Sample records for model based predictive

  1. The myth of science-based predictive modeling.

    SciTech Connect (OSTI)

    Hemez, F. M. (François M.)

    2004-01-01T23:59:59.000Z

    A key aspect of science-based predictive modeling is the assessment of prediction credibility. This publication argues that the credibility of a family of models and their predictions must combine three components: (1) the fidelity of predictions to test data; (2) the robustness of predictions to variability, uncertainty, and lack-of-knowledge; and (3) the prediction accuracy of models in cases where measurements are not available. Unfortunately, these three objectives are antagonistic. A recently published Theorem that demonstrates the irrevocable trade-offs between fidelity-to-data, robustness-to-uncertainty, and confidence in prediction is summarized. High-fidelity models cannot be made increasingly robust to uncertainty and lack-of-knowledge. Similarly, robustness-to-uncertainty can only be improved at the cost of reducing the confidence in prediction. The concept of confidence in prediction relies on a metric for total uncertainty, capable of aggregating different representations of uncertainty (probabilistic or not). The discussion is illustrated with an engineering application where a family of models is developed to predict the acceleration levels obtained when impacts of varying levels propagate through layers of crushable hyper-foam material of varying thicknesses. Convex modeling is invoked to represent a severe lack-of-knowledge about the constitutive material behavior. The analysis produces intervals of performance metrics from which the total uncertainty and confidence levels are estimated. Finally, performance, robustness and confidence are extrapolated throughout the validation domain to assess the predictive power of the family of models away from tested configurations.

  2. Model Predictive Control based Real Time Power System Protection Schemes

    E-Print Network [OSTI]

    Kumar, Ratnesh

    1 Model Predictive Control based Real Time Power System Protection Schemes Licheng Jin, Member by controlling the production, absorption as well as flow of reactive power at various locations in the system predictive control, trajectory sensitivity, voltage stabilization, switching control, power system I

  3. Predictive clothing insulation model based on outdoor air and indoor operative temperatures

    E-Print Network [OSTI]

    Schiavon, Stefano; Lee, Kwang Ho

    2012-01-01T23:59:59.000Z

    2012) Predictive clothing insulation model based on outdoorPredictive clothing insulation model based on outdoor airpredictive models of clothing insulation have been developed

  4. Application of Sampling Based Model Predictive Control to an Autonomous

    E-Print Network [OSTI]

    Collins, Emmanuel

    Unmanned Underwater Vehicles (UUVs) can be utilized to perform difficult tasks in cluttered environments55 Application of Sampling Based Model Predictive Control to an Autonomous Underwater Vehicle for an autonomous underwater vehicle (AUV). The algorithm combines the benefits of sampling-based motion planning

  5. Vehicle Trajectory Prediction based on Motion Model and Maneuver Recognition

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Vehicle Trajectory Prediction based on Motion Model and Maneuver Recognition Adam Houenou, Philippe is a crucial task for an autonomous vehicle, in order to avoid collisions on its planned trajectory. It is also necessary for many Advanced Driver Assistance Systems, where the ego- vehicle's trajectory has

  6. A Model to Predict Work-Related Fatigue Based on Hours of Work

    E-Print Network [OSTI]

    A Model to Predict Work-Related Fatigue Based on Hours of Work Gregory D. Roach, Adam Fletcher, and Drew Dawson ROACH GD, FLETCHER A, DAWSON D. A model to predict work- related fatigue based on hours

  7. Productivity prediction model based on Bayesian analysis and productivity console

    E-Print Network [OSTI]

    Yun, Seok Jun

    2005-08-29T23:59:59.000Z

    in poor planning and defies effective control of time and budgets in project management. In this research, we have built a productivity prediction model which uses productivity data from an ongoing project to reevaluate the initial productivity estimate...

  8. VISUALIZING MODEL-BASED PREDICTIVE CONTROLLERS StephanieGuerlain Greg JamjesonandPeter Bullemer

    E-Print Network [OSTI]

    Virginia, University of

    -based predictive controllers (MPC) are becoming very popular in petrochemical refineries, as they simultaneously control ayd optimize large sections of a petrochemical process;yqng a predictive model. However, current

  9. OPERATOR INTERACTION WITH MODEL-BASED PREDICTIVE CONTROLLERS IN PETROCHEMICAL REFINING

    E-Print Network [OSTI]

    Virginia, University of

    OPERATOR INTERACTION WITH MODEL-BASED PREDICTIVE CONTROLLERS IN PETROCHEMICAL REFINING Greg A success in the petrochemical industry, they have introduced new challenges for the operators and engineers

  10. Dynamic predictive clothing insulation models based on outdoor air and indoor operative temperatures

    E-Print Network [OSTI]

    Schiavon, Stefano; Lee, Kwang Ho

    2012-01-01T23:59:59.000Z

    predictive clothing insulation models based on outdoor airrange of the clothing insulation calculated for eachbuilding). Figure 8 Clothing insulation versus dress code [

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

    SciTech Connect (OSTI)

    Dowding, Kevin J.; Rutherford, Brian Milne

    2003-07-01T23:59:59.000Z

    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 hypothesis tests as a part of the validation step to provide feedback to analysts and modelers. Decisions on how to proceed in making model-based predictions are made based on these analyses together with the application requirements. Updating modifying and understanding the boundaries associated with the model are also assisted through this feedback. (4) We include a ''model supplement term'' when model problems are indicated. This term provides a (bias) correction to the model so that it will better match the experimental results and more accurately account for uncertainty. Presumably, as the models continue to develop and are used for future applications, the causes for these apparent biases will be identified and the need for this supplementary modeling will diminish. (5) We use a response-modeling approach for our predictions that allows for general types of prediction and for assessment of prediction uncertainty. This approach is demonstrated through a case study supporting the assessment of a weapons response when subjected to a hydrocarbon fuel fire. The foam decomposition model provides an important element of the response of a weapon system in this abnormal thermal environment. Rigid foam is used to encapsulate critical components in the weapon system providing the needed mechanical support as well as thermal isolation. Because the foam begins to decompose at temperatures above 250 C, modeling the decomposition is critical to assessing a weapons response. In the validation analysis it is indicated that the model tends to ''exaggerate'' the effect of temperature changes when compared to the experimental results. The data, however, are too few and to restricted in terms of experimental design to make confident statements regarding modeling problems. For illustration, we assume these indications are correct and compensate for this apparent bias by constructing a model supplement term for use in the model-based predictions. Several hypothetical prediction problems are created and addressed. Hypothetical problems are used because no guidance was provided concern

