step chemistry. Hydrogen is used as the fuel and three fuel injection schemes, namely, strut, staged (i.e., strut and wall) and wall injection, are considered to evaluate the impact of the chemistry models on the flow field predictions. Predictions of the mass fractions of major species, minor species, dimensionless stagnation temperature, dimensionless static pressure rise and thrust percentage along the combustor length are presented and discussed. Overall performance metrics such as mixing efficiency and combustion efficiency are used to draw inferences on the nature (whether mixing- or kinetic-controlled) and the completeness of the combustion process. The predicted values of the dimensionless wall static pressure are compared with experimental data reported in the literature. The calculations show that multi step chemistry predicts higher and more wide spread heat release than what is predicted by single step chemistry. In addition, it is also shown that multi step chemistry predicts intricate details of the combustion process such as the ignition distance and induction distance. (author)

  7. A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients

    SciTech Connect (OSTI)

    Oberije, Cary; De Ruysscher, Dirk; Houben, Ruud; Heuvel, Michel van de; Uyterlinde, Wilma; Deasy, Joseph O.; Belderbos, Jose; Dingemans, Anne-Marie C.; Rimner, Andreas; Din, Shaun; Lambin, Philippe

    2015-07-15

    Purpose: Although patients with stage III non-small cell lung cancer (NSCLC) are homogeneous according to the TNM staging system, they form a heterogeneous group, which is reflected in the survival outcome. The increasing amount of information for an individual patient and the growing number of treatment options facilitate personalized treatment, but they also complicate treatment decision making. Decision support systems (DSS), which provide individualized prognostic information, can overcome this but are currently lacking. A DSS for stage III NSCLC requires the development and integration of multiple models. The current study takes the first step in this process by developing and validating a model that can provide physicians with a survival probability for an individual NSCLC patient. Methods and Materials: Data from 548 patients with stage III NSCLC were available to enable the development of a prediction model, using stratified Cox regression. Variables were selected by using a bootstrap procedure. Performance of the model was expressed as the c statistic, assessed internally and on 2 external data sets (n=174 and n=130). Results: The final multivariate model, stratified for treatment, consisted of age, gender, World Health Organization performance status, overall treatment time, equivalent radiation dose, number of positive lymph node stations, and gross tumor volume. The bootstrapped c statistic was 0.62. The model could identify risk groups in external data sets. Nomograms were constructed to predict an individual patient's survival probability ( (www.predictcancer.org)). The data set can be downloaded at (https://www.cancerdata.org/10.1016/j.ijrobp.2015.02.048). Conclusions: The prediction model for overall survival of patients with stage III NSCLC highlights the importance of combining patient, clinical, and treatment variables. Nomograms were developed and validated. This tool could be used as a first building block for a decision support system.

  8. Improving Thermal Model Prediction Through Statistical Analysis of Irradiation and Post-Irradiation Data from AGR Experiments

    SciTech Connect (OSTI)

    Binh T. Pham; Grant L. Hawkes; Jeffrey J. Einerson

    2014-05-01

    As part of the High Temperature Reactors (HTR) R&D program, a series of irradiation tests, designated as Advanced Gas-cooled Reactor (AGR), have been defined to support development and qualification of fuel design, fabrication process, and fuel performance under normal operation and accident conditions. The AGR tests employ fuel compacts placed in a graphite cylinder shrouded by a steel capsule and instrumented with thermocouples (TC) embedded in graphite blocks enabling temperature control. While not possible to obtain by direct measurements in the tests, crucial fuel conditions (e.g., temperature, neutron fast fluence, and burnup) are calculated using core physics and thermal modeling codes. This paper is focused on AGR test fuel temperature predicted by the ABAQUS code's finite element-based thermal models. The work follows up on a previous study, in which several statistical analysis methods were adapted, implemented in the NGNP Data Management and Analysis System (NDMAS), and applied for qualification of AGR-1 thermocouple data. Abnormal trends in measured data revealed by the statistical analysis are traced to either measuring instrument deterioration or physical mechanisms in capsules that may have shifted the system thermal response. The main thrust of this work is to exploit the variety of data obtained in irradiation and post-irradiation examination (PIE) for assessment of modeling assumptions. As an example, the uneven reduction of the control gas gap in Capsule 5 found in the capsule metrology measurements in PIE helps identify mechanisms other than TC drift causing the decrease in TC readings. This suggests a more physics-based modification of the thermal model that leads to a better fit with experimental data, thus reducing model uncertainty and increasing confidence in the calculated fuel temperatures of the AGR-1 test.

  9. Prediction of dissolved actinide concentrations in concentrated electrolyte solutions: a conceptual model and model results for the Waste Isolation Pilot Plant (WIPP)

    SciTech Connect (OSTI)

    Novak, C.F.; Moore, R.C.; Bynum, R.V.

    1996-10-25

    The conceptual model for WIPP dissolved concentrations is a description of the complex natural and artificial chemical conditions expected to influence dissolved actinide concentrations in the repository. By a set of physical and chemical assumptions regarding chemical kinetics, sorption substrates, and waste-brine interactions, the system was simplified to be amenable to mathematical description. The analysis indicated that an equilibrium thermodynamic model for describing actinide solubilities in brines would be tractable and scientifically supportable. This paper summarizes the conceptualization and modeling approach and the computational results as used in the WIPP application for certification of compliance with relevant regulations for nuclear waste repositories. The WIPP site contains complex natural brines ranging from sea water to 10x more concentrated than sea water. Data bases for predicting solubility of Am(III) (as well as Pu(III) and Nd(III)), Th(IV), and Np(V) in these brines under potential repository conditions have been developed, focusing on chemical interactions with Na, K, Mg, Cl, SO{sub 4}, and CO{sub 3} ions, and the organic acid anions acetate, citrate, EDTA, and oxalate. The laboratory and modeling effort augmented the Harvie et al. parameterization of the Pitzer activity coefficient model so that it could be applied to the actinides and oxidation states important to the WIPP system.

  10. Modeling of stagnation-line nonequilibrium flows by means of quantum based collisional models

    SciTech Connect (OSTI)

    Munafò, A. Magin, T. E.

    2014-09-15

    The stagnation-line flow over re-entry bodies is analyzed by means of a quantum based collisional model which accounts for dissociation and energy transfer in N{sub 2}-N interactions. The physical model is based on a kinetic database developed at NASA Ames Research Center. The reduction of the kinetic mechanism is achieved by lumping the rovibrational energy levels of the N{sub 2} molecule in energy bins. The energy bins are treated as separate species, thus allowing for non-Boltzmann distributions of their populations. The governing equations are discretized in space by means of the Finite Volume method. A fully implicit time-integration is used to obtain steady-state solutions. The results show that the population of the energy bins strongly deviate from a Boltzmann distribution close to the shock wave and across the boundary layer. The sensitivity analysis to the number of energy bins reveals that accurate estimation of flow quantities (such as chemical composition and wall heat flux) can be obtained by using only 10 energy bins. A comparison with the predictions obtained by means of conventional multi-temperature models indicates that the former can lead to an overestimation of the wall heat flux, due to an inaccurate modeling of recombination in the boundary layer.

  11. Model-Based Transient Calibration Optimization for Next Generation...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Based Transient Calibration Optimization for Next Generation Diesel Engines Model-Based Transient Calibration Optimization for Next Generation Diesel Engines 2005 Diesel Engine...

  12. Demonstrating and Validating a Next Generation Model-Based Controller...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Model-Based Controller for Fuel Efficient, Low Emissions Diesel Engines Fully model-based, practically-mapless engine control concept is viable PDF icon deer09allain.pdf...

  13. Commercial Buildings Sector Agent-Based Model | Open Energy Informatio...

    Open Energy Info (EERE)

    OpenEI Keyword(s): EERE tool, Commercial Buildings Sector Agent-Based Model Language: English References: Building Efficiency: Development of an Agent-based Model of the US...

  14. Evaluation and prediction of color-tunable organic light-emitting diodes based on carrier/exciton adjusting interlayer

    SciTech Connect (OSTI)

    Liu, Shengqiang; Li, Jie; Yu, Junsheng; Du, Chunlei

    2015-07-27

    A color tuning index (I{sub CT}) parameter for evaluating the color change capability of color-tunable organic light-emitting diodes (CT-OLEDs) was proposed and formulated. And a series of CT-OLEDs, consisting of five different carrier/exciton adjusting interlayers (C/EALs) inserted between two complementary emitting layers, were fabricated and applied to disclose the relationship between I{sub CT} and C/EALs. The result showed that the trend of electroluminescence spectra behavior in CT-OLEDs has good accordance with I{sub CT} values, indicating that the I{sub CT} parameter is feasible for the evaluation of color variation. Meanwhile, by changing energy level and C/EAL thickness, the optimized device with the widest color tuning range was based on N,N′-dicarbazolyl-3,5-benzene C/EAL, exhibiting the highest I{sub CT} value of 41.2%. Based on carrier quadratic hopping theory and exciton transfer model, two fitting I{sub CT} formulas derived from the highest occupied molecular orbital (HOMO) energy level and triplet energy level were simulated. Finally, a color tuning prediction (CTP) model was developed to deduce the I{sub CT} via C/EAL HOMO and triplet energy levels, and verified by the fabricated OLEDs with five different C/EALs. We believe that the CTP model assisted with I{sub CT} parameter will be helpful for fabricating high performance CT-OLEDs with a broad range of color tuning.

  15. Development and application of a statistical methodology to evaluate the predictive accuracy of building energy baseline models

    SciTech Connect (OSTI)

    Granderson, Jessica; Price, Phillip N.

    2014-03-01

    This paper documents the development and application of a general statistical methodology to assess the accuracy of baseline energy models, focusing on its application to Measurement and Verification (M&V) of whole-­building energy savings. The methodology complements the principles addressed in resources such as ASHRAE Guideline 14 and the International Performance Measurement and Verification Protocol. It requires fitting a baseline model to data from a ``training period’’ and using the model to predict total electricity consumption during a subsequent ``prediction period.’’ We illustrate the methodology by evaluating five baseline models using data from 29 buildings. The training period and prediction period were varied, and model predictions of daily, weekly, and monthly energy consumption were compared to meter data to determine model accuracy. Several metrics were used to characterize the accuracy of the predictions, and in some cases the best-­performing model as judged by one metric was not the best performer when judged by another metric.

  16. Water and Heat Balance Model for Predicting Drainage Below the Plant Root Zone

    Energy Science and Technology Software Center (OSTI)

    1989-11-01

    UNSAT-H Version 2.0 is a one-dimensional model that simulates the dynamic processes of infiltration, drainage, redistribution, surface evaporation, and the uptake of water from soil by plants. The model was developed for assessing the water dynamics of arid sites used or proposed for near-surface waste disposal. In particular, the model is used for simulating the water balance of cover systems over buried waste and for estimating the recharge rate (i.e., the drainage rate beneath themore » plant root zone when a sizable vadose zone is present). The mathematical base of the model are Richards'' equation for water flow, Ficks'' law for vapor diffusion, and Fouriers law for heat flow. The simulated profile can be homogeneous or layered. The boundary conditions can be controlled as either constant (potential or temperature) or flux conditions to reflect actual conditions at a given site.« less

  17. Parametric Adaptive Model Based Diagnostics | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Parametric Adaptive Model Based Diagnostics Parametric Adaptive Model Based Diagnostics A model-based adaptive, robust technology is presented for on-board diagnostics of failure of diesel engine emission control devices and ethanol estimation of flex-fuel vehicles. p-06_franchek.pdf (256.08 KB) More Documents & Publications Model-Based Transient Calibration Optimization for Next Generation Diesel Engines Evaluation of 2010 Urea-SCR Technology for Hybrid Vehicles using PSAT System

  18. Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

    2015-10-30

    An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

  19. Modeling Stress Strain Relationships and Predicting Failure Probabilities For Graphite Core Components

    SciTech Connect (OSTI)

    Duffy, Stephen

    2013-09-09

    This project will implement inelastic constitutive models that will yield the requisite stress-strain information necessary for graphite component design. Accurate knowledge of stress states (both elastic and inelastic) is required to assess how close a nuclear core component is to failure. Strain states are needed to assess deformations in order to ascertain serviceability issues relating to failure, e.g., whether too much shrinkage has taken place for the core to function properly. Failure probabilities, as opposed to safety factors, are required in order to capture the bariability in failure strength in tensile regimes. The current stress state is used to predict the probability of failure. Stochastic failure models will be developed that can accommodate possible material anisotropy. This work will also model material damage (i.e., degradation of mechanical properties) due to radiation exposure. The team will design tools for components fabricated from nuclear graphite. These tools must readily interact with finite element software--in particular, COMSOL, the software algorithm currently being utilized by the Idaho National Laboratory. For the eleastic response of graphite, the team will adopt anisotropic stress-strain relationships available in COMSO. Data from the literature will be utilized to characterize the appropriate elastic material constants.

  20. Development of a model for predicting transient hydrogen venting in 55-gallon drums

    SciTech Connect (OSTI)

    Apperson, Jason W; Clemmons, James S; Garcia, Michael D; Sur, John C; Zhang, Duan Z; Romero, Michael J

    2008-01-01

    Remote drum venting was performed on a population of unvented high activity drums (HAD) in the range of 63 to 435 plutonium equivalent Curies (PEC). These 55-gallon Transuranic (TRU) drums will eventually be shipped to the Waste Isolation Pilot Plant (WIPP). As a part of this process, the development of a calculational model was required to predict the transient hydrogen concentration response of the head space and polyethylene liner (if present) within the 55-gallon drum. The drum and liner were vented using a Remote Drum Venting System (RDVS) that provided a vent sampling path for measuring flammable hydrogen vapor concentrations and allow hydrogen to diffuse below lower flammability limit (LFL) concentrations. One key application of the model was to determine the transient behavior of hydrogen in the head space, within the liner, and the sensitivity to the number of holes made in the liner or number of filters. First-order differential mass transport equations were solved using Laplace transformations and numerically to verify the results. the Mathematica 6.0 computing tool was also used as a validation tool and for examining larger than two chamber systems. Results will be shown for a variety of configurations, including 85-gallon and 110-gallon overpack drums. The model was also validated against hydrogen vapor concentration assay measurements.

  1. Depositional sequence analysis and sedimentologic modeling for improved prediction of Pennsylvanian reservoirs (Annex 1)

    SciTech Connect (OSTI)

    Watney, W.L.

    1992-01-01

    Interdisciplinary studies of the Upper Pennsylvanian Lansing and Kansas City groups have been undertaken in order to improve the geologic characterization of petroleum reservoirs and to develop a quantitative understanding of the processes responsible for formation of associated depositional sequences. To this end, concepts and methods of sequence stratigraphy are being used to define and interpret the three-dimensional depositional framework of the Kansas City Group. The investigation includes characterization of reservoir rocks in oil fields in western Kansas, description of analog equivalents in near-surface and surface sites in southeastern Kansas, and construction of regional structural and stratigraphic framework to link the site specific studies. Geologic inverse and simulation models are being developed to integrate quantitative estimates of controls on sedimentation to produce reconstructions of reservoir-bearing strata in an attempt to enhance our ability to predict reservoir characteristics.

  2. Physics-based statistical model and simulation method of RF propagation in urban environments

    DOE Patents [OSTI]

    Pao, Hsueh-Yuan; Dvorak, Steven L.

    2010-09-14

    A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.

  3. Validation of model based active control of combustion instability

    SciTech Connect (OSTI)

    Fleifil, M.; Ghoneim, Z.; Ghoniem, A.F.

    1998-07-01

    The demand for efficient, company and clean combustion systems have spurred research into the fundamental mechanisms governing their performance and means of interactively changing their performance characteristics. Thermoacoustic instability which is frequently observed in combustion systems with high power density, when burning close to the lean flammability limit, or using exhaust gas recirculation to meet more stringent emissions regulations, etc. Its occurrence and/or means to mitigate them passively lead to performance degradation such as reduced combustion efficiency, high local heat transfer rates, increase in the mixture equivalence ratio or system failure due to structural damage. This paper reports on their study of the origin of thermoacoustic instability, its dependence on system parameters and the means of actively controlling it. The authors have developed an analytical model of thermoacoustic instability in premixed combustors. The model combines a heat release dynamics model constructed using the kinematics of a premixed flame stabilized behind a perforated plate with the linearized conservation equations governing the system acoustics. This formulation allows model based controller design. In order to test the performance of the analytical model, a numerical solution of the partial differential equations governing the system has been carried out using the principle of harmonic separation and focusing on the dominant unstable mode. This leads to a system of ODEs governing the thermofluid variables. Analytical predictions of the frequency and growth ate of the unstable mode are shown to be in good agreement with the numerical simulations as well s with those obtained using experimental identification techniques when applied to a laboratory combustor. The authors use these results to confirm the validity of the assumptions used in formulating the analytical model. A controller based on the minimization of a cost function using the LQR technique has

  4. A physiologically based biodynamic (PBBD) model for estragole DNA binding in rat liver based on in vitro kinetic data and estragole DNA adduct formation in primary hepatocytes

    SciTech Connect (OSTI)

    Paini, Alicia; Punt, Ans; Viton, Florian; Scholz, Gabriele; Delatour, Thierry; Marin-Kuan, Maricel; Schilter, Benoit; Bladeren, Peter J. van; Rietjens, Ivonne M.C.M.

    2010-05-15

    Estragole has been shown to be hepatocarcinogenic in rodent species at high-dose levels. Translation of these results into the likelihood of formation of DNA adducts, mutation, and ultimately cancer upon more realistic low-dose exposures remains a challenge. Recently we have developed physiologically based biokinetic (PBBK) models for rat and human predicting bioactivation of estragole. These PBBK models, however, predict only kinetic characteristics. The present study describes the extension of the PBBK model to a so-called physiologically based biodynamic (PBBD) model predicting in vivo DNA adduct formation of estragole in rat liver. This PBBD model was developed using in vitro data on DNA adduct formation in rat primary hepatocytes exposed to 1'-hydroxyestragole. The model was extended by linking the area under the curve for 1'-hydroxyestragole formation predicted by the PBBK model to the area under the curve for 1'-hydroxyestragole in the in vitro experiments. The outcome of the PBBD model revealed a linear increase in DNA adduct formation with increasing estragole doses up to 100 mg/kg bw. Although DNA adduct formation of genotoxic carcinogens is generally seen as a biomarker of exposure rather than a biomarker of response, the PBBD model now developed is one step closer to the ultimate toxic effect of estragole than the PBBK model described previously. Comparison of the PBBD model outcome to available data showed that the model adequately predicts the dose-dependent level of DNA adduct formation. The PBBD model predicts DNA adduct formation at low levels of exposure up to a dose level showing to cause cancer in rodent bioassays, providing a proof of principle for modeling a toxicodynamic in vivo endpoint on the basis of solely in vitro experimental data.

  5. Radionuclide migration in groundwater at a low-level waste disposal site: a comparison of predictive performance modeling versus field observations

    SciTech Connect (OSTI)

    Robertson, D.E. Myers, D.A.; Bergeron, M.P.; Champ, D.R.; Killey, R.W.D.; Moltyaner, G.L.; Young, J.L.

    1985-08-01

    This paper describes a project which is structured to test the concept of modeling a shallow land low-level waste burial site. The project involves a comparison of the actual observed radionuclide migration in groundwaters at a 30-year-old well-monitored field site with the results of predictive transport modeling. The comparison is being conducted as a cooperative program with the Atomic Energy of Canada Ltd. (AECL) at the low-level waste management area at the Chalk River Nuclear Laboratories, Ontario, Canada. A joint PNL-AECL field inviestigation was conducted in 1983 and 1984 to complement the existing extensive data base on actual radionuclide migration. Predictive transport modeling is currently being conducted for this site; first, as if it were a new location being considered for a low-level waste shallow-land burial site and only minimal information about the site were available, and second, utilizing the extensive data base available for the site. The modeling results will then be compared with the empirical observations to provide insight into the level of effort needed to reasonably predict the spacial and temporal movement of radionuclides in the groundwater enviroment. 8 refs., 5 figs.,

  6. Predictive Treatment Management: Incorporating a Predictive Tumor Response Model Into Robust Prospective Treatment Planning for Non-Small Cell Lung Cancer

    SciTech Connect (OSTI)

    Zhang, Pengpeng; Yorke, Ellen; Hu, Yu-Chi; Mageras, Gig; Rimner, Andreas; Deasy, Joseph O.

    2014-02-01

    Purpose: We hypothesized that a treatment planning technique that incorporates predicted lung tumor regression into optimization, predictive treatment planning (PTP), could allow dose escalation to the residual tumor while maintaining coverage of the initial target without increasing dose to surrounding organs at risk (OARs). Methods and Materials: We created a model to estimate the geometric presence of residual tumors after radiation therapy using planning computed tomography (CT) and weekly cone beam CT scans of 5 lung cancer patients. For planning purposes, we modeled the dynamic process of tumor shrinkage by morphing the original planning target volume (PTV{sub orig}) in 3 equispaced steps to the predicted residue (PTV{sub pred}). Patients were treated with a uniform prescription dose to PTV{sub orig}. By contrast, PTP optimization started with the same prescription dose to PTV{sub orig} but linearly increased the dose at each step, until reaching the highest dose achievable to PTV{sub pred} consistent with OAR limits. This method is compared with midcourse adaptive replanning. Results: Initial parenchymal gross tumor volume (GTV) ranged from 3.6 to 186.5 cm{sup 3}. On average, the primary GTV and PTV decreased by 39% and 27%, respectively, at the end of treatment. The PTP approach gave PTV{sub orig} at least the prescription dose, and it increased the mean dose of the true residual tumor by an average of 6.0 Gy above the adaptive approach. Conclusions: PTP, incorporating a tumor regression model from the start, represents a new approach to increase tumor dose without increasing toxicities, and reduce clinical workload compared with the adaptive approach, although model verification using per-patient midcourse imaging would be prudent.

  7. Improving Thermal Model Prediction Through Statistical Analysis of Irradiation and Post-Irradiation Data from AGR Experiments

    SciTech Connect (OSTI)

    Dr. Binh T. Pham; Grant L. Hawkes; Jeffrey J. Einerson

    2012-10-01

    As part of the Research and Development program for Next Generation High Temperature Reactors (HTR), a series of irradiation tests, designated as Advanced Gas-cooled Reactor (AGR), have been defined to support development and qualification of fuel design, fabrication process, and fuel performance under normal operation and accident conditions. The AGR tests employ fuel compacts placed in a graphite cylinder shrouded by a steel capsule and instrumented with thermocouples (TC) embedded in graphite blocks enabling temperature control. The data representing the crucial test fuel conditions (e.g., temperature, neutron fast fluence, and burnup) while impossible to obtain from direct measurements are calculated by physics and thermal models. The irradiation and post-irradiation examination (PIE) experimental data are used in model calibration effort to reduce the inherent uncertainty of simulation results. This paper is focused on fuel temperature predicted by the ABAQUS code’s finite element-based thermal models. The work follows up on a previous study, in which several statistical analysis methods were adapted, implemented in the NGNP Data Management and Analysis System (NDMAS), and applied for improving qualification of AGR-1 thermocouple data. The present work exercises the idea that the abnormal trends of measured data observed from statistical analysis may be caused by either measuring instrument deterioration or physical mechanisms in capsules that may have shifted the system thermal response. As an example, the uneven reduction of the control gas gap in Capsule 5 revealed by the capsule metrology measurements in PIE helps justify the reduction in TC readings instead of TC drift. This in turn prompts modification of thermal model to better fit with experimental data, thus help increase confidence, and in other word reduce model uncertainties in thermal simulation results of the AGR-1 test.

  8. Development of a model for predicting intergranular stress corrosion cracking of Alloy 600 tubes in PWR primary water. Final report

    SciTech Connect (OSTI)

    Garud, Y.S.

    1985-01-01

    A preliminary mathematical model developed in this study may make it possible to predict stress corrosion cracking on the primary side of PWR steam generator tubing. The study outlines a comprehensive testing program that will provide the operational and experimental data to further develop and verify the model.

  9. Coupling a Mesoscale Numerical Weather Prediction Model with Large-Eddy Simulation for Realistic Wind Plant Aerodynamics Simulations (Poster)

    SciTech Connect (OSTI)

    Draxl, C.; Churchfield, M.; Mirocha, J.; Lee, S.; Lundquist, J.; Michalakes, J.; Moriarty, P.; Purkayastha, A.; Sprague, M.; Vanderwende, B.

    2014-06-01

    Wind plant aerodynamics are influenced by a combination of microscale and mesoscale phenomena. Incorporating mesoscale atmospheric forcing (e.g., diurnal cycles and frontal passages) into wind plant simulations can lead to a more accurate representation of microscale flows, aerodynamics, and wind turbine/plant performance. Our goal is to couple a numerical weather prediction model that can represent mesoscale flow [specifically the Weather Research and Forecasting model] with a microscale LES model (OpenFOAM) that can predict microscale turbulence and wake losses.

  10. Vehicle Technologies Office Merit Review 2014: Trip Prediction and Route-Based Vehicle Energy Management

    Broader source: Energy.gov [DOE]

    Presentation given by Argonne National Laboratory at 2014 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Office Annual Merit Review and Peer Evaluation Meeting about trip prediction...

  11. A predictive analytic model for the solar modulation of cosmic rays

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Cholis, Ilias; Hooper, Dan; Linden, Tim

    2016-02-23

    An important factor limiting our ability to understand the production and propagation of cosmic rays pertains to the effects of heliospheric forces, commonly known as solar modulation. The solar wind is capable of generating time- and charge-dependent effects on the spectrum and intensity of low-energy (≲10 GeV) cosmic rays reaching Earth. Previous analytic treatments of solar modulation have utilized the force-field approximation, in which a simple potential is adopted whose amplitude is selected to best fit the cosmic-ray data taken over a given period of time. Making use of recently available cosmic-ray data from the Voyager 1 spacecraft, along withmore » measurements of the heliospheric magnetic field and solar wind, we construct a time-, charge- and rigidity-dependent model of solar modulation that can be directly compared to data from a variety of cosmic-ray experiments. Here, we provide a simple analytic formula that can be easily utilized in a variety of applications, allowing us to better predict the effects of solar modulation and reduce the number of free parameters involved in cosmic-ray propagation models.« less

  12. Impact of Pilot Light Modeling on the Predicted Annual Performance of Residential Gas Water Heaters: Preprint

    SciTech Connect (OSTI)

    Maguire, J.; Burch, J.

    2013-08-01

    Modeling residential water heaters with dynamic simulation models can provide accurate estimates of their annual energy consumption, if the units? characteristics and use conditions are known. Most gas storage water heaters (GSWHs) include a standing pilot light. It is generally assumed that the pilot light energy will help make up standby losses and have no impact on the predicted annual energy consumption. However, that is not always the case. The gas input rate and conversion efficiency of a pilot light for a GSWH were determined from laboratory data. The data were used in simulations of a typical GSWH with and without a pilot light, for two cases: 1) the GSWH is used alone; and 2) the GSWH is the second tank in a solar water heating (SWH) system. The sensitivity of wasted pilot light energy to annual hot water use, climate, and installation location was examined. The GSWH used alone in unconditioned space in a hot climate had a slight increase in energy consumption. The GSWH with a pilot light used as a backup to an SWH used up to 80% more auxiliary energy than one without in hot, sunny locations, from increased tank losses.

  13. VALIDATION AND RESULTS OF A PSEUDO-MULTI-ZONE COMBUSTION TRAJECTORY PREDICTION MODEL FOR CAPTURING SOOT AND NOX FORMATION ON A MEDIUM DUTY DIESEL ENGINE

    SciTech Connect (OSTI)

    Bittle, Joshua A.; Gao, Zhiming; Jacobs, Timothy J.

    2013-01-01

    A pseudo-multi-zone phenomenological model has been created with the ultimate goal of supporting efforts to enable broader commercialization of low temperature combustion modes in diesel engines. The benefits of low temperature combustion are the simultaneous reduction in soot and nitric oxide emissions and increased engine efficiency if combustion is properly controlled. Determining what qualifies as low temperature combustion for any given engine can be difficult without expensive emissions analysis equipment. This determination can be made off-line using computer models or through factory calibration procedures. This process could potentially be simplified if a real-time prediction model could be implemented to run for any engine platform this is the motivation for this study. The major benefit of this model is the ability for it to predict the combustion trajectory, i.e. local temperature and equivalence ratio in the burning zones. The model successfully captures all the expected trends based on the experimental data and even highlights an opportunity for simply using the average reaction temperature and equivalence ratio as an indicator of emissions levels alone - without solving formation sub-models. This general type of modeling effort is not new, but a major effort was made to minimize the calculation duration to enable implementation as an input to real-time next-cycle engine controller Instead of simply using the predicted engine out soot and NOx levels, control decisions could be made based on the trajectory. This has the potential to save large amounts of calibration time because with minor tuning (the model has only one automatically determined constant) it is hoped that the control algorithm would be generally applicable.

  14. Predictions of flow through an isothermal serpentine passage with linear eddy-viscosity Reynolds Averaged Navier Stokes models.

    SciTech Connect (OSTI)

    Laskowski, Gregory Michael

    2005-12-01

    Flows with strong curvature present a challenge for turbulence models, specifically eddy viscosity type models which assume isotropy and a linear and instantaneous equilibrium relation between stress and strain. Results obtained from three different codes and two different linear eddy viscosity turbulence models are compared to a DNS simulation in order to gain some perspective on the turbulence modeling capability of SIERRA/Fuego. The Fuego v2f results are superior to the more common two-layer k-e model results obtained with both a commercial and research code in terms of the concave near wall behavior predictions. However, near the convex wall, including the separated region, little improvement is gained using the v2f model and in general the turbulent kinetic energy prediction is fair at best.

  15. REVIEW OF MECHANISTIC UNDERSTANDING AND MODELING AND UNCERTAINTY ANALYSIS METHODS FOR PREDICTING CEMENTITIOUS BARRIER PERFORMANCE

    SciTech Connect (OSTI)

    Langton, C.; Kosson, D.

    2009-11-30

    Cementitious barriers for nuclear applications are one of the primary controls for preventing or limiting radionuclide release into the environment. At the present time, performance and risk assessments do not fully incorporate the effectiveness of engineered barriers because the processes that influence performance are coupled and complicated. Better understanding the behavior of cementitious barriers is necessary to evaluate and improve the design of materials and structures used for radioactive waste containment, life extension of current nuclear facilities, and design of future nuclear facilities, including those needed for nuclear fuel storage and processing, nuclear power production and waste management. The focus of the Cementitious Barriers Partnership (CBP) literature review is to document the current level of knowledge with respect to: (1) mechanisms and processes that directly influence the performance of cementitious materials (2) methodologies for modeling the performance of these mechanisms and processes and (3) approaches to addressing and quantifying uncertainties associated with performance predictions. This will serve as an important reference document for the professional community responsible for the design and performance assessment of cementitious materials in nuclear applications. This review also provides a multi-disciplinary foundation for identification, research, development and demonstration of improvements in conceptual understanding, measurements and performance modeling that would be lead to significant reductions in the uncertainties and improved confidence in the estimating the long-term performance of cementitious materials in nuclear applications. This report identifies: (1) technology gaps that may be filled by the CBP project and also (2) information and computational methods that are in currently being applied in related fields but have not yet been incorporated into performance assessments of cementitious barriers. The various

  16. Reduced order models for prediction of groundwater quality impacts from CO₂ and brine leakage

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Zheng, Liange; Carroll, Susan; Bianchi, Marco; Mansoor, Kayyum; Sun, Yunwei; Birkholzer, Jens

    2014-12-31

    A careful assessment of the risk associated with geologic CO₂ storage is critical to the deployment of large-scale storage projects. A potential risk is the deterioration of groundwater quality caused by the leakage of CO₂ and brine leakage from deep subsurface reservoirs. In probabilistic risk assessment studies, numerical modeling is the primary tool employed to assess risk. However, the application of traditional numerical models to fully evaluate the impact of CO₂ leakage on groundwater can be computationally complex, demanding large processing times and resources, and involving large uncertainties. As an alternative, reduced order models (ROMs) can be used as highlymore » efficient surrogates for the complex process-based numerical models. In this study, we represent the complex hydrogeological and geochemical conditions in a heterogeneous aquifer and subsequent risk by developing and using two separate ROMs. The first ROM is derived from a model that accounts for the heterogeneous flow and transport conditions in the presence of complex leakage functions for CO₂ and brine. The second ROM is obtained from models that feature similar, but simplified flow and transport conditions, and allow for a more complex representation of all relevant geochemical reactions. To quantify possible impacts to groundwater aquifers, the basic risk metric is taken as the aquifer volume in which the water quality of the aquifer may be affected by an underlying CO₂ storage project. The integration of the two ROMs provides an estimate of the impacted aquifer volume taking into account uncertainties in flow, transport and chemical conditions. These two ROMs can be linked in a comprehensive system level model for quantitative risk assessment of the deep storage reservoir, wellbore leakage, and shallow aquifer impacts to assess the collective risk of CO₂ storage projects.« less

  17. Reduced order models for prediction of groundwater quality impacts from CO? and brine leakage

    SciTech Connect (OSTI)

    Zheng, Liange; Carroll, Susan; Bianchi, Marco; Mansoor, Kayyum; Sun, Yunwei; Birkholzer, Jens

    2014-12-31

    A careful assessment of the risk associated with geologic CO? storage is critical to the deployment of large-scale storage projects. A potential risk is the deterioration of groundwater quality caused by the leakage of CO? and brine leakage from deep subsurface reservoirs. In probabilistic risk assessment studies, numerical modeling is the primary tool employed to assess risk. However, the application of traditional numerical models to fully evaluate the impact of CO? leakage on groundwater can be computationally complex, demanding large processing times and resources, and involving large uncertainties. As an alternative, reduced order models (ROMs) can be used as highly efficient surrogates for the complex process-based numerical models. In this study, we represent the complex hydrogeological and geochemical conditions in a heterogeneous aquifer and subsequent risk by developing and using two separate ROMs. The first ROM is derived from a model that accounts for the heterogeneous flow and transport conditions in the presence of complex leakage functions for CO? and brine. The second ROM is obtained from models that feature similar, but simplified flow and transport conditions, and allow for a more complex representation of all relevant geochemical reactions. To quantify possible impacts to groundwater aquifers, the basic risk metric is taken as the aquifer volume in which the water quality of the aquifer may be affected by an underlying CO? storage project. The integration of the two ROMs provides an estimate of the impacted aquifer volume taking into account uncertainties in flow, transport and chemical conditions. These two ROMs can be linked in a comprehensive system level model for quantitative risk assessment of the deep storage reservoir, wellbore leakage, and shallow aquifer impacts to assess the collective risk of CO? storage projects.

  18. Numerical Prediction of Experimentally Observed Behavior of a Scale Model of an Offshore Wind Turbine Supported by a Tension-Leg Platform: Preprint

    SciTech Connect (OSTI)

    Prowell, I.; Robertson, A.; Jonkman, J.; Stewart, G. M.; Goupee, A. J.

    2013-01-01

    Realizing the critical importance the role physical experimental tests play in understanding the dynamics of floating offshore wind turbines, the DeepCwind consortium conducted a one-fiftieth-scale model test program where several floating wind platforms were subjected to a variety of wind and wave loading condition at the Maritime Research Institute Netherlands wave basin. This paper describes the observed behavior of a tension-leg platform, one of three platforms tested, and the systematic effort to predict the measured response with the FAST simulation tool using a model primarily based on consensus geometric and mass properties of the test specimen.

  19. Structural Bioinformatics-Based Prediction of Exceptional Selectivity of p38 MAP Kinase Inhibitor PH-797804

    SciTech Connect (OSTI)

    Xing, Li; Shieh, Huey S.; Selness, Shaun R.; Devraj, Rajesh V.; Walker, John K.; Devadas, Balekudru; Hope, Heidi R.; Compton, Robert P.; Schindler, John F.; Hirsch, Jeffrey L.; Benson, Alan G.; Kurumbail, Ravi G.; Stegeman, Roderick A.; Williams, Jennifer M.; Broadus, Richard M.; Walden, Zara; Monahan, Joseph B.; Pfizer

    2009-07-24

    PH-797804 is a diarylpyridinone inhibitor of p38{alpha} mitogen-activated protein (MAP) kinase derived from a racemic mixture as the more potent atropisomer (aS), first proposed by molecular modeling and subsequently confirmed by experiments. On the basis of structural comparison with a different biaryl pyrazole template and supported by dozens of high-resolution crystal structures of p38{alpha} inhibitor complexes, PH-797804 is predicted to possess a high level of specificity across the broad human kinase genome. We used a structural bioinformatics approach to identify two selectivity elements encoded by the TXXXG sequence motif on the p38{alpha} kinase hinge: (i) Thr106 that serves as the gatekeeper to the buried hydrophobic pocket occupied by 2,4-difluorophenyl of PH-797804 and (ii) the bidentate hydrogen bonds formed by the pyridinone moiety with the kinase hinge requiring an induced 180{sup o} rotation of the Met109-Gly110 peptide bond. The peptide flip occurs in p38{alpha} kinase due to the critical glycine residue marked by its conformational flexibility. Kinome-wide sequence mining revealed rare presentation of the selectivity motif. Corroboratively, PH-797804 exhibited exceptionally high specificity against MAP kinases and the related kinases. No cross-reactivity was observed in large panels of kinase screens (selectivity ratio of >500-fold). In cellular assays, PH-797804 demonstrated superior potency and selectivity consistent with the biochemical measurements. PH-797804 has met safety criteria in human phase I studies and is under clinical development for several inflammatory conditions. Understanding the rationale for selectivity at the molecular level helps elucidate the biological function and design of specific p38{alpha} kinase inhibitors.

  20. A coarse-grained model with implicit salt for RNAs: Predicting 3D structure, stability and salt effect

    SciTech Connect (OSTI)

    Shi, Ya-Zhou; Wang, Feng-Hua; Wu, Yuan-Yan; Tan, Zhi-Jie

    2014-09-14

    To bridge the gap between the sequences and 3-dimensional (3D) structures of RNAs, some computational models have been proposed for predicting RNA 3D structures. However, the existed models seldom consider the conditions departing from the room/body temperature and high salt (1M NaCl), and thus generally hardly predict the thermodynamics and salt effect. In this study, we propose a coarse-grained model with implicit salt for RNAs to predict 3D structures, stability, and salt effect. Combined with Monte Carlo simulated annealing algorithm and a coarse-grained force field, the model folds 46 tested RNAs (?45 nt) including pseudoknots into their native-like structures from their sequences, with an overall mean RMSD of 3.5 and an overall minimum RMSD of 1.9 from the experimental structures. For 30 RNA hairpins, the present model also gives the reliable predictions for the stability and salt effect with the mean deviation ? 1.0 C of melting temperatures, as compared with the extensive experimental data. In addition, the model could provide the ensemble of possible 3D structures for a short RNA at a given temperature/salt condition.

  1. A general unified non-equilibrium model for predicting saturated and subcooled critical two-phase flow rates through short and long tubes

    SciTech Connect (OSTI)

    Fraser, D.W.H.; Abdelmessih, A.H.

    1995-09-01

    A general unified model is developed to predict one-component critical two-phase pipe flow. Modelling of the two-phase flow is accomplished by describing the evolution of the flow between the location of flashing inception and the exit (critical) plane. The model approximates the nonequilibrium phase change process via thermodynamic equilibrium paths. Included are the relative effects of varying the location of flashing inception, pipe geometry, fluid properties and length to diameter ratio. The model predicts that a range of critical mass fluxes exist and is bound by a maximum and minimum value for a given thermodynamic state. This range is more pronounced at lower subcooled stagnation states and can be attributed to the variation in the location of flashing inception. The model is based on the results of an experimental study of the critical two-phase flow of saturated and subcooled water through long tubes. In that study, the location of flashing inception was accurately controlled and adjusted through the use of a new device. The data obtained revealed that for fixed stagnation conditions, the maximum critical mass flux occurred with flashing inception located near the pipe exit; while minimum critical mass fluxes occurred with the flashing front located further upstream. Available data since 1970 for both short and long tubes over a wide range of conditions are compared with the model predictions. This includes test section L/D ratios from 25 to 300 and covers a temperature and pressure range of 110 to 280{degrees}C and 0.16 to 6.9 MPa. respectively. The predicted maximum and minimum critical mass fluxes show an excellent agreement with the range observed in the experimental data.

  2. Predicting oropharyngeal tumor volume throughout the course of radiation therapy from pretreatment computed tomography data using general linear models

    SciTech Connect (OSTI)

    Yock, Adam D. Kudchadker, Rajat J.; Rao, Arvind; Dong, Lei; Beadle, Beth M.; Garden, Adam S.; Court, Laurence E.

    2014-05-15

    Purpose: The purpose of this work was to develop and evaluate the accuracy of several predictive models of variation in tumor volume throughout the course of radiation therapy. Methods: Nineteen patients with oropharyngeal cancers were imaged daily with CT-on-rails for image-guided alignment per an institutional protocol. The daily volumes of 35 tumors in these 19 patients were determined and used to generate (1) a linear model in which tumor volume changed at a constant rate, (2) a general linear model that utilized the power fit relationship between the daily and initial tumor volumes, and (3) a functional general linear model that identified and exploited the primary modes of variation between time series describing the changing tumor volumes. Primary and nodal tumor volumes were examined separately. The accuracy of these models in predicting daily tumor volumes were compared with those of static and linear reference models using leave-one-out cross-validation. Results: In predicting the daily volume of primary tumors, the general linear model and the functional general linear model were more accurate than the static reference model by 9.9% (range: −11.6%–23.8%) and 14.6% (range: −7.3%–27.5%), respectively, and were more accurate than the linear reference model by 14.2% (range: −6.8%–40.3%) and 13.1% (range: −1.5%–52.5%), respectively. In predicting the daily volume of nodal tumors, only the 14.4% (range: −11.1%–20.5%) improvement in accuracy of the functional general linear model compared to the static reference model was statistically significant. Conclusions: A general linear model and a functional general linear model trained on data from a small population of patients can predict the primary tumor volume throughout the course of radiation therapy with greater accuracy than standard reference models. These more accurate models may increase the prognostic value of information about the tumor garnered from pretreatment computed tomography

  3. Identifying at-risk employees: A behavioral model for predicting potential insider threats

    SciTech Connect (OSTI)

    Greitzer, Frank L.; Kangas, Lars J.; Noonan, Christine F.; Dalton, Angela C.

    2010-09-01

    A psychosocial model was developed to assess an employee’s behavior associated with an increased risk of insider abuse. The model is based on case studies and research literature on factors/correlates associated with precursor behavioral manifestations of individuals committing insider crimes. In many of these crimes, managers and other coworkers observed that the offenders had exhibited signs of stress, disgruntlement, or other issues, but no alarms were raised. Barriers to using such psychosocial indicators include the inability to recognize the signs and the failure to record the behaviors so that they could be assessed by a person experienced in psychosocial evaluations. We have developed a model using a Bayesian belief network with the help of human resources staff, experienced in evaluating behaviors in staff. We conducted an experiment to assess its agreement with human resources and management professionals, with positive results. If implemented in an operational setting, the model would be part of a set of management tools for employee assessment that can raise an alarm about employees who pose higher insider threat risks. In separate work, we combine this psychosocial model’s assessment with computer workstation behavior to raise the efficacy of recognizing an insider crime in the making.

  4. Using calibrated engineering models to predict energy savings in large-scale geothermal heat pump projects

    SciTech Connect (OSTI)

    Shonder, J.A.; Hughes, P.J.; Thornton, J.W.

    1998-10-01

    Energy savings performance contracting (ESPC) is now receiving greater attention as a means of implementing large-scale energy conservation projects in housing. Opportunities for such projects exist for military housing, federally subsidized low-income housing, and planned communities (condominiums, townhomes, senior centers), to name a few. Accurate prior (to construction) estimates of the energy savings in these projects reduce risk, decrease financing costs, and help avoid post-construction disputes over performance contract baseline adjustments. This paper demonstrates an improved method of estimating energy savings before construction takes place. Using an engineering model calibrated to pre-construction energy-use data collected in the field, this method is able to predict actual energy savings to a high degree of accuracy. This is verified with post-construction energy-use data from a geothermal heat pump ESPC at Fort Polk, Louisiana. This method also allows determination of the relative impact of the various energy conservation measures installed in a comprehensive energy conservation project. As an example, the breakout of savings at Fort Polk for the geothermal heat pumps, desuperheaters, lighting retrofits, and low-flow hot water outlets is provided.

  5. Using Calibrated Engineering Models To Predict Energy Savings In Large-Scale Geothermal Heat Pump Projects

    SciTech Connect (OSTI)

    Shonder, John A; Hughes, Patrick; Thornton, Jeff W.

    1998-01-01

    Energy savings performance contracting (ESPC) is now receiving greater attention as a means of implementing large-scale energy conservation projects in housing. Opportunities for such projects exist for military housing, federally subsidized low-income housing, and planned communities (condominiums, townhomes, senior centers), to name a few. Accurate prior (to construction) estimates of the energy savings in these projects reduce risk, decrease financing costs, and help avoid post-construction disputes over performance contract baseline adjustments. This paper demonstrates an improved method of estimating energy savings before construction takes place. Using an engineering model calibrated to pre-construction energy-use data collected in the field, this method is able to predict actual energy savings to a high degree of accuracy. This is verified with post-construction energy-use data from a geothermal heat pump ESPC at Fort Polk, Louisiana. This method also allows determination of the relative impact of the various energy conservation measures installed in a comprehensive energy conservation project. As an example, the breakout of savings at Fort Polk for the geothermal heat pumps, desuperheaters, lighting retrofits, and low-flow hot water outlets is provided.

  6. Model for the Prediction of the Hydriding Thermodynamics of Pd-Rh-Co Ternary Alloys

    SciTech Connect (OSTI)

    Teter, D.F.; Thoma, D.J.

    1999-03-01

    A dilute solution model (with respect to the substitutional alloying elements) has been developed, which accurately predicts the hydride formation and decomposition thermodynamics and the storage capacities of dilute ternary Pd-Rh-Co alloys. The effect of varying the rhodium and cobalt compositions on the thermodynamics of hydride formation and decomposition and hydrogen capacity of several palladium-rhodium-cobalt ternary alloys has been investigated using pressure-composition (PC) isotherms. Alloying in the dilute regime (<10 at.%) causes the enthalpy for hydride formation to linearly decrease with increasing alloying content. Cobalt has a stronger effect on the reduction in enthalpy than rhodium for equivalent alloying amounts. Also, cobalt reduces the hydrogen storage capacity with increasing alloying content. The plateau thermodynamics are strongly linked to the lattice parameters of the alloys. A near-linear dependence of the enthalpy of hydride formation on the lattice parameter was observed for both the binary Pd-Rh and Pd-Co alloys, as well as for the ternary Pd-Rh-Co alloys. The Pd-5Rh-3Co (at. %) alloy was found to have similar plateau thermodynamics as a Pd-10Rh alloy, however, this ternary alloy had a diminished hydrogen storage capacity relative to Pd-10Rh.

  7. Modeling Heavy/Medium-Duty Fuel Consumption Based on Drive Cycle Properties

    SciTech Connect (OSTI)

    Wang, Lijuan; Duran, Adam; Gonder, Jeffrey; Kelly, Kenneth

    2015-10-13

    This paper presents multiple methods for predicting heavy/medium-duty vehicle fuel consumption based on driving cycle information. A polynomial model, a black box artificial neural net model, a polynomial neural network model, and a multivariate adaptive regression splines (MARS) model were developed and verified using data collected from chassis testing performed on a parcel delivery diesel truck operating over the Heavy Heavy-Duty Diesel Truck (HHDDT), City Suburban Heavy Vehicle Cycle (CSHVC), New York Composite Cycle (NYCC), and hydraulic hybrid vehicle (HHV) drive cycles. Each model was trained using one of four drive cycles as a training cycle and the other three as testing cycles. By comparing the training and testing results, a representative training cycle was chosen and used to further tune each method. HHDDT as the training cycle gave the best predictive results, because HHDDT contains a variety of drive characteristics, such as high speed, acceleration, idling, and deceleration. Among the four model approaches, MARS gave the best predictive performance, with an average absolute percent error of -1.84% over the four chassis dynamometer drive cycles. To further evaluate the accuracy of the predictive models, the approaches were first applied to real-world data. MARS outperformed the other three approaches, providing an average absolute percent error of -2.2% of four real-world road segments. The MARS model performance was then compared to HHDDT, CSHVC, NYCC, and HHV drive cycles with the performance from Future Automotive System Technology Simulator (FASTSim). The results indicated that the MARS method achieved a comparative predictive performance with FASTSim.

  8. Empirical and physics based mathematical models of uranium hydride decomposition kinetics with quantified uncertainties.

    SciTech Connect (OSTI)

    Salloum, Maher N.; Gharagozloo, Patricia E.

    2013-10-01

    Metal particle beds have recently become a major technique for hydrogen storage. In order to extract hydrogen from such beds, it is crucial to understand the decomposition kinetics of the metal hydride. We are interested in obtaining a a better understanding of the uranium hydride (UH3) decomposition kinetics. We first developed an empirical model by fitting data compiled from different experimental studies in the literature and quantified the uncertainty resulting from the scattered data. We found that the decomposition time range predicted by the obtained kinetics was in a good agreement with published experimental results. Secondly, we developed a physics based mathematical model to simulate the rate of hydrogen diffusion in a hydride particle during the decomposition. We used this model to simulate the decomposition of the particles for temperatures ranging from 300K to 1000K while propagating parametric uncertainty and evaluated the kinetics from the results. We compared the kinetics parameters derived from the empirical and physics based models and found that the uncertainty in the kinetics predicted by the physics based model covers the scattered experimental data. Finally, we used the physics-based kinetics parameters to simulate the effects of boundary resistances and powder morphological changes during decomposition in a continuum level model. We found that the species change within the bed occurring during the decomposition accelerates the hydrogen flow by increasing the bed permeability, while the pressure buildup and the thermal barrier forming at the wall significantly impede the hydrogen extraction.

  9. Predictive Geosciences

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Predictive Geosciences Researchers in the Predictive Geosciences competency develop and calibrate efficient tools and quantitative relationships for the science-based prediction of the behavior of engineered-natural systems. Research includes fluid-rock geochemistry, fluid-rock geophysics, and geochemical engineering, specifically: Fluid-Rock Geochemistry Pursuing geomaterials science as it relates to the chemical interaction between subsurface fluids and solid materials (both natural and

  10. Commercial Implementation of Model-Based Manufacturing of Nanostructured Metals

    SciTech Connect (OSTI)

    Lowe, Terry C.

    2012-07-24

    Computational modeling is an essential tool for commercial production of nanostructured metals. Strength is limited by imperfections at the high strength levels that are achievable in nanostructured metals. Processing to achieve homogeneity at the micro- and nano-scales is critical. Manufacturing of nanostructured metals is intrinsically a multi-scale problem. Manufacturing of nanostructured metal products requires computer control, monitoring and modeling. Large scale manufacturing of bulk nanostructured metals by Severe Plastic Deformation is a multi-scale problem. Computational modeling at all scales is essential. Multiple scales of modeling must be integrated to predict and control nanostructural, microstructural, macrostructural product characteristics and production processes.

  11. Experiment-Based Model for the Chemical Interactions between Geothermal

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Rocks, Supercritical Carbon Dioxide and Water | Department of Energy Experiment-Based Model for the Chemical Interactions between Geothermal Rocks, Supercritical Carbon Dioxide and Water Experiment-Based Model for the Chemical Interactions between Geothermal Rocks, Supercritical Carbon Dioxide and Water Experiment-Based Model for the Chemical Interactions between Geothermal Rocks, Supercritical Carbon Dioxide and Water presentation at the April 2013 peer review meeting held in Denver,

  12. GIS-Based Infrastructure Modeling | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    GIS-Based Infrastructure Modeling GIS-Based Infrastructure Modeling Presentation by NREL's Keith Parks at the 2010 - 2025 Scenario Analysis for Hydrogen Fuel Cell Vehicles and Infrastructure Meeting on August 9 - 10, 2006 in Washington, D.C. parks_gis_infrastructure_modeling.pdf (993.56 KB) More Documents & Publications DOE Hydrogen Transition Analysis Workshop Geographically-Based Infrastructure Analysis for California Hydrogen and FCV Implementation Scenarios, 2010 - 2025

  13. Lattice and off-lattice side chain models of protein folding: Linear time structure prediction better than 86% of optimal

    SciTech Connect (OSTI)

    Hart, W.E.; Istrail, S. [Sandia National Labs., Albuquerque, NM (United States). Algorithms and Discrete Mathematics Dept.

    1996-08-09

    This paper considers the protein structure prediction problem for lattice and off-lattice protein folding models that explicitly represent side chains. Lattice models of proteins have proven extremely useful tools for reasoning about protein folding in unrestricted continuous space through analogy. This paper provides the first illustration of how rigorous algorithmic analyses of lattice models can lead to rigorous algorithmic analyses of off-lattice models. The authors consider two side chain models: a lattice model that generalizes the HP model (Dill 85) to explicitly represent side chains on the cubic lattice, and a new off-lattice model, the HP Tangent Spheres Side Chain model (HP-TSSC), that generalizes this model further by representing the backbone and side chains of proteins with tangent spheres. They describe algorithms for both of these models with mathematically guaranteed error bounds. In particular, the authors describe a linear time performance guaranteed approximation algorithm for the HP side chain model that constructs conformations whose energy is better than 865 of optimal in a face centered cubic lattice, and they demonstrate how this provides a 70% performance guarantee for the HP-TSSC model. This is the first algorithm in the literature for off-lattice protein structure prediction that has a rigorous performance guarantee. The analysis of the HP-TSSC model builds off of the work of Dancik and Hannenhalli who have developed a 16/30 approximation algorithm for the HP model on the hexagonal close packed lattice. Further, the analysis provides a mathematical methodology for transferring performance guarantees on lattices to off-lattice models. These results partially answer the open question of Karplus et al. concerning the complexity of protein folding models that include side chains.

  14. A Stochastic Reactor Based Virtual Engine Model Employing Detailed

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Chemistry for Kinetic Studies of In-Cylinder Combustion and Exhaust Aftertreatment | Department of Energy A Stochastic Reactor Based Virtual Engine Model Employing Detailed Chemistry for Kinetic Studies of In-Cylinder Combustion and Exhaust Aftertreatment A Stochastic Reactor Based Virtual Engine Model Employing Detailed Chemistry for Kinetic Studies of In-Cylinder Combustion and Exhaust Aftertreatment The model consists of an in-cylinder combustion engine model, an interconnecting exhaust

  15. Model-Based Sampling and Inference

    U.S. Energy Information Administration (EIA) Indexed Site

    ... Sarndal, C.-E., Swensson, B. and Wretman, J. (1992), Model Assisted Survey Sampling, Springer- Verlag. Steel, P.M. and Shao, J. (1997), "Estimation of Variance Due to Imputation in ...

  16. A Stochastic Reactor Based Virtual Engine Model Employing Detailed...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Detailed Chemistry for Kinetic Studies of In-Cylinder Combustion and Exhaust Aftertreatment A Stochastic Reactor Based Virtual Engine Model Employing Detailed Chemistry for ...

  17. A Model-Based Approach to Scintillator/Photomultiplier System...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: A Model-Based Approach to ScintillatorPhotomultiplier System ... Sponsoring Org: USDOE Country of Publication: United States Language: English Subject: 46 ...

  18. A Model-Based Approach to Scintillator/Photomultiplier System...

    Office of Scientific and Technical Information (OSTI)

    System Characterization Citation Details In-Document Search Title: A Model-Based Approach to ScintillatorPhotomultiplier System Characterization You are accessing ...

  19. Physics-Based Constraints in the Forward Modeling Analysis of...

    Office of Scientific and Technical Information (OSTI)

    Image Data, (Long Version) Citation Details In-Document Search Title: Physics-Based Constraints in the Forward Modeling Analysis of Time-Correlated Image Data, (Long Version) ...

  20. Experiment-Based Model for the Chemical Interactions between...

    Broader source: Energy.gov (indexed) [DOE]

    Experiment-Based Model for the Chemical Interactions between Geothermal Rocks, ... Enhanced Geothermal Systems (EGS) with CO2as Heat Transmission Fluid Chemical Impact of ...

  1. Physics-based constraints in the forward modeling analysis of...

    Office of Scientific and Technical Information (OSTI)

    Conference: Physics-based constraints in the forward modeling analysis of time-correlated image data Citation Details In-Document Search Title: Physics-based constraints in the ...

  2. Physics-Based Constraints in the Forward Modeling Analysis of...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Physics-Based Constraints in the Forward Modeling Analysis of Time-Correlated Image Data, (Long Version) Citation Details In-Document Search Title: Physics-Based ...

  3. Spectral methods for global atmospheric flow applied to the modified AFIT (Air Force Institute of Technology) fallout prediction model. Master's thesis

    SciTech Connect (OSTI)

    Palmer, D.L.

    1986-09-01

    This thesis predicted the airborne spatial distribution of a high-explosive-generated dust cloud. A comparison of predicted cloud center positions to experimental data collected from an aircraft flying through the dust cloud center at various times and altitudes was also studied. The analysis was accomplished using a model called AFGL which produces global complex spectral coefficients. Spectral coefficients were applied as inp fallout prediction model (called REDRAM) to predict dust mass/cu. m.

  4. A test of an expert-based bird-habitat relationship model in South Carolina.

    SciTech Connect (OSTI)

    Kilgo, John, C.; Gartner, David, L.; Chapman, Brian, R.; Dunning, John, B., Jr.; Franzreb, Kathleen, E.; Gauthreaux, Sidney, A.; Greenberg, Catheryn, H.; Levey, Douglas, J.; Miller, Karl, V.; Pearson, Scott, F.

    2002-01-01

    Wildlife-habitat relationships models are used widely by land managers to provide information on which species are likely to occur in an area of interest and may be impacted by a proposed management activity. Few such models have been tested. Recent Avian census data from the Savannah River Site, South Carolina was used to validate BIRDHAB, a geographic information system (GIS) model developed by United States Forest Service resource managers to predict relative habitat quality for birds at the stand level on national forests in the southeastern United States. BIRDHAB is based on the species-habitat matrices presented by Hamel (1992).

  5. Review and model-based analysis of factors influencing soil carbon sequestration beneath switchgrass (Panicum virgatum)

    SciTech Connect (OSTI)

    Garten Jr, Charles T [ORNL

    2012-01-01

    Abstract. A simple, multi-compartment model was developed to predict soil carbon sequestration beneath switchgrass (Panicum virgatum) plantations in the southeastern United States. Soil carbon sequestration is an important component of sustainable switchgrass production for bioenergy because soil organic matter promotes water retention, nutrient supply, and soil properties that minimize erosion. A literature review was included for the purpose of model parameterization and five model-based experiments were conducted to predict how changes in environment (temperature) or crop management (cultivar, fertilization, and harvest efficiency) might affect soil carbon storage and nitrogen losses. Predictions of soil carbon sequestration were most sensitive to changes in annual biomass production, the ratio of belowground to aboveground biomass production, and temperature. Predictions of ecosystem nitrogen loss were most sensitive to changes in annual biomass production, the soil C/N ratio, and nitrogen remobilization efficiency (i.e., nitrogen cycling within the plant). Model-based experiments indicated that 1) soil carbon sequestration can be highly site specific depending on initial soil carbon stocks, temperature, and the amount of annual nitrogen fertilization, 2) response curves describing switchgrass yield as a function of annual nitrogen fertilization were important to model predictions, 3) plant improvements leading to greater belowground partitioning of biomass could increase soil carbon sequestration, 4) improvements in harvest efficiency have no indicated effects on soil carbon and nitrogen, but improve cumulative biomass yield, and 5) plant improvements that reduce organic matter decomposition rates could also increase soil carbon sequestration, even though the latter may not be consistent with desired improvements in plant tissue chemistry to maximize yields of cellulosic ethanol.

  6. Prediction of subsurface fracture in mining zone of Papua using passive seismic tomography based on Fresnel zone

    SciTech Connect (OSTI)

    Setiadi, Herlan; Nurhandoko, Bagus Endar B.; Wely, Woen; Riyanto, Erwin

    2015-04-16

    Fracture prediction in a block cave of underground mine is very important to monitor the structure of the fracture that can be harmful to the mining activities. Many methods can be used to obtain such information, such as TDR (Time Domain Relectometry) and open hole. Both of them have limitations in range measurement. Passive seismic tomography is one of the subsurface imaging method. It has advantage in terms of measurements, cost, and rich of rock physical information. This passive seismic tomography studies using Fresnel zone to model the wavepath by using frequency parameter. Fresnel zone was developed by Nurhandoko in 2000. The result of this study is tomography of P and S wave velocity which can predict position of fracture. The study also attempted to use sum of the wavefronts to obtain position and time of seismic event occurence. Fresnel zone tomography and the summation wavefront can predict location of geological structure of mine area as well.

  7. A Human Life-Stage Physiologically Based Pharmacokinetic and Pharmacodynamic Model for Chlorpyrifos: Development and Validation

    SciTech Connect (OSTI)

    Smith, Jordan N.; Hinderliter, Paul M.; Timchalk, Charles; Bartels, M. J.; Poet, Torka S.

    2014-08-01

    Sensitivity to chemicals in animals and humans are known to vary with age. Age-related changes in sensitivity to chlorpyrifos have been reported in animal models. A life-stage physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model was developed to computationally predict disposition of CPF and its metabolites, chlorpyrifos-oxon (the ultimate toxicant) and 3,5,6-trichloro-2-pyridinol (TCPy), as well as B-esterase inhibition by chlorpyrifos-oxon in humans. In this model, age-dependent body weight was calculated from a generalized Gompertz function, and compartments (liver, brain, fat, blood, diaphragm, rapid, and slow) were scaled based on body weight from polynomial functions on a fractional body weight basis. Blood flows among compartments were calculated as a constant flow per compartment volume. The life-stage PBPK/PD model was calibrated and tested against controlled adult human exposure studies. Model simulations suggest age-dependent pharmacokinetics and response may exist. At oral doses ? 0.55 mg/kg of chlorpyrifos (significantly higher than environmental exposure levels), 6 mo old children are predicted to have higher levels of chlorpyrifos-oxon in blood and higher levels of red blood cell cholinesterase inhibition compared to adults from equivalent oral doses of chlorpyrifos. At lower doses that are more relevant to environmental exposures, the model predicts that adults will have slightly higher levels of chlorpyrifos-oxon in blood and greater cholinesterase inhibition. This model provides a computational framework for age-comparative simulations that can be utilized to predict CPF disposition and biological response over various postnatal life-stages.

  8. A validated model to predict microalgae growth in outdoor pond cultures subjected to fluctuating light intensities and water temperatures

    SciTech Connect (OSTI)

    Huesemann, Michael H.; Crowe, Braden J.; Waller, Peter; Chavis, Aaron R.; Hobbs, Samuel J.; Edmundson, Scott J.; Wigmosta, Mark S.

    2015-12-11

    Here, a microalgae biomass growth model was developed for screening novel strains for their potential to exhibit high biomass productivities under nutrient-replete conditions in outdoor ponds subjected to fluctuating light intensities and water temperatures. Growth is modeled by first estimating the light attenuation by biomass according to a scatter-corrected Beer-Lambert Law, and then calculating the specific growth rate in discretized culture volume slices that receive declining light intensities due to attenuation. The model requires the following experimentally determined strain-specific input parameters: specific growth rate as a function of light intensity and temperature, biomass loss rate in the dark as a function of temperature and average light intensity during the preceding light period, and the scatter-corrected biomass light absorption coefficient. The model was successful in predicting the growth performance and biomass productivity of three different microalgae species (Chlorella sorokiniana, Nannochloropsis salina, and Picochlorum sp.) in raceway pond cultures (batch and semi-continuous) subjected to diurnal sunlight intensity and water temperature variations. Model predictions were moderately sensitive to minor deviations in input parameters. To increase the predictive power of this and other microalgae biomass growth models, a better understanding of the effects of mixing-induced rapid light dark cycles on photo-inhibition and short-term biomass losses due to dark respiration in the aphotic zone of the pond is needed.

  9. A validated model to predict microalgae growth in outdoor pond cultures subjected to fluctuating light intensities and water temperatures

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Huesemann, Michael H.; Crowe, Braden J.; Waller, Peter; Chavis, Aaron R.; Hobbs, Samuel J.; Edmundson, Scott J.; Wigmosta, Mark S.

    2015-12-11

    Here, a microalgae biomass growth model was developed for screening novel strains for their potential to exhibit high biomass productivities under nutrient-replete conditions in outdoor ponds subjected to fluctuating light intensities and water temperatures. Growth is modeled by first estimating the light attenuation by biomass according to a scatter-corrected Beer-Lambert Law, and then calculating the specific growth rate in discretized culture volume slices that receive declining light intensities due to attenuation. The model requires the following experimentally determined strain-specific input parameters: specific growth rate as a function of light intensity and temperature, biomass loss rate in the dark as amore » function of temperature and average light intensity during the preceding light period, and the scatter-corrected biomass light absorption coefficient. The model was successful in predicting the growth performance and biomass productivity of three different microalgae species (Chlorella sorokiniana, Nannochloropsis salina, and Picochlorum sp.) in raceway pond cultures (batch and semi-continuous) subjected to diurnal sunlight intensity and water temperature variations. Model predictions were moderately sensitive to minor deviations in input parameters. To increase the predictive power of this and other microalgae biomass growth models, a better understanding of the effects of mixing-induced rapid light dark cycles on photo-inhibition and short-term biomass losses due to dark respiration in the aphotic zone of the pond is needed.« less

  10. Agent-based modeling of complex infrastructures

    SciTech Connect (OSTI)

    North, M. J.

    2001-06-01

    Complex Adaptive Systems (CAS) can be applied to investigate complex infrastructures and infrastructure interdependencies. The CAS model agents within the Spot Market Agent Research Tool (SMART) and Flexible Agent Simulation Toolkit (FAST) allow investigation of the electric power infrastructure, the natural gas infrastructure and their interdependencies.

  11. Kinetic data base for combustion modeling

    SciTech Connect (OSTI)

    Tsang, W.; Herron, J.T.

    1993-12-01

    The aim of this work is to develop a set of evaluated rate constants for use in the simulation of hydrocarbon combustion. The approach has been to begin with the small molecules and then introduce larger species with the various structural elements that can be found in all hydrocarbon fuels and decomposition products. Currently, the data base contains most of the species present in combustion systems with up to four carbon atoms. Thus, practically all the structural grouping found in aliphatic compounds have now been captured. The direction of future work is the addition of aromatic compounds to the data base.

  12. Reduced Order Modeling for Prediction and Control of Large-Scale Systems.

    SciTech Connect (OSTI)

    Kalashnikova, Irina; Arunajatesan, Srinivasan; Barone, Matthew Franklin; van Bloemen Waanders, Bart Gustaaf; Fike, Jeffrey A.

    2014-05-01

    This report describes work performed from June 2012 through May 2014 as a part of a Sandia Early Career Laboratory Directed Research and Development (LDRD) project led by the first author. The objective of the project is to investigate methods for building stable and efficient proper orthogonal decomposition (POD)/Galerkin reduced order models (ROMs): models derived from a sequence of high-fidelity simulations but having a much lower computational cost. Since they are, by construction, small and fast, ROMs can enable real-time simulations of complex systems for onthe- spot analysis, control and decision-making in the presence of uncertainty. Of particular interest to Sandia is the use of ROMs for the quantification of the compressible captive-carry environment, simulated for the design and qualification of nuclear weapons systems. It is an unfortunate reality that many ROM techniques are computationally intractable or lack an a priori stability guarantee for compressible flows. For this reason, this LDRD project focuses on the development of techniques for building provably stable projection-based ROMs. Model reduction approaches based on continuous as well as discrete projection are considered. In the first part of this report, an approach for building energy-stable Galerkin ROMs for linear hyperbolic or incompletely parabolic systems of partial differential equations (PDEs) using continuous projection is developed. The key idea is to apply a transformation induced by the Lyapunov function for the system, and to build the ROM in the transformed variables. It is shown that, for many PDE systems including the linearized compressible Euler and linearized compressible Navier-Stokes equations, the desired transformation is induced by a special inner product, termed the symmetry inner product. Attention is then turned to nonlinear conservation laws. A new transformation and corresponding energy-based inner product for the full nonlinear compressible Navier

  13. High-throughput prediction of Acacia and eucalypt lignin syringyl/guaiacyl content using FT-Raman spectroscopy and partial least squares modeling

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Lupoi, Jason S.; Healey, Adam; Singh, Seema; Sykes, Robert; Davis, Mark; Lee, David J.; Shepherd, Merv; Simmons, Blake A.; Henry, Robert J.

    2015-01-16

    High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acaciamore » and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. In conclusion, this research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials.« less

  14. High-throughput prediction of Acacia and eucalypt lignin syringyl/guaiacyl content using FT-Raman spectroscopy and partial least squares modeling

    SciTech Connect (OSTI)

    Lupoi, Jason S.; Healey, Adam; Singh, Seema; Sykes, Robert; Davis, Mark; Lee, David J.; Shepherd, Merv; Simmons, Blake A.; Henry, Robert J.

    2015-01-16

    High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. In conclusion, this research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials.

  15. Eulerian CFD Models to Predict Thermophoretic Deposition of Soot Particles in EGR Coolers

    Broader source: Energy.gov [DOE]

    This paper describes an Eulerian axisymmetric method in Fluent(R) to predict the overall heat transfer reduction of a surrogate tube due to thermophoretic deposition of submicron particles.

  16. Computational modeling predicts simultaneous targeting of fibroblasts and epithelial cells is necessary for treatment of pulmonary fibrosis

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Warsinske, Hayley C.; Wheaton, Amanda K.; Kim, Kevin K.; Linderman, Jennifer J.; Moore, Bethany B.; Kirschner, Denise E.

    2016-06-23

    Pulmonary fibrosis is pathologic remodeling of lung tissue that can result in difficulty breathing, reduced quality of life, and a poor prognosis for patients. Fibrosis occurs as a result of insult to lung tissue, though mechanisms of this response are not well-characterized. The disease is driven in part by dysregulation of fibroblast proliferation and differentiation into myofibroblast cells, as well as pro-fibrotic mediator-driven epithelial cell apoptosis. The most well-characterized pro-fibrotic mediator associated with pulmonary fibrosis is TGF-β1. Excessive synthesis of, and sensitivity to, pro-fibrotic mediators as well as insufficient production of and sensitivity to anti-fibrotic mediators has been credited withmore » enabling fibroblast accumulation. Available treatments neither halt nor reverse lung damage. In this study we have two aims: to identify molecular and cellular scale mechanisms driving fibroblast proliferation and differentiation as well as epithelial cell survival in the context of fibrosis, and to predict therapeutic targets and strategies. We combine in vitro studies with a multi-scale hybrid agent-based computational model that describes fibroblasts and epithelial cells in co-culture. Within this model TGF-β1 represents a pro-fibrotic mediator and we include detailed dynamics of TGFβ1 receptor ligand signaling in fibroblasts. PGE2 represents an anti-fibrotic mediator. Using uncertainty and sensitivity analysis we identify TGF-β1 synthesis, TGF-β1 activation, and PGE2 synthesis among the key mechanisms contributing to fibrotic outcomes. We further demonstrate that intervention strategies combining potential therapeutics targeting both fibroblast regulation and epithelial cell survival can promote healthy tissue repair better than individual strategies. Combinations of existing drugs and compounds may provide significant improvements to the current standard of care for pulmonary fibrosis. In conclusion, a two-hit therapeutic

  17. Solid phase evolution in the Biosphere 2 hillslope experiment as predicted by modeling of hydrologic and geochemical fluxes

    SciTech Connect (OSTI)

    Dontsova, K.; Steefel, C.I.; Desilets, S.; Thompson, A.; Chorover, J.

    2009-07-15

    A reactive transport geochemical modeling study was conducted to help predict the mineral transformations occurring over a ten year time-scale that are expected to impact soil hydraulic properties in the Biosphere 2 (B2) synthetic hillslope experiment. The modeling sought to predict the rate and extent of weathering of a granular basalt (selected for hillslope construction) as a function of climatic drivers, and to assess the feedback effects of such weathering processes on the hydraulic properties of the hillslope. Flow vectors were imported from HYDRUS into a reactive transport code, CrunchFlow2007, which was then used to model mineral weathering coupled to reactive solute transport. Associated particle size evolution was translated into changes in saturated hydraulic conductivity using Rosetta software. We found that flow characteristics, including velocity and saturation, strongly influenced the predicted extent of incongruent mineral weathering and neo-phase precipitation on the hillslope. Results were also highly sensitive to specific surface areas of the soil media, consistent with surface reaction controls on dissolution. Effects of fluid flow on weathering resulted in significant differences in the prediction of soil particle size distributions, which should feedback to alter hillslope hydraulic conductivities.

  18. Development of Modeling Methods and Tools for Predicting Coupled Reactive Transport Processes in Porous Media at Multiple Scales

    SciTech Connect (OSTI)

    Clement, T Prabhakar; Barnett, Mark O; Zheng, Chunmiao; Jones, Norman L

    2010-05-05

    DE-FG02-06ER64213: Development of Modeling Methods and Tools for Predicting Coupled Reactive Transport Processes in Porous Media at Multiple Scales Investigators: T. Prabhakar Clement (PD/PI) and Mark O. Barnett (Auburn), Chunmiao Zheng (Univ. of Alabama), and Norman L. Jones (BYU). The objective of this project was to develop scalable modeling approaches for predicting the reactive transport of metal contaminants. We studied two contaminants, a radioactive cation [U(VI)] and a metal(loid) oxyanion system [As(III/V)], and investigated their interactions with two types of subsurface materials, iron and manganese oxyhydroxides. We also developed modeling methods for describing the experimental results. Overall, the project supported 25 researchers at three universities. Produced 15 journal articles, 3 book chapters, 6 PhD dissertations and 6 MS theses. Three key journal articles are: 1) Jeppu et al., A scalable surface complexation modeling framework for predicting arsenate adsorption on goethite-coated sands, Environ. Eng. Sci., 27(2): 147-158, 2010. 2) Loganathan et al., Scaling of adsorption reactions: U(VI) experiments and modeling, Applied Geochemistry, 24 (11), 2051-2060, 2009. 3) Phillippi, et al., Theoretical solid/solution ratio effects on adsorption and transport: uranium (VI) and carbonate, Soil Sci. Soci. of America, 71:329-335, 2007

  19. Model-Predictive Cascade Mitigation in Electric Power Systems With Storage and Renewables-Part I: Theory and Implementation

    SciTech Connect (OSTI)

    Almassalkhi, MR; Hiskens, IA

    2015-01-01

    A novel model predictive control (MPC) scheme is developed for mitigating the effects of severe line-overload disturbances in electrical power systems. A piece-wise linear convex approximation of line losses is employed to model the effect of transmission line power flow on conductor temperatures. Control is achieved through a receding-horizon model predictive control (MPC) strategy which alleviates line temperature overloads and thereby prevents the propagation of outages. The MPC strategy adjusts line flows by rescheduling generation, energy storage and controllable load, while taking into account ramp-rate limits and network limitations. In Part II of this paper, the MPC strategy is illustrated through simulation of the IEEE RTS-96 network, augmented to incorporate energy storage and renewable generation.

  20. Modelling Residential-Scale Combustion-Based Cogeneration in Building Simulation

    SciTech Connect (OSTI)

    Ferguson, A.; Kelly, N.; Weber, A.; Griffith, B.

    2009-03-01

    This article describes the development, calibration and validation of a combustion-cogeneration model for whole-building simulation. As part of IEA Annex 42, we proposed a parametric model for studying residentialscale cogeneration systems based on both Stirling and internal combustion engines. The model can predict the fuel use, thermal output and electrical generation of a cogeneration device in response to changing loads, coolant temperatures and flow rates, and control strategies. The model is now implemented in the publicly-available EnergyPlus, ESP-r and TRNSYS building simulation programs. We vetted all three implementations using a comprehensive comparative testing suite, and validated the model's theoretical basis through comparison to measured data. The results demonstrate acceptable-to-excellent agreement, and suggest the model can be used with confidence when studying the energy performance of cogeneration equipment in non-condensing operation.