  12. Prediction of Physico-Chemical Properties for REACH Based on QSPR Models

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Prediction of Physico-Chemical Properties for REACH Based on QSPR Models Guillaume Fayeta models have been developed for the prediction of flash points of two families of organic compounds respected all OECD validation principles with excellent performances in predictivity, the one dedicated

  13. Prediction Models for a Smart Home based Health Care System Vikramaditya R. Jakkula1

    E-Print Network [OSTI]

    Cook, Diane J.

    Prediction Models for a Smart Home based Health Care System Vikramaditya R. Jakkula1 , Diane J health care. Smart health care systems at home can be used to provide such solutions. A technology a prediction model in an intelligent smart home system can be used for identifying health trends over time

  14. A Physically Based Analytical Model to Predict Quantized Eigen Energies and Wave Functions Incorporating Penetration Effect

    E-Print Network [OSTI]

    Nadim Chowdhury; Imtiaz Ahmed; Zubair Al Azim; Md. Hasibul Alam; Iftikhar Ahmad Niaz; Quazi D. M. Khosru

    2014-04-14T23:59:59.000Z

    We propose a physically based analytical compact model to calculate Eigen energies and Wave functions which incorporates penetration effect. The model is applicable for a quantum well structure that frequently appears in modern nano-scale devices. This model is equally applicable for both silicon and III-V devices. Unlike other models already available in the literature, our model can accurately predict all the eigen energies without the inclusion of any fitting parameters. The validity of our model has been checked with numerical simulations and the results show significantly better agreement compared to the available methods.

  15. Control of Airborne Wind Energy Systems Based on Nonlinear Model Predictive Control & Moving Horizon Estimation

    E-Print Network [OSTI]

    Control of Airborne Wind Energy Systems Based on Nonlinear Model Predictive Control & Moving arising in the Airborne Wind Energy paradigm, an essential one is the control of the tethered airfoil], [3], the Airborne Wind Energy (AWE) paradigm shift proposes to get rid of the structural elements

  16. Scenario-Based Fault-Tolerant Model Predictive Control for Diesel-Electric Marine Power Plant

    E-Print Network [OSTI]

    Johansen, Tor Arne

    Scenario-Based Fault-Tolerant Model Predictive Control for Diesel-Electric Marine Power Plant Email: torstein.bo@itk.ntnu.no, tor.arne.johansen@itk.ntnu.no Abstract--Diesel-electric propulsion generation control, Ma- rine safety, Optimal control. I. INTRODUCTION Diesel electric propulsion is a system

  17. Trace-Based Analysis and Prediction of Cloud Computing User Behavior Using the Fractal Modeling Technique

    E-Print Network [OSTI]

    Pedram, Massoud

    Trace-Based Analysis and Prediction of Cloud Computing User Behavior Using the Fractal Modeling and technology. In this paper, we investigate the characteristics of the cloud computing requests received the alpha- stable distribution. Keywords- cloud computing; alpha-stable distribution; fractional order

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

    SciTech Connect (OSTI)

    Kohler, Christian

    2012-08-01T23:59:59.000Z

    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.

  19. A voxel-based finite element model for the prediction of bladder deformation

    SciTech Connect (OSTI)

    Chai Xiangfei; Herk, Marcel van; Hulshof, Maarten C. C. M.; Bel, Arjan [Radiation Oncology Department, Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam (Netherlands); Radiation Oncology Department, Netherlands Cancer Institute, 1066 CX Amsterdam (Netherlands); Radiation Oncology Department, Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam (Netherlands)

    2012-01-15T23:59:59.000Z

    Purpose: A finite element (FE) bladder model was previously developed to predict bladder deformation caused by bladder filling change. However, two factors prevent a wide application of FE models: (1) the labor required to construct a FE model with high quality mesh and (2) long computation time needed to construct the FE model and solve the FE equations. In this work, we address these issues by constructing a low-resolution voxel-based FE bladder model directly from the binary segmentation images and compare the accuracy and computational efficiency of the voxel-based model used to simulate bladder deformation with those of a classical FE model with a tetrahedral mesh. Methods: For ten healthy volunteers, a series of MRI scans of the pelvic region was recorded at regular intervals of 10 min over 1 h. For this series of scans, the bladder volume gradually increased while rectal volume remained constant. All pelvic structures were defined from a reference image for each volunteer, including bladder wall, small bowel, prostate (male), uterus (female), rectum, pelvic bone, spine, and the rest of the body. Four separate FE models were constructed from these structures: one with a tetrahedral mesh (used in previous study), one with a uniform hexahedral mesh, one with a nonuniform hexahedral mesh, and one with a low-resolution nonuniform hexahedral mesh. Appropriate material properties were assigned to all structures and uniform pressure was applied to the inner bladder wall to simulate bladder deformation from urine inflow. Performance of the hexahedral meshes was evaluated against the performance of the standard tetrahedral mesh by comparing the accuracy of bladder shape prediction and computational efficiency. Results: FE model with a hexahedral mesh can be quickly and automatically constructed. No substantial differences were observed between the simulation results of the tetrahedral mesh and hexahedral meshes (<1% difference in mean dice similarity coefficient to manual contours and <0.02 cm difference in mean standard deviation of residual errors). The average equation solving time (without manual intervention) for the first two types of hexahedral meshes increased to 2.3 h and 2.6 h compared to the 1.1 h needed for the tetrahedral mesh, however, the low-resolution nonuniform hexahedral mesh dramatically decreased the equation solving time to 3 min without reducing accuracy. Conclusions: Voxel-based mesh generation allows fast, automatic, and robust creation of finite element bladder models directly from binary segmentation images without user intervention. Even the low-resolution voxel-based hexahedral mesh yields comparable accuracy in bladder shape prediction and more than 20 times faster in computational speed compared to the tetrahedral mesh. This approach makes it more feasible and accessible to apply FE method to model bladder deformation in adaptive radiotherapy.