  1. Physically-based strength model of tantalum incorporating effects of temperature, strain rate and pressure

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Lim, Hojun; Battaile, Corbett C.; Brown, Justin L.; Weinberger, Christopher R.

    2016-06-14

    In this work, we develop a tantalum strength model that incorporates e ects of temperature, strain rate and pressure. Dislocation kink-pair theory is used to incorporate temperature and strain rate e ects while the pressure dependent yield is obtained through the pressure dependent shear modulus. Material constants used in the model are parameterized from tantalum single crystal tests and polycrystalline ramp compression experiments. It is shown that the proposed strength model agrees well with the temperature and strain rate dependent yield obtained from polycrystalline tantalum experiments. Furthermore, the model accurately reproduces the pressure dependent yield stresses up to 250 GPa.more » The proposed strength model is then used to conduct simulations of a Taylor cylinder impact test and validated with experiments. This approach provides a physically-based multi-scale strength model that is able to predict the plastic deformation of polycrystalline tantalum through a wide range of temperature, strain and pressure regimes.« less

  2. Failure Mode Classification for Life Prediction Modeling of Solid-State Lighting

    SciTech Connect (OSTI)

    Sakalaukus, Peter Joseph

    2015-08-01

    light power” of the SSL luminaire. The use of the Arrhenius equation necessitates two different temperature conditions, 25°C and 45°C are suggested by TM28, to determine the SSL lamp specific activation energy. One principal issue with TM28 is the lack of additional stresses or parameters needed to characterize non-temperature dependent failure mechanisms. Another principal issue with TM28 is the assumption that lumen maintenance or lumen depreciation gives an adequate comparison between SSL luminaires. Additionally, TM28 has no process for the determination of acceleration factors or lifetime estimations. Currently, a literature gap exists for established accelerated test methods for SSL devices to assess quality, reliability and durability before being introduced into the marketplace. Furthermore, there is a need for Physics-of-Failure based approaches to understand the processes and mechanisms that induce failure for the assessment of SSL reliability in order to develop generalized acceleration factors that better represent SSL product lifetime. This and the deficiencies in TM28 validate the need behind the development of acceleration techniques to quantify SSL reliability under a variety of environmental conditions. The ability to assess damage accrual and investigate reliability of SSL components and systems is essential to understanding the life time of the SSL device itself. The methodologies developed in this work increases the understanding of SSL devices iv through the investigation of component and device reliability under a variety of accelerated test conditions. The approaches for suitable lifetime predictions through the development of novel generalized acceleration factors, as well as a prognostics and health management framework, will greatly reduce the time and effort needed to produce SSL acceleration factors for the development of lifetime predictions.

  3. Model based control of dynamic atomic force microscope

    SciTech Connect (OSTI)

    Lee, Chibum; Salapaka, Srinivasa M.

    2015-04-15

    A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H{sub ∞} control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.

  4. Stem thrust prediction model for Westinghouse wedge gate valves with linkage type stem-to-disk connection

    SciTech Connect (OSTI)

    Wang, J.K.; Sharma, V.; Kalsi, M.S.

    1996-12-01

    The Electric Power Research Institute (EPRI) conducted a comprehensive research program with the objective of providing nuclear utilities with analytical methods to predict motor operated valve (MOV) performance under design basis conditions. This paper describes the stem thrust calculation model developed for evaluating the performance of one such valve, the Westinghouse flexible wedge gate valve. These procedures account for the unique functional characteristics of this valve design. In addition, model results are compared to available flow loop and in situ test data as a basis for evaluating the performance of the valve model.

  5. CPUF - a chemical-structure-based polyurethane foam decomposition and foam response model.

    SciTech Connect (OSTI)

    Fletcher, Thomas H. (Brigham Young University, Provo, UT); Thompson, Kyle Richard; Erickson, Kenneth L.; Dowding, Kevin J.; Clayton, Daniel (Brigham Young University, Provo, UT); Chu, Tze Yao; Hobbs, Michael L.; Borek, Theodore Thaddeus III

    2003-07-01

    A Chemical-structure-based PolyUrethane Foam (CPUF) decomposition model has been developed to predict the fire-induced response of rigid, closed-cell polyurethane foam-filled systems. The model, developed for the B-61 and W-80 fireset foam, is based on a cascade of bondbreaking reactions that produce CO2. Percolation theory is used to dynamically quantify polymer fragment populations of the thermally degrading foam. The partition between condensed-phase polymer fragments and gas-phase polymer fragments (i.e. vapor-liquid split) was determined using a vapor-liquid equilibrium model. The CPUF decomposition model was implemented into the finite element (FE) heat conduction codes COYOTE and CALORE, which support chemical kinetics and enclosure radiation. Elements were removed from the computational domain when the calculated solid mass fractions within the individual finite element decrease below a set criterion. Element removal, referred to as ?element death,? creates a radiation enclosure (assumed to be non-participating) as well as a decomposition front, which separates the condensed-phase encapsulant from the gas-filled enclosure. All of the chemistry parameters as well as thermophysical properties for the CPUF model were obtained from small-scale laboratory experiments. The CPUF model was evaluated by comparing predictions to measurements. The validation experiments included several thermogravimetric experiments at pressures ranging from ambient pressure to 30 bars. Larger, component-scale experiments were also used to validate the foam response model. The effects of heat flux, bulk density, orientation, embedded components, confinement and pressure were measured and compared to model predictions. Uncertainties in the model results were evaluated using a mean value approach. The measured mass loss in the TGA experiments and the measured location of the decomposition front were within the 95% prediction limit determined using the CPUF model for all of the

  6. Final predictions of ambient conditions along the east-west crossdrift using the 3-D UZ site-scale model. Level 4 milestoneSP33ABM4.

    SciTech Connect (OSTI)

    Ritcey, A.C.; Sonnenthal, E.L.; Wu, Y.S.; Haukwa, C.; Bodvarsson,G.S.

    1998-03-01

    In 1998, the Yucca Mountain Site Characterization Project (YMP) is expected to continue construction of an East-West Cross Drift. The 5-meter diameter drift will extend from the North Ramp of the Exploratory Studies Facility (ESF), near Station 19+92, southwest through the repository block, and over to and through the Solitario Canyon Fault. This drift is part of a program designed to enhance characterization of Yucca Mountain and to complement existing surface-based and ESF testing studies. The objective of this milestone is to use the three-dimensional (3-D) unsaturated zone (UZ) site-scale model to predict ambient conditions along the East-West Cross Drift. These predictions provide scientists and engineers with a priori information that can support design and construction of the East-West Cross Drift and associated testing program. The predictions also provide, when compared with data collected after drift construction, an opportunity to test and verify the calibration of the 3-D UZ site-scale model.

  7. Tornado missile simulation and design methodology. Volume 2: model verification and data base updates. Final report

    SciTech Connect (OSTI)

    Twisdale, L.A.; Dunn, W.L.

    1981-08-01

    A probabilistic methodology has been developed to predict the probabilities of tornado-propelled missiles impacting and damaging nuclear power plant structures. Mathematical models of each event in the tornado missile hazard have been developed and sequenced to form an integrated, time-history simulation methodology. The models are data based where feasible. The data include documented records of tornado occurrence, field observations of missile transport, results of wind tunnel experiments, and missile impact tests. Probabilistic Monte Carlo techniques are used to estimate the risk probabilities. The methodology has been encoded in the TORMIS computer code to facilitate numerical analysis and plant-specific tornado missile probability assessments.

  8. Transient PVT measurements and model predictions for vessel heat transfer. Part II.

    SciTech Connect (OSTI)

    Felver, Todd G.; Paradiso, Nicholas Joseph; Winters, William S., Jr.; Evans, Gregory Herbert; Rice, Steven F.

    2010-07-01

    Part I of this report focused on the acquisition and presentation of transient PVT data sets that can be used to validate gas transfer models. Here in Part II we focus primarily on describing models and validating these models using the data sets. Our models are intended to describe the high speed transport of compressible gases in arbitrary arrangements of vessels, tubing, valving and flow branches. Our models fall into three categories: (1) network flow models in which flow paths are modeled as one-dimensional flow and vessels are modeled as single control volumes, (2) CFD (Computational Fluid Dynamics) models in which flow in and between vessels is modeled in three dimensions and (3) coupled network/CFD models in which vessels are modeled using CFD and flows between vessels are modeled using a network flow code. In our work we utilized NETFLOW as our network flow code and FUEGO for our CFD code. Since network flow models lack three-dimensional resolution, correlations for heat transfer and tube frictional pressure drop are required to resolve important physics not being captured by the model. Here we describe how vessel heat transfer correlations were improved using the data and present direct model-data comparisons for all tests documented in Part I. Our results show that our network flow models have been substantially improved. The CFD modeling presented here describes the complex nature of vessel heat transfer and for the first time demonstrates that flow and heat transfer in vessels can be modeled directly without the need for correlations.

  9. Comparison of chiller models for use in model-based fault detection

    SciTech Connect (OSTI)

    Sreedharan, Priya; Haves, Philip

    2001-06-07

    Selecting the model is an important and essential step in model based fault detection and diagnosis (FDD). Factors that are considered in evaluating a model include accuracy, training data requirements, calibration effort, generality, and computational requirements. The objective of this study was to evaluate different modeling approaches for their applicability to model based FDD of vapor compression chillers. Three different models were studied: the Gordon and Ng Universal Chiller model (2nd generation) and a modified version of the ASHRAE Primary Toolkit model, which are both based on first principles, and the DOE-2 chiller model, as implemented in CoolTools{trademark}, which is empirical. The models were compared in terms of their ability to reproduce the observed performance of an older, centrifugal chiller operating in a commercial office building and a newer centrifugal chiller in a laboratory. All three models displayed similar levels of accuracy. Of the first principles models, the Gordon-Ng model has the advantage of being linear in the parameters, which allows more robust parameter estimation methods to be used and facilitates estimation of the uncertainty in the parameter values. The ASHRAE Toolkit Model may have advantages when refrigerant temperature measurements are also available. The DOE-2 model can be expected to have advantages when very limited data are available to calibrate the model, as long as one of the previously identified models in the CoolTools library matches the performance of the chiller in question.

  10. Predicting Overall Survival After Stereotactic Ablative Radiation Therapy in Early-Stage Lung Cancer: Development and External Validation of the Amsterdam Prognostic Model

    SciTech Connect (OSTI)

    Louie, Alexander V.; Haasbeek, Cornelis J.A.; Mokhles, Sahar; Rodrigues, George B.; Stephans, Kevin L.; Lagerwaard, Frank J.; Palma, David A.; Videtic, Gregory M.M.; Warner, Andrew; Takkenberg, Johanna J.M.; Reddy, Chandana A.; Maat, Alex P.W.M.; Woody, Neil M.; Slotman, Ben J.; Senan, Suresh

    2015-09-01

    Purpose: A prognostic model for 5-year overall survival (OS), consisting of recursive partitioning analysis (RPA) and a nomogram, was developed for patients with early-stage non-small cell lung cancer (ES-NSCLC) treated with stereotactic ablative radiation therapy (SABR). Methods and Materials: A primary dataset of 703 ES-NSCLC SABR patients was randomly divided into a training (67%) and an internal validation (33%) dataset. In the former group, 21 unique parameters consisting of patient, treatment, and tumor factors were entered into an RPA model to predict OS. Univariate and multivariate models were constructed for RPA-selected factors to evaluate their relationship with OS. A nomogram for OS was constructed based on factors significant in multivariate modeling and validated with calibration plots. Both the RPA and the nomogram were externally validated in independent surgical (n=193) and SABR (n=543) datasets. Results: RPA identified 2 distinct risk classes based on tumor diameter, age, World Health Organization performance status (PS) and Charlson comorbidity index. This RPA had moderate discrimination in SABR datasets (c-index range: 0.52-0.60) but was of limited value in the surgical validation cohort. The nomogram predicting OS included smoking history in addition to RPA-identified factors. In contrast to RPA, validation of the nomogram performed well in internal validation (r{sup 2}=0.97) and external SABR (r{sup 2}=0.79) and surgical cohorts (r{sup 2}=0.91). Conclusions: The Amsterdam prognostic model is the first externally validated prognostication tool for OS in ES-NSCLC treated with SABR available to individualize patient decision making. The nomogram retained strong performance across surgical and SABR external validation datasets. RPA performance was poor in surgical patients, suggesting that 2 different distinct patient populations are being treated with these 2 effective modalities.

  11. A nonlocal, ordinary, state-based plasticity model for peridynamics...

    Office of Scientific and Technical Information (OSTI)

    An implicit time integration algorithm for a non-local, state-based, peridynamics plasticity model is developed. The flow rule was proposed in 3 without an integration strategy ...

  12. A Geothermal Field Model Based On Geophysical And Thermal Prospectings...

    Open Energy Info (EERE)

    Field Model Based On Geophysical And Thermal Prospectings In Nea Kessani (Ne Greece) Jump to: navigation, search OpenEI Reference LibraryAdd to library Journal Article: A...

  13. Managing Model Data Introduced Uncertainties in Simulator Predictions for Generation IV Systems via Optimum Experimental Design

    SciTech Connect (OSTI)

    Turinsky, Paul J; Abdel-Khalik, Hany S; Stover, Tracy E

    2011-03-31

    An optimization technique has been developed to select optimized experimental design specifications to produce data specifically designed to be assimilated to optimize a given reactor concept. Data from the optimized experiment is assimilated to generate posteriori uncertainties on the reactor concept’s core attributes from which the design responses are computed. The reactor concept is then optimized with the new data to realize cost savings by reducing margin. The optimization problem iterates until an optimal experiment is found to maximize the savings. A new generation of innovative nuclear reactor designs, in particular fast neutron spectrum recycle reactors, are being considered for the application of closing the nuclear fuel cycle in the future. Safe and economical design of these reactors will require uncertainty reduction in basic nuclear data which are input to the reactor design. These data uncertainty propagate to design responses which in turn require the reactor designer to incorporate additional safety margin into the design, which often increases the cost of the reactor. Therefore basic nuclear data needs to be improved and this is accomplished through experimentation. Considering the high cost of nuclear experiments, it is desired to have an optimized experiment which will provide the data needed for uncertainty reduction such that a reactor design concept can meet its target accuracies or to allow savings to be realized by reducing the margin required due to uncertainty propagated from basic nuclear data. However, this optimization is coupled to the reactor design itself because with improved data the reactor concept can be re-optimized itself. It is thus desired to find the experiment that gives the best optimized reactor design. Methods are first established to model both the reactor concept and the experiment and to efficiently propagate the basic nuclear data uncertainty through these models to outputs. The representativity of the experiment

  14. Model-Based Transient Calibration Optimization for Next Generation Diesel

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Engines | Department of Energy Model-Based Transient Calibration Optimization for Next Generation Diesel Engines Model-Based Transient Calibration Optimization for Next Generation Diesel Engines 2005 Diesel Engine Emissions Reduction (DEER) Conference Presentations and Posters 2005_deer_atkinson.pdf (585.55 KB) More Documents & Publications Future Diesel Engine Thermal Efficiency Improvement andn Emissions Control Technology Integrated Engine and Aftertreatment Technology Roadmap for EPA

  15. Increased Efficiency with Model Based Calibration | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Efficiency with Model Based Calibration Increased Efficiency with Model Based Calibration Meeting future TIER 4 emission limits requires the integration of many new technology elements. deer09_diewald.pdf (1.04 MB) More Documents & Publications Vehicle Evaluation of Downsized Dow ACM DPF Exhaust Aftertreatment and Low Pressure Loop EGR Applied to an Off-Highway Engine Review of Emerging Diesel Emissions and Control

  16. ALE3D Model Predictions and Materials Characterization for the Cookoff Response of PBXN-109

    SciTech Connect (OSTI)

    McClelland, M A; Maienschein, J L; Nichols, A L; Wardell, J F; Atwood, A I; Curran, P O

    2002-03-19

    ALE3D simulations are presented for the thermal explosion of PBXN-109 (RDX, AI, HTPB, DOA) in support of an effort by the U. S. Navy and Department of Energy (DOE) to validate computational models. The U.S. Navy is performing benchmark tests for the slow cookoff of PBXN-109 in a sealed tube. Candidate models are being tested using the ALE3D code, which can simulate the coupled thermal, mechanical, and chemical behavior during heating, ignition, and explosion. The strength behavior of the solid constituents is represented by a Steinberg-Guinan model while polynomial and gamma-law expressions are used for the Equation Of State (EOS) for the solid and gas species, respectively. A void model is employed to represent the air in gaps. ALE3D model 'parameters are specified using measurements of thermal and mechanical properties including thermal expansion, heat capacity, shear modulus, and bulk modulus. A standard three-step chemical kinetics model is used during the thermal ramp, and a pressure-dependent burn front model is employed during the rapid expansion. Parameters for the three-step kinetics model are specified using measurements of the One-Dimensional-Time-to-Explosion (ODTX), while measurements for burn rate of pristine and thermally damaged material are employed to determine parameters in the burn front model. Results are given for calculations in which heating, ignition, and explosion are modeled in a single simulation. We compare model results to measurements for the cookoff temperature and tube wall strain.

  17. Validation of a Fast-Fluid-Dynamics Model for Predicting Distribution of Particles with Low Stokes Number

    SciTech Connect (OSTI)

    Zuo, Wangda; Chen, Qingyan

    2011-06-01

    To design a healthy indoor environment, it is important to study airborne particle distribution indoors. As an intermediate model between multizone models and computational fluid dynamics (CFD), a fast fluid dynamics (FFD) model can be used to provide temporal and spatial information of particle dispersion in real time. This study evaluated the accuracy of the FFD for predicting transportation of particles with low Stokes number in a duct and in a room with mixed convection. The evaluation was to compare the numerical results calculated by the FFD with the corresponding experimental data and the results obtained by the CFD. The comparison showed that the FFD could capture major pattern of particle dispersion, which is missed in models with well-mixed assumptions. Although the FFD was less accurate than the CFD partially due to its simplification in numeric schemes, it was 53 times faster than the CFD.

  18. Progress toward bridging from atomistic to continuum modeling to predict nuclear waste glass dissolution.

    SciTech Connect (OSTI)

    Zapol, Peter; Bourg, Ian; Criscenti, Louise Jacqueline; Steefel, Carl I.; Schultz, Peter Andrew

    2011-10-01

    This report summarizes research performed for the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Subcontinuum and Upscaling Task. The work conducted focused on developing a roadmap to include molecular scale, mechanistic information in continuum-scale models of nuclear waste glass dissolution. This information is derived from molecular-scale modeling efforts that are validated through comparison with experimental data. In addition to developing a master plan to incorporate a subcontinuum mechanistic understanding of glass dissolution into continuum models, methods were developed to generate constitutive dissolution rate expressions from quantum calculations, force field models were selected to generate multicomponent glass structures and gel layers, classical molecular modeling was used to study diffusion through nanopores analogous to those in the interfacial gel layer, and a micro-continuum model (K{mu}C) was developed to study coupled diffusion and reaction at the glass-gel-solution interface.

  19. Divergent predictions of carbon storage between two global land models: attribution of the causes through traceability analysis

    SciTech Connect (OSTI)

    Rafique, Rashid; Xia, Jianyang; Hararuk, Oleksandra; Asrar, Ghassem R.; Wang, Yingping; Luo, Yiqi

    2015-08-27

    Representations of the terrestrial carbon cycle in land models are becoming increasingly complex. It is crucial to develop approaches for critical assessment of the complex model properties in order to understand key factors contributing to models’ performance. In this study, we applied a traceability analysis, which decomposes carbon cycle models into traceable components, to two global land models (CABLE and CLM-CASA’) to diagnose the causes of their differences in simulating ecosystem carbon storage capacity. Driven with similar forcing data, the CLM-CASA’ model predicted ~31% larger carbon storage capacity than the CABLE model. Since ecosystem carbon storage capacity is a product of net primary productivity (NPP) and ecosystem residence time (τE), the predicted difference in the storage capacity between the two models results from differences in either NPP or τE or both. Our analysis showed that CLM-CASA’ simulated 37% higher NPP than CABLE due to higher rates of carboxylation (Vcmax) in CLM-CASA’. On the other hand, τE , which was a function the baseline carbon residence time (τ´E) and environmental effect on carbon residence time, was on average 11 years longer in CABLE than CLM-CASA’. The difference in τE was mainly found to be caused by longer τ´E in CABLE than CLM-CASA’. This difference in τE was mainly caused by longer τ´E of woody biomass (23 vs. 14 years in CLM-CASA’) and higher proportion of NPP allocated to woody biomass (23% vs. 16%). Differences in environmental effects on carbon residence times had smaller influences on differences in ecosystem carbon storage capacities compared to differences in NPP and τ´E. Overall; the traceability analysis is an effective method for identifying sources of variations between the two models.

  20. Visual agent-based model development with repast simphony.

    SciTech Connect (OSTI)

    North, M. J.; Tatara, E.; Collier, N. T.; Ozik, J.; Decision and Information Sciences; Univ. of Chicago; PantaRei Corp.

    2007-01-01

    Repast is a widely used, free, and open-source agent-based modeling and simulation toolkit. Three Repast platforms are currently available, each of which has the same core features but a different environment for these features. Repast Simphony (Repast S) extends the Repast portfolio by offering a new approach to simulation development and execution. This paper presents a model of physical infrastructure network interdependency as an introductory tutorial and illustration of the visual modeling capabilities of Repast S.

  1. Development of a land ice core for the Model for Prediction Across...

    Office of Scientific and Technical Information (OSTI)

    Resource Relation: Conference: Community Earth System Model Workshop ; 2012-06-18 - ... Sponsoring Org: DOELANL Country of Publication: United States Language: English Subject: ...

  2. Development of Chemical Model to Predict the Interactions between Supercritical CO2and Fluid, and Rocks in EGS Reservoirs

    Broader source: Energy.gov [DOE]

    This project will develop a chemical model, based on existing models and databases, that is capable of simulating chemical reactions between supercritical (SC) CO2 and Enhanced Geothermal System (EGS) reservoir rocks of various compositions in aqueous, non-aqueous and 2-phase environments.

  3. A Novel Method for Predicting Late Genitourinary Toxicity After Prostate Radiation Therapy and the Need for Age-Based Risk-Adapted Dose Constraints

    SciTech Connect (OSTI)

    Ahmed, Awad A.; Egleston, Brian; Alcantara, Pino; Li, Linna; Pollack, Alan; Horwitz, Eric M.; Buyyounouski, Mark K.

    2013-07-15

    Background: There are no well-established normal tissue sparing dosevolume histogram (DVH) criteria that limit the risk of urinary toxicity from prostate radiation therapy (RT). The aim of this study was to determine which criteria predict late toxicity among various DVH parameters when contouring the entire solid bladder and its contents versus the bladder wall. The area under the histogram curve (AUHC) was also analyzed. Methods and Materials: From 1993 to 2000, 503 men with prostate cancer received 3-dimensional conformal RT (median follow-up time, 71 months). The whole bladder and the bladder wall were contoured in all patients. The primary endpoint was grade ?2 genitourinary (GU) toxicity occurring ?3 months after completion of RT. Cox regressions of time to grade ?2 toxicity were estimated separately for the entire bladder and bladder wall. Concordance probability estimates (CPE) assessed model discriminative ability. Before training the models, an external random test group of 100 men was set aside for testing. Separate analyses were performed based on the mean age (? 68 vs >68 years). Results: Age, pretreatment urinary symptoms, mean dose (entire bladder and bladder wall), and AUHC (entire bladder and bladder wall) were significant (P<.05) in multivariable analysis. Overall, bladder wall CPE values were higher than solid bladder values. The AUHC for bladder wall provided the greatest discrimination for late bladder toxicity when compared with alternative DVH points, with CPE values of 0.68 for age ?68 years and 0.81 for age >68 years. Conclusion: The AUHC method based on bladder wall volumes was superior for predicting late GU toxicity. Age >68 years was associated with late grade ?2 GU toxicity, which suggests that risk-adapted dose constraints based on age should be explored.

  4. Multi-scale modeling of microstructure dependent intergranular brittle fracture using a quantitative phase-field based method

    SciTech Connect (OSTI)

    Chakraborty, Pritam; Zhang, Yongfeng; Tonks, Michael R.

    2015-12-07

    In this study, the fracture behavior of brittle materials is strongly influenced by their underlying microstructure that needs explicit consideration for accurate prediction of fracture properties and the associated scatter. In this work, a hierarchical multi-scale approach is pursued to model microstructure sensitive brittle fracture. A quantitative phase-field based fracture model is utilized to capture the complex crack growth behavior in the microstructure and the related parameters are calibrated from lower length scale atomistic simulations instead of engineering scale experimental data. The workability of this approach is demonstrated by performing porosity dependent intergranular fracture simulations in UO2 and comparing the predictions with experiments.

  5. A grillage model for predicting wrinkles in annular graphene under circular shearing

    SciTech Connect (OSTI)

    Zhang, Z.; Duan, W. H.; Wang, C. M.

    2013-01-07

    This paper is concerned with a Timoshenko grillage model for modeling the wrinkling phenomenon in annular graphene under circular shearing applied at its inner edge. By calibrating the grillage model results against the molecular mechanics (MM) results, the grillage model comprising beams of elliptical cross-section orientated along the carbon-carbon bond has section dimensions of 0.06 nm for the major axis length and 0.036 nm for the minor axis length. Moreover, the beams are connected to one another at 0.00212 nm from the geometric centric. This eccentric connection of beams allows the proposed grillage model to cater for the cross-couplings among bonds that produce the out-of-plane wrinkling pattern. The out-of-plane to in-plane bending stiffnesses' ratio is 0.36, and the cross bending stiffness provided by the ellipse eccentricity is 0.025 times that of the in-plane bending stiffness. Besides furnishing identical wave numbers as well as amplitudes and wavelengths that are in good agreement with MM results, the grillage model can capture wrinkling patterns with a boundary layer, whereas plate and membrane models could not mimic the boundary layer.

  6. Thermodynamic Prediction of Compositional Phases Confirmed by Transmission Electron Microscopy on Tantalum-Based Alloy Weldments

    SciTech Connect (OSTI)

    Moddeman, William E.; Birkbeck, Janine C.; Barklay, Chadwick D.; Kramer, Daniel P.; Miller, Roger G.; Allard, Lawrence F.

    2007-01-30

    Tantalum alloys have been used by the U.S. Department of Energy as structural alloys for radioisotope based thermal to electrical power systems since the 1960s. Tantalum alloys are attractive for high temperature structural applications due to their high melting point, excellent formability, good thermal conductivity, good ductility (even at low temperatures), corrosion resistance, and weldability. Tantalum alloys have demonstrated sufficient high-temperature toughness to survive prolonged exposure to the radioisotope power-system working environment. Typically, the fabrication of power systems requires the welding of various components including the structural members made of tantalum alloys. Issues such as thermodynamics, lattice structure, weld pool dynamics, material purity and contamination, and welding atmosphere purity all potentially confound the understanding of the differences between the weldment properties of the different tantalum-based alloys. The objective of this paper is to outline the thermodynamically favorable material phases in tantalum alloys, with and without small amounts of hafnium, during and following solidification, based on the results derived from the FactSage(c) Integrated Thermodynamic Databank. In addition, Transition Electron Microscopy (TEM) data will show for the first time, the changes occurring in the HfC before and after welding, and the data will elucidate the role HfC plays in pinning grain boundaries.

  7. Recovery Act. Development and Validation of an Advanced Stimulation Prediction Model for Enhanced Geothermal Systems

    SciTech Connect (OSTI)

    Gutierrez, Marte

    2013-12-31

    This research project aims to develop and validate an advanced computer model that can be used in the planning and design of stimulation techniques to create engineered reservoirs for Enhanced Geothermal Systems. The specific objectives of the proposal are to; Develop a true three-dimensional hydro-thermal fracturing simulator that is particularly suited for EGS reservoir creation; Perform laboratory scale model tests of hydraulic fracturing and proppant flow/transport using a polyaxial loading device, and use the laboratory results to test and validate the 3D simulator; Perform discrete element/particulate modeling of proppant transport in hydraulic fractures, and use the results to improve understand of proppant flow and transport; Test and validate the 3D hydro-thermal fracturing simulator against case histories of EGS energy production; and Develop a plan to commercialize the 3D fracturing and proppant flow/transport simulator. The project is expected to yield several specific results and benefits. Major technical products from the proposal include; A true-3D hydro-thermal fracturing computer code that is particularly suited to EGS; Documented results of scale model tests on hydro-thermal fracturing and fracture propping in an analogue crystalline rock; Documented procedures and results of discrete element/particulate modeling of flow and transport of proppants for EGS applications; and Database of monitoring data, with focus of Acoustic Emissions (AE) from lab scale modeling and field case histories of EGS reservoir creation.

  8. Tritium monitoring in groundwater and evaluation of model predictions for the Hanford Site 200 Area Effluent Treatment Facility

    SciTech Connect (OSTI)

    Barnett, D.B.; Bergeron, M.P.; Cole, C.R.; Freshley, M.D.; Wurstner, S.K.

    1997-08-01

    The Effluent Treatment Facility (ETF) disposal site, also known as the State-Approved Land Disposal Site (SALDS), receives treated effluent containing tritium, which is allowed to infiltrate through the soil column to the water table. Tritium was first detected in groundwater monitoring wells around the facility in July 1996. The SALDS groundwater monitoring plan requires revision of a predictive groundwater model and reevaluation of the monitoring well network one year from the first detection of tritium in groundwater. This document is written primarily to satisfy these requirements and to report on analytical results for tritium in the SALDS groundwater monitoring network through April 1997. The document also recommends an approach to continued groundwater monitoring for tritium at the SALDS. Comparison of numerical groundwater models applied over the last several years indicate that earlier predictions, which show tritium from the SALDS approaching the Columbia River, were too simplified or overly robust in source assumptions. The most recent modeling indicates that concentrations of tritium above 500 pCi/L will extend, at most, no further than {approximately}1.5 km from the facility, using the most reasonable projections of ETF operation. This extent encompasses only the wells in the current SALDS tritium-tracking network.

  9. Methods and apparatus for measurement of a dimensional characteristic and methods of predictive modeling related thereto

    DOE Patents [OSTI]

    Robertson, Eric P; Christiansen, Richard L.

    2007-05-29

    A method of optically determining a change in magnitude of at least one dimensional characteristic of a sample in response to a selected chamber environment. A magnitude of at least one dimension of the at least one sample may be optically determined subsequent to altering the at least one environmental condition within the chamber. A maximum change in dimension of the at least one sample may be predicted. A dimensional measurement apparatus for indicating a change in at least one dimension of at least one sample. The dimensional measurement apparatus may include a housing with a chamber configured for accommodating pressure changes and an optical perception device for measuring a dimension of at least one sample disposed in the chamber. Methods of simulating injection of a gas into a subterranean formation, injecting gas into a subterranean formation, and producing methane from a coal bed are also disclosed.

  10. Methods for measurement of a dimensional characteristic and methods of predictive modeling related thereto

    DOE Patents [OSTI]

    Robertson, Eric P; Christiansen, Richard L.

    2007-10-23

    A method of optically determining a change in magnitude of at least one dimensional characteristic of a sample in response to a selected chamber environment. A magnitude of at least one dimension of the at least one sample may be optically determined subsequent to altering the at least one environmental condition within the chamber. A maximum change in dimension of the at least one sample may be predicted. A dimensional measurement apparatus for indicating a change in at least one dimension of at least one sample. The dimensional measurement apparatus may include a housing with a chamber configured for accommodating pressure changes and an optical perception device for measuring a dimension of at least one sample disposed in the chamber. Methods of simulating injection of a gas into a subterranean formation, injecting gas into a subterranean formation, and producing methane from a coal bed are also disclosed.

  11. A new model for predicting the fouling deposit weight of coal

    SciTech Connect (OSTI)

    Yeakel, J.D. ); Finkelman, R.B. )

    1988-06-01

    One of the major problems associated with coal combustion is the buildup of sintered ash deposits in the convective passes of boilers. These deposits, referred to as fouling deposits, can drastically reduce heat transfer, cause erosion by channelizing gas flow, and contribute to the corrosion of exposed metal surfaces. Downtime for cleaning fouled commercial boilers can be a multi-million-dollar expense. Utility boilers generally are designed to burn coal that falls within a specific fouling behavior range. Therefore, to minimize the deleterious effects of boiler fouling and to maximize boiler efficiency, it is necessary to anticipate or assess the fouling characteristics of a coal prior to combustion. This paper introduces a new method for predicting fouling deposit weights by using commonly available coal quality data. The authors have developed a modified concept of the coal quality characteristics that influence fouling. This concept evolved from a review of the literature and from the statistical analysis of results from 44 combustion tests.

  12. A connectivity-based modeling approach for representing hysteresis in macroscopic two-phase flow properties

    SciTech Connect (OSTI)

    Cihan, Abdullah; Birkholzer, Jens; Trevisan, Luca; Bianchi, Marco; Zhou, Quanlin; Illangasekare, Tissa

    2014-12-31

    During CO2 injection and storage in deep reservoirs, the injected CO2 enters into an initially brine saturated porous medium, and after the injection stops, natural groundwater flow eventually displaces the injected mobile-phase CO2, leaving behind residual non-wetting fluid. Accurate modeling of two-phase flow processes are needed for predicting fate and transport of injected CO2, evaluating environmental risks and designing more effective storage schemes. The entrapped non-wetting fluid saturation is typically a function of the spatially varying maximum saturation at the end of injection. At the pore-scale, distribution of void sizes and connectivity of void space play a major role for the macroscopic hysteresis behavior and capillary entrapment of wetting and non-wetting fluids. This paper presents development of an approach based on the connectivity of void space for modeling hysteretic capillary pressure-saturation-relative permeability relationships. The new approach uses void-size distribution and a measure of void space connectivity to compute the hysteretic constitutive functions and to predict entrapped fluid phase saturations. Two functions, the drainage connectivity function and the wetting connectivity function, are introduced to characterize connectivity of fluids in void space during drainage and wetting processes. These functions can be estimated through pore-scale simulations in computer-generated porous media or from traditional experimental measurements of primary drainage and main wetting curves. The hysteresis model for saturation-capillary pressure is tested successfully by comparing the model-predicted residual saturation and scanning curves with actual data sets obtained from column experiments found in the literature. A numerical two-phase model simulator with the new hysteresis functions is tested against laboratory experiments conducted in a quasi-two-dimensional flow cell (91.4cm5.6cm61cm

  13. A connectivity-based modeling approach for representing hysteresis in macroscopic two-phase flow properties

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Cihan, Abdullah; Birkholzer, Jens; Trevisan, Luca; Bianchi, Marco; Zhou, Quanlin; Illangasekare, Tissa

    2014-12-31

    During CO2 injection and storage in deep reservoirs, the injected CO2 enters into an initially brine saturated porous medium, and after the injection stops, natural groundwater flow eventually displaces the injected mobile-phase CO2, leaving behind residual non-wetting fluid. Accurate modeling of two-phase flow processes are needed for predicting fate and transport of injected CO2, evaluating environmental risks and designing more effective storage schemes. The entrapped non-wetting fluid saturation is typically a function of the spatially varying maximum saturation at the end of injection. At the pore-scale, distribution of void sizes and connectivity of void space play a major role formore » the macroscopic hysteresis behavior and capillary entrapment of wetting and non-wetting fluids. This paper presents development of an approach based on the connectivity of void space for modeling hysteretic capillary pressure-saturation-relative permeability relationships. The new approach uses void-size distribution and a measure of void space connectivity to compute the hysteretic constitutive functions and to predict entrapped fluid phase saturations. Two functions, the drainage connectivity function and the wetting connectivity function, are introduced to characterize connectivity of fluids in void space during drainage and wetting processes. These functions can be estimated through pore-scale simulations in computer-generated porous media or from traditional experimental measurements of primary drainage and main wetting curves. The hysteresis model for saturation-capillary pressure is tested successfully by comparing the model-predicted residual saturation and scanning curves with actual data sets obtained from column experiments found in the literature. A numerical two-phase model simulator with the new hysteresis functions is tested against laboratory experiments conducted in a quasi-two-dimensional flow cell (91.4cm×5.6cm×61cm), packed with homogeneous and

  14. Statistical circuit simulation with measurement-based active device models: Implications for process control and IC manufacturability

    SciTech Connect (OSTI)

    Root, D.E.; McGinty, D.; Hughes, B.

    1995-12-31

    This paper presents a new approach to statistical active circuit design which unifies device parametric-based process control and non-parametric circuit simulation. Predictions of circuit sensitivity to process variation and yield-loss of circuits fabricated in two different GaAs IC processes are described. The simulations make use of measurement-based active device models which are not formulated in terms of conventional parametric statistical variables. The technique is implemented in commercially available simulation software (HP MDS).

  15. Development of a Mechanistic-Based Healing Model for Self-Healing Glass Seals

    SciTech Connect (OSTI)

    Xu, Wei; Stephens, Elizabeth V.; Sun, Xin; Khaleel, Mohammad A.; Zbib, Hussein M.

    2012-10-01

    Self-healing glass, a recent development of hermetic sealant materials, has the ability to effectively repair damage when heated to elevated temperatures; thus, able to extend its service life. Since crack healing morphological changes in the glass material are usually temperature and stress dependent, quantitative studies to determine the effects of thermo-mechanical conditions on the healing behavior of the self-healing glass sealants are extremely useful to accommodate the design and optimization of the sealing systems within SOFCs. The goal of this task is to develop a mechanistic-based healing model to quantify the stress and temperature dependent healing behavior. A two-step healing mechanism was developed and implemented into finite element (FE) models through user-subroutines. Integrated experimental/kinetic Monte Carlo (kMC) simulation methodology was taken to calibrate the model parameters. The crack healing model is able to investigate the effects of various thermo-mechanical factors; therefore, able to determine the critical conditions under which the healing mechanism will be activated. Furthermore, the predicted results can be used to formulate the continuum damage-healing model and to assist the SOFC stack level simulations in predicting and evaluating the effectiveness and the performance of various engineering seal designs.

  16. Fish Individual-based Numerical Simulator (FINS): A particle-based model of juvenile salmonid movement and dissolved gas exposure history in the Columbia River Basin

    SciTech Connect (OSTI)

    Scheibe, Timothy D.; Richmond, Marshall C.

    2002-01-30

    This paper describes a numerical model of juvenile salmonid migration in the Columbia and Snake Rivers. The model, called the Fish Individual-based Numerical Simulator or FINS, employs a discrete, particle-based approach to simulate the migration and history of exposure to dissolved gases of individual fish. FINS is linked to a two-dimensional (vertically-averaged) hydrodynamic simulator that quantifies local water velocity, temperature, and dissolved gas levels as a function of river flow rates and dam operations. Simulated gas exposure histories can be input to biological mortality models to predict the effects of various river configurations on fish injury and mortality due to dissolved gas supersaturation. Therefore, FINS serves as a critical linkage between hydrodynamic models of the river system and models of biological impacts. FINS was parameterized and validated based on observations of individual fish movements collected using radiotelemetry methods during 1997 and 1998. A quasi-inverse approach was used to decouple fish swimming movements from advection with the local water velocity, allowing inference of time series of non-advective displacements of individual fish from the radiotelemetry data. Statistical analyses of these displacements are presented, and confirm that strong temporal correlation of fish swimming behavior persists in some cases over several hours. A correlated random-walk model was employed to simulate the observed migration behavior, and parameters of the model were estimated that lead to close correspondence between predictions and observations.

  17. Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

    SciTech Connect (OSTI)

    Seaver, Samuel M.D.; Bradbury, Louis M.T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

    2015-03-10

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.

  18. Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Seaver, Samuel M.D.; Bradbury, Louis M.T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

    2015-03-10

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions andmore » possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.« less

  19. Comparison of Uncertainty of Two Precipitation Prediction Models at Los Alamos National Lab Technical Area 54

    SciTech Connect (OSTI)

    Shield, Stephen Allan; Dai, Zhenxue

    2015-08-18

    Meteorological inputs are an important part of subsurface flow and transport modeling. The choice of source for meteorological data used as inputs has significant impacts on the results of subsurface flow and transport studies. One method to obtain the meteorological data required for flow and transport studies is the use of weather generating models. This paper compares the difference in performance of two weather generating models at Technical Area 54 of Los Alamos National Lab. Technical Area 54 is contains several waste pits for low-level radioactive waste and is the site for subsurface flow and transport studies. This makes the comparison of the performance of the two weather generators at this site particularly valuable.

  20. Early prediction of tumor recurrence based on CT texture changes after stereotactic ablative radiotherapy (SABR) for lung cancer

    SciTech Connect (OSTI)

    Mattonen, Sarah A.; Palma, David A.; Haasbeek, Cornelis J. A.; Senan, Suresh; Ward, Aaron D.

    2014-03-15

    Purpose: Benign computed tomography (CT) changes due to radiation induced lung injury (RILI) are common following stereotactic ablative radiotherapy (SABR) and can be difficult to differentiate from tumor recurrence. The authors measured the ability of CT image texture analysis, compared to more traditional measures of response, to predict eventual cancer recurrence based on CT images acquired within 5 months of treatment. Methods: A total of 24 lesions from 22 patients treated with SABR were selected for this study: 13 with moderate to severe benign RILI, and 11 with recurrence. Three-dimensional (3D) consolidative and ground-glass opacity (GGO) changes were manually delineated on all follow-up CT scans. Two size measures of the consolidation regions (longest axial diameter and 3D volume) and nine appearance features of the GGO were calculated: 2 first-order features [mean density and standard deviation of density (first-order texture)], and 7 second-order texture features [energy, entropy, correlation, inverse difference moment (IDM), inertia, cluster shade, and cluster prominence]. For comparison, the corresponding response evaluation criteria in solid tumors measures were also taken for the consolidation regions. Prediction accuracy was determined using the area under the receiver operating characteristic curve (AUC) and two-fold cross validation (CV). Results: For this analysis, 46 diagnostic CT scans scheduled for approximately 3 and 6 months post-treatment were binned based on their recorded scan dates into 2–5 month and 5–8 month follow-up time ranges. At 2–5 months post-treatment, first-order texture, energy, and entropy provided AUCs of 0.79–0.81 using a linear classifier. On two-fold CV, first-order texture yielded 73% accuracy versus 76%–77% with the second-order features. The size measures of the consolidative region, longest axial diameter and 3D volume, gave two-fold CV accuracies of 60% and 57%, and AUCs of 0.72 and 0.65, respectively

  1. Cloud-Based Model Calibration Using OpenStudio: Preprint

    SciTech Connect (OSTI)

    Hale, E.; Lisell, L.; Goldwasser, D.; Macumber, D.; Dean, J.; Metzger, I.; Parker, A.; Long, N.; Ball, B.; Schott, M.; Weaver, E.; Brackney, L.

    2014-03-01

    OpenStudio is a free, open source Software Development Kit (SDK) and application suite for performing building energy modeling and analysis. The OpenStudio Parametric Analysis Tool has been extended to allow cloud-based simulation of multiple OpenStudio models parametrically related to a baseline model. This paper describes the new cloud-based simulation functionality and presents a model cali-bration case study. Calibration is initiated by entering actual monthly utility bill data into the baseline model. Multiple parameters are then varied over multiple iterations to reduce the difference between actual energy consumption and model simulation results, as calculated and visualized by billing period and by fuel type. Simulations are per-formed in parallel using the Amazon Elastic Cloud service. This paper highlights model parameterizations (measures) used for calibration, but the same multi-nodal computing architecture is available for other purposes, for example, recommending combinations of retrofit energy saving measures using the calibrated model as the new baseline.

  2. A voxel-based multiscale model to simulate the radiation response of hypoxic tumors

    SciTech Connect (OSTI)

    Espinoza, I.; Peschke, P.; Karger, C. P.

    2015-01-15

    Purpose: In radiotherapy, it is important to predict the response of tumors to irradiation prior to the treatment. This is especially important for hypoxic tumors, which are known to be highly radioresistant. Mathematical modeling based on the dose distribution, biological parameters, and medical images may help to improve this prediction and to optimize the treatment plan. Methods: A voxel-based multiscale tumor response model for simulating the radiation response of hypoxic tumors was developed. It considers viable and dead tumor cells, capillary and normal cells, as well as the most relevant biological processes such as (i) proliferation of tumor cells, (ii) hypoxia-induced angiogenesis, (iii) spatial exchange of cells leading to tumor growth, (iv) oxygen-dependent cell survival after irradiation, (v) resorption of dead cells, and (vi) spatial exchange of cells leading to tumor shrinkage. Oxygenation is described on a microscopic scale using a previously published tumor oxygenation model, which calculates the oxygen distribution for each voxel using the vascular fraction as the most important input parameter. To demonstrate the capabilities of the model, the dependence of the oxygen distribution on tumor growth and radiation-induced shrinkage is investigated. In addition, the impact of three different reoxygenation processes is compared and tumor control probability (TCP) curves for a squamous cells carcinoma of the head and neck (HNSSC) are simulated under normoxic and hypoxic conditions. Results: The model describes the spatiotemporal behavior of the tumor on three different scales: (i) on the macroscopic scale, it describes tumor growth and shrinkage during radiation treatment, (ii) on a mesoscopic scale, it provides the cell density and vascular fraction for each voxel, and (iii) on the microscopic scale, the oxygen distribution may be obtained in terms of oxygen histograms. With increasing tumor size, the simulated tumors develop a hypoxic core. Within the

  3. Short-term, econometrically based coal-supply model

    SciTech Connect (OSTI)

    Soyster, A.L.; Enscore, E.E.

    1984-01-01

    A short-term coal supply model is described. The model is econometric in nature and is based on several statistical regressions in which coal prices are regressed against such explanatory variables as productivity, wages and mine size. The basic objective is to relate coal prices with various economic and engineering variables. A whole set of alternative regressions is provided to account for different geographical regions as well as varying coal quality. 3 references, 1 figure, 3 tables.

  4. Midtemperature solar systems test facility predictions for thermal performance based on test data. Toltec two-axis tracking solar collector with 3M acrylic polyester film reflector surface

    SciTech Connect (OSTI)

    Harrison, T.D.

    1981-06-01

    Thermal performance predictions based on test data are presented for the Toltec solar collector, with acrylic film reflector surface, for three output temperatures at five cities in the United States.

  5. Development and Validation of an Advanced Stimulation Prediction Model for Enhanced Geothermal Systems (EGS)

    Broader source: Energy.gov [DOE]

    Project objectives: Develop a true 3D hydro-thermal fracturing and proppant flow/transport simulator that is particularly suited for EGS reservoir creation. Perform laboratory scale model tests of hydraulic fracturing and proppant flow/transport using a polyaxial loading device, and use the laboratory results to test and validate the 3D simulator.

  6. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

    SciTech Connect (OSTI)

    Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Tropsha, Alexander

    2015-04-15

    Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. • Putative

  7. REDUCING UNCERTAINTIES IN MODEL PREDICTIONS VIA HISTORY MATCHING OF CO2 MIGRATION AND REACTIVE TRANSPORT MODELING OF CO2 FATE AT THE SLEIPNER PROJECT

    SciTech Connect (OSTI)

    Zhu, Chen

    2015-03-31

    An important question for the Carbon Capture, Storage, and Utility program is “can we adequately predict the CO2 plume migration?” For tracking CO2 plume development, the Sleipner project in the Norwegian North Sea provides more time-lapse seismic monitoring data than any other sites, but significant uncertainties still exist for some of the reservoir parameters. In Part I, we assessed model uncertainties by applying two multi-phase compositional simulators to the Sleipner Benchmark model for the uppermost layer (Layer 9) of the Utsira Sand and calibrated our model against the time-lapsed seismic monitoring data for the site from 1999 to 2010. Approximate match with the observed plume was achieved by introducing lateral permeability anisotropy, adding CH4 into the CO2 stream, and adjusting the reservoir temperatures. Model-predicted gas saturation, CO2 accumulation thickness, and CO2 solubility in brine—none were used as calibration metrics—were all comparable with the interpretations of the seismic data in the literature. In Part II & III, we evaluated the uncertainties of predicted long-term CO2 fate up to 10,000 years, due to uncertain reaction kinetics. Under four scenarios of the kinetic rate laws, the temporal and spatial evolution of CO2 partitioning into the four trapping mechanisms (hydrodynamic/structural, solubility, residual/capillary, and mineral) was simulated with ToughReact, taking into account the CO2-brine-rock reactions and the multi-phase reactive flow and mass transport. Modeling results show that different rate laws for mineral dissolution and precipitation reactions resulted in different predicted amounts of trapped CO2 by carbonate minerals, with scenarios of the conventional linear rate law for feldspar dissolution having twice as much mineral trapping (21% of the injected CO2) as scenarios with a Burch-type or Alekseyev et al.–type rate law for feldspar dissolution (11%). So far, most reactive transport modeling (RTM) studies for

  8. Predicting reservoir facies distribution using high resolution forward stratigraphic modeling (upper Permian Zechstein 2 carbonate, North Germany)

    SciTech Connect (OSTI)

    Leyrer, K.; Strohmenger, C.; Rockenbauch, K.

    1995-08-01

    To improve the prediction of facies within the Upper Permian Zechstein 2 Carbonate (Ca2), high resolution forward stratigraphic modeling was performed. The results show differences in the sedimentary history of various parts of the Southern Permian Basin, permitting a better prediction of reservoir facies distribution. The Zechstein 2 Carbonate contains North Germany`s largest hydrocarbon accumulation. The reservoir overlies the anhydrites of the first Zechstein cycle (Werra Anhydrite, or A1) and is sealed by the anhydrites of the second Zechstein cycle (Basal Anhydrite, or A2). The Ca2 can be subdivided into platform, upper slope, middle slope, lower slope, and basina1 facies with a total of 26 subfacies types. It comprises the transgressive and highstand systems tract, of the third Zechstein sequence (ZS3) and the lowstand systems tract of the fourth Zechstein sequence (ZS4). Furthermore the Ca2 can be subdivided into seven parasequences indicating high-order fluctuations. Although the Ca2 in both Northwest and Northeast Germany share this geological framework, many differences concerning reservoir distribution exist between the two areas. A general stratigraphic, simulation program (PHIL{sup TM} 1.5) was used for two-dimensional modeling of the Ca2 throughout North Germany. Using well data along with published data and modifying the sedimentation-governing factors, it was possible to simulate the current sequence stratigraphic and facies model. Sedimentation during Ca2-time can be characterized as a highly complex system; thus, only slight variations of the input data result in vastly different facies and stratigraphic patterns. This sensitivity offers the possibility to test depositional models and to estimate the relative influences of the sediment-controlling parameters during Ca2-time in different paleotopographic settings.

  9. Improved atmosphere-ocean coupled modeling in the tropics for climate prediction

    SciTech Connect (OSTI)

    Zhang, Minghua

    2015-01-01

    We investigated the initial development of the double ITCZ in the Community Climate System Model (CCSM Version 3) in the central Pacific. Starting from a resting initial condition of the ocean in January, the model developed a warm bias of sea-surface temperature (SST) in the central Pacific from 5oS to 10oS in the first three months. We found this initial bias to be caused by excessive surface shortwave radiation that is also present in the standalone atmospheric model. The initial bias is further amplified by biases in both surface latent heat flux and horizontal heat transport in the upper ocean. These biases are caused by the responses of surface winds to SST bias and the thermocline structure to surface wind curls. We also showed that the warming biases in surface solar radiation and latent heat fluxes are seasonally offset by cooling biases from reduced solar radiation after the austral summer due to cloud responses and in the austral fall due to enhanced evaporation when the maximum SST is closest to the equator. The warming biases from the dynamic heat transport by ocean currents however stay throughout all seasons once they are developed, which are eventually balanced by enhanced energy exchange and penetration of solar radiation below the mixed layer. Our results also showed that the equatorial cold tongue develops after the warm biases in the south central Pacific, and the overestimation of surface shortwave radiation recurs in the austral summer in each year.

  10. Comparison of high pressure transient PVT measurements and model predictions. Part I.

    SciTech Connect (OSTI)

    Felver, Todd G.; Paradiso, Nicholas Joseph; Evans, Gregory Herbert; Rice, Steven F.; Winters, William Stanley, Jr.

    2010-07-01

    A series of experiments consisting of vessel-to-vessel transfers of pressurized gas using Transient PVT methodology have been conducted to provide a data set for optimizing heat transfer correlations in high pressure flow systems. In rapid expansions such as these, the heat transfer conditions are neither adiabatic nor isothermal. Compressible flow tools exist, such as NETFLOW that can accurately calculate the pressure and other dynamical mechanical properties of such a system as a function of time. However to properly evaluate the mass that has transferred as a function of time these computational tools rely on heat transfer correlations that must be confirmed experimentally. In this work new data sets using helium gas are used to evaluate the accuracy of these correlations for receiver vessel sizes ranging from 0.090 L to 13 L and initial supply pressures ranging from 2 MPa to 40 MPa. The comparisons show that the correlations developed in the 1980s from sparse data sets perform well for the supply vessels but are not accurate for the receivers, particularly at early time during the transfers. This report focuses on the experiments used to obtain high quality data sets that can be used to validate computational models. Part II of this report discusses how these data were used to gain insight into the physics of gas transfer and to improve vessel heat transfer correlations. Network flow modeling and CFD modeling is also discussed.

  11. Equation-based languages – A new paradigm for building energy modeling, simulation and optimization

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Wetter, Michael; Bonvini, Marco; Nouidui, Thierry S.

    2016-04-01

    Most of the state-of-the-art building simulation programs implement models in imperative programming languages. This complicates modeling and excludes the use of certain efficient methods for simulation and optimization. In contrast, equation-based modeling languages declare relations among variables, thereby allowing the use of computer algebra to enable much simpler schematic modeling and to generate efficient code for simulation and optimization. We contrast the two approaches in this paper. We explain how such manipulations support new use cases. In the first of two examples, we couple models of the electrical grid, multiple buildings, HVAC systems and controllers to test a controller thatmore » adjusts building room temperatures and PV inverter reactive power to maintain power quality. In the second example, we contrast the computing time for solving an optimal control problem for a room-level model predictive controller with and without symbolic manipulations. As a result, exploiting the equation-based language led to 2, 200 times faster solution« less

  12. HELIOSPHERIC PROPAGATION OF CORONAL MASS EJECTIONS: COMPARISON OF NUMERICAL WSA-ENLIL+CONE MODEL AND ANALYTICAL DRAG-BASED MODEL

    SciTech Connect (OSTI)

    Vrnak, B.; ic, T.; Dumbovi?, M.; Temmer, M.; Mstl, C.; Veronig, A. M.; Taktakishvili, A.; Mays, M. L.; Odstr?il, D. E-mail: tzic@geof.hr E-mail: manuela.temmer@uni-graz.at E-mail: astrid.veronig@uni-graz.at E-mail: m.leila.mays@nasa.gov

    2014-08-01

    Real-time forecasting of the arrival of coronal mass ejections (CMEs) at Earth, based on remote solar observations, is one of the central issues of space-weather research. In this paper, we compare arrival-time predictions calculated applying the numerical ''WSA-ENLIL+Cone model'' and the analytical ''drag-based model'' (DBM). Both models use coronagraphic observations of CMEs as input data, thus providing an early space-weather forecast two to four days before the arrival of the disturbance at the Earth, depending on the CME speed. It is shown that both methods give very similar results if the drag parameter ? = 0.1 is used in DBM in combination with a background solar-wind speed of w = 400 km s{sup 1}. For this combination, the mean value of the difference between arrival times calculated by ENLIL and DBM is ?-bar =0.099.0 hr with an average of the absolute-value differences of |?|-bar =7.1 hr. Comparing the observed arrivals (O) with the calculated ones (C) for ENLIL gives O C = 0.3 16.9 hr and, analogously, O C = +1.1 19.1 hr for DBM. Applying ? = 0.2 with w = 450 km s{sup 1} in DBM, one finds O C = 1.7 18.3 hr, with an average of the absolute-value differences of 14.8 hr, which is similar to that for ENLIL, 14.1 hr. Finally, we demonstrate that the prediction accuracy significantly degrades with increasing solar activity.

  13. In-situ model analysis of STARS missile flight data and comparison to per-flight predictions from test-reconciled models

    SciTech Connect (OSTI)

    James, G.H.; Carne, T.G.; Marek, E.L.

    1994-08-01

    The Natural Excitation Technique (NExT) was used to analyze STARS launch data during first and second stage flight using telemetered acceleration data. A continuous track of modal frequencies and modal damping was acquired for the first and second elastic modes of the system during first stage flight and for the first mode during second stage flight. Generally, the first mode was predicted to be lower than seen in actual flight. The second mode predictions were very close to those seen in flight. Damping values were found to be within the range estimated by ground testing or slightly less. The results from this modal analysis of launch data allowed a final quantification of the inherent bias errors which resulted from the STARS ground-based modal tests as well as pointing out structures which were in need of further test/analysis correlation.

  14. Product Lifecycle Management Architecture: A Model Based Systems Engineering Analysis.

    SciTech Connect (OSTI)

    Noonan, Nicholas James

    2015-07-01

    This report is an analysis of the Product Lifecycle Management (PLM) program. The analysis is centered on a need statement generated by a Nuclear Weapons (NW) customer. The need statement captured in this report creates an opportunity for the PLM to provide a robust service as a solution. Lifecycles for both the NW and PLM are analyzed using Model Based System Engineering (MBSE).

  15. Predicting Individual Fuel Economy

    SciTech Connect (OSTI)

    Lin, Zhenhong; Greene, David L

    2011-01-01

    To make informed decisions about travel and vehicle purchase, consumers need unbiased and accurate information of the fuel economy they will actually obtain. In the past, the EPA fuel economy estimates based on its 1984 rules have been widely criticized for overestimating on-road fuel economy. In 2008, EPA adopted a new estimation rule. This study compares the usefulness of the EPA's 1984 and 2008 estimates based on their prediction bias and accuracy and attempts to improve the prediction of on-road fuel economies based on consumer and vehicle attributes. We examine the usefulness of the EPA fuel economy estimates using a large sample of self-reported on-road fuel economy data and develop an Individualized Model for more accurately predicting an individual driver's on-road fuel economy based on easily determined vehicle and driver attributes. Accuracy rather than bias appears to have limited the usefulness of the EPA 1984 estimates in predicting on-road MPG. The EPA 2008 estimates appear to be equally inaccurate and substantially more biased relative to the self-reported data. Furthermore, the 2008 estimates exhibit an underestimation bias that increases with increasing fuel economy, suggesting that the new numbers will tend to underestimate the real-world benefits of fuel economy and emissions standards. By including several simple driver and vehicle attributes, the Individualized Model reduces the unexplained variance by over 55% and the standard error by 33% based on an independent test sample. The additional explanatory variables can be easily provided by the individuals.

  16. Computational Tools for Predictive Modeling of Properties in Complex Actinide Systems

    SciTech Connect (OSTI)

    Autschbach, Jochen; Govind, Niranjan; Atta Fynn, Raymond; Bylaska, Eric J.; Weare, John H.; de Jong, Wibe A.

    2015-03-30

    In this chapter we focus on methodological and computational aspects that are key to accurately modeling the spectroscopic and thermodynamic properties of molecular systems containing actinides within the density functional theory (DFT) framework. Our focus is on properties that require either an accurate relativistic all-electron description or an accurate description of the dynamical behavior of actinide species in an environment at finite temperature, or both. The implementation of the methods and the calculations discussed in this chapter were done with the NWChem software suite (Valiev et al. 2010). In the first two sections we discuss two methods that account for relativistic effects, the ZORA and the X2C Hamiltonian. Section 1.2.1 discusses the implementation of the approximate relativistic ZORA Hamiltonian and its extension to magnetic properties. Section 1.3 focuses on the exact X2C Hamiltonian and the application of this methodology to obtain accurate molecular properties. In Section 1.4 we examine the role of a dynamical environment at finite temperature as well as the presence of other ions on the thermodynamics of hydrolysis and exchange reaction mechanisms. Finally, Section 1.5 discusses the modeling of XAS (EXAFS, XANES) properties in realistic environments accounting for both the dynamics of the system and (for XANES) the relativistic effects.

  17. Predictive models of circulating fluidized bed combustors. 12th technical progress report

    SciTech Connect (OSTI)

    Gidaspow, D.

    1992-07-01

    Steady flows influenced by walls cannot be described by inviscid models. Flows in circulating fluidized beds have significant wall effects. Particles in the form of clusters or layers can be seen to run down the walls. Hence modeling of circulating fluidized beds (CFB) without a viscosity is not possible. However, in interpreting Equations (8-1) and (8-2) it must be kept in mind that CFB or most other two phase flows are never in a true steady state. Then the viscosity in Equations (8-1) and (8-2) may not be the true fluid viscosity to be discussed next, but an Eddy type viscosity caused by two phase flow oscillations usually referred to as turbulence. In view of the transient nature of two-phase flow, the drag and the boundary layer thickness may not be proportional to the square root of the intrinsic viscosity but depend upon it to a much smaller extent. As another example, liquid-solid flow and settling of colloidal particles in a lamella electrosettler the settling process is only moderately affected by viscosity. Inviscid flow with settling is a good first approximation to this electric field driven process. The physical meaning of the particulate phase viscosity is described in detail in the chapter on kinetic theory. Here the conventional derivation resented in single phase fluid mechanics is generalized to multiphase flow.

  18. Evaluation Of The Integrated Solubility Model, A Graded Approach For Predicting Phase Distribution In Hanford Tank Waste

    SciTech Connect (OSTI)

    Pierson, Kayla L.; Belsher, Jeremy D.; Seniow, Kendra R.

    2012-10-19

    The mission of the DOE River Protection Project (RPP) is to store, retrieve, treat and dispose of Hanford's tank waste. Waste is retrieved from the underground tanks and delivered to the Waste Treatment and Immobilization Plant (WTP). Waste is processed through a pretreatment facility where it is separated into low activity waste (LAW), which is primarily liquid, and high level waste (HLW), which is primarily solid. The LAW and HLW are sent to two different vitrification facilities and glass canisters are then disposed of onsite (for LAW) or shipped off-site (for HLW). The RPP mission is modeled by the Hanford Tank Waste Operations Simulator (HTWOS), a dynamic flowsheet simulator and mass balance model that is used for mission analysis and strategic planning. The integrated solubility model (ISM) was developed to improve the chemistry basis in HTWOS and better predict the outcome of the RPP mission. The ISM uses a graded approach to focus on the components that have the greatest impact to the mission while building the infrastructure for continued future improvement and expansion. Components in the ISM are grouped depending upon their relative solubility and impact to the RPP mission. The solubility of each group of components is characterized by sub-models of varying levels of complexity, ranging from simplified correlations to a set of Pitzer equations used for the minimization of Gibbs Energy.

  19. A Physically Based Runoff Routing Model for Land Surface and Earth System Models

    SciTech Connect (OSTI)

    Li, Hongyi; Wigmosta, Mark S.; Wu, Huan; Huang, Maoyi; Ke, Yinghai; Coleman, Andre M.; Leung, Lai-Yung R.

    2013-06-13

    A new physically based runoff routing model, called the Model for Scale Adaptive River Transport (MOSART), has been developed to be applicable across local, regional, and global scales. Within each spatial unit, surface runoff is first routed across hillslopes and then discharged along with subsurface runoff into a tributary subnetwork before entering the main channel. The spatial units are thus linked via routing through the main channel network, which is constructed in a scale-consistent way across different spatial resolutions. All model parameters are physically based, and only a small subset requires calibration.MOSART has been applied to the Columbia River basin at 1/ 168, 1/ 88, 1/ 48, and 1/ 28 spatial resolutions and was evaluated using naturalized or observed streamflow at a number of gauge stations. MOSART is compared to two other routing models widely used with land surface models, the River Transport Model (RTM) in the Community Land Model (CLM) and the Lohmann routing model, included as a postprocessor in the Variable Infiltration Capacity (VIC) model package, yielding consistent performance at multiple resolutions. MOSART is further evaluated using the channel velocities derived from field measurements or a hydraulic model at various locations and is shown to be capable of producing the seasonal variation and magnitude of channel velocities reasonably well at different resolutions. Moreover, the impacts of spatial resolution on model simulations are systematically examined at local and regional scales. Finally, the limitations ofMOSART and future directions for improvements are discussed.

  20. Feasibility of High-Power Diode Laser Array Surrogate to Support Development of Predictive Laser Lethality Model

    SciTech Connect (OSTI)

    Lowdermilk, W H; Rubenchik, A M; Springer, H K

    2011-01-13

    Predictive modeling and simulation of high power laser-target interactions is sufficiently undeveloped that full-scale, field testing is required to assess lethality of military directed-energy (DE) systems. The cost and complexity of such testing programs severely limit the ability to vary and optimize parameters of the interaction. Thus development of advanced simulation tools, validated by experiments under well-controlled and diagnosed laboratory conditions that are able to provide detailed physics insight into the laser-target interaction and reduce requirements for full-scale testing will accelerate development of DE weapon systems. The ultimate goal is a comprehensive end-to-end simulation capability, from targeting and firing the laser system through laser-target interaction and dispersal of target debris; a 'Stockpile Science' - like capability for DE weapon systems. To support development of advanced modeling and simulation tools requires laboratory experiments to generate laser-target interaction data. Until now, to make relevant measurements required construction and operation of very high power and complex lasers, which are themselves costly and often unique devices, operating in dedicated facilities that don't permit experiments on targets containing energetic materials. High power diode laser arrays, pioneered by LLNL, provide a way to circumvent this limitation, as such arrays capable of delivering irradiances characteristic of De weapon requires are self-contained, compact, light weight and thus easily transportable to facilities, such as the High Explosives Applications Facility (HEAF) at Lawrence Livermore National Laboratory (LLNL) where testing with energetic materials can be performed. The purpose of this study was to establish the feasibility of using such arrays to support future development of advanced laser lethality and vulnerability simulation codes through providing data for materials characterization and laser-material interaction

  1. An integrated model supporting histological and biometric responses as predictive biomarkers of fish health status

    SciTech Connect (OSTI)

    Torres Junior, Audalio Rebelo; Sousa, Débora Batista Pinheiro; Neta, Raimunda Nonata Fortes Carvalho

    2014-10-06

    In this work, an experimental system of histological (branchial lesions) biomarkers and biometric data in catfish (Sciades herzbergii) was modeled. The fish were sampled along known pollution areas (S1) and from environmental protect areas (S2) in São Marcos' Bay, Brazil. Gills were fixed in 10% formalin and usual histological techniques were used in the first gill arch right. The lesions were observed by light microscopy. There were no histopathological changes in animals captured at reference site (S1). However, in the catfish collected in the potentially contaminated area (S2) was observed several branchial lesions, such as lifting of the lamellar epithelium, fusion of some secondary lamellae, hypertrophy of epithelial cells and lamellar aneurysm. The analysis using the biometric data showed significant differences, being highest in fish analyzed in the reference area. This approach revealed spatial differences related with biometric patterns and morphological modifications of catfish.

  2. Nuclear Shell Model Analyses and Predictions of Double-Beta Decay Observables

    SciTech Connect (OSTI)

    Horoi, Mihai [Department of Physics, Central Michigan University, Mount Pleasant, Michigan, 48859 (United States)

    2010-11-24

    Recent results from neutrino oscillation experiments have convincingly demonstrated that neutrinos have mass and they can mix. The neutrinoless double beta decay is the most sensitive process to determine the absolute scale of the neutrino masses, and the only one that can distinguish whether neutrino is a Dirac or a Majorana particle. A key ingredient for extracting the absolute neutrino masses from neutrinoless double beta decay experiments is a precise knowledge of the nuclear matrix elements (NME) for this process. Newly developed shell model approaches for computing the NME and half-lifes for the two-neutrino and neutrinoless double beta decay modes using modern effective interactions are presented. The implications of the new results on the experimental limits of the effective neutrino mass are discussed by comparing the decays of {sup 48}Ca and {sup 76}Ge.

  3. Life Prediction and Classification of Failure Modes in Solid State Luminaires Using Bayesian Probabilistic Models

    SciTech Connect (OSTI)

    Lall, Pradeep; Wei, Junchao; Sakalaukus, Peter

    2014-05-27

    A new method has been developed for assessment of the onset of degradation in solid state luminaires to classify failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identify luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. It is expected that, the new test technique will allow the development of failure distributions without testing till L70 life for the manifestation of failure.

  4. Bayesian Models for Life Prediction and Fault-Mode Classification in Solid State Lamps

    SciTech Connect (OSTI)

    Lall, Pradeep; Wei, Junchao; Sakalaukus, Peter

    2015-04-19

    A new method has been developed for assessment of the onset of degradation in solid state luminaires to classifY failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identifY luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. It is expected that, the new test technique will allow the development of failure distributions without testing till L 70 life for the manifestation of failure.

  5. Predictive modeling of CO{sub 2} sequestration in deep saline sandstone reservoirs: Impacts of geochemical kinetics

    SciTech Connect (OSTI)

    Balashov, Victor N.; Guthrie, George D.; Hakala, J. Alexandra; Lopano, Christina L. J.; Rimstidt, Donald; Brantley, Susan L.

    2013-03-01

    One idea for mitigating the increase in fossil-fuel generated CO{sub 2} in the atmosphere is to inject CO{sub 2} into subsurface saline sandstone reservoirs. To decide whether to try such sequestration at a globally significant scale will require the ability to predict the fate of injected CO{sub 2}. Thus, models are needed to predict the rates and extents of subsurface rock-water-gas interactions. Several reactive transport models for CO{sub 2} sequestration created in the last decade predicted sequestration in sandstone reservoirs of ~17 to ~90 kg CO{sub 2} m{sup -3|. To build confidence in such models, a baseline problem including rock + water chemistry is proposed as the basis for future modeling so that both the models and the parameterizations can be compared systematically. In addition, a reactive diffusion model is used to investigate the fate of injected supercritical CO{sub 2} fluid in the proposed baseline reservoir + brine system. In the baseline problem, injected CO{sub 2} is redistributed from the supercritical (SC) free phase by dissolution into pore brine and by formation of carbonates in the sandstone. The numerical transport model incorporates a full kinetic description of mineral-water reactions under the assumption that transport is by diffusion only. Sensitivity tests were also run to understand which mineral kinetics reactions are important for CO{sub 2} trapping. The diffusion transport model shows that for the first ~20 years after CO{sub 2} diffusion initiates, CO{sub 2} is mostly consumed by dissolution into the brine to form CO{sub 2,aq} (solubility trapping). From 20-200 years, both solubility and mineral trapping are important as calcite precipitation is driven by dissolution of oligoclase. From 200 to 1000 years, mineral trapping is the most important sequestration mechanism, as smectite dissolves and calcite precipitates. Beyond 2000 years, most trapping is due to formation of aqueous HCO{sub 3}{sup -}. Ninety-seven percent of the

  6. Spatial process and data models : toward integration of agent-based models and GIS.

    SciTech Connect (OSTI)

    Brown, D. G.; North, M. J.; Robinson, D. T.; Riolo, R.; Rand, W.; Decision and Information Sciences; Univ. of Michigan

    2007-10-01

    The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, we identify four key relationships affecting how geographic data (fields and objects) and agent-based process models can interact: identity, causal, temporal and topological. We discuss approaches to implementing tight integration, focusing on a middleware approach that links existing GIS and ABM development platforms, and illustrate the need and approaches with example agent-based models.

  7. Model-based performance monitoring: Review of diagnostic methods and chiller case study

    SciTech Connect (OSTI)

    Haves, Phil; Khalsa, Sat Kartar

    2000-05-01

    The paper commences by reviewing the variety of technical approaches to the problem of detecting and diagnosing faulty operation in order to improve the actual performance of buildings. The review covers manual and automated methods, active testing and passive monitoring, the different classes of models used in fault detection, and methods of diagnosis. The process of model-based fault detection is then illustrated by describing the use of relatively simple empirical models of chiller energy performance to monitor equipment degradation and control problems. The CoolTools(trademark) chiller model identification package is used to fit the DOE-2 chiller model to on-site measurements from a building instrumented with high quality sensors. The need for simple algorithms to reject transient data, detect power surges and identify control problems is discussed, as is the use of energy balance checks to detect sensor problems. The accuracy with which the chiller model can be expected! to predict performance is assessed from the goodness of fit obtained and the implications for fault detection sensitivity and sensor accuracy requirements are discussed. A case study is described in which the model was applied retroactively to high-quality data collected in a San Francisco office building as part of a related project (Piette et al. 1999).

  8. Predicting tropospheric ozone and hydroxyl radical in a global, three-dimensional, chemistry, transport, and deposition model

    SciTech Connect (OSTI)

    Atherton, C.S.

    1995-01-05

    Two of the most important chemically reactive tropospheric gases are ozone (O{sub 3}) and the hydroxyl radical (OH). Although ozone in the stratosphere is a necessary protector against the sun`s radiation, tropospheric ozone is actually a pollutant which damages materials and vegetation, acts as a respiratory irritant, and is a greenhouse gas. One of the two main sources of ozone in the troposphere is photochemical production. The photochemistry is initiated when hydrocarbons and carbon monoxide (CO) react with nitrogen oxides (NO{sub x} = NO + NO{sub 2}) in the presence of sunlight. Reaction with the hydroxyl radical, OH, is the main sink for many tropospheric gases. The hydroxyl radical is highly reactive and has a lifetime on the order of seconds. Its formation is initiated by the photolysis of tropospheric ozone. Tropospheric chemistry involves a complex, non-linear set of chemical reactions between atmospheric species that vary substantially in time and space. To model these and other species on a global scale requires the use of a global, three-dimensional chemistry, transport, and deposition (CTD) model. In this work, I developed two such three dimensional CTD models. The first model incorporated the chemistry necessary to model tropospheric ozone production from the reactions of nitrogen oxides with carbon monoxide (CO) and methane (CH{sub 4}). The second also included longer-lived alkane species and the biogenic hydrocarbon isoprene, which is emitted by growing plants and trees. The models` ability to predict a number of key variables (including the concentration of O{sub 3}, OH, and other species) were evaluated. Then, several scenarios were simulated to understand the change in the chemistry of the troposphere since preindustrial times and the role of anthropogenic NO{sub x} on present day conditions.

  9. Predicting for thermodynamic instabilities in water/oil/surfactant microemulsions: A mesoscopic modelling approach

    SciTech Connect (OSTI)

    Duvail, Magali Zemb, Thomas; Dufrêche, Jean-François; Arleth, Lise

    2014-04-28

    The thermodynamics and structural properties of flexible and rigid nonionic water/oil/surfactant microemulsions have been investigated using a two level-cut Gaussian random field method based on the Helfrich formalism. Ternary stability diagrams and scattering spectra have been calculated for different surfactant rigidities and spontaneous curvatures. A more important contribution of the Gaussian elastic constants compared to the bending one is observed on the ternary stability diagrams. Furthermore, influence of the spontaneous curvature of the surfactant points out a displacement of the instability domains which corresponds to the difference between the spontaneous and effective curvatures. We enlighten that a continuous transition from a connected water in oil droplets to a frustrated locally lamellar (oil in water in oil droplets) microstructure is found to occur when increasing the temperature for an oil-rich microemulsion. This continuous transition translated in a shift in the scattering functions, points out that the phase inversion phenomenon occurs by a coalescence of the water droplets.

  10. BRANCH-BASED MODEL FOR THE DIAMETERS OF THE PULMONARY AIRWAYS...

    Office of Scientific and Technical Information (OSTI)

    BRANCH-BASED MODEL FOR THE DIAMETERS OF THE PULMONARY AIRWAYS: ACCOUNTING FOR DEPARTURES ... Title: BRANCH-BASED MODEL FOR THE DIAMETERS OF THE PULMONARY AIRWAYS: ACCOUNTING FOR ...

  11. Energy-efficient housing alternatives: a predictive model of factors affecting household perceptions

    SciTech Connect (OSTI)

    Schreckengost, R.L.

    1985-01-01

    The major purpose of this investigation was to assess the impact of household socio-economic factors, dwelling characteristics, energy conservation behavior, and energy attitudes on the perceptions of energy-efficient housing alternatives. Perceptions of passive solar, active solar, earth sheltered, and retrofitted housing were examined. Data used were from the Southern Regional Research Project, S-141, Housing for Low and Moderate Income Families. Responses from 1804 households living in seven southern states were analyzed. A conceptual model was proposed to test the hypothesized relationships which were examined by path analysis. Perceptions of energy efficient housing alternatives were found to be a function of selected household and dwelling characteristics, energy attitude, household economic factors, and household conservation behavior. Age and education of the respondent, family size, housing-income ratio, utility income ratio, energy attitude, and size of the dwelling unit were found to have direct and indirect effects on perceptions of energy-efficient housing alternatives. Energy conservation behavior made a significant direct impact with behavioral energy conservation changes having the most profound influence. Conservation behavior was influenced by selected household and dwelling characteristics, energy attitude, and household economic factors.