  20. Towards Accurate and Practical Predictive Models of Active-Vision-Based Visual Search

    E-Print Network [OSTI]

    Hornof, Anthony

    which permit increasingly realistic and accurate predictions for visual human-computer interaction tasks not practical. For as long as human-computer interaction has been studied, researchers have been working@cs.uoregon.edu ABSTRACT Being able to predict the performance of interface designs using models of human cognition

  1. Autonomous Reactor Control Using Model Based Predictive Control for Space Propulsion Applications

    SciTech Connect (OSTI)

    Bragg-Sitton, Shannon M.; Holloway, James Paul [University of Michigan, Nuclear Engineering and Radiological Sciences, Ann Arbor, MI 48109 (United States)

    2005-02-06T23:59:59.000Z

    Reliable reactor control is important to reactor safety, both in terrestrial and space systems. For a space system, where the time for communication to Earth is significant, autonomous control is imperative. Based on feedback from reactor diagnostics, a controller must be able to automatically adjust to changes in reactor temperature and power level to maintain nominal operation without user intervention. Model-based predictive control (MBPC) (Clarke 1994; Morari 1994) is investigated as a potential control methodology for reactor start-up and transient operation in the presence of an external source. Bragg-Sitton and Holloway (2004) assessed the applicability of MBPC to reactor start-up from a cold, zero-power condition in the presence of a time-varying external radiation source, where large fluctuations in the external radiation source can significantly impact a reactor during start-up operations. The MBPC algorithm applied the point kinetics model to describe the reactor dynamics, using a single group of delayed neutrons; initial application considered a fast neutron lifetime (10-3 sec) to simplify calculations during initial controller analysis. The present study will more accurately specify the dynamics of a fast reactor, using a more appropriate fast neutron lifetime (10-7 sec) than in the previous work. Controller stability will also be assessed by carefully considering the dependencies of each component in the defined cost (objective) function and its subsequent effect on the selected 'optimal' control maneuvers.

  2. ghMulti-Level Approach for Model-Based Predictive Control (MPC) in Buildings: A Preliminary Overview

    E-Print Network [OSTI]

    Candanedo, J. A.; Dehkordi, V. R.

    2013-01-01T23:59:59.000Z

    Model-based predictive control (MPC) has emerged in recent years as a promising approach to building operation. MPC uses models of the system(s) under control -and knowledge about future disturbances- to select an optimal set of actions. Despite its...

  3. BFEPM:Best Fit Energy Prediction Modeling Based on CPU Utilization Xiao Zhang, Jianjun Lu, Xiao Qin

    E-Print Network [OSTI]

    Qin, Xiao

    Engineering Auburn University Auburn, AL USA 36849-5347 Email: xqin@auburn.edu Abstract--Energy cost becomes different servers have different energy consumption characters even with same CPU. In this paper, we present BFEPM, a best fit energy prediction model. It choose best model based on the power consumption benchmark

  4. Model prediction for reactor control

    SciTech Connect (OSTI)

    Ardell, G.G.; Gumowski, B.

    1983-06-01T23:59:59.000Z

    Model prediction is offered as a substitute to lengthy analysis of sample procedures to control product properties not amendable to direct measurement during chemical processing. A computer model of a reactor is set up, and control actions, based on current predicted values, are established. The control is based on predicted ''measurements'' which are derived using a dynamic process model solved on-line. The model is corrected by real measurements in the process operation. A two phase exothermic catalyzed reaction, with the objective of producing material with specified properties, is tested in this paper. The model prediction performance was very good. Model systems enable a more effective control to be exercised than the sample method.

  5. Short-term Wind Power Prediction for Offshore Wind Farms -Evaluation of Fuzzy-Neural Network Based Models

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Short-term Wind Power Prediction for Offshore Wind Farms - Evaluation of Fuzzy-Neural Network Based of offshore farms and their secure integration to the grid. Modeling the behavior of large wind farms presents the new considerations that have to be made when dealing with large offshore wind farms

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

    SciTech Connect (OSTI)

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

    2006-10-01T23:59:59.000Z

    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. Pressure vessel embrittlement predictions based on a composite model of copper precipitation and point defect clustering

    SciTech Connect (OSTI)

    Stoller, R.E. [Oak Ridge National Lab., TN (United States). Metals and Ceramics Div.

    1996-12-31T23:59:59.000Z

    A theoretical model is used to investigate the relative importance of point defect clusters (PDC) and copper-rich precipitates in reactor pressure vessel (RPV) embrittlement and to examine the influence of a broad range of irradiation and material parameters on predicted yield strength changes. The results indicate that there are temperature and displacement rate regimes wherein either CRP or PDC can dominate the material`s response to irradiation, with both interstitial and vacancy type defects contributing to the PDC component. The different dependencies of the CRP and PDC on temperature and displacement rate indicate that simple data extrapolations could lead to poor predictions of RPV embrittlement. It is significant that the yield strength changes predicted by the composite PDC/CRP model exhibit very little dependence on displacement rate below about 10{sup {minus}9} dpa/s. If this result is confirmed, concerns about accelerated displacement rates in power reactor surveillance programs should be minimized. The sensitivity of the model to microstructural parameters highlights the need for more detailed microstructural characterization of RPV steels.

  8. MULTIPLE ARX MODEL-BASED AIR-FUEL RATIO PREDICTIVE CONTROL FOR SI

    E-Print Network [OSTI]

    Johansen, Tor Arne

    strategy for combustion engines. The mix- ture quality is essential for efficiency of a three- way control problems. One of the most popular approaches to combustion engine modeling is based on neural where the amount of the fuel is a function of the control action. It was demonstrated by simulation

  9. Mechanistic-based Ductility Prediction

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

    Predictive modeling & performance: - Performance validation of "demo" structure in corrosion, fatigue, and durability Total project funding DOE: 3,000,000 ...

  10. Optimization-based Design of Plant-Friendly Input Signals for Model-on-Demand Estimation and Model Predictive Control

    E-Print Network [OSTI]

    Mittelmann, Hans D.

    is shown by applying it to a case study involving composition control of a binary distillation column. I is demonstrated in a binary high-purity distillation column case study by Weischedel and McAvoy [7], a demandingOptimization-based Design of Plant-Friendly Input Signals for Model-on-Demand Estimation and Model

  11. Predicting error in detecting mammographic masses among radiology trainees using statistical models based on BI-RADS features

    SciTech Connect (OSTI)

    Grimm, Lars J., E-mail: Lars.grimm@duke.edu; Ghate, Sujata V.; Yoon, Sora C.; Kim, Connie [Department of Radiology, Duke University Medical Center, Box 3808, Durham, North Carolina 27710 (United States)] [Department of Radiology, Duke University Medical Center, Box 3808, Durham, North Carolina 27710 (United States); Kuzmiak, Cherie M. [Department of Radiology, University of North Carolina School of Medicine, 2006 Old Clinic, CB No. 7510, Chapel Hill, North Carolina 27599 (United States)] [Department of Radiology, University of North Carolina School of Medicine, 2006 Old Clinic, CB No. 7510, Chapel Hill, North Carolina 27599 (United States); Mazurowski, Maciej A. [Duke University Medical Center, Box 2731 Medical Center, Durham, North Carolina 27710 (United States)] [Duke University Medical Center, Box 2731 Medical Center, Durham, North Carolina 27710 (United States)

    2014-03-15T23:59:59.000Z

    Purpose: The purpose of this study is to explore Breast Imaging-Reporting and Data System (BI-RADS) features as predictors of individual errors made by trainees when detecting masses in mammograms. Methods: Ten radiology trainees and three expert breast imagers reviewed 100 mammograms comprised of bilateral medial lateral oblique and craniocaudal views on a research workstation. The cases consisted of normal and biopsy proven benign and malignant masses. For cases with actionable abnormalities, the experts recorded breast (density and axillary lymph nodes) and mass (shape, margin, and density) features according to the BI-RADS lexicon, as well as the abnormality location (depth and clock face). For each trainee, a user-specific multivariate model was constructed to predict the trainee's likelihood of error based on BI-RADS features. The performance of the models was assessed using area under the receive operating characteristic curves (AUC). Results: Despite the variability in errors between different trainees, the individual models were able to predict the likelihood of error for the trainees with a mean AUC of 0.611 (range: 0.502–0.739, 95% Confidence Interval: 0.543–0.680,p < 0.002). Conclusions: Patterns in detection errors for mammographic masses made by radiology trainees can be modeled using BI-RADS features. These findings may have potential implications for the development of future educational materials that are personalized to individual trainees.

  12. 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.

    1981-05-01T23:59:59.000Z

    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.

  13. Prediction Intervals in Generalized Linear Mixed Models

    E-Print Network [OSTI]

    Yang, Cheng-Hsueh

    2013-01-01T23:59:59.000Z

    3.1. BLP Based Prediction Intervals………………………………………..……3.2. BP Based Prediction Intervals………………..………………………..……4.1.1. BLP Based Prediction Interval………………………………………. 4.1.2.

  14. OIKOS 98: 316, 2002 Using niche-based GIS modeling to test geographic predictions of

    E-Print Network [OSTI]

    Anderson, Robert P.

    and Marcela Go´mez-Laverde Anderson, R. P., Peterson, A. T. and Go´mez-Laverde, M. 2002. Using niche-based GIS, rpa@amnh.org). ­ M. Go´mez- La6erde, Fundacio´n Ulama´, Aptdo Ae´reo 93674, Santafe´ de Bogota

  15. Mirzahosseini et. al. ANN-Based Prediction Model for Rutting Propensity of Asphalt Mixtures1

    E-Print Network [OSTI]

    Fernandez, Thomas

    in a repeated load permanent deformation test.21 Dynamic creep test is one of the best tools for assessing of load cycles is the most23 important output of the dynamic creep test. This curve includes primary based on volumetric proportioning of the asphalt mixture. This method does16 not include any direct test

  16. Physically Based Model-Predictive Control for SOFC Stacks and Systems Tyrone L. Vincent, Borhan Sanandaji

    E-Print Network [OSTI]

    Sanandaji, Borhan M.

    for the sleeper cab on a long-haul truck. Depending upon the activities and appliances in the cab, the power incorporate physical knowledge of fuel-cell behavior into real-time multiple-input­multiple-output (MIMO model that represents the physical and chemical processes responsible for fuel-cell function. However

  17. Autobiography based prediction in a situated Ladislau Boloni

    E-Print Network [OSTI]

    Bölöni, Ladislau L

    feature of any situated AGI system. The most widely used approach is to create a model of the world system. A widely used way to perform such predictions is through model build- ing coupled with simulation. Predictive power and performance: does this even make sense? The proposed AM-based prediction immediately