  12. Physiologically-based pharmacokinetic model for Fentanyl in support of the development of Provisional Advisory Levels

    SciTech Connect (OSTI)

    Shankaran, Harish; Adeshina, Femi; Teeguarden, Justin G.

    2013-12-15

    Provisional Advisory Levels (PALs) are tiered exposure limits for toxic chemicals in air and drinking water that are developed to assist in emergency responses. Physiologically-based pharmacokinetic (PBPK) modeling can support this process by enabling extrapolations across doses, and exposure routes, thereby addressing gaps in the available toxicity data. Here, we describe the development of a PBPK model for Fentanyl – a synthetic opioid used clinically for pain management – to support the establishment of PALs. Starting from an existing model for intravenous Fentanyl, we first optimized distribution and clearance parameters using several additional IV datasets. We then calibrated the model using pharmacokinetic data for various formulations, and determined the absorbed fraction, F, and time taken for the absorbed amount to reach 90% of its final value, t90. For aerosolized pulmonary Fentanyl, F = 1 and t90 < 1 min indicating complete and rapid absorption. The F value ranged from 0.35 to 0.74 for oral and various transmucosal routes. Oral Fentanyl was absorbed the slowest (t90 ∼ 300 min); the absorption of intranasal Fentanyl was relatively rapid (t90 ∼ 20–40 min); and the various oral transmucosal routes had intermediate absorption rates (t90 ∼ 160–300 min). Based on these results, for inhalation exposures, we assumed that all of the Fentanyl inhaled from the air during each breath directly, and instantaneously enters the arterial circulation. We present model predictions of Fentanyl blood concentrations in oral and inhalation scenarios relevant for PAL development, and provide an analytical expression that can be used to extrapolate between oral and inhalation routes for the derivation of PALs. - Highlights: • We develop a Fentanyl PBPK model for relating external dose to internal levels. • We calibrate the model to oral and inhalation exposures using > 50 human datasets. • Model predictions are in good agreement with the available

  13. Validation of the thermal transport model used for ITER startup scenario predictions with DIII-D experimental data

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Casper, T. A.; Meyer, W. H.; Jackson, G. L.; Luce, T. C.; Hyatt, A. W.; Humphreys, D. A.; Turco, F.

    2010-12-08

    We are exploring characteristics of ITER startup scenarios in similarity experiments conducted on the DIII-D Tokamak. In these experiments, we have validated scenarios for the ITER current ramp up to full current and developed methods to control the plasma parameters to achieve stability. Predictive simulations of ITER startup using 2D free-boundary equilibrium and 1D transport codes rely on accurate estimates of the electron and ion temperature profiles that determine the electrical conductivity and pressure profiles during the current rise. Here we present results of validation studies that apply the transport model used by the ITER team to DIII-D discharge evolutionmore » and comparisons with data from our similarity experiments.« less

  14. Ammonia concentration modeling based on retained gas sampler data

    SciTech Connect (OSTI)

    Terrones, G.; Palmer, B.J.; Cuta, J.M.

    1997-09-01

    The vertical ammonia concentration distributions determined by the retained gas sampler (RGS) apparatus were modeled for double-shell tanks (DSTs) AW-101, AN-103, AN-104, and AN-105 and single-shell tanks (SSTs) A-101, S-106, and U-103. One the vertical transport of ammonia in the tanks were used for the modeling. Transport in the non-convective settled solids and floating solids layers is assumed to occur primarily via some type of diffusion process, while transport in the convective liquid layers is incorporated into the model via mass transfer coefficients based on empirical correlations. Mass transfer between the top of the waste and the tank headspace and the effects of ventilation of the headspace are also included in the models. The resulting models contain a large number of parameters, but many of them can be determined from known properties of the waste configuration or can be estimated within reasonable bounds from data on the waste samples themselves. The models are used to extract effective diffusion coefficients for transport in the nonconvective layers based on the measured values of ammonia from the RGS apparatus. The modeling indicates that the higher concentrations of ammonia seen in bubbles trapped inside the waste relative to the ammonia concentrations in the tank headspace can be explained by a combination of slow transport of ammonia via diffusion in the nonconvective layers and ventilation of the tank headspace by either passive or active means. Slow transport by diffusion causes a higher concentration of ammonia to build up deep within the waste until the concentration gradients between the interior and top of the waste are sufficient to allow ammonia to escape at the same rate at which it is being generated in the waste.

  15. Likelihood-based gene annotations for gap filling and quality assessment in genome-scale metabolic models

    SciTech Connect (OSTI)

    Benedict, Matthew N.; Mundy, Michael B.; Henry, Christopher S.; Chia, Nicholas; Price, Nathan D.; Maranas, Costas D.

    2014-10-16

    Genome-scale metabolic models provide a powerful means to harness information from genomes to deepen biological insights. With exponentially increasing sequencing capacity, there is an enormous need for automated reconstruction techniques that can provide more accurate models in a short time frame. Current methods for automated metabolic network reconstruction rely on gene and reaction annotations to build draft metabolic networks and algorithms to fill gaps in these networks. However, automated reconstruction is hampered by database inconsistencies, incorrect annotations, and gap filling largely without considering genomic information. Here we develop an approach for applying genomic information to predict alternative functions for genes and estimate their likelihoods from sequence homology. We show that computed likelihood values were significantly higher for annotations found in manually curated metabolic networks than those that were not. We then apply these alternative functional predictions to estimate reaction likelihoods, which are used in a new gap filling approach called likelihood-based gap filling to predict more genomically consistent solutions. To validate the likelihood-based gap filling approach, we applied it to models where essential pathways were removed, finding that likelihood-based gap filling identified more biologically relevant solutions than parsimony-based gap filling approaches. We also demonstrate that models gap filled using likelihood-based gap filling provide greater coverage and genomic consistency with metabolic gene functions compared to parsimony-based approaches. Interestingly, despite these findings, we found that likelihoods did not significantly affect consistency of gap filled models with Biolog and knockout lethality data. This indicates that the phenotype data alone cannot necessarily be used to discriminate between alternative solutions for gap filling and therefore, that the use of other information is necessary to

  16. Likelihood-based gene annotations for gap filling and quality assessment in genome-scale metabolic models

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Benedict, Matthew N.; Mundy, Michael B.; Henry, Christopher S.; Chia, Nicholas; Price, Nathan D.; Maranas, Costas D.

    2014-10-16

    Genome-scale metabolic models provide a powerful means to harness information from genomes to deepen biological insights. With exponentially increasing sequencing capacity, there is an enormous need for automated reconstruction techniques that can provide more accurate models in a short time frame. Current methods for automated metabolic network reconstruction rely on gene and reaction annotations to build draft metabolic networks and algorithms to fill gaps in these networks. However, automated reconstruction is hampered by database inconsistencies, incorrect annotations, and gap filling largely without considering genomic information. Here we develop an approach for applying genomic information to predict alternative functions for genesmore » and estimate their likelihoods from sequence homology. We show that computed likelihood values were significantly higher for annotations found in manually curated metabolic networks than those that were not. We then apply these alternative functional predictions to estimate reaction likelihoods, which are used in a new gap filling approach called likelihood-based gap filling to predict more genomically consistent solutions. To validate the likelihood-based gap filling approach, we applied it to models where essential pathways were removed, finding that likelihood-based gap filling identified more biologically relevant solutions than parsimony-based gap filling approaches. We also demonstrate that models gap filled using likelihood-based gap filling provide greater coverage and genomic consistency with metabolic gene functions compared to parsimony-based approaches. Interestingly, despite these findings, we found that likelihoods did not significantly affect consistency of gap filled models with Biolog and knockout lethality data. This indicates that the phenotype data alone cannot necessarily be used to discriminate between alternative solutions for gap filling and therefore, that the use of other information is necessary

  17. Application of a fuzzy neural network model in predicting polycyclic aromatic hydrocarbon-mediated perturbations of the Cyp1b1 transcriptional regulatory network in mouse skin

    SciTech Connect (OSTI)

    Larkin, Andrew; Siddens, Lisbeth K.; Krueger, Sharon K.; Tilton, Susan C.; Waters, Katrina M.; Williams, David E.; Baird, William M.

    2013-03-01

    Polycyclic aromatic hydrocarbons (PAHs) are present in the environment as complex mixtures with components that have diverse carcinogenic potencies and mostly unknown interactive effects. Non-additive PAH interactions have been observed in regulation of cytochrome P450 (CYP) gene expression in the CYP1 family. To better understand and predict biological effects of complex mixtures, such as environmental PAHs, an 11 gene input-1 gene output fuzzy neural network (FNN) was developed for predicting PAH-mediated perturbations of dermal Cyp1b1 transcription in mice. Input values were generalized using fuzzy logic into low, medium, and high fuzzy subsets, and sorted using k-means clustering to create Mamdani logic functions for predicting Cyp1b1 mRNA expression. Model testing was performed with data from microarray analysis of skin samples from FVB/N mice treated with toluene (vehicle control), dibenzo[def,p]chrysene (DBC), benzo[a]pyrene (BaP), or 1 of 3 combinations of diesel particulate extract (DPE), coal tar extract (CTE) and cigarette smoke condensate (CSC) using leave-one-out cross-validation. Predictions were within 1 log{sub 2} fold change unit of microarray data, with the exception of the DBC treatment group, where the unexpected down-regulation of Cyp1b1 expression was predicted but did not reach statistical significance on the microarrays. Adding CTE to DPE was predicted to increase Cyp1b1 expression, whereas adding CSC to CTE and DPE was predicted to have no effect, in agreement with microarray results. The aryl hydrocarbon receptor repressor (Ahrr) was determined to be the most significant input variable for model predictions using back-propagation and normalization of FNN weights. - Highlights: ? Tested a model to predict PAH mixture-mediated changes in Cyp1b1 expression ? Quantitative predictions in agreement with microarrays for Cyp1b1 induction ? Unexpected difference in expression between DBC and other treatments predicted ? Model predictions for

  18. Ecological Impacts of the Cerro Grande Fire: Predicting Elk Movement and Distribution Patterns in Response to Vegetative Recovery through Simulation Modeling October 2005

    SciTech Connect (OSTI)

    S.P. Rupp

    2005-10-01

    SAVANNA included a land cover map, long-term weather data, soil maps, and a digital elevation model. Parameterization and calibration were conducted using field plots. Model predictions of herbaceous biomass production and weather were consistent with available data and spatial interpolations of snow were considered reasonable for this study. Dynamic outputs generated by SAVANNA were integrated with static variables, movement rules, and parameters developed for the individual-based model through the application of a habitat suitability index. Model validation indicated reasonable model fit when compared to an independent test set. The finished model was applied to 2 realistic management scenarios for the Jemez Mountains and management implications were discussed. Ongoing validation of the individual-based model presented in this dissertation provides an adaptive management tool that integrates interdisciplinary experience and scientific information, which allows users to make predictions about the impact of alternative management policies.

  19. THERMODYNAMIC MODEL FOR URANIUM DIOXIDE BASED NUCLEAR FUEL

    SciTech Connect (OSTI)

    Thompson, Dr. William T.; Lewis, Dr. Brian J; Corcoran, E. C.; Kaye, Dr. Matthew H.; White, S. J.; Akbari, F.; Higgs, Jamie D.; Thompson, D. M.; Besmann, Theodore M; Vogel, S. C.

    2007-01-01

    Many projects involving nuclear fuel rest on a quantitative understanding of the co-existing phases at various stages of burnup. Since the many fission products have considerably different abilities to chemically associate with oxygen, and the oxygen-to-metal molar ratio is slowly changing, the chemical potential of oxygen is a function of burnup. Concurrently, well-recognized small fractions of new phases such as inert gas, noble metals, zirconates, etc. also develop. To further complicate matters, the dominant UO2 fuel phase may be non-stoichiometric and most of the minor phases themselves have a variable composition dependent on temperature and possible contact with the coolant in the event of a sheathing breach. A thermodynamic fuel model to predict the phases in partially burned CANDU (CANada Deuterium Uranium) nuclear fuel containing many major fission products has been under development. The building blocks of the model are the standard Gibbs energies of formation of the many possible compounds expressed as a function of temperature. To these data are added mixing terms associated with the appearance of the component species in particular phases. In operational terms, the treatment rests on the ability to minimize the Gibbs energy in a multicomponent system, in our case using the algorithms developed by Eriksson. The model is capable of handling non-stoichiometry in the UO2 fluorite phase, dilute solution behaviour of significant solute oxides, noble metal inclusions, a second metal solid solution U(Pd-Rh-Ru)3, zirconate, molybdate, and uranate solutions as well as other minor solid phases, and volatile gaseous species.

  20. A Habitat-based Wind-Wildlife Collision Model with Application to the Upper Great Plains Region

    SciTech Connect (OSTI)

    Forcey, Greg, M.

    2012-08-28

    compared among species, our model outputs provide a convenient and easy landscape-level tool to quickly screen for siting issues at a high level. The model resolution is suitable for state or multi-county siting but users are cautioned against using these models for micrositing. The U.S. Fish and Wildlife Service recently released voluntary land-based wind energy guidelines for assessing impacts of a wind facility to wildlife using a tiered approach. The tiered approach uses an iterative approach for assessing impacts to wildlife in levels of increasing detail from landscape-level screening to site-specific field studies. Our models presented in this paper would be applicable to be used as tools to conduct screening at the tier 1 level and would not be appropriate to complete smaller scale tier 2 and tier 3 level studies. For smaller scale screening ancillary field studies should be conducted at the site-specific level to validate collision predictions.

  1. Formulation of an experimental substructure model using a Craig-Bampton based transmission simulator

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Kammer, Daniel C.; Allen, Matthew S.; Mayes, Randall L.

    2015-09-26

    An experimental–analytical substructuring is attractive when there is motivation to replace one or more system subcomponents with an experimental model. This experimentally derived substructure can then be coupled to finite element models of the rest of the structure to predict the system response. The transmission simulator method couples a fixture to the component of interest during a vibration test in order to improve the experimental model for the component. The transmission simulator is then subtracted from the tested system to produce the experimental component. This method reduces ill-conditioning by imposing a least squares fit of constraints between substructure modal coordinatesmore » to connect substructures, instead of directly connecting physical interface degrees of freedom. This paper presents an alternative means of deriving the experimental substructure model, in which a Craig–Bampton representation of the transmission simulator is created and subtracted from the experimental measurements. The corresponding modal basis of the transmission simulator is described by the fixed-interface modes, rather than free modes that were used in the original approach. Moreover, these modes do a better job of representing the shape of the transmission simulator as it responds within the experimental system, leading to more accurate results using fewer modes. The new approach is demonstrated using a simple finite element model based example with a redundant interface.« less

  2. A multiscale MDCT image-based breathing lung model with time-varying regional ventilation

    SciTech Connect (OSTI)

    Yin, Youbing, E-mail: youbing-yin@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States) [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Choi, Jiwoong, E-mail: jiwoong-choi@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States) [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Hoffman, Eric A., E-mail: eric-hoffman@uiowa.edu [Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Department of Biomedical Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Internal Medicine, The University of Iowa, Iowa City, IA 52242 (United States); Tawhai, Merryn H., E-mail: m.tawhai@auckland.ac.nz [Auckland Bioengineering Institute, The University of Auckland, Auckland (New Zealand); Lin, Ching-Long, E-mail: ching-long-lin@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States) [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States)

    2013-07-01

    A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C{sub 1} continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.

  3. Structure Based Drug Design for HIM Protease: From Molecular Modeling to Cheminformatics

    SciTech Connect (OSTI)

    Volarath, Patra; Weber, Irene T.; Harrison, Robert W.

    2008-06-06

    Significant progress over the past decade in virtual representations of molecules and their physicochemical properties has produced new drugs from virtual screening of the structures of single protein molecules by conventional modeling methods. The development of clinical antiviral drugs from structural data for HIV protease has been a major success in structure based drug design. Techniques for virtual screening involve the ranking of the affinity of potential ligands for the target site on a protein. Two main alternatives have been developed: modeling of the target protein with a series of related ligand molecules, and docking molecules from a database to the target protein site. The computational speed and prediction accuracy will depend on the representation of the molecular structure and chemistry, the search or simulation algorithm, and the scoring function to rank the ligands. Moreover, the general challenges in modern computational drug design arise from the profusion of data, including whole genomes of DNA, protein structures, chemical libraries, affinity and pharmacological data. Therefore, software tools are being developed to manage and integrate diverse data, and extract and visualize meaningful relationships. Current areas of research include the development of searchable chemical databases, which requires new algorithms to represent molecules and search for structurally or chemically similar molecules, and the incorporation of machine learning techniques for data mining to improve the accuracy of predictions. Examples will be presented for the virtual screening of drugs that target HIV protease.

  4. Predictivity of dog co-culture model, primary human hepatocytes and HepG2 cells for the detection of hepatotoxic drugs in humans

    SciTech Connect (OSTI)

    Atienzar, Franck A.; Novik, Eric I.; Gerets, Helga H.; Parekh, Amit; Delatour, Claude; Cardenas, Alvaro; MacDonald, James; Yarmush, Martin L.; Dhalluin, Stphane

    2014-02-15

    Drug Induced Liver Injury (DILI) is a major cause of attrition during early and late stage drug development. Consequently, there is a need to develop better in vitro primary hepatocyte models from different species for predicting hepatotoxicity in both animals and humans early in drug development. Dog is often chosen as the non-rodent species for toxicology studies. Unfortunately, dog in vitro models allowing long term cultures are not available. The objective of the present manuscript is to describe the development of a co-culture dog model for predicting hepatotoxic drugs in humans and to compare the predictivity of the canine model along with primary human hepatocytes and HepG2 cells. After rigorous optimization, the dog co-culture model displayed metabolic capacities that were maintained up to 2 weeks which indicates that such model could be also used for long term metabolism studies. Most of the human hepatotoxic drugs were detected with a sensitivity of approximately 80% (n = 40) for the three cellular models. Nevertheless, the specificity was low approximately 40% for the HepG2 cells and hepatocytes compared to 72.7% for the canine model (n = 11). Furthermore, the dog co-culture model showed a higher superiority for the classification of 5 pairs of close structural analogs with different DILI concerns in comparison to both human cellular models. Finally, the reproducibility of the canine system was also satisfactory with a coefficient of correlation of 75.2% (n = 14). Overall, the present manuscript indicates that the dog co-culture model may represent a relevant tool to perform chronic hepatotoxicity and metabolism studies. - Highlights: Importance of species differences in drug development. Relevance of dog co-culture model for metabolism and toxicology studies. Hepatotoxicity: higher predictivity of dog co-culture vs HepG2 and human hepatocytes.

  5. Midtemperature solar systems test facility predictions for thermal performance based on test data: Sun-Heet nontracking solar collector

    SciTech Connect (OSTI)

    Harrison, T.D.

    1981-03-01

    Sandia National Laboratories, Albuquerque (SNLA), is currently conducting a program to predict the performance and measure the characteristics of commercially available solar collectors that have the potential for use in industrial process heat and enhanced oil recovery applications. The thermal performance predictions for the Sun-Heet nontracking, line-focusing parabolic trough collector at five cities in the US are presented. (WHK)

  6. REVIEW OF EXPERIMENTAL CAPABILITIES AND HYDRODYNAMIC DATA FOR VALIDATION OF CFD-BASED PREDICTIONS FOR SLURRY BUBBLE COLUMN REACTORS

    SciTech Connect (OSTI)

    Donna Post Guillen; Daniel S. Wendt; Steven P. Antal; Michael Z. Podowski

    2007-11-01

    The purpose of this paper is to document the review of several open-literature sources of both experimental capabilities and published hydrodynamic data to aid in the validation of a Computational Fluid Dynamics (CFD) based model of a slurry bubble column (SBC). The review included searching the Web of Science, ISI Proceedings, and Inspec databases, internet searches as well as other open literature sources. The goal of this study was to identify available experimental facilities and relevant data. Integral (i.e., pertaining to the SBC system), as well as fundamental (i.e., separate effects are considered), data are included in the scope of this effort. The fundamental data is needed to validate the individual mechanistic models or closure laws used in a Computational Multiphase Fluid Dynamics (CMFD) simulation of a SBC. The fundamental data is generally focused on simple geometries (i.e., flow between parallel plates or cylindrical pipes) or custom-designed tests to focus on selected interfacial phenomena. Integral data covers the operation of a SBC as a system with coupled effects. This work highlights selected experimental capabilities and data for the purpose of SBC model validation, and is not meant to be an exhaustive summary.

  7. REVIEW OF EXPERIMENTAL CAPABILITIES AND HYDRODYNAMIC DATA FOR VALIDATION OF CFD BASED PREDICTIONS FOR SLURRY BUBBLE COLUMN REACTORS

    SciTech Connect (OSTI)

    Donna Post Guillen; Daniel S. Wendt

    2007-11-01

    The purpose of this paper is to document the review of several open-literature sources of both experimental capabilities and published hydrodynamic data to aid in the validation of a Computational Fluid Dynamics (CFD) based model of a slurry bubble column (SBC). The review included searching the Web of Science, ISI Proceedings, and Inspec databases, internet searches as well as other open literature sources. The goal of this study was to identify available experimental facilities and relevant data. Integral (i.e., pertaining to the SBC system), as well as fundamental (i.e., separate effects are considered), data are included in the scope of this effort. The fundamental data is needed to validate the individual mechanistic models or closure laws used in a Computational Multiphase Fluid Dynamics (CMFD) simulation of a SBC. The fundamental data is generally focused on simple geometries (i.e., flow between parallel plates or cylindrical pipes) or custom-designed tests to focus on selected interfacial phenomena. Integral data covers the operation of a SBC as a system with coupled effects. This work highlights selected experimental capabilities and data for the purpose of SBC model validation, and is not meant to be an exhaustive summary.

  8. Chiller condition monitoring using topological case-based modeling

    SciTech Connect (OSTI)

    Tsutsui, Hiroaki; Kamimura, Kazuyuki

    1996-11-01

    To increase energy efficiency and economy, commercial building projects now often utilize centralized, shared sources of heat such as district heating and cooling (DHC) systems. To maintain efficiency, precise monitoring and scheduling of maintenance for chillers and heat pumps is essential. Low-performance operation results in energy loss, while unnecessary maintenance is expensive and wasteful. Plant supervisors are responsible for scheduling and supervising maintenance. Modeling systems that assist in analyzing system deterioration are of great benefit for these tasks. Topological case-based modeling (TCBM) (Tsutsui et al. 1993; Tsutsui 1995) is an effective tool for chiller performance deterioration monitoring. This paper describes TCBM and its application to this task using recorded historical performance data.

  9. A dislocation-based, strain–gradient–plasticity strengthening model for deformation processed metal–metal composites

    SciTech Connect (OSTI)

    Tian, Liang; Russell, Alan; Anderson, Iver

    2014-01-03

    Deformation processed metal–metal composites (DMMCs) are high-strength, high-electrical conductivity composites developed by severe plastic deformation of two ductile metal phases. The extraordinarily high strength of DMMCs is underestimated using the rule of mixture (or volumetric weighted average) of conventionally work-hardened metals. A dislocation-density-based, strain–gradient–plasticity model is proposed to relate the strain-gradient effect with the geometrically necessary dislocations emanating from the interface to better predict the strength of DMMCs. The model prediction was compared with our experimental findings of Cu–Nb, Cu–Ta, and Al–Ti DMMC systems to verify the applicability of the new model. The results show that this model predicts the strength of DMMCs better than the rule-of-mixture model. The strain-gradient effect, responsible for the exceptionally high strength of heavily cold worked DMMCs, is dominant at large deformation strain since its characteristic microstructure length is comparable with the intrinsic material length.

  10. A dislocation-based, strain–gradient–plasticity strengthening model for deformation processed metal–metal composites

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Tian, Liang; Russell, Alan; Anderson, Iver

    2014-01-03

    Deformation processed metal–metal composites (DMMCs) are high-strength, high-electrical conductivity composites developed by severe plastic deformation of two ductile metal phases. The extraordinarily high strength of DMMCs is underestimated using the rule of mixture (or volumetric weighted average) of conventionally work-hardened metals. A dislocation-density-based, strain–gradient–plasticity model is proposed to relate the strain-gradient effect with the geometrically necessary dislocations emanating from the interface to better predict the strength of DMMCs. The model prediction was compared with our experimental findings of Cu–Nb, Cu–Ta, and Al–Ti DMMC systems to verify the applicability of the new model. The results show that this model predicts themore » strength of DMMCs better than the rule-of-mixture model. The strain-gradient effect, responsible for the exceptionally high strength of heavily cold worked DMMCs, is dominant at large deformation strain since its characteristic microstructure length is comparable with the intrinsic material length.« less

  11. Experimentally validated long-term energy production prediction model for solar dish/Stirling electric generating systems

    SciTech Connect (OSTI)

    Stine, W.B.

    1995-12-31

    Dish/Stirling solar electric systems are currently being tested for performance and longevity in order to bring them to the electric power generation market. Studies both in Germany and the United States indicate that a significant market exists for these systems if they perform in actual installations according to tested conditions, and if, when produced in large numbers their cost will drop to goals currently being projected. In the 1980`s, considerable experience was gained operating eight dish/Stirling systems of three different designs. One of these recorded the world`s record for converting solar energy into electricity of 29.4%. The approach to system performance prediction taken in this presentation results from lessons learned in testing these early systems, and those currently being tested. Recently the IEA through the SolarPACES working group, has embarked on a program to develop uniform guidelines for measuring and presenting performance data. These guidelines are to help potential buyers who want to evaluate a specific system relative to other dish/Stirling systems, or relative to other technologies such as photovoltaic, parabolic trough or central receiver systems. In this paper, a procedure is described that permits modeling of long-term energy production using only a few experimentally determined parameters. The benefit of using this technique is that relatively simple tests performed over a period of a few months can provide performance parameters that can be used in a computer model requiring only the input of insolation and ambient temperature data to determine long-term energy production information. A portion of this analytical procedure has been tested on the three 9-kW(e) systems in operation in Almeria, Spain. Further evaluation of these concepts is planned on a 7.5-kW(e) system currently undergoing testing at Cal Poly University in Pomona, California and later on the 25 kW(e) USJVP systems currently under development.

  12. FINAL REPORT: Mechanistically-Base Field Scale Models of Uranium Biogeochemistry from Upscaling Pore-Scale Experiments and Models

    SciTech Connect (OSTI)

    Wood, Brian D.

    2013-11-04

    Biogeochemical reactive transport processes in the subsurface environment are important to many contemporary environmental issues of significance to DOE. Quantification of risks and impacts associated with environmental management options, and design of remediation systems where needed, require that we have at our disposal reliable predictive tools (usually in the form of numerical simulation models). However, it is well known that even the most sophisticated reactive transport models available today have poor predictive power, particularly when applied at the field scale. Although the lack of predictive ability is associated in part with our inability to characterize the subsurface and limitations in computational power, significant advances have been made in both of these areas in recent decades and can be expected to continue. In this research, we examined the upscaling (pore to Darcy and Darcy to field) the problem of bioremediation via biofilms in porous media. The principle idea was to start with a conceptual description of the bioremediation process at the pore scale, and apply upscaling methods to formally develop the appropriate upscaled model at the so-called Darcy scale. The purpose was to determine (1) what forms the upscaled models would take, and (2) how one might parameterize such upscaled models for applications to bioremediation in the field. We were able to effectively upscale the bioremediation process to explain how the pore-scale phenomena were linked to the field scale. The end product of this research was to produce a set of upscaled models that could be used to help predict field-scale bioremediation. These models were mechanistic, in the sense that they directly incorporated pore-scale information, but upscaled so that only the essential features of the process were needed to predict the effective parameters that appear in the model. In this way, a direct link between the microscale and the field scale was made, but the upscaling process

  13. Determination of High-Frequency Current Distribution Using EMTP-Based Transmission Line Models with Resulting Radiated Electromagnetic Fields

    SciTech Connect (OSTI)

    Mork, B; Nelson, R; Kirkendall, B; Stenvig, N

    2009-11-30

    Application of BPL technologies to existing overhead high-voltage power lines would benefit greatly from improved simulation tools capable of predicting performance - such as the electromagnetic fields radiated from such lines. Existing EMTP-based frequency-dependent line models are attractive since their parameters are derived from physical design dimensions which are easily obtained. However, to calculate the radiated electromagnetic fields, detailed current distributions need to be determined. This paper presents a method of using EMTP line models to determine the current distribution on the lines, as well as a technique for using these current distributions to determine the radiated electromagnetic fields.

  14. Midtemperature Solar Systems Test Facility predictions for thermal performance based on test data: Custom Engineering trough with glass reflector surface and Sandia-designed receivers

    SciTech Connect (OSTI)

    Harrison, T.D.

    1981-05-01

    Thermal performance predictions based on test data are presented for the Custom Engineering trough and Sandia-designed receivers, with glass reflector surface, for three output temperatures at five cities in the United States. Two experimental receivers were tested, one with an antireflective coating on the glass envelope around the receiver tube and one without the antireflective coating.

  15. Absorption of ethanol, acetone, benzene and 1,2-dichloroethane through human skin in vitro: a test of diffusion model predictions

    SciTech Connect (OSTI)

    Gajjar, Rachna M.; Kasting, Gerald B.

    2014-11-15

    The overall goal of this research was to further develop and improve an existing skin diffusion model by experimentally confirming the predicted absorption rates of topically-applied volatile organic compounds (VOCs) based on their physicochemical properties, the skin surface temperature, and the wind velocity. In vitro human skin permeation of two hydrophilic solvents (acetone and ethanol) and two lipophilic solvents (benzene and 1,2-dichloroethane) was studied in Franz cells placed in a fume hood. Four doses of each {sup 14}C-radiolabed compound were tested — 5, 10, 20, and 40 μL cm{sup −2}, corresponding to specific doses ranging in mass from 5.0 to 63 mg cm{sup −2}. The maximum percentage of radiolabel absorbed into the receptor solutions for all test conditions was 0.3%. Although the absolute absorption of each solvent increased with dose, percentage absorption decreased. This decrease was consistent with the concept of a stratum corneum deposition region, which traps small amounts of solvent in the upper skin layers, decreasing the evaporation rate. The diffusion model satisfactorily described the cumulative absorption of ethanol; however, values for the other VOCs were underpredicted in a manner related to their ability to disrupt or solubilize skin lipids. In order to more closely describe the permeation data, significant increases in the stratum corneum/water partition coefficients, K{sub sc}, and modest changes to the diffusion coefficients, D{sub sc}, were required. The analysis provided strong evidence for both skin swelling and barrier disruption by VOCs, even by the minute amounts absorbed under these in vitro test conditions. - Highlights: • Human skin absorption of small doses of VOCs was measured in vitro in a fume hood. • The VOCs tested were ethanol, acetone, benzene and 1,2-dichloroethane. • Fraction of dose absorbed for all compounds at all doses tested was less than 0.3%. • The more aggressive VOCs absorbed at higher levels than

  16. Common Approach to Obtaining Experimental Data for Developing Predictive

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    NOx Absorber Models | Department of Energy Common Approach to Obtaining Experimental Data for Developing Predictive NOx Absorber Models Common Approach to Obtaining Experimental Data for Developing Predictive NOx Absorber Models 2005 Diesel Engine Emissions Reduction (DEER) Conference Presentations and Posters 2005_deer_currier.pdf (318.51 KB) More Documents & Publications Pt-free, Perovskite-based Lean NOx Trap Catalysts Lean NOx Traps - Microstructural Studies of Real World and Model

  17. Status of the phenomena representation, 3D modeling, and cloud-based software architecture development

    SciTech Connect (OSTI)

    Smith, Curtis L.; Prescott, Steven; Kvarfordt, Kellie; Sampath, Ram; Larson, Katie

    2015-09-01

    Early in 2013, researchers at the Idaho National Laboratory outlined a technical framework to support the implementation of state-of-the-art probabilistic risk assessment to predict the safety performance of advanced small modular reactors. From that vision of the advanced framework for risk analysis, specific tasks have been underway in order to implement the framework. This report discusses the current development of a several tasks related to the framework implementation, including a discussion of a 3D physics engine that represents the motion of objects (including collision and debris modeling), cloud-based analysis tools such as a Bayesian-inference engine, and scenario simulations. These tasks were performed during 2015 as part of the technical work associated with the Advanced Reactor Technologies Program.

  18. Multi-scale modeling of microstructure dependent intergranular brittle fracture using a quantitative phase-field based method

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Chakraborty, Pritam; Zhang, Yongfeng; Tonks, Michael R.

    2015-12-07

    In this study, the fracture behavior of brittle materials is strongly influenced by their underlying microstructure that needs explicit consideration for accurate prediction of fracture properties and the associated scatter. In this work, a hierarchical multi-scale approach is pursued to model microstructure sensitive brittle fracture. A quantitative phase-field based fracture model is utilized to capture the complex crack growth behavior in the microstructure and the related parameters are calibrated from lower length scale atomistic simulations instead of engineering scale experimental data. The workability of this approach is demonstrated by performing porosity dependent intergranular fracture simulations in UO2 and comparing themore » predictions with experiments.« less

  19. Generic vehicle speed models based on traffic simulation: Development and application

    SciTech Connect (OSTI)

    Margiotta, R.; Cohen, H.; Elkins, G.; Rathi, A.; Venigalla, M.

    1994-12-15

    This paper summarizes the findings of a research project to develop new methods of estimating speeds for inclusion in the Highway Performance Monitoring System (HPMS) Analytical Process. The paper focuses on the effects of traffic conditions excluding incidents (recurring congestion) on daily average ed and excess fuel consumption. A review of the literature revealed that many techniques have been used to predict speeds as a function of congestion but most fail to address the effects of queuing. However, the method of Dowling and Skabardonis avoids this limitation and was adapted to the research. The methodology used the FRESIM and NETSIM microscopic traffic simulation models to develop uncongested speed functions and as a calibration base for the congested flow functions. The chief contributions of the new speed models are the simplicity of application and their explicit accounting for the effects of queuing. Specific enhancements include: (1) the inclusion of a queue discharge rate for freeways; (2) use of newly defined uncongested flow speed functions; (3) use of generic temporal distributions that account for peak spreading; and (4) a final model form that allows incorporation of other factors that influence speed, such as grades and curves. The main limitation of the new speed models is the fact that they are based on simulation results and not on field observations. They also do not account for the effect of incidents on speed. While appropriate for estimating average national conditions, the use of fixed temporal distributions may not be suitable for analyzing specific facilities, depending on observed traffic patterns. Finally, it is recommended that these and all future speed models be validated against field data where incidents can be adequately identified in the data.

  20. Integration of the predictions of two models with dose measurements in a case study of children exposed to the emissions of a lead smelter

    SciTech Connect (OSTI)

    Bonnard, R.; McKone, T.E.

    2009-03-01

    The predictions of two source-to-dose models are systematically evaluated with observed data collected in a village polluted by a currently operating secondary lead smelter. Both models were built up from several sub-models linked together and run using Monte-Carlo simulation, to calculate the distribution children's blood lead levels attributable to the emissions from the facility. The first model system is composed of the CalTOX model linked to a recoded version of the IEUBK model. This system provides the distribution of the media-specific lead concentrations (air, soil, fruit, vegetables and blood) in the whole area investigated. The second model consists of a statistical model to estimate the lead deposition on the ground, a modified version of the model HHRAP and the same recoded version of the IEUBK model. This system provides an estimate of the concentration of exposure of specific individuals living in the study area. The predictions of the first model system were improved in terms of accuracy and precision by performing a sensitivity analysis and using field data to correct the default value provided for the leaf wet density. However, in this case study, the first model system tends to overestimate the exposure due to exposed vegetables. The second model was tested for nine children with contrasting exposure conditions. It managed to capture the blood levels for eight of them. In the last case, the exposure of the child by pathways not considered in the model may explain the failure of the model. The interest of this integrated model is to provide outputs with lower variance than the first model system, but at the moment further tests are necessary to conclude about its accuracy.

  1. On deformation twinning in a 17.5%Mn-TWIP steel: A physically-based phenomenological model

    SciTech Connect (OSTI)

    Soulami, Ayoub; Choi, Kyoo Sil; Shen, Y. F.; Liu, Wenning N.; Sun, Xin; Khaleel, Mohammad A.

    2011-01-25

    TWinning Induced Plasticity (TWIP) steel is a typical representative of the 2nd generation of advanced high strength steel (AHSS) which exhibits a combination of high strength and excellent ductility due to the twinning mechanisms. This paper discusses the principal features of deformation twinning in faced-centered cubic austenitic steels and shows how a physiscally-based macroscopic model can be derived from microscopic considerations. In fact, a dislocation-based phenomenological model, with internal state variables such as dislocation density and micro-twins volume fraction representing the microstructure evolution during deformation process, is proposed to describe the deformation behavior of TWIP steels. The contribution of this work is the incorporation of a physically-based twin’s nucleation and volume fraction evolution model in a conventional dislocation-based approach. Microstructural level investigations, using scanning electron microscope (SEM) and transmission electron microscope (TEM) techniques, for the TWIP steel Fe–17.5 wt.% Mn–1.4 wt.% Al- 0.56 wt.% C, are used to validate and verify modeling assumptions. The model could be regarded as a semi-phenomenological approach with sufficient links between microstructure and overall properties and therefore offers good predictive capabilities. Its simplicity also allows a modular implementation in finite element-based metal forming simulations.

  2. Characterization and Modeling of a Water-based Liquid Scintillator

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    L. J. Bignell; Beznosko, D.; Diwan, M. V.; Hans, S.; Jaffe, D. E.; S. Kettell; Rosero, R.; Themann, H. W.; Viren, B.; Worcester, E.; et al

    2015-12-15

    We characterised Water-based Liquid Scintillator (WbLS) using low energy protons, UV-VIS absorbance, and fluorescence spectroscopy. We have also developed and validated a simulation model that describes the behaviour of WbLS in our detector configurations for proton beam energies of 210 MeV, 475 MeV, and 2 GeV and for two WbLS compositions. These results have enabled us to estimate the light yield and ionisation quenching of WbLS, as well as to understand the influence of the wavelength shifting of Cherenkov light on our measurements. These results are relevant to the suitability of WbLS materials for next generation intensity frontier experiments.