  18. Model Predictive Control for Smooth Distributed Power Adaptation

    E-Print Network [OSTI]

    Boyer, Edmond

    1 Model Predictive Control for Smooth Distributed Power Adaptation Virgile Garcia1,2,3 , Nikolai the variations of other BS powers. The trajectories are then updated using a Model Predictive Control (MPC-based power control, no inter-cell cooperation, power trajectory, model predictive control, smooth power

  19. Model Predictive Control Wind Turbines

    E-Print Network [OSTI]

    Model Predictive Control of Wind Turbines Martin Klauco Kongens Lyngby 2012 IMM-MSc-2012-65 #12;Summary Wind turbines are the biggest part of the green energy industry. Increasing interest control strategies. Control strategy has a significant impact on the wind turbine operation on many levels

  20. A real time model to forecast 24 hours ahead, ozone peaks and exceedance levels. Model based on artificial neural networks, neural classifier and weather predictions.

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    on artificial neural networks, neural classifier and weather predictions. Application in an urban atmosphere - will be solved. Keywords: Artificial neural network; Multilayer Perceptron; ozone modelling; statistical stepwise and Software 22, 9 (2007) 1261-1269" DOI : 10.1016/j.envsoft.2006.08.002 #12;Abstract A neural network combined

  1. Fast Prediction of HCCI and PCCI Combustion with an Artificial Neural Network-Based Chemical Kinetic Model

    SciTech Connect (OSTI)

    Piggott, W T; Aceves, S M; Flowers, D L; Chen, J Y

    2007-09-26T23:59:59.000Z

    We have added the capability to look at in-cylinder fuel distributions using a previously developed ignition model within a fluid mechanics code (KIVA3V) that uses an artificial neural network (ANN) to predict ignition (The combined code: KIVA3V-ANN). KIVA3V-ANN was originally developed and validated for analysis of Homogeneous Charge Compression Ignition (HCCI) combustion, but it is also applicable to the more difficult problem of Premixed Charge Compression Ignition (PCCI) combustion. PCCI combustion refers to cases where combustion occurs as a nonmixing controlled, chemical kinetics dominated, autoignition process, where the fuel, air, and residual gas mixtures are not necessarily as homogeneous as in HCCI combustion. This paper analyzes the effects of introducing charge non-uniformity into a KIVA3V-ANN simulation. The results are compared to experimental results, as well as simulation results using a more physically representative and computationally intensive code (KIVA3V-MPI-MZ), which links a fluid mechanics code to a multi-zone detailed chemical kinetics solver. The results indicate that KIVA3V-ANN produces reasonable approximations to the more accurate KIVA3V-MPI-MZ at a much reduced computational cost.

  2. Predicting Improved Chiller Performance Through Thermodynamic Modeling

    E-Print Network [OSTI]

    Figueroa, I. E.; Cathey, M.; Medina, M. A.; Nutter, D. W.

    This paper presents two case studies in which thermodynamic modeling was used to predict improved chiller performance. The model predicted the performance (COP and total energy consumption) of water-cooled centrifugal chillers as a function...

  3. Kinetic Modeling of Halogen-Based Plasma Etching of Complex Oxide Films and its Application to Predictive Feature Profile Simulation

    E-Print Network [OSTI]

    Marchack, Nathan

    2012-01-01T23:59:59.000Z

    calculations, it was predicted that at typical plasma reactorof calculation. The etch rate of HfO 2 in this reactor at -calculation to be valid, it must also be assumed that at the operating conditions of the ICP reactor,

  4. 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.

    1981-04-01T23:59:59.000Z

    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.

  5. Nonlinear Model Predictive Control of an Omnidirectional Mobile Robot

    E-Print Network [OSTI]

    Zell, Andreas

    , University of Tübingen, Sand 1, 72076 Tübingen, Germany Abstract. This paper focuses on motion controlNonlinear Model Predictive Control of an Omnidirectional Mobile Robot Xiang LI a,1 , Kiattisin problems of an omnidirectional robot based on the Nonlinear Model Predictive Control (NMPC) method

  6. Plug-and-Play Decentralized Model Predictive Control Stefano Riverso

    E-Print Network [OSTI]

    Ferrari-Trecate, Giancarlo

    Plug-and-Play Decentralized Model Predictive Control Stefano Riverso , Marcello Farina. When this is possible, we show how to automatize the design of local controllers so that it can information with neighboring subsystems. In particular, local controllers exploit tube-based Model Predictive

  7. Kinetic Modeling of Halogen-Based Plasma Etching of Complex Oxide Films and its Application to Predictive Feature Profile Simulation

    E-Print Network [OSTI]

    Marchack, Nathan

    2012-01-01T23:59:59.000Z

    model for Si etching by fluorocarbon plasmas." Journal Ofwith inductively coupled fluorocarbon plasmas." Journal ofwith inductively coupled fluorocarbon plasmas." Journal of

  8. Synchrotron-based microanalysis of iron distribution after thermal processing and predictive modeling of resulting solar cell efficiency

    E-Print Network [OSTI]

    Fenning, David P.

    2013-04-10T23:59:59.000Z

    Synchrotron-based X-ray fluorescence microscopy is applied to study the evolution of iron silicide precipitates during phosphorus diffusion gettering and low-temperature annealing. Heavily Fe-contaminated ingot border ...