  3. Prediction of Thermal Conductivity for Irradiated SiC/SiC Composites by Informing Continuum Models with Molecular Dynamics Data

    SciTech Connect (OSTI)

    Nguyen, Ba Nghiep; Gao, Fei; Henager, Charles H.; Kurtz, Richard J.

    2014-05-01

    This article proposes a new method to estimate the thermal conductivity of SiC/SiC composites subjected to neutron irradiation. The modeling method bridges different scales from the atomic scale to the scale of a 2D SiC/SiC composite. First, it studies the irradiation-induced point defects in perfect crystalline SiC using molecular dynamics (MD) simulations to compute the defect thermal resistance as a function of vacancy concentration and irradiation dose. The concept of defect thermal resistance is explored explicitly in the MD data using vacancy concentrations and thermal conductivity decrements due to phonon scattering. Point defect-induced swelling for chemical vapor deposited (CVD) SiC as a function of irradiation dose is approximated by scaling the corresponding MD results for perfect crystal ?-SiC to experimental data for CVD-SiC at various temperatures. The computed thermal defect resistance, thermal conductivity as a function of grain size, and definition of defect thermal resistance are used to compute the thermal conductivities of CVD-SiC, isothermal chemical vapor infiltrated (ICVI) SiC and nearly-stoichiometric SiC fibers. The computed fiber and ICVI-SiC matrix thermal conductivities are then used as input for an Eshelby-Mori-Tanaka approach to compute the thermal conductivities of 2D SiC/SiC composites subjected to neutron irradiation within the same irradiation doses. Predicted thermal conductivities for an irradiated Tyranno-SA/ICVI-SiC composite are found to be comparable to available experimental data for a similar composite ICVI-processed with these fibers.

  4. Advanced product realization through model-based design and virtual prototyping

    SciTech Connect (OSTI)

    Andreas, R.D.

    1995-03-01

    Several government agencies and industrial sectors have recognized the need for, and payoff of, investing in the methodologies and associated technologies for improving the product realization process. Within the defense community as well as commercial industry, there are three major needs. First, they must reduce the cost of military products, of related manufacturing processes, and of the enterprises that have to be maintained. Second, they must reduce the time required to realize products while still applying the latest technologies. Finally, they must improve the predictability of process attributes, product performance, cost, schedule and quality. They must continue to advance technology, quickly incorporate their innovations in new products and in processes to produce them, and they need to capitalize on the raw computational power and communications bandwidth that continues to become available at decreasing cost. Sandia National Laboratories initiative is pursuing several interrelated, key concepts and technologies in order to enable such product realization process improvements: model-based design; intelligent manufacturing processes; rapid virtual and physical prototyping; and agile people/enterprises. While progress in each of these areas is necessary, this paper only addresses a portion of the overall initiative. First a vision of a desired future capability in model-based design and virtual prototyping is presented. This is followed by a discussion of two specific activities parametric design analysis of Synthetic Aperture Radars (SARs) and virtual prototyping of miniaturized high-density electronics -- that exemplify the vision as well as provide a status report on relevant work in progress.

  5. Integrated Experimental and Model-based Analysis Reveals the Spatial Aspects of EGFR Activation Dynamics

    SciTech Connect (OSTI)

    Shankaran, Harish; Zhang, Yi; Chrisler, William B.; Ewald, Jonathan A.; Wiley, H. S.; Resat, Haluk

    2012-10-02

    The epidermal growth factor receptor (EGFR) belongs to the ErbB family of receptor tyrosine kinases, and controls a diverse set of cellular responses relevant to development and tumorigenesis. ErbB activation is a complex process involving receptor-ligand binding, receptor dimerization, phosphorylation, and trafficking (internalization, recycling and degradation), which together dictate the spatio-temporal distribution of active receptors within the cell. The ability to predict this distribution, and elucidation of the factors regulating it, would help to establish a mechanistic link between ErbB expression levels and the cellular response. Towards this end, we constructed mathematical models for deconvolving the contributions of receptor dimerization and phosphorylation to EGFR activation, and to examine the dependence of these processes on sub-cellular location. We collected experimental datasets for EGFR activation dynamics in human mammary epithelial cells, with the specific goal of model parameterization, and used the data to estimate parameters for several alternate models. Model-based analysis indicated that: 1) signal termination via receptor dephosphorylation in late endosomes, prior to degradation, is an important component of the response, 2) less than 40% of the receptors in the cell are phosphorylated at any given time, even at saturating ligand doses, and 3) receptor dephosphorylation rates at the cell surface and early endosomes are comparable. We validated the last finding by measuring EGFR dephosphorylation rates at various times following ligand addition both in whole cells, and in endosomes using ELISAs and fluorescent imaging. Overall, our results provide important information on how EGFR phosphorylation levels are regulated within cells. Further, the mathematical model described here can be extended to determine receptor dimer abundances in cells co-expressing various levels of ErbB receptors. This study demonstrates that an iterative cycle of

  6. Integrated Sensing and Controls for Coal Gasification - Development of Model-Based Controls for GE's Gasifier and Syngas Cooler

    SciTech Connect (OSTI)

    Aditya Kumar

    2010-12-30

    This report summarizes the achievements and final results of this program. The objective of this program is to develop a comprehensive systems approach to integrated design of sensing and control systems for an Integrated Gasification Combined Cycle (IGCC) plant, using advanced model-based techniques. In particular, this program is focused on the model-based sensing and control system design for the core gasification section of an IGCC plant. The overall approach consists of (i) developing a first-principles physics-based dynamic model of the gasification section, (ii) performing model-reduction where needed to derive low-order models suitable for controls analysis and design, (iii) developing a sensing system solution combining online sensors with model-based estimation for important process variables not measured directly, and (iv) optimizing the steady-state and transient operation of the plant for normal operation as well as for startup using model predictive controls (MPC). Initially, available process unit models were implemented in a common platform using Matlab/Simulink{reg_sign}, and appropriate model reduction and model updates were performed to obtain the overall gasification section dynamic model. Also, a set of sensor packages were developed through extensive lab testing and implemented in the Tampa Electric Company IGCC plant at Polk power station in 2009, to measure temperature and strain in the radiant syngas cooler (RSC). Plant operation data was also used to validate the overall gasification section model. The overall dynamic model was then used to develop a sensing solution including a set of online sensors coupled with model-based estimation using nonlinear extended Kalman filter (EKF). Its performance in terms of estimating key unmeasured variables like gasifier temperature, carbon conversion, etc., was studied through extensive simulations in the presence sensing errors (noise and bias) and modeling errors (e.g. unknown gasifier kinetics, RSC

  7. Agent-Based Knowledge Discovery for Modeling and Simulation

    SciTech Connect (OSTI)

    Haack, Jereme N.; Cowell, Andrew J.; Marshall, Eric J.; Fligg, Alan K.; Gregory, Michelle L.; McGrath, Liam R.

    2009-09-15

    This paper describes an approach to using agent technology to extend the automated discovery mechanism of the Knowledge Encapsulation Framework (KEF). KEF is a suite of tools to enable the linking of knowledge inputs (relevant, domain-specific evidence) to modeling and simulation projects, as well as other domains that require an effective collaborative workspace for knowledge-based tasks. This framework can be used to capture evidence (e.g., trusted material such as journal articles and government reports), discover new evidence (covering both trusted and social media), enable discussions surrounding domain-specific topics and provide automatically generated semantic annotations for improved corpus investigation. The current KEF implementation is presented within a semantic wiki environment, providing a simple but powerful collaborative space for team members to review, annotate, discuss and align evidence with their modeling frameworks. The novelty in this approach lies in the combination of automatically tagged and user-vetted resources, which increases user trust in the environment, leading to ease of adoption for the collaborative environment.

  8. MODEL-BASED HYDROACOUSTIC BLOCKAGE ASSESSMENT AND DEVELOPMENT OF AN EXPLOSIVE SOURCE DATABASE

    SciTech Connect (OSTI)

    Matzel, E; Ramirez, A; Harben, P

    2005-07-11

    We are continuing the development of the Hydroacoustic Blockage Assessment Tool (HABAT) which is designed for use by analysts to predict which hydroacoustic monitoring stations can be used in discrimination analysis for any particular event. The research involves two approaches (1) model-based assessment of blockage, and (2) ground-truth data-based assessment of blockage. The tool presents the analyst with a map of the world, and plots raypath blockages from stations to sources. The analyst inputs source locations and blockage criteria, and the tool returns a list of blockage status from all source locations to all hydroacoustic stations. We are currently using the tool in an assessment of blockage criteria for simple direct-path arrivals. Hydroacoustic data, predominantly from earthquake sources, are read in and assessed for blockage at all available stations. Several measures are taken. First, can the event be observed at a station above background noise? Second, can we establish backazimuth from the station to the source. Third, how large is the decibel drop at one station relative to other stations. These observational results are then compared with model estimates to identify the best set of blockage criteria and used to create a set of blockage maps for each station. The model-based estimates are currently limited by the coarse bathymetry of existing databases and by the limitations inherent in the raytrace method. In collaboration with BBN Inc., the Hydroacoustic Coverage Assessment Model (HydroCAM) that generates the blockage files that serve as input to HABAT, is being extended to include high-resolution bathymetry databases in key areas that increase model-based blockage assessment reliability. An important aspect of this capability is to eventually include reflected T-phases where they reliably occur and to identify the associated reflectors. To assess how well any given hydroacoustic discriminant works in separating earthquake and in-water explosion

  9. A physiologically based biokinetic (PBBK) model for estragole bioactivation and detoxification in rat

    SciTech Connect (OSTI)

    Punt, Ans Freidig, Andreas P.; Delatour, Thierry; Scholz, Gabriele; Boersma, Marelle G.; Schilter, Benoit; Bladeren, Peter J. van; Rietjens, Ivonne M.C.M.

    2008-09-01

    The present study defines a physiologically based biokinetic (PBBK) model for the alkenylbenzene estragole in rat based on in vitro metabolic parameters determined using relevant tissue fractions, in silico derived partition coefficients, and physiological parameters derived from the literature. The model consists of eight compartments including liver, lung and kidney as metabolizing compartments, and additional compartments for fat, arterial blood, venous blood, rapidly perfused tissue and slowly perfused tissue. Evaluation of the model was performed by comparing the PBBK predicted dose-dependent formation of the estragole metabolites 4-allylphenol and 1'-hydroxyestragole glucuronide to literature reported levels of these metabolites, which were demonstrated to be in the same order of magnitude. With the model obtained the relative extent of bioactivation and detoxification of estragole at different oral doses was examined. At low doses formation of 4-allylphenol, leading to detoxification, is observed to be the major metabolic pathway, occurring mainly in the lung and kidney due to formation of this metabolite with high affinity in these organs. Saturation of this metabolic pathway in the lung and kidney leads to a relative increase in formation of the proximate carcinogenic metabolite 1'-hydroxyestragole, occurring mainly in the liver. This relative increase in formation of 1'-hydroxyestragole leads to a relative increase in formation of 1'-hydroxyestragole glucuronide and 1'-sulfooxyestragole the latter being the ultimate carcinogenic metabolite of estragole. These results indicate that the relative importance of different metabolic pathways of estragole may vary in a dose-dependent way, leading to a relative increase in bioactiviation of estragole at higher doses.

  10. A CFD-based wind solver for a fast response transport and dispersion model

    SciTech Connect (OSTI)

    Gowardhan, Akshay A; Brown, Michael J; Pardyjak, Eric R; Senocak, Inanc

    2010-01-01

    In many cities, ambient air quality is deteriorating leading to concerns about the health of city inhabitants. In urban areas with narrow streets surrounded by clusters of tall buildings, called street canyons, air pollution from traffic emissions and other sources is difficult to disperse and may accumulate resulting in high pollutant concentrations. For various situations, including the evacuation of populated areas in the event of an accidental or deliberate release of chemical, biological and radiological agents, it is important that models should be developed that produce urban flow fields quickly. For these reasons it has become important to predict the flow field in urban street canyons. Various computational techniques have been used to calculate these flow fields, but these techniques are often computationally intensive. Most fast response models currently in use are at a disadvantage in these cases as they are unable to correlate highly heterogeneous urban structures with the diagnostic parameterizations on which they are based. In this paper, a fast and reasonably accurate computational fluid dynamics (CFD) technique that solves the Navier-Stokes equations for complex urban areas has been developed called QUIC-CFD (Q-CFD). This technique represents an intermediate balance between fast (on the order of minutes for a several block problem) and reasonably accurate solutions. The paper details the solution procedure and validates this model for various simple and complex urban geometries.

  11. Durability-Based Design Guide for an Automotive Structural Composite: Part 2. Background Data and Models

    SciTech Connect (OSTI)

    Corum, J.M.; Battiste, R.L.; Brinkman, C.R.; Ren, W.; Ruggles, M.B.; Weitsman, Y.J.; Yahr, G.T.

    1998-02-01

    This background report is a companion to the document entitled ''Durability-Based Design Criteria for an Automotive Structural Composite: Part 1. Design Rules'' (ORNL-6930). The rules and the supporting material characterization and modeling efforts described here are the result of a U.S. Department of Energy Advanced Automotive Materials project entitled ''Durability of Lightweight Composite Structures.'' The overall goal of the project is to develop experimentally based, durability-driven design guidelines for automotive structural composites. The project is closely coordinated with the Automotive Composites Consortium (ACC). The initial reference material addressed by the rules and this background report was chosen and supplied by ACC. The material is a structural reaction injection-molded isocyanurate (urethane), reinforced with continuous-strand, swirl-mat, E-glass fibers. This report consists of 16 position papers, each summarizing the observations and results of a key area of investigation carried out to provide the basis for the durability-based design guide. The durability issues addressed include the effects of cyclic and sustained loadings, temperature, automotive fluids, vibrations, and low-energy impacts (e.g., tool drops and roadway kickups) on deformation, strength, and stiffness. The position papers cover these durability issues. Topics include (1) tensile, compressive, shear, and flexural properties; (2) creep and creep rupture; (3) cyclic fatigue; (4) the effects of temperature, environment, and prior loadings; (5) a multiaxial strength criterion; (6) impact damage and damage tolerance design; (7) stress concentrations; (8) a damage-based predictive model for time-dependent deformations; (9) confirmatory subscale component tests; and (10) damage development and growth observations.

  12. Dynamic model of Italy`s Progetto Energia cogeneration plants aims to better predict plant performance, cut start-up costs

    SciTech Connect (OSTI)

    1996-12-31

    Over the next four years, the Progetto Energia project will be building several cogeneration plants to help satisfy the increasing demands of Italy`s industrial users and the country`s demand for electrical power. Located at six different sites within Italy, these combined-cycle cogeneration plants will supply a total of 500 MW of electricity and 100 tons/hr of process steam to Italian industries and residences. To ensure project success, a dynamic model of the 50-MW base unit was developed. The goal established for the model was to predict the dynamic behavior of the complex thermodynamic system in order to assess equipment performance and control system effectiveness for normal operation and, more importantly, abrupt load changes. In addition to fulfilling its goals, the dynamic study guided modifications to controller logic that significantly improved steam drum pressure control and bypassed steam desuperheating performance simulations of normal and abrupt transient events allowed engineers to define optimum controller gain coefficients. The dynamic study will undoubtedly reduce the associated plant start-up costs and contribute to a smooth commercial plant acceptance. As a result of the work, the control system has already been through its check-out and performance evaluation, usually performed during the plant start-up phase. Field engineers will directly benefit from this effort to identify and resolve control system {open_quotes}bugs{close_quotes} before the equipment reaches the field. High thermal efficiency, rapid dispatch and high plant availability were key reasons why the natural gas combined-cycle plant was chosen. Other favorable attributes of the combined-cycle plant contributing to the decision were: Minimal environmental impact; a simple and effective process and control philosophy to result in safe and easy plant operation; a choice of technologies and equipment proven in a large number of applications.

  13. Machine Learning Based Multi-Physical-Model Blending for Enhancing Renewable Energy Forecast -- Improvement via Situation Dependent Error Correction

    SciTech Connect (OSTI)

    Lu, Siyuan; Hwang, Youngdeok; Khabibrakhmanov, Ildar; Marianno, Fernando J.; Shao, Xiaoyan; Zhang, Jie; Hodge, Bri-Mathias; Hamann, Hendrik F.

    2015-07-15

    With increasing penetration of solar and wind energy to the total energy supply mix, the pressing need for accurate energy forecasting has become well-recognized. Here we report the development of a machine-learning based model blending approach for statistically combining multiple meteorological models for improving the accuracy of solar/wind power forecast. Importantly, we demonstrate that in addition to parameters to be predicted (such as solar irradiance and power), including additional atmospheric state parameters which collectively define weather situations as machine learning input provides further enhanced accuracy for the blended result. Functional analysis of variance shows that the error of individual model has substantial dependence on the weather situation. The machine-learning approach effectively reduces such situation dependent error thus produces more accurate results compared to conventional multi-model ensemble approaches based on simplistic equally or unequally weighted model averaging. Validation over an extended period of time results show over 30% improvement in solar irradiance/power forecast accuracy compared to forecasts based on the best individual model.

  14. Validation of mathematical models for the prediction of organs-at-risk dosimetric metrics in high-dose-rate gynecologic interstitial brachytherapy

    SciTech Connect (OSTI)

    Damato, Antonio L.; Viswanathan, Akila N.; Cormack, Robert A.

    2013-10-15

    Purpose: Given the complicated nature of an interstitial gynecologic brachytherapy treatment plan, the use of a quantitative tool to evaluate the quality of the achieved metrics compared to clinical practice would be advantageous. For this purpose, predictive mathematical models to predict the D{sub 2cc} of rectum and bladder in interstitial gynecologic brachytherapy are discussed and validated.Methods: Previous plans were used to establish the relationship between D2cc and the overlapping volume of the organ at risk with the targeted area (C0) or a 1-cm expansion of the target area (C1). Three mathematical models were evaluated: D{sub 2cc}=α*C{sub 1}+β (LIN); D{sub 2cc}=α– exp(–β*C{sub 0}) (EXP); and a mixed approach (MIX), where both C{sub 0} and C{sub 1} were inputs of the model. The parameters of the models were optimized on a training set of patient data, and the predictive error of each model (predicted D{sub 2cc}− real D{sub 2cc}) was calculated on a validation set of patient data. The data of 20 patients were used to perform a K-fold cross validation analysis, with K = 2, 4, 6, 8, 10, and 20.Results: MIX was associated with the smallest mean prediction error <6.4% for an 18-patient training set; LIN had an error <8.5%; EXP had an error <8.3%. Best case scenario analysis shows that an error ≤5% can be achieved for a ten-patient training set with MIX, an error ≤7.4% for LIN, and an error ≤6.9% for EXP. The error decreases with the increase in training set size, with the most marked decrease observed for MIX.Conclusions: The MIX model can predict the D{sub 2cc} of the organs at risk with an error lower than 5% with a training set of ten patients or greater. The model can be used in the development of quality assurance tools to identify treatment plans with suboptimal sparing of the organs at risk. It can also be used to improve preplanning and in the development of real-time intraoperative planning tools.

  15. On-line Chemistry within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model

    SciTech Connect (OSTI)

    Grell, Georg; Fast, Jerome D.; Gustafson, William I.; Peckham, Steven E.; McKeen, Stuart A.; Salzmann, Marc; Freitas, Saulo

    2010-01-01

    This is a conference proceeding that is now being put together as a book. This is chapter 2 of the book: "INTEGRATED SYSTEMS OF MESO-METEOROLOGICAL AND CHEMICAL TRANSPORT MODELS" published by Springer. The chapter title is "On-line Chemistry within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model." The original conference was the COST-728/NetFAM workshop on Integrated systems of meso-meteorological and chemical transport models, Danish Meteorological Institute, Copenhagen, May 21-23, 2007.

  16. Three orbital model for the iron-based superconductors

    SciTech Connect (OSTI)

    Daghofer, Maria [ORNL; Nicholson, Andrew D [ORNL; Moreo, Adriana [ORNL; Dagotto, Elbio R [ORNL

    2010-01-01

    The theoretical need to study the properties of the Fe-based high-Tc superconductors using reliable manybody techniques has highlighted the importance of determining what is the minimum number of orbital degrees of freedom that will capture the physics of these materials. While the shape of the Fermi surface FS obtained with the local-density approximation LDA can be reproduced by a two-orbital model, it has been argued that the bands that cross the chemical potential result from the strong hybridization of three of the Fe 3d orbitals. For this reason, a three orbital Hamiltonian for LaOFeAs obtained with the Slater-Koster formalism by considering the hybridization of the As p orbitals with the Fe dxz, dyz, and dxy orbitals is discussed here. This model reproduces qualitatively the FS shape and orbital composition obtained by LDA calculations for undoped LaOFeAs when four electrons per Fe are considered. Within a mean-field approximation, its magnetic and orbital properties in the undoped case are here described for intermediate values of J/U. Increasing the Coulomb repulsion U at zero temperature, four different regimes are obtained: 1 paramagnetic, 2 magnetic ,0 spin order, 3 the same ,0 spin order but now including orbital order, and finally 4 a magnetic and orbital ordered insulator. The spin-singlet pairing operators allowed by the lattice and orbital symmetries are also constructed. It is found that for pairs of electrons involving up to diagonal nearest-neighbors sites, the only fully gapped and purely intraband spin-singlet pairing operator is given by k= fkdk,, d k,, with fk=1 or cos kx cos ky which would arise only if the electrons in all different orbitals couple with equal strength to the source of pairing.

  17. A neural network model for predicting the silicon content of the hot metal at No. 2 blast furnace of SSAB Luleaa

    SciTech Connect (OSTI)

    Zuo Guangqing; Ma Jitang; Bo, B.

    1996-12-31

    To predict the silicon content of hot metal at No. 2 blast furnace, SSAB, Luleaa Works, a three-layer Back-Propagation network model has been established. The network consists of twenty-eight inputs, six middle nodes and one output and uses a generalized delta rule for training. Different network structures and different training strategies have been tested. A well-functioning network with dynamic updating has been designed. The off-line test and the on-line application results showed that more than 80% of the predictions can match the actual silicon content in hot metal in a normal operation, if the allowable prediction error was set to {+-}0.05% Si, while the actual fluctuation of the silicon content was larger than {+-}0.10% Si.

  18. COLLABORATIVE RESEARCH: TOWARDS ADVANCED UNDERSTANDING AND PREDICTIVE CAPABILITY OF CLIMATE CHANGE IN THE ARCTIC USING A HIGH-RESOLUTION REGIONAL ARCTIC CLIMATE SYSTEM MODEL

    SciTech Connect (OSTI)

    Gutowski, William J.

    2013-02-07

    The motivation for this project was to advance the science of climate change and prediction in the Arctic region. Its primary goals were to (i) develop a state-of-the-art Regional Arctic Climate system Model (RACM) including high-resolution atmosphere, land, ocean, sea ice and land hydrology components and (ii) to perform extended numerical experiments using high performance computers to minimize uncertainties and fundamentally improve current predictions of climate change in the northern polar regions. These goals were realized first through evaluation studies of climate system components via one-way coupling experiments. Simulations were then used to examine the effects of advancements in climate component systems on their representation of main physics, time-mean fields and to understand variability signals at scales over many years. As such this research directly addressed some of the major science objectives of the BER Climate Change Research Division (CCRD) regarding the advancement of long-term climate prediction.

  19. Microsoft Word - NRAP-TRS-I-005-2014_Use of Science-Based Prediction to Characterize Reservoir Behavior as a Function of Inject

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Use of Science-Based Prediction to Characterize Reservoir Behavior as a Function of Injection Characteristics, Geological Variables, and Time 12 November 2014 Office of Fossil Energy NRAP-TRS-I-005-2014 Disclaimer This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for

  20. Recovery Act: Web-based CO{sub 2} Subsurface Modeling

    SciTech Connect (OSTI)

    Paolini, Christopher; Castillo, Jose

    2012-11-30

    The Web-based CO{sub 2} Subsurface Modeling project focused primarily on extending an existing text-only, command-line driven, isothermal and isobaric, geochemical reaction-transport simulation code, developed and donated by Sienna Geodynamics, into an easier-to-use Web-based application for simulating long-term storage of CO{sub 2} in geologic reservoirs. The Web-based interface developed through this project, publically accessible via URL http://symc.sdsu.edu/, enables rapid prototyping of CO{sub 2} injection scenarios and allows students without advanced knowledge of geochemistry to setup a typical sequestration scenario, invoke a simulation, analyze results, and then vary one or more problem parameters and quickly re-run a simulation to answer what-if questions. symc.sdsu.edu has 2x12 core AMD Opteron™ 6174 2.20GHz processors and 16GB RAM. The Web-based application was used to develop a new computational science course at San Diego State University, COMP 670: Numerical Simulation of CO{sub 2} Sequestration, which was taught during the fall semester of 2012. The purpose of the class was to introduce graduate students to Carbon Capture, Use and Storage (CCUS) through numerical modeling and simulation, and to teach students how to interpret simulation results to make predictions about long-term CO{sub 2} storage capacity in deep brine reservoirs. In addition to the training and education component of the project, significant software development efforts took place. Two computational science doctoral and one geological science masters student, under the direction of the PIs, extended the original code developed by Sienna Geodynamics, named Sym.8. New capabilities were added to Sym.8 to simulate non-isothermal and non-isobaric flows of charged aqueous solutes in porous media, in addition to incorporating HPC support into the code for execution on many-core XSEDE clusters. A successful outcome of this project was the funding and training of three new computational

  1. Comparison of Hydrodynamic Load Predictions Between Engineering Models and Computational Fluid Dynamics for the OC4-DeepCwind Semi-Submersible: Preprint

    SciTech Connect (OSTI)

    Benitz, M. A.; Schmidt, D. P.; Lackner, M. A.; Stewart, G. M.; Jonkman, J.; Robertson, A.

    2014-09-01

    Hydrodynamic loads on the platforms of floating offshore wind turbines are often predicted with computer-aided engineering tools that employ Morison's equation and/or potential-flow theory. This work compares results from one such tool, FAST, NREL's wind turbine computer-aided engineering tool, and the computational fluid dynamics package, OpenFOAM, for the OC4-DeepCwind semi-submersible analyzed in the International Energy Agency Wind Task 30 project. Load predictions from HydroDyn, the offshore hydrodynamics module of FAST, are compared with high-fidelity results from OpenFOAM. HydroDyn uses a combination of Morison's equations and potential flow to predict the hydrodynamic forces on the structure. The implications of the assumptions in HydroDyn are evaluated based on this code-to-code comparison.

  2. A synthetic ecology perspective: How well does behavior of model organisms in the laboratory predict microbial activities in natural habitats?

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Yu, Zheng; Krause, Sascha M. B.; Beck, David A. C.; Chistoserdova, Ludmila

    2016-06-15

    In this perspective article, we question how well model organisms, the ones that are easy to cultivate in the laboratory and that show robust growth and biomass accumulation, reflect the dynamics and interactions of microbial communities observed in nature. Today's -omics toolbox allows assessing the genomic potential of microbes in natural environments in a high-throughput fashion and at a strain-level resolution. However, understanding of the details of microbial activities and of the mechanistic bases of community function still requires experimental validation in simplified and fully controlled systems such as synthetic communities. We have studied methane utilization in Lake Washington sedimentmore » for a few decades and have identified a number of species genetically equipped for this activity. We have also identified cooccurring satellite species that appear to form functional communities together with the methanotrophs. Here, we compare experimental findings from manipulation of natural communities involved in metabolism of methane in this niche with findings from manipulation of synthetic communities assembled in the laboratory of species originating from the same study site, from very simple (two-species) to rather complex (50-species) synthetic communities. We observe some common trends in community dynamics between the two types of communities, toward representation of specific functional guilds. However, we also identify strong discrepancies between the dominant methane oxidizers in synthetic communities compared to natural communities, under similar incubation conditions. Furthermore, these findings highlight the challenges that exist in using the synthetic community approach to modeling dynamics and species interactions in natural communities.« less

  3. Inter-comparison of Computer Codes for TRISO-based Fuel Micro-Modeling and Performance Assessment

    SciTech Connect (OSTI)

    Brian Boer; Chang Keun Jo; Wen Wu; Abderrafi M. Ougouag; Donald McEachren; Francesco Venneri

    2010-10-01

    The Next Generation Nuclear Plant (NGNP), the Deep Burn Pebble Bed Reactor (DB-PBR) and the Deep Burn Prismatic Block Reactor (DB-PMR) are all based on fuels that use TRISO particles as their fundamental constituent. The TRISO particle properties include very high durability in radiation environments, hence the designs reliance on the TRISO to form the principal barrier to radioactive materials release. This durability forms the basis for the selection of this fuel type for applications such as Deep Bun (DB), which require exposures up to four times those expected for light water reactors. It follows that the study and prediction of the durability of TRISO particles must be carried as part of the safety and overall performance characterization of all the designs mentioned above. Such evaluations have been carried out independently by the performers of the DB project using independently developed codes. These codes, PASTA, PISA and COPA, incorporate models for stress analysis on the various layers of the TRISO particle (and of the intervening matrix material for some of them), model for fission products release and migration then accumulation within the SiC layer of the TRISO particle, just next to the layer, models for free oxygen and CO formation and migration to the same location, models for temperature field modeling within the various layers of the TRISO particle and models for the prediction of failure rates. All these models may be either internal to the code or external. This large number of models and the possibility of different constitutive data and model formulations and the possibility of a variety of solution techniques makes it highly unlikely that the model would give identical results in the modeling of identical situations. The purpose of this paper is to present the results of an inter-comparison between the codes and to identify areas of agreement and areas that need reconciliation. The inter-comparison has been carried out by the cooperating

  4. Correlation of a hypoxia based tumor control model with observed local control rates in nasopharyngeal carcinoma treated with chemoradiotherapy

    SciTech Connect (OSTI)

    Avanzo, Michele; Stancanello, Joseph; Franchin, Giovanni; Sartor, Giovanna; Jena, Rajesh; Drigo, Annalisa; Dassie, Andrea; Gigante, Marco; Capra, Elvira

    2010-04-15

    Purpose: To extend the application of current radiation therapy (RT) based tumor control probability (TCP) models of nasopharyngeal carcinoma (NPC) to include the effects of hypoxia and chemoradiotherapy (CRT). Methods: A TCP model is described based on the linear-quadratic model modified to account for repopulation, chemotherapy, heterogeneity of dose to the tumor, and hypoxia. Sensitivity analysis was performed to determine which parameters exert the greatest influence on the uncertainty of modeled TCP. On the basis of the sensitivity analysis, the values of specific radiobiological parameters were set to nominal values reported in the literature for NPC or head and neck tumors. The remaining radiobiological parameters were determined by fitting TCP to clinical local control data from published randomized studies using both RT and CRT. Validation of the model was performed by comparison of estimated TCP and average overall local control rate (LCR) for 45 patients treated at the institution with conventional linear-accelerator-based or helical tomotherapy based intensity-modulated RT and neoadjuvant chemotherapy. Results: Sensitivity analysis demonstrates that the model is most sensitive to the radiosensitivity term {alpha} and the dose per fraction. The estimated values of {alpha} and OER from data fitting were 0.396 Gy{sup -1} and 1.417. The model estimate of TCP (average 90.9%, range 26.9%-99.2%) showed good correlation with the LCR (86.7%). Conclusions: The model implemented in this work provides clinicians with a useful tool to predict the success rate of treatment, optimize treatment plans, and compare the effects of multimodality therapy.

  5. Lipid-Based Nanodiscs as Models for Studying Mesoscale Coalescence A Transport Limited Case

    SciTech Connect (OSTI)

    Hu, Andrew; Fan, Tai-Hsi; Katsaras, John; Xia, Yan; Li, Ming; Nieh, Mu-Ping

    2014-01-01

    Lipid-based nanodiscs (bicelles) are able to form in mixtures of long- and short-chain lipids. Initially, they are of uniform size but grow upon dilution. Previously, nanodisc growth kinetics have been studied using time-resolved small angle neutron scattering (SANS), a technique which is not well suited for probing their change in size immediately after dilution. To address this, we have used dynamic light scattering (DLS), a technique which permits the collection of useful data in a short span of time after dilution of the system. The DLS data indicate that the negatively charged lipids in nanodiscs play a significant role in disc stability and growth. Specifically, the charged lipids are most likely drawn out from the nanodiscs into solution, thereby reducing interparticle repulsion and enabling the discs to grow. We describe a population balance model, which takes into account Coulombic interactions and adequately predicts the initial growth of nanodiscs with a single parameter i.e., surface potential. The results presented here strongly support the notion that the disc coalescence rate strongly depends on nanoparticle charge density. The present system containing low-polydispersity lipid nanodiscs serves as a good model for understanding how charged discoidal micelles coalesce.

  6. Operational forecasting based on a modified Weather Research and Forecasting model

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

    Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

  7. Spectral softening in the X-RAY afterglow of GRB 130925A as predicted by the dust scattering model

    SciTech Connect (OSTI)

    Zhao, Yi-Nan; Shao, Lang, E-mail: lshao@hebtu.edu.cn [Department of Space Science and Astronomy, Hebei Normal University, Shijiazhuang 050024 (China)

    2014-07-01

    Gamma-ray bursts (GRBs) usually occur in a dense star-forming region with a massive circumburst medium. The small-angle scattering of intense prompt X-ray emission off the surrounding dust grains will have observable consequences and sometimes can dominate the X-ray afterglow. In most of the previous studies, only the Rayleigh-Gans (RG) approximation is employed for describing the scattering process, which works accurately for the typical size of grains (with radius of a ? 0.1 ?m) in the diffuse interstellar medium. When the size of the grains may significantly increase, as in a more dense region where GRBs would occur, the RG approximation may not be valid enough for modeling detailed observational data. In order to study the temporal and spectral properties of the scattered X-ray emission more accurately with potentially larger dust grains, we provide a practical approach using the series expansions of anomalous diffraction (AD) approximation based on the complicated Mie theory. We apply our calculations to understand the puzzling X-ray afterglow of recently observed GRB 130925A that showed a significant spectral softening. We find that the X-ray scattering scenarios with either AD or RG approximation adopted could well reproduce both the temporal and spectral profile simultaneously. Given the plateau present in the early X-ray light curve, a typical distribution of smaller grains as in the interstellar medium would be suggested for GRB 130925A.

  8. Macromodel for assessing residential concentrations of combustion-generated pollutants: Model development and preliminary predictions for CO, NO/sub 2/, and respirable suspended particles

    SciTech Connect (OSTI)

    Traynor, G.W.; Aceti, J.C.; Apte, M.G.; Smith, B.V.; Green, L.L.; Smith-Reiser, A.; Novak, K.M.; Moses, D.O.

    1989-01-01

    A simulation model (also called a ''macromodel'') has been developed to predict residential air pollutant concentration distributions for specified populations. The model inputs include the market penetration of pollution sources, pollution source characteristics (e.g., emission rates, source usage rates), building characteristics (e.g., house volume, air exchange rates), and meteorological parameters (e.g., outside temperature). Four geographically distinct regions of the US have been modeled using Monte Carlo and deterministic simulation techniques. Single-source simulations were also conducted. The highest predicted CO and NO/sub 2/ residential concentrations were associated with the winter-time use of unvented gas and kerosene space heaters. The highest predicted respirable suspended particulate concentrations were associated with indoor cigarette smoking and the winter-time use of non-airtight wood stoves, radiant kerosene heaters, convective unvented gas space heaters, and oil forced-air furnaces. Future field studies in this area should (1) fill information gaps identified in this report, and (2) collect information on the macromodel input parameters to properly interpret the results. It is almost more important to measure the parameters that affect indoor concentration than it is to measure the concentrations themselves.

  9. Prediction and analysis of infra and low-frequency noise of upwind horizontal axis wind turbine using statistical wind speed model

    SciTech Connect (OSTI)

    Lee, Gwang-Se; Cheong, Cheolung

    2014-12-15

    Despite increasing concern about low-frequency noise of modern large horizontal-axis wind turbines (HAWTs), few studies have focused on its origin or its prediction methods. In this paper, infra- and low-frequency (the ILF) wind turbine noise are closely examined and an efficient method is developed for its prediction. Although most previous studies have assumed that the ILF noise consists primarily of blade passing frequency (BPF) noise components, these tonal noise components are seldom identified in the measured noise spectrum, except for the case of downwind wind turbines. In reality, since modern HAWTs are very large, during rotation, a single blade of the turbine experiences inflow with variation in wind speed in time as well as in space, breaking periodic perturbations of the BPF. Consequently, this transforms acoustic contributions at the BPF harmonics into broadband noise components. In this study, the ILF noise of wind turbines is predicted by combining Lowson’s acoustic analogy with the stochastic wind model, which is employed to reproduce realistic wind speed conditions. In order to predict the effects of these wind conditions on pressure variation on the blade surface, unsteadiness in the incident wind speed is incorporated into the XFOIL code by varying incident flow velocities on each blade section, which depend on the azimuthal locations of the rotating blade. The calculated surface pressure distribution is subsequently used to predict acoustic pressure at an observing location by using Lowson’s analogy. These predictions are compared with measured data, which ensures that the present method can reproduce the broadband characteristics of the measured low-frequency noise spectrum. Further investigations are carried out to characterize the IFL noise in terms of pressure loading on blade surface, narrow-band noise spectrum and noise maps around the turbine.

  10. Constraint-Based Modeling of Carbon Fixation and the Energetics of Electron Transfer in Geobacter metallireducens

    SciTech Connect (OSTI)

    Feist, AM; Nagarajan, H; Rotaru, AE; Tremblay, PL; Zhang, T; Nevin, KP; Lovley, DR; Zengler, K

    2014-04-24

    Geobacter species are of great interest for environmental and biotechnology applications as they can carry out direct electron transfer to insoluble metals or other microorganisms and have the ability to assimilate inorganic carbon. Here, we report on the capability and key enabling metabolic machinery of Geobacter metallireducens GS-15 to carry out CO2 fixation and direct electron transfer to iron. An updated metabolic reconstruction was generated, growth screens on targeted conditions of interest were performed, and constraint-based analysis was utilized to characterize and evaluate critical pathways and reactions in G. metallireducens. The novel capability of G. metallireducens to grow autotrophically with formate and Fe(III) was predicted and subsequently validated in vivo. Additionally, the energetic cost of transferring electrons to an external electron acceptor was determined through analysis of growth experiments carried out using three different electron acceptors (Fe(III), nitrate, and fumarate) by systematically isolating and examining different parts of the electron transport chain. The updated reconstruction will serve as a knowledgebase for understanding and engineering Geobacter and similar species. Author Summary The ability of microorganisms to exchange electrons directly with their environment has large implications for our knowledge of industrial and environmental processes. For decades, it has been known that microbes can use electrodes as electron acceptors in microbial fuel cell settings. Geobacter metallireducens has been one of the model organisms for characterizing microbe-electrode interactions as well as environmental processes such as bioremediation. Here, we significantly expand the knowledge of metabolism and energetics of this model organism by employing constraint-based metabolic modeling. Through this analysis, we build the metabolic pathways necessary for carbon fixation, a desirable property for industrial chemical production. We

  11. Collaborative Research: Towards Advanced Understanding and Predictive Capability of Climate Change in the Arctic Using a High-Resolution Regional Arctic Climate Model

    SciTech Connect (OSTI)

    Cassano, John

    2013-06-30

    The primary research task completed for this project was the development of the Regional Arctic Climate Model (RACM). This involved coupling existing atmosphere, ocean, sea ice, and land models using the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM) coupler (CPL7). RACM is based on the Weather Research and Forecasting (WRF) atmospheric model, the Parallel Ocean Program (POP) ocean model, the CICE sea ice model, and the Variable Infiltration Capacity (VIC) land model. A secondary research task for this project was testing and evaluation of WRF for climate-scale simulations on the large pan-Arctic model domain used in RACM. This involved identification of a preferred set of model physical parameterizations for use in our coupled RACM simulations and documenting any atmospheric biases present in RACM.

  12. TWENTY FIRST CENTURY UTILITIES, LLC THE MILLION RATE BASE MODEL

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    ... When cost overruns occur in this context, they measure in the hundreds or thousands of ... As societal needs change, our model enables utilities to test innovative customer facing ...

  13. An improved empirical model of electron and ion fluxes at geosynchronous orbit based on upstream solar wind conditions

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Denton, M. H.; Henderson, M. G.; Jordanova, V. K.; Thomsen, M. F.; Borovsky, J. E.; Woodroffe, J.; Hartley, D. P.; Pitchford, D.

    2016-07-27

    In this study, a new empirical model of the electron fluxes and ion fluxes at geosynchronous orbit (GEO) is introduced, based on observations by Los Alamos National Laboratory (LANL) satellites. The model provides flux predictions in the energy range ~1 eV to ~40 keV, as a function of local time, energy, and the strength of the solar wind electric field (the negative product of the solar wind speed and the z component of the magnetic field). Given appropriate upstream solar wind measurements, the model provides a forecast of the fluxes at GEO with a ~1 h lead time. Model predictionsmore » are tested against in-sample observations from LANL satellites and also against out-of-sample observations from the Compact Environmental Anomaly Sensor II detector on the AMC-12 satellite. The model does not reproduce all structure seen in the observations. However, for the intervals studied here (quiet and storm times) the normalized root-mean-square deviation < ~0.3. It is intended that the model will improve forecasting of the spacecraft environment at GEO and also provide improved boundary/input conditions for physical models of the magnetosphere.« less

  14. Development of a GIS Based Dust Dispersion Modeling System.

    SciTech Connect (OSTI)

    Rutz, Frederick C.; Hoopes, Bonnie L.; Crandall, Duard W.; Allwine, K Jerry

    2004-08-12

    With residential areas moving closer to military training sites, the effects upon the environment and neighboring civilians due to dust generated by training exercises has become a growing concern. Under a project supported by the Strategic Environmental Research and Development Program (SERDP) of the Department of Defense, a custom application named DUSTRAN is currently under development that integrates a system of EPA atmospheric dispersion models with the ArcGIS application environment in order to simulate the dust dispersion generated by a planned training maneuver. This integration between modeling system and GIS application allows for the use of real world geospatial data such as terrain, land-use, and domain size as input by the modeling system. Output generated by the modeling system, such as concentration and deposition plumes, can then be displayed upon accurate maps representing the training site. This paper discusses the development of this integration between modeling system and Arc GIS application.

  15. Identification and design of novel polymer-based mechanical transducers: A nano-structural model for thin film indentation

    SciTech Connect (OSTI)

    Villanueva, Joshua; Huang, Qian; Sirbuly, Donald J.

    2014-09-14

    Mechanical characterization is important for understanding small-scale systems and developing devices, particularly at the interface of biology, medicine, and nanotechnology. Yet, monitoring sub-surface forces is challenging with current technologies like atomic force microscopes (AFMs) or optical tweezers due to their probe sizes and sophisticated feedback mechanisms. An alternative transducer design relying on the indentation mechanics of a compressible thin polymer would be an ideal system for more compact and versatile probes, facilitating measurements in situ or in vivo. However, application-specific tuning of a polymer's mechanical properties can be burdensome via experimental optimization. Therefore, efficient transducer design requires a fundamental understanding of how synthetic parameters such as the molecular weight and grafting density influence the bulk material properties that determine the force response. In this work, we apply molecular-level polymer scaling laws to a first order elastic foundation model, relating the conformational state of individual polymer chains to the macroscopic compression of thin film systems. A parameter sweep analysis was conducted to observe predicted model trends under various system conditions and to understand how nano-structural elements influence the material stiffness. We validate the model by comparing predicted force profiles to experimental AFM curves for a real polymer system and show that it has reasonable predictive power for initial estimates of the force response, displaying excellent agreement with experimental force curves. We also present an analysis of the force sensitivity of an example transducer system to demonstrate identification of synthetic protocols based on desired mechanical properties. These results highlight the usefulness of this simple model as an aid for the design of a new class of compact and tunable nanomechanical force transducers.

  16. Demonstrating and Validating a Next Generation Model-Based Controller for

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Fuel Efficient, Low Emissions Diesel Engines | Department of Energy and Validating a Next Generation Model-Based Controller for Fuel Efficient, Low Emissions Diesel Engines Demonstrating and Validating a Next Generation Model-Based Controller for Fuel Efficient, Low Emissions Diesel Engines Fully model-based, practically-mapless engine control concept is viable deer09_allain.pdf (625.73 KB) More Documents & Publications Increased Engine Efficiency via Advancements in Engine Combustion

  17. Approximate Bisimulation-Based Reduction of Power System Dynamic Models

    SciTech Connect (OSTI)

    Stankovic, AM; Dukic, SD; Saric, AT

    2015-05-01

    In this paper we propose approximate bisimulation relations and functions for reduction of power system dynamic models in differential- algebraic (descriptor) form. The full-size dynamic model is obtained by linearization of the nonlinear transient stability model. We generalize theoretical results on approximate bisimulation relations and bisimulation functions, originally derived for a class of constrained linear systems, to linear systems in descriptor form. An algorithm for transient stability assessment is proposed and used to determine whether the power system is able to maintain the synchronism after a large disturbance. Two benchmark power systems are used to illustrate the proposed algorithm and to evaluate the applicability of approximate bisimulation relations and bisimulation functions for reduction of the power system dynamic models.

  18. A nonlocal, ordinary, state-based plasticity model for peridynamics...

    Office of Scientific and Technical Information (OSTI)

    Just as in local theories of plasticity (LTP), state variables are required. It is shown that the resulting constitutive model does not violate the 2nd law of thermodynamics. The ...

  19. Image-based Stokes flow modeling in bulk proppant packs and propped...

    Office of Scientific and Technical Information (OSTI)

    Image-based Stokes flow modeling in bulk proppant packs and propped fractures under high loading stresses Citation Details In-Document Search This content will become publicly ...

  20. Demonstrating Fuel Consumption and Emissions Reductions with Next Generation Model-Based Diesel Engine Control

    Broader source: Energy.gov [DOE]

    Presents a next generation model-based engine controller that incorporates real-time fuel efficiency optimization and tested under fully transient engine and vehicle operating conditions.

  1. Development of Acoustic Model-Based Iterative Reconstruction Technique for Thick-Concrete Imaging

    SciTech Connect (OSTI)

    Almansouri, Hani; Clayton, Dwight A; Kisner, Roger A; Polsky, Yarom; Bouman, Charlie; Santos-Villalobos, Hector J

    2015-01-01

    Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well s health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.

  2. Development of Acoustic Model-Based Iterative Reconstruction Technique for Thick-Concrete Imaging

    SciTech Connect (OSTI)

    Almansouri, Hani; Clayton, Dwight A; Kisner, Roger A; Polsky, Yarom; Bouman, Charlie; Santos-Villalobos, Hector J

    2016-01-01

    Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well's health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.

  3. Nuclear matrix elements for 0??{sup ?}?{sup ?} decays: Comparative analysis of the QRPA, shell model and IBM predictions

    SciTech Connect (OSTI)

    Civitarese, Osvaldo; Suhonen, Jouni

    2013-12-30

    In this work we report on general properties of the nuclear matrix elements involved in the neutrinoless double ?{sup ?} decays (0??{sup ?}?{sup ?} decays) of several nuclei. A summary of the values of the NMEs calculated along the years by the Jyvskyl-La Plata collaboration is presented. These NMEs, calculated in the framework of the quasiparticle random phase approximation (QRPA), are compared with those of the other available calculations, like the Shell Model (ISM) and the interacting boson model (IBA-2)

  4. Evaluation of Clear Sky Models for Satellite-Based Irradiance Estimates

    SciTech Connect (OSTI)

    Sengupta, M.; Gotseff, P.

    2013-12-01

    This report describes an intercomparison of three popular broadband clear sky solar irradiance model results with measured data, as well as satellite-based model clear sky results compared to measured clear sky data. The authors conclude that one of the popular clear sky models (the Bird clear sky model developed by Richard Bird and Roland Hulstrom) could serve as a more accurate replacement for current satellite-model clear sky estimations. Additionally, the analysis of the model results with respect to model input parameters indicates that rather than climatological, annual, or monthly mean input data, higher-time-resolution input parameters improve the general clear sky model performance.

  5. Predictive Technology Development and Crash Energy Management...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Predictive Technology Development and Crash Energy Management Predictive Technology ... Merit Review 2015: Validation of Material Models for Crash Simulation of Automotive Carbon ...

  6. Workshop on Current Issues in Predictive Approaches to Intelligence and Security Analytics: Fostering the Creation of Decision Advantage through Model Integration and Evaluation

    SciTech Connect (OSTI)

    Sanfilippo, Antonio P.

    2010-05-23

    The increasing asymmetric nature of threats to the security, health and sustainable growth of our society requires that anticipatory reasoning become an everyday activity. Currently, the use of anticipatory reasoning is hindered by the lack of systematic methods for combining knowledge- and evidence-based models, integrating modeling algorithms, and assessing model validity, accuracy and utility. The workshop addresses these gaps with the intent of fostering the creation of a community of interest on model integration and evaluation that may serve as an aggregation point for existing efforts and a launch pad for new approaches.

  7. Predicting long-term carbon sequestration in response to CO2 enrichment: How and why do current ecosystem models differ?

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Walker, Anthony P.; Zaehle, Sönke; Medlyn, Belinda E.; De Kauwe, Martin G.; Asao, Shinichi; Hickler, Thomas; Parton, William; Ricciuto, Daniel M.; Wang, Ying -Ping; Wårlind, David; et al

    2015-04-27

    Large uncertainty exists in model projections of the land carbon (C) sink response to increasing atmospheric CO2. Free-Air CO2 Enrichment (FACE) experiments lasting a decade or more have investigated ecosystem responses to a step change in atmospheric CO2 concentration. To interpret FACE results in the context of gradual increases in atmospheric CO2 over decades to centuries, we used a suite of seven models to simulate the Duke and Oak Ridge FACE experiments extended for 300 years of CO2 enrichment. We also determine key modeling assumptions that drive divergent projections of terrestrial C uptake and evaluate whether these assumptions can bemore » constrained by experimental evidence. All models simulated increased terrestrial C pools resulting from CO2 enrichment, though there was substantial variability in quasi-equilibrium C sequestration and rates of change. In two of two models that assume that plant nitrogen (N) uptake is solely a function of soil N supply, the net primary production response to elevated CO2 became progressively N limited. In four of five models that assume that N uptake is a function of both soil N supply and plant N demand, elevated CO2 led to reduced ecosystem N losses and thus progressively relaxed nitrogen limitation. Many allocation assumptions resulted in increased wood allocation relative to leaves and roots which reduced the vegetation turnover rate and increased C sequestration. Additionally, self-thinning assumptions had a substantial impact on C sequestration in two models. As a result, accurate representation of N process dynamics (in particular N uptake), allocation, and forest self-thinning is key to minimizing uncertainty in projections of future C sequestration in response to elevated atmospheric CO2.« less

  8. Individualized Positron Emission Tomography–Based Isotoxic Accelerated Radiation Therapy Is Cost-Effective Compared With Conventional Radiation Therapy: A Model-Based Evaluation

    SciTech Connect (OSTI)

    Bongers, Mathilda L.; Coupé, Veerle M.H.; De Ruysscher, Dirk; Oberije, Cary; Lambin, Philippe; Uyl-de Groot, Cornelia A.

    2015-03-15

    Purpose: To evaluate long-term health effects, costs, and cost-effectiveness of positron emission tomography (PET)-based isotoxic accelerated radiation therapy treatment (PET-ART) compared with conventional fixed-dose CT-based radiation therapy treatment (CRT) in non-small cell lung cancer (NSCLC). Methods and Materials: Our analysis uses a validated decision model, based on data of 200 NSCLC patients with inoperable stage I-IIIB. Clinical outcomes, resource use, costs, and utilities were obtained from the Maastro Clinic and the literature. Primary model outcomes were the difference in life-years (LYs), quality-adjusted life-years (QALYs), costs, and the incremental cost-effectiveness and cost/utility ratio (ICER and ICUR) of PET-ART versus CRT. Model outcomes were obtained from averaging the predictions for 50,000 simulated patients. A probabilistic sensitivity analysis and scenario analyses were carried out. Results: The average incremental costs per patient of PET-ART were €569 (95% confidence interval [CI] €−5327-€6936) for 0.42 incremental LYs (95% CI 0.19-0.61) and 0.33 QALYs gained (95% CI 0.13-0.49). The base-case scenario resulted in an ICER of €1360 per LY gained and an ICUR of €1744 per QALY gained. The probabilistic analysis gave a 36% probability that PET-ART improves health outcomes at reduced costs and a 64% probability that PET-ART is more effective at slightly higher costs. Conclusion: On the basis of the available data, individualized PET-ART for NSCLC seems to be cost-effective compared with CRT.

  9. Application for managing model-based material properties for simulation-based engineering

    DOE Patents [OSTI]

    Hoffman, Edward L.

    2009-03-03

    An application for generating a property set associated with a constitutive model of a material includes a first program module adapted to receive test data associated with the material and to extract loading conditions from the test data. A material model driver is adapted to receive the loading conditions and a property set and operable in response to the loading conditions and the property set to generate a model response for the material. A numerical optimization module is adapted to receive the test data and the model response and operable in response to the test data and the model response to generate the property set.

  10. Mathematical modeling of the lithium deposition overcharge reaction in lithium-ion batteries using carbon-based negative electrodes

    SciTech Connect (OSTI)

    Arora, P.; Doyle, M.; White, R.E.

    1999-10-01

    Two major issues facing lithium-ion battery technology are safety and capacity grade during cycling. A significant amount of work has been done to improve the cycle life and to reduce the safety problems associated with these cells. This includes newer and better electrode materials, lower-temperature shutdown separators, nonflammable or self-extinguishing electrolytes, and improved cell designs. The goal of this work is to predict the conditions for the lithium deposition overcharge reaction on the negative electrode (graphite and coke) and to investigate the effect of various operating conditions, cell designs and charging protocols on the lithium deposition side reaction. The processes that lead to capacity fading affect severely the cycle life and rate behavior of lithium-ion cells. One such process is the overcharge of the negative electrode causing lithium deposition, which can lead to capacity losses including a loss of active lithium and electrolyte and represents a potential safety hazard. A mathematical model is presented to predict lithium deposition on the negative electrode under a variety of operating conditions. The Li{sub x}C{sub 6} {vert{underscore}bar} 1 M LiPF{sub 6}, 2:1 ethylene carbonate/dimethyl carbonate, poly(vinylidene fluoride-hexafluoropropylene) {vert{underscore}bar} LiMn{sub 2}O{sub 4} cell is simulated to investigate the influence of lithium deposition on the charging behavior of intercalation electrodes. The model is used to study the effect of key design parameters (particle size, electrode thickness, and mass ratio) on the lithium deposition overcharge reaction. The model predictions are compared for coke and graphite-based negative electrodes. The cycling behavior of these cells is simulated before and after overcharge to understand the hazards and capacity fade problems, inherent in these cells, can be minimized.

  11. Frit Development Efforts for Sludge Batch 4 (SB4): Model-Based Assessments

    SciTech Connect (OSTI)

    Peeler, D. K.; Edwards, T. B.

    2005-03-05

    The model-based assessments of nominal Sludge Batch 4 (SB4) compositions suggest that a viable frit candidate does not appear to be a limiting factor as the Closure Business Unit (CBU) considers various tank blending options and/or washing strategies. This statement is based solely on the projected operating windows derived from model predictions and does not include assessments of SO{sub 4} solubility or melt rate issues. The viable frit candidates covered a range of Na{sub 2}O concentrations (from 8% to 13%--including Frit 418 and Frit 320) using a ''sliding Na{sub 2}O scale'' concept (i.e., 1% increase in Na{sub 2}O being balanced by a 1% reduction in SiO{sub 2}) which effectively balances the alkali content of the incoming sludge with that in the frit to maintain and/or increase the projected operating window size while potentially leading to improved melt rate and/or waste loadings. This strategy or approach allows alternative tank blending strategies and/or different washing scenarios to be considered and accounted for in an effective manner without wholesale changes to the frit composition. In terms of projected operating windows, in general, the sludge/frit systems evaluated resulted in waste loading intervals from 25 to the mid-40%'s or even the mid-50%'s. The results suggest that a single frit could be selected for use with all 20 options which indicates some degree of frit robustness with respect to sludge compositional variation. In fact, use of Frit 418 or Frit 320 (the ''cornerstone'' frits given previous processing experience in the Defense Waste Processing Facility (DWPF)) are plausible for most (if not all) options being considered. However, the frit selection process also needs to consider potential processing issues such as melt rate. Based on historical trends between melt rate and total alkali content, one may elect to use the frit with the highest alkali content that still yields an acceptable operating window. However, other constraints may

  12. Normalized Elution Time Prediction Utility

    Energy Science and Technology Software Center (OSTI)

    2011-02-17

    This program is used to compute the predicted normalized elution time (NET) for a list of peptide sequences. It includes the Kangas/Petritis neural network trained model, the Krokhin hydrophobicity model, and the Mant hydrophobicity model. In addition, it can compute the predicted strong cation exchange (SCX) fraction (on a 0 to 1 scale) in which a given peptide will appear.

  13. The potential use of Chernobyl fallout data to test and evaluate the predictions of environmental radiological assessment models

    SciTech Connect (OSTI)

    Richmond, C.R.; Hoffman, F.O.; Blaylock, B.G.; Eckerman, K.F.; Lesslie, P.A.; Miller, C.W.; Ng, Y.C.; Till, J.E.

    1988-06-01

    The objectives of the Model Validation Committee were to collaborate with US and foreign scientists to collect, manage, and evaluate data for identifying critical research issues and data needs to support an integrated assessment of the Chernobyl nuclear accident; test environmental transport, human dosimetric, and health effects models against measured data to determine their efficacy in guiding decisions on protective actions and in estimating exposures to populations and individuals following a nuclear accident; and apply Chernobyl data to quantifications of key processes governing the environmental transport, fate and effects of radionuclides and other trace substances. 55 refs.

  14. Security of statistical data bases: invasion of privacy through attribute correlational modeling

    SciTech Connect (OSTI)

    Palley, M.A.

    1985-01-01

    This study develops, defines, and applies a statistical technique for the compromise of confidential information in a statistical data base. Attribute Correlational Modeling (ACM) recognizes that the information contained in a statistical data base represents real world statistical phenomena. As such, ACM assumes correlational behavior among the database attributes. ACM proceeds to compromise confidential information through creation of a regression model, where the confidential attribute is treated as the dependent variable. The typical statistical data base may preclude the direct application of regression. In this scenario, the research introduces the notion of a synthetic data base, created through legitimate queries of the actual data base, and through proportional random variation of responses to these queries. The synthetic data base is constructed to resemble the actual data base as closely as possible in a statistical sense. ACM then applies regression analysis to the synthetic data base, and utilizes the derived model to estimate confidential information in the actual database.

  15. SU-E-QI-13: Predictable Models for Radio-Sensitizing Agent Kinetics: Application to Stereotactic Synchrotron Radiation Therapy

    SciTech Connect (OSTI)

    Obeid, L; Schmitt, M; Esteve, F; Adam, J

    2014-06-15

    Purpose: Iodine-enhanced radiotherapy is an innovative treatment combining the selective accumulation of an iodinated contrast agent in brain tumors with irradiations using monochromatic medium energy x-rays. The radiation dose enhancement depends on the time course of iodine in the tumors. A prolonged CT scanning (∼30 min) is required to follow-up iodine kinetics for recruited patients. This protocol could lead to substantial radiation dose to the patient. A novel method is proposed to reduce the acquisition time. Methods: 12 patients received an intravenous bolus of iodinated contrast agent, followed by a steady-state infusion to ensure stable intra-tumoral amounts of iodine during the treatment. Absolute iodine concentrations (IC) were derived from 40 multi-slice dynamic conventional CT images of the brain. The impulse response function (IRF) to the bolus was estimated using the adiabatic approximation of the Johnson and Wilson's model. The arterial input function (AIF) of the steady-state infusion was fitted with several models: Gamma, Gamma with recirculation and hybrid. Estimated IC were calculated by convolving the IRF with the modeled AIF and were compared to the measured data. Results: The gamma variate function was not relevant to model the AIF due to high differences with the measured AIF. The hybrid and the gamma with recirculation models provided differences below 8% during the whole acquisition time. The absolute difference between the measured and the estimated IC was lower than 0.5 mg/ml, which corresponds to 5% of dose enhancement error. Conclusion: The proposed method allows a good estimation of the iodine time course with reduced scanning delays (3 instead of 30 min) and dose to the patient. The results suggest that the dose errors may stay within the radiotherapy standards.

  16. Sensitization and IGSCC susceptibility prediction in stainless steel pipe weldments

    SciTech Connect (OSTI)

    Atteridge, D.G.; Simmons, J.W.; Li, Ming ); Bruemmer, S.M. )

    1991-11-01

    An analytical model, based on prediction of chromium depletion, has been developed for predicting thermomechanical effects on austenitic stainless steel intergranular stress corrosion cracking (IGSCC) susceptibility. Model development and validation is based on sensitization development analysis of over 30 Type 316 and 304 stainless steel heats. The data base included analysis of deformation effects on resultant sensitization development. Continuous Cooling sensitization behavior is examined and modelled with and without strain. Gas tungsten are (GTA) girth pipe weldments are also characterized by experimental measurements of heat affected zone (HAZ) temperatures, strains and sensitization during/after each pass; pass by pass thermal histories are also predicted. The model is then used to assess pipe chemistry changes on IGSCC resistance.

  17. Magnetic BiMn-α phase synthesis prediction: First-principles calculation, thermodynamic modeling and nonequilibrium chemical partitioning

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Zhou, S. H.; Liu, C.; Yao, Y. X.; Du, Y.; Zhang, L. J.; Wang, C. -Z.; Ho, K. -M.; Kramer, M. J.

    2016-04-29

    BiMn-α is promising permanent magnet. Due to its peritectic formation feature, there is a synthetic challenge to produce single BiMn-α phase. The objective of this study is to assess driving force for crystalline phase pathways under far-from-equilibrium conditions. First-principles calculations with Hubbard U correction are performed to provide a robust description of the thermodynamic behavior. The energetics associated with various degrees of the chemical partitioning are quantified to predict temperature, magnetic field, and time dependence of the phase selection. By assessing the phase transformation under the influence of the chemical partitioning, temperatures, and cooling rate from our calculations, we suggestmore » that it is possible to synthesize the magnetic BiMn-α compound in a congruent manner by rapid solidification. The external magnetic field enhances the stability of the BiMn-α phase. In conclusion, the compositions of the initial compounds from these highly driven liquids can be far from equilibrium.« less

  18. A knowledge based model of electric utility operations. Final report

    SciTech Connect (OSTI)

    1993-08-11

    This report consists of an appendix to provide a documentation and help capability for an analyst using the developed expert system of electric utility operations running in CLIPS. This capability is provided through a separate package running under the WINDOWS Operating System and keyed to provide displays of text, graphics and mixed text and graphics that explain and elaborate on the specific decisions being made within the knowledge based expert system.

  19. Feature Based Tolerancing Product Modeling V4.1

    Energy Science and Technology Software Center (OSTI)

    2001-11-30

    FBTol is a component technology in the form of software linkable library. The purpose of FBToI is to augment the shape of a nominal solid model with an explicit representation of a product’s tolerances and other non-shape attributes. This representation enforces a complete and unambiguous definition of non-shape information, permits an open architecture to dynamically create, modify, delete, and query tolerance information, and incorporates verify and checking algorithms to assure the quality of the tolerancemore » design.« less

  20. Phase formation sequences in the silicon-phosphorous system : determined by in-situ synchrotron andj conventional x-ray diffraction measurements and predicted by a theoretical model.

    SciTech Connect (OSTI)

    Carlsson, J. R. A.; Clevenger, L.; Madsen, L. D.; Hultman, L.; Li, X.-H.; Jordan-Sweet, J.; Lavoie, C.; Roy, R. A.; Cabral, C., Jr.; Morales, G.; Ludwig, K. L.; Stephenson, G. B.; Hentzell, H. T. G.; Materials Science Division; Linkoeping Univ.; IBM T. J. Watson Research Center; Boston Univ.

    1997-01-01

    The phase formation sequences of Si-P alloy thin films with P concentrations between 20 and 44 at. % have been studied. The samples were annealed at progressively higher temperatures and the newly formed phases were identified both after each annealing step by ex-situ conventional X-ray diffraction (XRD) and continuously by in-situ synchrotron XRD. It was found that Si was the only phase to form in a sample with 20 at.% P since the evaporation of P at the crystallization temperature prevented phosphides from forming. For a sample with 30at.% P, the Si{sub 12}P{sub 5} phase formed prior to the SiP phase. For samples with 35 and 44at.%P, the formation of SiP preceded the formation of the Si{sub 12}P{sub 5} phase. The experimentally determined phase formation sequences were successfully predicted by a proposed model. According to the model, the first and second crystalline phases to form are those with the lowest and next-lowest crystallization temperatures of the competing compounds predicted by the Gibbs free-energy diagram.

  1. What are the Starting Points? Evaluating Base-Year Assumptions in the Asian Modeling Exercise

    SciTech Connect (OSTI)

    Chaturvedi, Vaibhav; Waldhoff, Stephanie; Clarke, Leon E.; Fujimori, Shinichiro

    2012-12-01

    A common feature of model inter-comparison efforts is that the base year numbers for important parameters such as population and GDP can differ substantially across models. This paper explores the sources and implications of this variation in Asian countries across the models participating in the Asian Modeling Exercise (AME). Because the models do not all have a common base year, each team was required to provide data for 2005 for comparison purposes. This paper compares the year 2005 information for different models, noting the degree of variation in important parameters, including population, GDP, primary energy, electricity, and CO2 emissions. It then explores the difference in these key parameters across different sources of base-year information. The analysis confirms that the sources provide different values for many key parameters. This variation across data sources and additional reasons why models might provide different base-year numbers, including differences in regional definitions, differences in model base year, and differences in GDP transformation methodologies, are then discussed in the context of the AME scenarios. Finally, the paper explores the implications of base-year variation on long-term model results.

  2. Predictive model for the determination of the economic feasibility of construction and demolition waste recycling in the Air Force. Master's thesis

    SciTech Connect (OSTI)

    Dixon, B.L.

    1993-09-01

    This study created a model to be used at a CONUS Air Force base to determine the economic feasibility of Construction and Demolition (CD) waste recycling. Three areas investigated to develop this model: the methods to determine amounts and types of CD waste generated at a specific location, the markets for recycled CD wastes, and the recycling methods currently available. From this data, gathered through records searches and interviews, a procedure was developed to perform cost/benefit analyses on the available recycling options. A model was then created based on these calculations which can arm a manager with information to either support or reject a recycling program by indicating cost savings or losses from recycling CD waste. Also, the model aids managers in determining the approximate quantities of recyclable materials being generated, which could be valuable in reaching base recycling goals. To demonstrate the model, the feasibility of recycling CD waste at Hill AFB, Utah in 1994 was evaluated. In addition to determining recycling feasibility, a method was presented to perform sensitivity analyses on the base-specific input variables. This procedure can help determine when it will become feasible to create a CD waste recycling program.

  3. Integration of a constraint-based metabolic model of Brassica napus developing seeds with 13C-metabolic flux analysis

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Hay, Jordan O.; Shi, Hai; Heinzel, Nicolas; Hebbelmann, Inga; Rolletschek, Hardy; Schwender, Jorg

    2014-12-19

    The use of large-scale or genome-scale metabolic reconstructions for modeling and simulation of plant metabolism and integration of those models with large-scale omics and experimental flux data is becoming increasingly important in plant metabolic research. Here we report an updated version of bna572, a bottom-up reconstruction of oilseed rape (Brassica napus L.; Brassicaceae) developing seeds with emphasis on representation of biomass-component biosynthesis. New features include additional seed-relevant pathways for isoprenoid, sterol, phenylpropanoid, flavonoid, and choline biosynthesis. Being now based on standardized data formats and procedures for model reconstruction, bna572+ is available as a COBRA-compliant Systems Biology Markup Language (SBML) modelmore » and conforms to the Minimum Information Requested in the Annotation of Biochemical Models (MIRIAM) standards for annotation of external data resources. Bna572+ contains 966 genes, 671 reactions, and 666 metabolites distributed among 11 subcellular compartments. It is referenced to the Arabidopsis thaliana genome, with gene-protein-reaction (GPR) associations resolving subcellular localization. Detailed mass and charge balancing and confidence scoring were applied to all reactions. Using B. napus seed specific transcriptome data, expression was verified for 78% of bna572+ genes and 97% of reactions. Alongside bna572+ we also present a revised carbon centric model for 13C-Metabolic Flux Analysis (13C-MFA) with all its reactions being referenced to bna572+ based on linear projections. By integration of flux ratio constraints obtained from 13C-MFA and by elimination of infinite flux bounds around thermodynamically infeasible loops based on COBRA loopless methods, we demonstrate improvements in predictive power of Flux Variability Analysis (FVA). In conclusion, using this combined approach we characterize the difference in metabolic flux of developing seeds of two B. napus genotypes contrasting in starch

  4. Physiologically based kinetic modeling of bioactivation and detoxification of the alkenylbenzene methyleugenol in human as compared with rat

    SciTech Connect (OSTI)

    Al-Subeihi, Ala' A.A.; Spenkelink, Bert; Punt, Ans; Boersma, Marelle G.; Bladeren, Peter J. van; Rietjens, Ivonne M.C.M.

    2012-05-01

    This study defines a physiologically based kinetic (PBK) model for methyleugenol (ME) in human based on in vitro and in silico derived parameters. With the model obtained, bioactivation and detoxification of methyleugenol (ME) at different doses levels could be investigated. The outcomes of the current model were compared with those of a previously developed PBK model for methyleugenol (ME) in male rat. The results obtained reveal that formation of 1′-hydroxymethyleugenol glucuronide (1′HMEG), a major metabolic pathway in male rat liver, appears to represent a minor metabolic pathway in human liver whereas in human liver a significantly higher formation of 1′-oxomethyleugenol (1′OME) compared with male rat liver is observed. Furthermore, formation of 1′-sulfooxymethyleugenol (1′HMES), which readily undergoes desulfonation to a reactive carbonium ion (CA) that can form DNA or protein adducts (DA), is predicted to be the same in the liver of both human and male rat at oral doses of 0.0034 and 300 mg/kg bw. Altogether despite a significant difference in especially the metabolic pathways of the proximate carcinogenic metabolite 1′-hydroxymethyleugenol (1′HME) between human and male rat, the influence of species differences on the ultimate overall bioactivation of methyleugenol (ME) to 1′-sulfooxymethyleugenol (1′HMES) appears to be negligible. Moreover, the PBK model predicted the formation of 1′-sulfooxymethyleugenol (1′HMES) in the liver of human and rat to be linear from doses as high as the benchmark dose (BMD{sub 10}) down to as low as the virtual safe dose (VSD). This study shows that kinetic data do not provide a reason to argue against linear extrapolation from the rat tumor data to the human situation. -- Highlights: ► A PBK model is made for bioactivation and detoxification of methyleugenol in human. ► Comparison to the PBK model in male rat revealed species differences. ► PBK results support linear extrapolation from high to low

  5. Reaction-based reactive transport modeling of Fe(III)

    SciTech Connect (OSTI)

    Kemner, K.M.; Kelly, S.D.; Burgos, Bill; Roden, Eric

    2006-06-01

    This research project (started Fall 2004) was funded by a grant to Argonne National Laboratory, The Pennsylvania State University, and The University of Alabama in the Integrative Studies Element of the NABIR Program (DE-FG04-ER63914/63915/63196). Dr. Eric Roden, formerly at The University of Alabama, is now at the University of Wisconsin, Madison. Our project focuses on the development of a mechanistic understanding and quantitative models of coupled Fe(III)/U(VI) reduction in FRC Area 2 sediments. This work builds on our previous studies of microbial Fe(III) and U(VI) reduction, and is directly aligned with the Scheibe et al. NABIR FRC Field Project at Area 2.

  6. APT Blanket System Model Based on Initial Conceptual Design - Integrated 1D TRAC System Model

    SciTech Connect (OSTI)

    Hamm, L.L.

    1998-10-07

    This report documents the approaches taken in establishing a 1-dimensional integrated blanket system model using the TRAC code, developed by Los Alamos National Laboratory.

  7. Relative potency based on hepatic enzyme induction predicts immunosuppressive effects of a mixture of PCDDS/PCDFS and PCBS

    SciTech Connect (OSTI)

    Smialowicz, R.J.; DeVito, M.J. Williams, W.C.; Birnbaum, L.S.

    2008-03-15

    The toxic equivalency factor (TEF) approach was employed to compare immunotoxic potency of mixtures containing polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans and polychlorinated biphenyls relative to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), using the antibody response to sheep erythrocytes (SRBC). Mixture-1 (MIX-1) contained TCDD, 1,2,3,7,8-pentachlorodibenzo-p-dioxin (PeCDD), 2,3,7,8-tetrachlorodibenzofuran (TCDF), 1,2,3,7,8-pentachlorodibenzofuran (1-PeCDF), 2,3,4,7,8-pentachlorodibenzofuran (4-PeCDF), and 1,2,3,4,6,7,8,9-octachlorodibenzofuran (OCDF). Mixture-2 (MIX-2) contained MIX-1 and the following PCBs, 3,3',4,4'-tetrachlorobiphenyl (IUPAC No. 77), 3,3',4,4',5-pentachlorobiphenyl (126), 3,3',4,4',5,5N-hexachlorobiphenyl (169), 2,3,3',4,4'-pentachlorobiphenyl (105), 2,3',4,4',5-pentachlorobiphenyl (118), and 2,3,3',4,4',5-hexachlorobiphenyl (156). The mixture compositions were based on relative chemical concentrations in food and human tissues. TCDD equivalents (TEQ) of the mixture were estimated using relative potency factors from hepatic enzyme induction in mice [DeVito, M.J., Diliberto, J.J., Ross, D.G., Menache, M.G., Birnbaum, L.S., 1997. Dose-response relationships for polyhalogenated dioxins and dibenzofurans following subchronic treatment in mice. I .CYP1A1 and CYP1A2 enzyme activity in liver, lung and skin. Toxicol. Appl. Pharmacol. 130, 197-208; DeVito, M.J., Menache, G., Diliberto, J.J., Ross, D.G., Birnbaum L.S., 2000. Dose-response relationships for induction of CYP1A1 and CYP1A2 enzyme activity in liver, lung, and skin in female mice following subchronic exposure to polychlorinated biphenyls. Toxicol. Appl. Pharmacol. 167, 157-172] Female mice received 0, 1.5, 15, 150 or 450 ng TCDD/kg/day or approximately 0, 1.5, 15, 150 or 450 ng TEQ/kg/day of MIX-1 or MIX-2 by gavage 5 days per week for 13 weeks. Mice were immunized 3 days after the last exposure and 4 days later, body, spleen, thymus, and liver weights were measured

  8. A novel multi-model neuro-fuzzy-based MPPT for three-phase grid-connected photovoltaic system

    SciTech Connect (OSTI)

    Chaouachi, Aymen; Kamel, Rashad M.; Nagasaka, Ken

    2010-12-15

    This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three multi-layered feed forwarded Artificial Neural Networks (ANN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated ANN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and nonlinear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network and the Perturb and Observe (P and O) algorithm dispositive. (author)

  9. Near-edge band structures and band gaps of Cu-based semiconductors predicted by the modified Becke-Johnson potential plus an on-site Coulomb U

    SciTech Connect (OSTI)

    Zhang, Yubo; Zhang, Jiawei; Wang, Youwei; Gao, Weiwei; Abtew, Tesfaye A.; Zhang, Peihong E-mail: wqzhang@mail.sic.ac.cn; Beijing Computational Science Research Center, Beijing 100084 ; Zhang, Wenqing E-mail: wqzhang@mail.sic.ac.cn; School of Chemistry and Chemical Engineering and Sate Key Laboratory of Coordination Chemistry, Nanjing University, Jiangsu 210093

    2013-11-14

    Diamond-like Cu-based multinary semiconductors are a rich family of materials that hold promise in a wide range of applications. Unfortunately, accurate theoretical understanding of the electronic properties of these materials is hindered by the involvement of Cu d electrons. Density functional theory (DFT) based calculations using the local density approximation or generalized gradient approximation often give qualitative wrong electronic properties of these materials, especially for narrow-gap systems. The modified Becke-Johnson (mBJ) method has been shown to be a promising alternative to more elaborate theory such as the GW approximation for fast materials screening and predictions. However, straightforward applications of the mBJ method to these materials still encounter significant difficulties because of the insufficient treatment of the localized d electrons. We show that combining the promise of mBJ potential and the spirit of the well-established DFT + U method leads to a much improved description of the electronic structures, including the most challenging narrow-gap systems. A survey of the band gaps of about 20 Cu-based semiconductors calculated using the mBJ + U method shows that the results agree with reliable values to within 0.2 eV.