  9. Optimization Online - Nonlinear Model Predictive Control via ...

    E-Print Network [OSTI]

    M. J. Tenny

    2002-08-15T23:59:59.000Z

    Aug 15, 2002 ... Nonlinear Model Predictive Control via Feasibility-Perturbed Sequential Quadratic Programming. M. J. Tenny (tenny ***at*** bevo.che.wisc.edu)

  10. Prediction Markets Partition model of knowledge

    E-Print Network [OSTI]

    Fiat, Amos

    Prediction Markets Partition model of knowledge Distributed information markets Convergence time bounds Computational Aspects of Prediction Markets David M. Pennock and Rahul Sami December 5, 2012 Presented by: Rami Eitan David M. Pennock and Rahul Sami Computational Aspects of Prediction Markets #12

  11. 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.

    2013-03-19T23:59:59.000Z

    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.

  12. Latent feature models for dyadic prediction /

    E-Print Network [OSTI]

    Menon, Aditya Krishna

    2013-01-01T23:59:59.000Z

    prediction . . . . . . . . . . . . . . . . . . . . . . . . .Response prediction . . . . . . . . . . . . . . . . . . .2.4.3 Weighted link prediction . . . . . .

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

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

    PNNL: Mechanistic-Based Ductility Prediction for Complex Mg Castings PNNL: Mechanistic-Based Ductility Prediction for Complex Mg Castings 2012 DOE Hydrogen and Fuel Cells Program...

  14. Machine learning based prediction for peptide drift times in...

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

    Machine learning based prediction for peptide drift times in ion mobility spectrometry . Machine learning based prediction for peptide drift times in ion mobility spectrometry ....

  15. Ensemble climate predictions using climate models and observational constraints

    E-Print Network [OSTI]

    REVIEW Ensemble climate predictions using climate models and observational constraints BY PETER A. STOTT 1,* AND CHRIS E. FOREST 2 1 Hadley Centre for Climate Change (Reading Unit), Meteorology Building for constraining climate predictions based on observations of past climate change. The first uses large ensembles

  16. Predictive modelling of boiler fouling. Final report.

    SciTech Connect (OSTI)

    Chatwani, A

    1990-12-31T23:59:59.000Z

    A spectral element method embodying Large Eddy Simulation based on Re- Normalization Group theory for simulating Sub Grid Scale viscosity was chosen for this work. This method is embodied in a computer code called NEKTON. NEKTON solves the unsteady, 2D or 3D,incompressible Navier Stokes equations by a spectral element method. The code was later extended to include the variable density and multiple reactive species effects at low Mach numbers, and to compute transport of large particles governed by inertia. Transport of small particles is computed by treating them as trace species. Code computations were performed for a number of test conditions typical of flow past a deep tube bank in a boiler. Results indicate qualitatively correct behavior. Predictions of deposition rates and deposit shape evolution also show correct qualitative behavior. These simulations are the first attempts to compute flow field results at realistic flow Reynolds numbers of the order of 10{sup 4}. Code validation was not done; comparison with experiment also could not be made as many phenomenological model parameters, e.g., sticking or erosion probabilities and their dependence on experimental conditions were not known. The predictions however demonstrate the capability to predict fouling from first principles. Further work is needed: use of large or massively parallel machine; code validation; parametric studies, etc.

  17. Influence Of Three Dynamic Predictive Clothing Insulation Models On Building Energy Use, HVAC Sizing And Thermal Comfort

    E-Print Network [OSTI]

    Schiavon, Stefano; Lee, Kwang Ho

    2013-01-01T23:59:59.000Z

    Predictive Clothing Insulation Models based on Outdoor AirPREDICTIVE CLOTHING INSULATION MODELS ON BUILDING ENERGYthat the clothing insulation is equal to a constant value of

  18. A two-timescale approach to nonlinear Model Predictive Control

    SciTech Connect (OSTI)

    Buescher, K.L.; Baum, C.C.

    1994-10-01T23:59:59.000Z

    Model Predictive Control (MPC) schemes generate controls by using a model to predict the plant`s response to various control strategies. A problem arises when the underlying model is obtained by fitting a general nonlinear function, such as a neural network, to data: an exorbitant amount of data may be required to obtain accurate enough predictions. We describe a means of avoiding this problem that involves a simplified plant model which bases its predictions on averages of past control inputs. This model operates on a timescale slower than- the rate at which the controls are updated and the plant outputs are sampled. Not only does this technique give better closed-loop performance from the same amount of open-loop data, but it requires far less on-line computation as well. We illustrate the usefulness of this two-timescale approach by applying it to a simulated exothermic continuously stirred tank reactor with jacket dynamics.

  19. GIS-BASED PREDICTION OF HURRICANE FLOOD INUNDATION

    SciTech Connect (OSTI)

    JUDI, DAVID [Los Alamos National Laboratory; KALYANAPU, ALFRED [Los Alamos National Laboratory; MCPHERSON, TIMOTHY [Los Alamos National Laboratory; BERSCHEID, ALAN [Los Alamos National Laboratory

    2007-01-17T23:59:59.000Z

    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.

  20. In silico modeling to predict drug-induced phospholipidosis

    SciTech Connect (OSTI)

    Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov; Sadrieh, Nakissa

    2013-06-01T23:59:59.000Z

    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 structure–activity 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 80–81% 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.

  1. Predictive modelling of boiler fouling

    SciTech Connect (OSTI)

    Not Available

    1992-01-01T23:59:59.000Z

    In this reporting period, efforts were initiated to supplement the comprehensive flow field description obtained from the RNG-Spectral Element Simulations by incorporating, in a general framework, appropriate modules to model particle and condensable species transport to the surface. Specifically, a brief survey of the literature revealed the following possible mechanisms for transporting different ash constituents from the host gas to boiler tubes as deserving prominence in building the overall comprehensive model: (1) Flame-volatilized species, chiefly sulfates, are deposited on cooled boiler tubes via the mechanism of classical vapor diffusion. This mechanism is more efficient than the particulate ash deposition, and as a result there is usually an enrichment of condensable salts, chiefly sulfates, in boiler deposits; (2) Particle diffusion (Brownian motion) may account for deposition of some fine particles below 0. 1 mm in diameter in comparison with the mechanism of vapor diffusion and particle depositions, however, the amount of material transported to the tubes via this route is probably small. (3) Eddy diffusion, thermophoretic and electrophoretic deposition mechanisms are likely to have a marked influence in transporting 0.1 to 5[mu]m particles from the host gas to cooled boiler tubes; (4) Inertial impaction is the dominant mechanism in transporting particles above 5[mu]m in diameter to water and steam tubes in pulverized coal fired boiler, where the typical flue gas velocity is between 10 to 25 m/s. Particles above 10[mu]m usually have kinetic energies in excess of what can be dissipated at impact (in the absence of molten sulfate or viscous slag deposit), resulting in their entrainment in the host gas.

  2. Predictive modelling of boiler fouling

    SciTech Connect (OSTI)

    Not Available

    1992-01-01T23:59:59.000Z

    As this study incorporates in a general framework, appropriate modules to model condensable species transport to the surface along with particles, the need for a suitable solver for the reaction component of the species equations with regard to issues of stability, stiffness, economy, etc. becomes obvious. It is generally agreed in the literature that the major problem associated with the simultaneous integration of large sets of chemical kinetic rate equations is that of stiffness. Although stiffness does not have a simple definition, it is characterized by widely varying time constants. For example, in hydrogen-air combustion, the induction time is of the order of microseconds whereas the nitric oxide formation time is of the order of milliseconds. These widely different time constants present classical methods (such as the popular explicit Runge-Kutta method) with the following difficulty: to ensure stability of the numerical solution, these methods are restricted to using very short time steps that are determined by the smallest time constant. However, the time for all chemical species to reach near-equilibrium values is determined by the longest time constant. As a result, classical methods require excessive amounts of computer time to solve stiff systems of ordinary differential equations (ODE's). Several approaches for the solution of stiff ODE's have been proposed. Of all these techniques, the general purpose codes EPISODE and LSODE are regarded as the best available packaged'' codes for the solution of stiff systems of ODE'S. However, although these codes may be the best available for solving an arbitrary systems ODE'S, it may be possible to construct superior methods for solving a particular system of ODE's governing the behavior of a specific problem. In this view, an exponentially fitted method, CREK1D, deserves a special mention and is described briefly.

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

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

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

  4. area prediction models: Topics by E-print Network

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

    a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared Skogestad, Sigurd 159 Model predictive...

  5. 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, E-mail: hesheng@umich.edu [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Feng, Mary [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Frey, Kirk A. [Department of Radiology, University of Michigan, Ann Arbor, Michigan (United States); Ten Haken, Randall K.; Lawrence, Theodore S. [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Cao, Yue [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Department of Radiology, University of Michigan, Ann Arbor, Michigan (United States); Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan (United States)

    2013-08-01T23:59:59.000Z

    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 to maximize tumor control and minimize the risk of liver damage.

  6. A speed prediction model for a U.S. operating speed-based design consistency procedure on two-lane rural highways

    E-Print Network [OSTI]

    Ottesen, Jeffery Lynn

    1993-01-01T23:59:59.000Z

    was selected (MSE=l0. 43, R'=0. 802). No significant difference was found between the estimated values gencratcd by fourth-order polynomial model and the simple linear model (or=0. 05). Other factors such as the posted speed limit and operational... the design speed concept exclusively. ~g speed- based geometric design attempts to do what the design speed concept originally intended: Transportation Resemh Record 1195, National Research Council, Washington, D. C. , 1988, is used as a model...

  7. Prediction-Based Compression Ratio Boundaries for Medical Images

    E-Print Network [OSTI]

    Qi, Xiaojun

    Prediction-Based Compression Ratio Boundaries for Medical Images Xiaojun Qi Computer Science present prediction-based image compression techniques take advantage of either intra- or inter function. The prediction-based compression technique has been applied on some magnetic resonance (MR) brain

  8. Prediction-based estimating functions: review and new developments

    E-Print Network [OSTI]

    Sørensen, Michael

    Prediction-based estimating functions: review and new developments Michael Sørensen University@math.ku.dk March 9, 2011 Abstract The general theory of prediction-based estimating functions for stochastic differential equations. The Pearson diffusions, for which explicit optimal prediction-based estimating func

  9. Combining Modeling and Gaming for Predictive Analytics

    SciTech Connect (OSTI)

    Riensche, Roderick M.; Whitney, Paul D.

    2012-08-22T23:59:59.000Z

    Many of our most significant challenges involve people. While human behavior has long been studied, there are recent advances in computational modeling of human behavior. With advances in computational capabilities come increases in the volume and complexity of data that humans must understand in order to make sense of and capitalize on these modeling advances. Ultimately, models represent an encapsulation of human knowledge. One inherent challenge in modeling is efficient and accurate transfer of knowledge from humans to models, and subsequent retrieval. The simulated real-world environment of games presents one avenue for these knowledge transfers. In this paper we describe our approach of combining modeling and gaming disciplines to develop predictive capabilities, using formal models to inform game development, and using games to provide data for modeling.