  10. Mechanistically-Based Field-Scale Models of Uranium Biogeochemistry from Upscaling Pore-Scale Experiments and Models

    SciTech Connect (OSTI)

    Tim Scheibe; Alexandre Tartakovsky; Brian Wood; Joe Seymour

    2007-04-19

    Effective environmental management of DOE sites requires reliable prediction of reactive transport phenomena. A central issue in prediction of subsurface reactive transport is the impact of multiscale physical, chemical, and biological heterogeneity. Heterogeneity manifests itself through incomplete mixing of reactants at scales below those at which concentrations are explicitly defined (i.e., the numerical grid scale). This results in a mismatch between simulated reaction processes (formulated in terms of average concentrations) and actual processes (controlled by local concentrations). At the field scale, this results in apparent scale-dependence of model parameters and inability to utilize laboratory parameters in field models. Accordingly, most field modeling efforts are restricted to empirical estimation of model parameters by fitting to field observations, which renders extrapolation of model predictions beyond fitted conditions unreliable. The objective of this project is to develop a theoretical and computational framework for (1) connecting models of coupled reactive transport from pore-scale processes to field-scale bioremediation through a hierarchy of models that maintain crucial information from the smaller scales at the larger scales; and (2) quantifying the uncertainty that is introduced by both the upscaling process and uncertainty in physical parameters. One of the challenges of addressing scale-dependent effects of coupled processes in heterogeneous porous media is the problem-specificity of solutions. Much effort has been aimed at developing generalized scaling laws or theories, but these require restrictive assumptions that render them ineffective in many real problems. We propose instead an approach that applies physical and numerical experiments at small scales (specifically the pore scale) to a selected model system in order to identify the scaling approach appropriate to that type of problem. Although the results of such studies will

  11. SU-E-J-258: Prediction of Cervical Cancer Treatment Response Using Radiomics Features Based On F18-FDG Uptake in PET Images

    SciTech Connect (OSTI)

    Altazi, B; Fernandez, D; Zhang, G; Biagioli, M; Moros, E; Moffitt, H. Lee

    2015-06-15

    Purpose: Radiomics have shown potential for predicting treatment outcomes in several body sites. This study investigated the correlation between PET Radiomics features and treatment response of cervical cancer outcomes. Methods: our dataset consisted of a cohort of 79 patients diagnosed with cervical cancer, FIGO stage IB-IVA, age range 25–86 years, (median age at diagnosis: 50 years) all treated between: 2009–14 with external beam radiation therapy to a dose range between: 45–50.4 Gy (median= 45 Gy), concurrent cisplatin chemotherapy and MRI-based brachytherapy to a dose of 20–30 Gy (median= 28 Gy). Metabolic Tumor Volume (MTV) in patient’s primary site was delineated on pretreatment PET/CT by two board certified Radiation Oncologists. The features extracted from each patient’s volume were: 26 Co-occurrence matrix (COM) Feature, 11 Run-Length Matrix (RLM), 11 Gray Level Size Zone Matrix (GLSZM) and 33 Intensity-based features (IBF). The treatment outcome was divided based on the last follow up status into three classes: No Evidence of Disease (NED), Alive with Disease (AWD) and Dead of Disease (DOD). The ability for the radiomics features to differentiate between the 3 treatments outcome categories were assessed by One-Way ANOVA test with p-value < 0.05 was to be statistically significant. The results from the analysis were compared with the ones obtained previously for standard Uptake Value (SUV). Results: Based on patients last clinical follow-up; 52 showed NED, 17 AWD and 10 DOD. Radiomics Features were able to classify the patients based on their treatment response. A parallel analysis was done for SUV measurements for comparison. Conclusion: Radiomics features were able to differentiate between the three different classes of treatment outcomes. However, most of the features were only able to differentiate between NED and DOD class. Also, The ability or radiomics features to differentiate types of response were more significant than SUV.

  12. Chemical structures of low-pressure premixed methylcyclohexane flames as benchmarks for the development of a predictive combustion chemistry model

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Skeen, Scott A.; Yang, Bin; Jasper, Ahren W.; Pitz, William J.; Hansen, Nils

    2011-11-14

    The chemical compositions of three low-pressure premixed flames of methylcyclohexane (MCH) are investigated with the emphasis on the chemistry of MCH decomposition and the formation of aromatic species, including benzene and toluene. The flames are stabilized on a flat-flame (McKenna type) burner at equivalence ratios of φ = 1.0, 1.75, and 1.9 and at low pressures between 15 Torr (= 20 mbar) and 30 Torr (= 40 mbar). The complex chemistry of MCH consumption is illustrated in the experimental identification of several C7H12, C7H10, C6H12, and C6H10 isomers sampled from the flames as a function of distance from the burner.more » Three initiation steps for MCH consumption are discussed: ring-opening to heptenes and methyl-hexenes (isomerization), methyl radical loss yielding the cyclohexyl radical (dissociation), and H abstraction from MCH. Mole fraction profiles as a function of distance from the burner for the C7 species supplemented by theoretical calculations are presented, indicating that flame structures resulting in steeper temperature gradients and/or greater peak temperatures can lead to a relative increase in MCH consumption through the dissociation and isomerization channels. Trends observed among the stable C6 species as well as 1,3-pentadiene and isoprene also support this conclusion. Relatively large amounts of toluene and benzene are observed in the experiments, illustrating the importance of sequential H-abstraction steps from MCH to toluene and from cyclohexyl to benzene. Furthermore, modeled results using the detailed chemical model of Pitz et al. (Proc. Combust. Inst.2007, 31, 267–275) are also provided to illustrate the use of these data as a benchmark for the improvement or future development of a MCH mechanism.« less

  13. Steady state and dynamic modeling of a packed bed reactor for the partial oxidation of methanol to formaldehyde: experimental results compared with model predictions

    SciTech Connect (OSTI)

    Schwedock, M.J.; Windes, L.C.; Ray, W.H.

    1985-01-01

    Heterogeneous and pseudohomogeneous models are compared to experimental data from a packed bed reactor for the partical oxidation of methanol to formaldehyde over an iron oxide-molybdenum oxide catalyst. Heat transfer parameters which were successful in matching data from experiments without reaction were not successful in matching temperature data from experiments with reaction. This made it necessary to decrease the fluid radial heat transfer to obtain good fit. A good fit was obtained for steady state composition profiles by optimizing selected frequency factors and the activation energy for methanol. A redox rate expression for the oxidation of formaldehyde to carbon monoxide was proposed since a simple first-order rate expression did not fit the data. The pseudohomogeneous model gave results similar to the heterogeneous model for both steady state and dynamic experiments and has been recommended for future experimental state estimation and control studies. 21 refs., 31 figs., 6 tabs.

  14. A Physically Based Framework for Modelling the Organic Fractionation of Sea Spray Aerosol from Bubble Film Langmuir Equilibria

    SciTech Connect (OSTI)

    Burrows, Susannah M.; Ogunro, O.; Frossard, Amanda; Russell, Lynn M.; Rasch, Philip J.; Elliott, S.

    2014-12-19

    The presence of a large fraction of organic matter in primary sea spray aerosol (SSA) can strongly affect its cloud condensation nuclei activity and interactions with marine clouds. Global climate models require new parameterizations of the SSA composition in order to improve the representation of these processes. Existing proposals for such a parameterization use remotely-sensed chlorophyll-a concentrations as a proxy for the biogenic contribution to the aerosol. However, both observations and theoretical considerations suggest that existing relationships with chlorophyll-a, derived from observations at only a few locations, may not be representative for all ocean regions. We introduce a novel framework for parameterizing the fractionation of marine organic matter into SSA based on a competitive Langmuir adsorption equilibrium at bubble surfaces. Marine organic matter is partitioned into classes with differing molecular weights, surface excesses, and Langmuir adsorption parameters. The classes include a lipid-like mixture associated with labile dissolved organic carbon (DOC), a polysaccharide-like mixture associated primarily with semi-labile DOC, a protein-like mixture with concentrations intermediate between lipids and polysaccharides, a processed mixture associated with recalcitrant surface DOC, and a deep abyssal humic-like mixture. Box model calculations have been performed for several cases of organic adsorption to illustrate the underlying concepts. We then apply the framework to output from a global marine biogeochemistry model, by partitioning total dissolved organic carbon into several classes of macromolecule. Each class is represented by model compounds with physical and chemical properties based on existing laboratory data. This allows us to globally map the predicted organic mass fraction of the nascent submicron sea spray aerosol. Predicted relationships between chlorophyll-\\textit{a} and organic fraction are similar to existing empirical

  15. Geology of offshore southern Namibia: Evidence from tectonic and basin-fill modeling based on modern seismic data

    SciTech Connect (OSTI)

    Houghton, M.L.; Peacock, D.N. )

    1993-09-01

    License 2815 is located offshore southern Namibia between Cape Dernberg and the South African border, approximately 50 km east of the 1974 Kudu gas discovery. Interactive workstation modeling of modern two-dimensional seismic data from the License area provides an improved understanding of the geology and tectonic history of this unexplored region. Although presently a broad submarine shelf influenced by late Cretaceous-Tertiary deltaic sedimentation from the Orange River, Interpretation based on modern seismic coverage has resulted in the recognition of a Late Jurassic-Early Cretaceous rift complex associated with the initial opening of the Atlantic Ocean. Geologic modeling suggests that a seismically-identified elongate rift localized along a major westward-dipping bounding fault may contain significant thicknesses of Neocomian( ) clastic sediments. Barremian-Aptian marine flooding of this area followed the rifting episode. Mixed marine and deltaic sedimentation has dominated the region since the middle Aptian. Palinspastic restorations of depth-converted seismic lines have helped to unravel the episodic tectonic history of rifting in this area. Input of geologic parameters, including relative sea level changes and sedimentation rates, has yielded computer-derived basin-fill models, which have in turn been integrated with the local tectonic model to make lithology predictions.

  16. A full-spectral Bayesian reconstruction approach based on the material decomposition model applied in dual-energy computed tomography

    SciTech Connect (OSTI)

    Cai, C.; Rodet, T.; Mohammad-Djafari, A.; Legoupil, S.

    2013-11-15

    necessary to have the accurate spectrum information about the source-detector system. When dealing with experimental data, the spectrum can be predicted by a Monte Carlo simulator. For the materials between water and bone, less than 5% separation errors are observed on the estimated decomposition fractions.Conclusions: The proposed approach is a statistical reconstruction approach based on a nonlinear forward model counting the full beam polychromaticity and applied directly to the projections without taking negative-log. Compared to the approaches based on linear forward models and the BHA correction approaches, it has advantages in noise robustness and reconstruction accuracy.

  17. Atomistic simulation of laser-pulse surface modification: Predictions of models with various length and time scales

    SciTech Connect (OSTI)

    Starikov, Sergey V. Pisarev, Vasily V.

    2015-04-07

    In this work, the femtosecond laser pulse modification of surface is studied for aluminium (Al) and gold (Au) by use of two-temperature atomistic simulation. The results are obtained for various atomistic models with different scales: from pseudo-one-dimensional to full-scale three-dimensional simulation. The surface modification after laser irradiation can be caused by ablation and melting. For low energy laser pulses, the nanoscale ripples may be induced on a surface by melting without laser ablation. In this case, nanoscale changes of the surface are due to a splash of molten metal under temperature gradient. Laser ablation occurs at a higher pulse energy when a crater is formed on the surface. There are essential differences between Al ablation and Au ablation. In the first step of shock-wave induced ablation, swelling and void formation occur for both metals. However, the simulation of ablation in gold shows an additional athermal type of ablation that is associated with electron pressure relaxation. This type of ablation takes place at the surface layer, at a depth of several nanometers, and does not induce swelling.

  18. Development and Integration of Genome-Enabled Techniques to Track and Predict the Cycling of Carbon in Model Microbial Communities

    SciTech Connect (OSTI)

    Banfield, Jillian

    2014-11-26

    The primary objective of this project was to establish widely applicable, high-throughput omics methods for tracking carbon flow in microbial communities at a strain-resolved molecular level. We developed and applied these methods to study a well-established microbial community model system with a long history of omics innovation: chemoautotrophic biofilms grown in an acid mine drainage (AMD) environment. The methods are now being transitioned (in a new project) to study soil. Using metagenomics, stable-isotope proteomics, stable-isotope metabolomics, transcriptomics, and microscopy, we tracked carbon flow during initial biofilm growth involving CO2 fixation, through the maturing biofilm community consisting of multiple trophic levels, and during an anaerobic degradative phase after biofilms sink. This work included explicit consideration of the often overlooked roles of archaea and microbial eukaryotes (fungi) in carbon turnover. We also analyzed where the eosystem begins to fail in response to thermal perturbation, and how perturbation propagates through a carbon cycle. We investigated the form of strain variation in microbial communities, the importance of strain variants, and the rate and form of strain evolution. Overall, the project generated an array of new, integrated omics approaches and provided unprecedented insight into the functioning of a natural ecosystem. This project supported graduate training for five Ph.D. students and three post doctoral fellows and contributed directly to at least 26 publications (two in Science).

  19. Physics based model for online fault detection in autonomous cryogenic loading system

    SciTech Connect (OSTI)

    Kashani, Ali; Ponizhovskaya, Ekaterina; Luchinsky, Dmitry; Smelyanskiy, Vadim; Patterson-Hine, Anna; Sass, Jared; Brown, Barbara

    2014-01-29

    We report the progress in the development of the chilldown model for a rapid cryogenic loading system developed at NASA-Kennedy Space Center. The nontrivial characteristic feature of the analyzed chilldown regime is its active control by dump valves. The two-phase flow model of the chilldown is approximated as one-dimensional homogeneous fluid flow with no slip condition for the interphase velocity. The model is built using commercial SINDA/FLUINT software. The results of numerical predictions are in good agreement with the experimental time traces. The obtained results pave the way to the application of the SINDA/FLUINT model as a verification tool for the design and algorithm development required for autonomous loading operation.

  20. Evaluation of the interindividual human variation in bioactivation of methyleugenol using physiologically based kinetic modeling and Monte Carlo simulations

    SciTech Connect (OSTI)

    Al-Subeihi, Ala' A.A.; Alhusainy, Wasma; Kiwamoto, Reiko; Spenkelink, Bert; Bladeren, Peter J. van; Rietjens, Ivonne M.C.M.; Punt, Ans

    2015-03-01

    The present study aims at predicting the level of formation of the ultimate carcinogenic metabolite of methyleugenol, 1′-sulfooxymethyleugenol, in the human population by taking variability in key bioactivation and detoxification reactions into account using Monte Carlo simulations. Depending on the metabolic route, variation was simulated based on kinetic constants obtained from incubations with a range of individual human liver fractions or by combining kinetic constants obtained for specific isoenzymes with literature reported human variation in the activity of these enzymes. The results of the study indicate that formation of 1′-sulfooxymethyleugenol is predominantly affected by variation in i) P450 1A2-catalyzed bioactivation of methyleugenol to 1′-hydroxymethyleugenol, ii) P450 2B6-catalyzed epoxidation of methyleugenol, iii) the apparent kinetic constants for oxidation of 1′-hydroxymethyleugenol, and iv) the apparent kinetic constants for sulfation of 1′-hydroxymethyleugenol. Based on the Monte Carlo simulations a so-called chemical-specific adjustment factor (CSAF) for intraspecies variation could be derived by dividing different percentiles by the 50th percentile of the predicted population distribution for 1′-sulfooxymethyleugenol formation. The obtained CSAF value at the 90th percentile was 3.2, indicating that the default uncertainty factor of 3.16 for human variability in kinetics may adequately cover the variation within 90% of the population. Covering 99% of the population requires a larger uncertainty factor of 6.4. In conclusion, the results showed that adequate predictions on interindividual human variation can be made with Monte Carlo-based PBK modeling. For methyleugenol this variation was observed to be in line with the default variation generally assumed in risk assessment. - Highlights: • Interindividual human differences in methyleugenol bioactivation were simulated. • This was done using in vitro incubations, PBK modeling

  1. Web-based DOE/ORNL Heat Pump Design Model Released

    Office of Energy Efficiency and Renewable Energy (EERE)

    DOE/Oak Ridge National Laboratory's (ORNL) Heat Pump Design Model (HPDM), a hardware-based vapor-compression system research and design tool originally developed in the mid-1970s, remains cutting edge through continuous evolution.

  2. Depositional sequence analysis and sedimentologic modeling for improved prediction of Pennsylvanian reservoirs (Annex 1). Annual report, February 1, 1991--January 31, 1992

    SciTech Connect (OSTI)

    Watney, W.L.

    1992-08-01

    Interdisciplinary studies of the Upper Pennsylvanian Lansing and Kansas City groups have been undertaken in order to improve the geologic characterization of petroleum reservoirs and to develop a quantitative understanding of the processes responsible for formation of associated depositional sequences. To this end, concepts and methods of sequence stratigraphy are being used to define and interpret the three-dimensional depositional framework of the Kansas City Group. The investigation includes characterization of reservoir rocks in oil fields in western Kansas, description of analog equivalents in near-surface and surface sites in southeastern Kansas, and construction of regional structural and stratigraphic framework to link the site specific studies. Geologic inverse and simulation models are being developed to integrate quantitative estimates of controls on sedimentation to produce reconstructions of reservoir-bearing strata in an attempt to enhance our ability to predict reservoir characteristics.

  3. A Subbasin-based framework to represent land surface processes in an Earth System Model

    SciTech Connect (OSTI)

    Tesfa, Teklu K.; Li, Hongyi; Leung, Lai-Yung R.; Huang, Maoyi; Ke, Yinghai; Sun, Yu; Liu, Ying

    2014-05-20

    Realistically representing spatial heterogeneity and lateral land surface processes within and between modeling units in earth system models is important because of their implications to surface energy and water exchange. The traditional approach of using regular grids as computational units in land surface models and earth system models may lead to inadequate representation of lateral movements of water, energy and carbon fluxes, especially when the grid resolution increases. Here a new subbasin-based framework is introduced in the Community Land Model (CLM), which is the land component of the Community Earth System Model (CESM). Local processes are represented assuming each subbasin as a grid cell on a pseudo grid matrix with no significant modifications to the existing CLM modeling structure. Lateral routing of water within and between subbasins is simulated with the subbasin version of a recently-developed physically based routing model, Model for Scale Adaptive River Routing (MOSART). As an illustration, this new framework is implemented in the topographically diverse region of the U.S. Pacific Northwest. The modeling units (subbasins) are delineated from high-resolution Digital Elevation Model while atmospheric forcing and surface parameters are remapped from the corresponding high resolution datasets. The impacts of this representation on simulating hydrologic processes are explored by comparing it with the default (grid-based) CLM representation. In addition, the effects of DEM resolution on parameterizing topography and the subsequent effects on runoff processes are investigated. Limited model evaluation and comparison showed that small difference between the averaged forcing can lead to more significant difference in the simulated runoff and streamflow because of nonlinear horizontal processes. Topographic indices derived from high resolution DEM may not improve the overall water balance, but affect the partitioning between surface and subsurface runoff

  4. The Coastal Ocean Prediction Systems program: Understanding and managing our coastal ocean

    SciTech Connect (OSTI)

    Eden, H.F.; Mooers, C.N.K.

    1990-06-01

    The goal of COPS is to couple a program of regular observations to numerical models, through techniques of data assimilation, in order to provide a predictive capability for the US coastal ocean including the Great Lakes, estuaries, and the entire Exclusive Economic Zone (EEZ). The objectives of the program include: determining the predictability of the coastal ocean and the processes that govern the predictability; developing efficient prediction systems for the coastal ocean based on the assimilation of real-time observations into numerical models; and coupling the predictive systems for the physical behavior of the coastal ocean to predictive systems for biological, chemical, and geological processes to achieve an interdisciplinary capability. COPS will provide the basis for effective monitoring and prediction of coastal ocean conditions by optimizing the use of increased scientific understanding, improved observations, advanced computer models, and computer graphics to make the best possible estimates of sea level, currents, temperatures, salinities, and other properties of entire coastal regions.

  5. Predicting Stimulation Response Relationships For Engineered...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    Predicting Stimulation Response Relationships For Engineered Geothermal Reservoirs Project objectives: Using existing LLNL computer programs, develop realistic models of EGS ...

  6. TH-E-BRF-03: A Multivariate Interaction Model for Assessment of Hippocampal Vascular Dose-Response and Early Prediction of Radiation-Induced Neurocognitive Dysfunction

    SciTech Connect (OSTI)

    Farjam, R; Pramanik, P; Srinivasan, A; Chapman, C; Tsien, C; Lawrence, T; Cao, Y

    2014-06-15

    Purpose: Vascular injury could be a cause of hippocampal dysfunction leading to late neurocognitive decline in patients receiving brain radiotherapy (RT). Hence, our aim was to develop a multivariate interaction model for characterization of hippocampal vascular dose-response and early prediction of radiation-induced late neurocognitive impairments. Methods: 27 patients (17 males and 10 females, age 31–80 years) were enrolled in an IRB-approved prospective longitudinal study. All patients were diagnosed with a low-grade glioma or benign tumor and treated by 3-D conformal or intensity-modulated RT with a median dose of 54 Gy (50.4–59.4 Gy in 1.8− Gy fractions). Six DCE-MRI scans were performed from pre-RT to 18 months post-RT. DCE data were fitted to the modified Toft model to obtain the transfer constant of gadolinium influx from the intravascular space into the extravascular extracellular space, Ktrans, and the fraction of blood plasma volume, Vp. The hippocampus vascular property alterations after starting RT were characterized by changes in the hippocampal mean values of, μh(Ktrans)τ and μh(Vp)τ. The dose-response, Δμh(Ktrans/Vp)pre->τ, was modeled using a multivariate linear regression considering integrations of doses with age, sex, hippocampal laterality and presence of tumor/edema near a hippocampus. Finally, the early vascular dose-response in hippocampus was correlated with neurocognitive decline 6 and 18 months post-RT. Results: The μh(Ktrans) increased significantly from pre-RT to 1 month post-RT (p<0.0004). The multivariate model showed that the dose effect on Δμh(Ktrans)pre->1M post-RT was interacted with sex (p<0.0007) and age (p<0.00004), with the dose-response more pronounced in older females. Also, the vascular dose-response in the left hippocampus of females was significantly correlated with memory function decline at 6 (r = − 0.95, p<0.0006) and 18 (r = −0.88, p<0.02) months post-RT. Conclusion: The hippocampal vascular

  7. Laser shock peening on Zr-based bulk metallic glass and its effect on plasticity: Experiment and modeling

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Cao, Yunfeng; Xie, Xie; Antonaglia, James; Winiarski, Bartlomiej; Wang, Gongyao; Shin, Yung C.; Withers, Philip J.; Dahmen, Karin A.; Liaw, Peter K.

    2015-05-20

    The Zr-based bulk metallic glasses (BMGs) are a new family of attractive materials with good glass-forming ability and excellent mechanical properties, such as high strength and excellent wear resistance, which make them candidates for structural and biomedical materials. Although the mechanical behavior of BMGs has been widely investigated, their deformation mechanisms are still poorly understood. In particular, their poor ductility significantly impedes their industrial application. In the present work, we show that the ductility of Zr-based BMGs with nearly zero plasticity is improved by a laser shock peening technique. Moreover, we map the distribution of laser-induced residual stresses via themore » micro-slot cutting method, and then predict them using a three dimensional finite-element method coupled with a confined plasma model. Reasonable agreement is achieved between the experimental and modeling results. The analysis of serrated flow reveals plentiful and useful information of the underlying deformation process. As a result, our work provides an easy and effective way to extend the ductility of intrinsically-brittle BMGs, opening up wider applications of these materials.« less

  8. Laser shock peening on Zr-based bulk metallic glass and its effect on plasticity: Experiment and modeling

    SciTech Connect (OSTI)

    Cao, Yunfeng; Xie, Xie; Antonaglia, James; Winiarski, Bartlomiej; Wang, Gongyao; Shin, Yung C.; Withers, Philip J.; Dahmen, Karin A.; Liaw, Peter K.

    2015-05-20

    The Zr-based bulk metallic glasses (BMGs) are a new family of attractive materials with good glass-forming ability and excellent mechanical properties, such as high strength and excellent wear resistance, which make them candidates for structural and biomedical materials. Although the mechanical behavior of BMGs has been widely investigated, their deformation mechanisms are still poorly understood. In particular, their poor ductility significantly impedes their industrial application. In the present work, we show that the ductility of Zr-based BMGs with nearly zero plasticity is improved by a laser shock peening technique. Moreover, we map the distribution of laser-induced residual stresses via the micro-slot cutting method, and then predict them using a three dimensional finite-element method coupled with a confined plasma model. Reasonable agreement is achieved between the experimental and modeling results. The analysis of serrated flow reveals plentiful and useful information of the underlying deformation process. As a result, our work provides an easy and effective way to extend the ductility of intrinsically-brittle BMGs, opening up wider applications of these materials.

  9. Proposed mechanistic description of dose-dependent BDE-47 urinary elimination in mice using a physiologically based pharmacokinetic model

    SciTech Connect (OSTI)

    Emond, Claude; Sanders, J. Michael; Wikoff, Daniele; Birnbaum, Linda S.

    2013-12-01

    Polybrominated diphenyl ethers (PBDEs) have been used in a wide variety of consumer applications as additive flame retardants. In North America, scientists have noted continuing increases in the levels of PBDE congeners measured in human serum. Some recent studies have found that PBDEs are associated with adverse health effects in humans, in experimental animals, and wildlife. This laboratory previously demonstrated that urinary elimination of 2,2′,4,4′-tetrabromodiphenyl ether (BDE-47) is saturable at high doses in mice; however, this dose-dependent urinary elimination has not been observed in adult rats or immature mice. Thus, the primary objective of this study was to examine the mechanism of urinary elimination of BDE-47 in adult mice using a physiologically based pharmacokinetic (PBPK) model. To support this objective, additional laboratory data were collected to evaluate the predictions of the PBPK model using novel information from adult multi-drug resistance 1a/b knockout mice. Using the PBPK model, the roles of mouse major urinary protein (a blood protein carrier) and P-glycoprotein (an apical membrane transporter in proximal tubule cells in the kidneys, brain, intestines, and liver) were investigated in BDE-47 elimination. The resulting model and new data supported the major role of m-MUP in excretion of BDE-47 in the urine of adult mice, and a lesser role of P-gp as a transporter of BDE-47 in mice. This work expands the knowledge of BDE-47 kinetics between species and provides information for determining the relevancy of these data for human risk assessment purposes. - Highlights: • We report the first study on PBPK model on flame retardant in mice for BDE-47. • We examine mechanism of urinary elimination of BDE-47 in mice using a PBPK model. • We investigated roles of m-MUP and P-gp as transporters in urinary elimination.

  10. A Smoothed Particle Hydrodynamics-Based Fluid Model With a Spatially

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Dependent Viscosity | Argonne Leadership Computing Facility Smoothed Particle Hydrodynamics-Based Fluid Model With a Spatially Dependent Viscosity Authors: Martys, N.S., George, W.L., Chun, B., Lootens, D. A smoothed particle hydrodynamics approach is utilized to model a non-Newtonian fluid with a spatially varying viscosity. In the limit of constant viscosity, this approach recovers an earlier model for Newtonian fluids of Espa Publication Date: September, 2010 Name of Publication Source:

  11. Reduced order model based on principal component analysis for process simulation and optimization

    SciTech Connect (OSTI)

    Lang, Y.; Malacina, A.; Biegler, L.; Munteanu, S.; Madsen, J.; Zitney, S.

    2009-01-01

    It is well-known that distributed parameter computational fluid dynamics (CFD) models provide more accurate results than conventional, lumped-parameter unit operation models used in process simulation. Consequently, the use of CFD models in process/equipment co-simulation offers the potential to optimize overall plant performance with respect to complex thermal and fluid flow phenomena. Because solving CFD models is time-consuming compared to the overall process simulation, we consider the development of fast reduced order models (ROMs) based on CFD results to closely approximate the high-fidelity equipment models in the co-simulation. By considering process equipment items with complicated geometries and detailed thermodynamic property models, this study proposes a strategy to develop ROMs based on principal component analysis (PCA). Taking advantage of commercial process simulation and CFD software (for example, Aspen Plus and FLUENT), we are able to develop systematic CFD-based ROMs for equipment models in an efficient manner. In particular, we show that the validity of the ROM is more robust within well-sampled input domain and the CPU time is significantly reduced. Typically, it takes at most several CPU seconds to evaluate the ROM compared to several CPU hours or more to solve the CFD model. Two case studies, involving two power plant equipment examples, are described and demonstrate the benefits of using our proposed ROM methodology for process simulation and optimization.

  12. A method for modeling oxygen diffusion in an agent-based model with application to host-pathogen infection

    SciTech Connect (OSTI)

    Plimpton, Steven J.; Sershen, Cheryl L.; May, Elebeoba E.

    2015-01-01

    This paper describes a method for incorporating a diffusion field modeling oxygen usage and dispersion in a multi-scale model of Mycobacterium tuberculosis (Mtb) infection mediated granuloma formation. We implemented this method over a floating-point field to model oxygen dynamics in host tissue during chronic phase response and Mtb persistence. The method avoids the requirement of satisfying the Courant-Friedrichs-Lewy (CFL) condition, which is necessary in implementing the explicit version of the finite-difference method, but imposes an impractical bound on the time step. Instead, diffusion is modeled by a matrix-based, steady state approximate solution to the diffusion equation. Moreover, presented in figure 1 is the evolution of the diffusion profiles of a containment granuloma over time.

  13. A method for modeling oxygen diffusion in an agent-based model with application to host-pathogen infection

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Plimpton, Steven J.; Sershen, Cheryl L.; May, Elebeoba E.

    2015-01-01

    This paper describes a method for incorporating a diffusion field modeling oxygen usage and dispersion in a multi-scale model of Mycobacterium tuberculosis (Mtb) infection mediated granuloma formation. We implemented this method over a floating-point field to model oxygen dynamics in host tissue during chronic phase response and Mtb persistence. The method avoids the requirement of satisfying the Courant-Friedrichs-Lewy (CFL) condition, which is necessary in implementing the explicit version of the finite-difference method, but imposes an impractical bound on the time step. Instead, diffusion is modeled by a matrix-based, steady state approximate solution to the diffusion equation. Moreover, presented in figuremore » 1 is the evolution of the diffusion profiles of a containment granuloma over time.« less

  14. Modeling Long-term Creep Performance for Welded Nickel-base Superalloy Structures for Power Generation Systems

    SciTech Connect (OSTI)

    Shen, Chen

    2015-01-01

    We report here a constitutive model for predicting long-term creep strain evolution in ’ strengthened Ni-base superalloys. Dislocation climb-bypassing ’, typical in intermediate ’ volume fraction (~20%) alloys, is considered as the primary deformation mechanism. Dislocation shearing ’ to anti-phase boundary (APB) faults and diffusional creep are also considered for high-stress and high-temperature low-stress conditions, respectively. Additional damage mechanism is taken into account for rapid increase in tertiary creep strain. The model has been applied to Alloy 282, and calibrated in a temperature range of 1375-1450˚F, and stress range of 15-45ksi. The model parameters and a MATLAB code are provided. This report is prepared by Monica Soare and Chen Shen at GE Global Research. Technical discussions with Dr. Vito Cedro are greatly appreciated. This work was supported by DOE program DE-FE0005859

  15. Predictive Technology Development and Crash Energy Management

    Broader source: Energy.gov (indexed) [DOE]

    ... projects titled: * Multiscale Modeling for Crash Prediction of Composite Structures * Modeling of The Manufacturing Process Induced Effects on Matrix Properties of Textile ...

  16. Methane modeling: predicting the inflow of methane gas into coal mines. Quarterly technical progress report, April 1, 1982-June 30, 1982

    SciTech Connect (OSTI)

    Boyer, C.M. II; Hoysan, P.M.; Pavone, A.M.; Richmond, O.; Schwerer, F.C.; Smelser, R.E.

    1982-01-01

    Work on Phase I of the Contract program is essentially complete and was reported in the Phase I Technical Report which has been reviewed and accepted by the Contract Technical Project Officer. Phase I work included a survey of relevant technical literature and development, demonstration and documentation of a computer model, MINE1D, for flow of methane and water in coal strata for geometries corresponding to an advancing mine face and to a mine pillar. The Phase I models are one-dimensional in the space variable but describe time-dependent (nonsteady) phenomena and include gas sorption phenomena. Some revisions have been made to input/output sections of MINE1D and the documentation has been expanded. These modifications will be reported in the next Quarterly Technical Report. Preliminary test scenarios have been formulated and reviewed with the Contract Technical Project Officer for measurement of emissions during room-and-pillar and longwall mining operations. These preliminary scenarios are described in this report. A mathematical model has been developed to describe the increased stresses on the coal seam near mine openings. The model is based on an approximate elastic/plastic treatment of the coal seam and an elastic treatment of surrounding strata. In this model, elastic compaction of the coal seam decreases porosity and permeability, whereas plastic deformation increases the porosity of the natural fracture network and thereby increases the permeability. The model takes into account the effect of changes in pore fluid pressure (in the natural fracture network of the coal seam) on the deformation of the coal seam. This model is described in this report, and will be programmed for inclusion in revised versions of MINE1D and for use in the two-dimensional computer models now under development. 8 figures.

  17. Architectural considerations for agent-based national scale policy models : LDRD final report.

    SciTech Connect (OSTI)

    Backus, George A.; Strip, David R.

    2007-09-01

    The need to anticipate the consequences of policy decisions becomes ever more important as the magnitude of the potential consequences grows. The multiplicity of connections between the components of society and the economy makes intuitive assessments extremely unreliable. Agent-based modeling has the potential to be a powerful tool in modeling policy impacts. The direct mapping between agents and elements of society and the economy simplify the mapping of real world functions into the world of computation assessment. Our modeling initiative is motivated by the desire to facilitate informed public debate on alternative policies for how we, as a nation, provide healthcare to our population. We explore the implications of this motivation on the design and implementation of a model. We discuss the choice of an agent-based modeling approach and contrast it to micro-simulation and systems dynamics approaches.

  18. Modeling the Integrated Performance of Dispersion and Monolithic U-Mo Based Fuels

    SciTech Connect (OSTI)

    Daniel M. Wachs; Douglas E. Burkes; Steven L. Hayes; Karen Moore; Greg Miller; Gerard Hofman; Yeon Soo Kim

    2006-10-01

    The evaluation and prediction of integrated fuel performance is a critical component of the Reduced Enrichment for Research and Test Reactors (RERTR) program. The PLATE code is the primary tool being developed and used to perform these functions. The code is being modified to incorporate the most recent fuel/matrix interaction correlations as they become available for both aluminum and aluminum/silicon matrices. The code is also being adapted to treat cylindrical and square pin geometries to enhance the validation database by including the results gathered from various international partners. Additional modeling work has been initiated to evaluate the thermal and mechanical performance requirements unique to monolithic fuels during irradiation.

  19. Modeling the thermal deformation of TATB-based explosives. Part 1: Thermal expansion of neat-pressed polycrystalline TATB

    SciTech Connect (OSTI)

    Luscher, Darby J.

    2014-05-08

    We detail a modeling approach to simulate the anisotropic thermal expansion of polycrystalline (1,3,5-triamino-2,4,6-trinitrobenzene) TATB-based explosives that utilizes microstructural information including porosity, crystal aspect ratio, and processing-induced texture. This report, the first in a series, focuses on nonlinear thermal expansion of neat-pressed polycrystalline TATB specimens which do not contain any binder; additional complexities related to polymeric binder and irreversible ratcheting behavior are briefly discussed, however detailed investigation of these aspects are deferred to subsequent reports. In this work we have, for the first time, developed a mesoscale continuum model relating the thermal expansion of polycrystal TATB specimens to their microstructural characteristics. A self-consistent homogenization procedure is used to relate macroscopic thermoelastic response to the constitutive behavior of single-crystal TATB. The model includes a representation of grain aspect ratio, porosity, and crystallographic texture attributed to the consolidation process. A quantitative model is proposed to describe the evolution of preferred orientation of graphitic planes in TATB during consolidation and an algorithm constructed to develop a discrete representation of the associated orientation distribution function. Analytical and numerical solutions using this model are shown to produce textures consistent with previous measurements and characterization for isostatic and uniaxial die-pressed specimens. Predicted thermal strain versus temperature for textured specimens are shown to be in agreement with corresponding experimental measurements. Using the developed modeling approach, several simulations have been run to investigate the influence of microstructure on macroscopic thermal expansion behavior. Results from these simulations are used to identify qualitative trends. Implications of the identified trends are discussed in the context of thermal

  20. Process-based modeling of the aeloian environment at the dune scale

    SciTech Connect (OSTI)

    Stam, J.M.T. )

    1993-09-01

    Process-based models are quantitative models that simulate the physical process of sedimentation with the objective of reconstructing the spatial distribution, stratification, and properties of the subsurface. In this study, a two-dimensional, process-based model of the aeolian environment, at the dune-interdune scale, has been developed. Sedimentation is governed by the variation of wind velocity over the topography, which is calculated analytically. Velocity calculations are coupled to a sediment transport equation, to determine where erosion and deposition occur. The resulting change in topography determines a new velocity field, which is then calculated. Features that the model simulates include ripple formation and dune migration, as well as the resulting internal sedimentary structures. Process-based models can be used as tool to help interpret structures in ancient formations. This model has been applied specifically to reconstruct dune-interdune sequences observed in cores from the Rotliegendes, localized in the southern Permian basin (North Sea). The interdune strata are characterized by a low permeability. A flow simulation has been done on the aeolian section generated by the model, showing the effect of these heterogeneities on fluid flow.