  10. Autonomous Helicopter Formation using Model Predictive Control

    E-Print Network [OSTI]

    Sastry, S. Shankar

    Autonomous Helicopter Formation using Model Predictive Control Hoam Chung and S. Shankar Sastry are required to fly in tight formations and under harsh conditions. The starting point for safe autonomous into a formation, so that each vehicle can safely maintain sufficient space between it and all other vehicles

  11. Can Fault Prediction Models and Metrics be Used for Vulnerability Prediction? Yonghee Shin and Laurie Williams

    E-Print Network [OSTI]

    Young, R. Michael

    Can Fault Prediction Models and Metrics be Used for Vulnerability Prediction? Yonghee Shin to prioritize security inspection and testing efforts may be better served by a prediction model that indicates commonalities that may allow development teams to use traditional fault prediction models and metrics

  12. ISDA 2004--Budapest Model-Based Autonomy

    E-Print Network [OSTI]

    Sprinkle, Jonathan

    ISDA 2004--Budapest Model-Based Autonomy Jonathan Sprinkle, UC Berkeley127 August 2004 U n i v e r s i t y o f C a l i f o r n i a Berkeley Toward Design Parameterization Support for Model Predictive a Berkeley Model Predictive Control · MPC is a method for restricting/encouraging behavior · A "fortune

  13. Model Predictive Control of a Wind Lars Christian Henriksen

    E-Print Network [OSTI]

    wind turbines is on the sea as their is a more stable wind. These water based wind farms are confined locations to become potential wind farms. This thesis investigates control of both wind turbines mountedModel Predictive Control of a Wind Turbine Lars Christian Henriksen Kongens Lyngby 2007 IMM

  14. Statistical Prediction Based on Censored Life Data Luis A. Escobar

    E-Print Network [OSTI]

    Statistical Prediction Based on Censored Life Data Luis A. Escobar Dept. of Experimental Statistics life data to construct prediction bounds or intervals for future outcomes. Both new­sample prediction (e.g., using data from a previous sample to make predictions on the future failure time of a new unit

  15. Statistical Prediction Based on Censored Life Data Luis A. Escobar

    E-Print Network [OSTI]

    Statistical Prediction Based on Censored Life Data Luis A. Escobar Dept. of Experimental Statistics life data to construct prediction bounds or intervals for future outcomes. Both new-sample prediction (e.g., using data from a previous sample to make predictions on the future failure time of a new unit

  16. Disease Prediction Models and Operational Readiness

    SciTech Connect (OSTI)

    Corley, Courtney D.; Pullum, Laura L.; Hartley, David M.; Benedum, Corey M.; Noonan, Christine F.; Rabinowitz, Peter M.; Lancaster, Mary J.

    2014-03-19T23:59:59.000Z

    INTRODUCTION: The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. One of the primary goals of this research was to characterize the viability of biosurveillance models to provide operationally relevant information for decision makers to identify areas for future research. Two critical characteristics differentiate this work from other infectious disease modeling reviews. First, we reviewed models that attempted to predict the disease event, not merely its transmission dynamics. Second, we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011). Methods: We searched dozens of commercial and government databases and harvested Google search results for eligible models utilizing terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche-modeling, The publication date of search results returned are bound by the dates of coverage of each database and the date in which the search was performed, however all searching was completed by December 31, 2010. This returned 13,767 webpages and 12,152 citations. After de-duplication and removal of extraneous material, a core collection of 6,503 items was established and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. Next, PNNL’s IN-SPIRE visual analytics software was used to cross-correlate these publications with the definition for a biosurveillance model resulting in the selection of 54 documents that matched the criteria resulting Ten of these documents, However, dealt purely with disease spread models, inactivation of bacteria, or the modeling of human immune system responses to pathogens rather than predicting disease events. As a result, we systematically reviewed 44 papers and the results are presented in this analysis.

  17. AIMR (Azimuth and Inclination Modeling in Realtime): A Method for Prediction of Dog-Leg Severity based on Mechanical Specific Energy 

    E-Print Network [OSTI]

    Noynaert, Samuel F

    2013-08-13T23:59:59.000Z

    foot by foot basis while accurately predicting the effects of each parameter is impossible for the human brain alone. Given current rig rates, any amount of increased slide time and its reduced ROP which occurred due to poorly predicted directional...

  18. Solar Radiation Prediction and Energy Allocation for Energy Harvesting Base Stations

    E-Print Network [OSTI]

    Solar Radiation Prediction and Energy Allocation for Energy Harvesting Base Stations Yanan Bao@tsinghua.edu.cn Abstract--In this paper, we study how to use the solar radiation model to predict energy arrivals solar radiation is reviewed and summarized. We present two solar energy models for cloudless days

  19. Gamma-Ray Pulsars: Models and Predictions

    E-Print Network [OSTI]

    Alice K. Harding

    2000-12-12T23:59:59.000Z

    Pulsed emission from gamma-ray pulsars originates inside the magnetosphere, from radiation by charged particles accelerated near the magnetic poles or in the outer gaps. In polar cap models, the high energy spectrum is cut off by magnetic pair production above an energy that is dependent on the local magnetic field strength. While most young pulsars with surface fields in the range B = 10^{12} - 10^{13} G are expected to have high energy cutoffs around several GeV, the gamma-ray spectra of old pulsars having lower surface fields may extend to 50 GeV. Although the gamma-ray emission of older pulsars is weaker, detecting pulsed emission at high energies from nearby sources would be an important confirmation of polar cap models. Outer gap models predict more gradual high-energy turnovers at around 10 GeV, but also predict an inverse Compton component extending to TeV energies. Detection of pulsed TeV emission, which would not survive attenuation at the polar caps, is thus an important test of outer gap models. Next-generation gamma-ray telescopes sensitive to GeV-TeV emission will provide critical tests of pulsar acceleration and emission mechanisms.

  20. Trip Prediction and Route-Based Vehicle Energy Management

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

    Trip Prediction and Route-Based Vehicle Energy Management 2014 DOE Hydrogen Program and Vehicle Technologies Annual Merit Review June 18 th , 2014 Dominik Karbowski (PI), Aymeric...

  1. Model Predictive Control of Variable Density Multiphase Flows Governed by

    E-Print Network [OSTI]

    Hinze, Michael

    of model predictive control (MPC) consists in steering or keeping the state of a dynamical systemModel Predictive Control of Variable Density Multiphase Flows Governed by Diffuse Interface Models appearing in the model predictive control strategy. The resulting control concept is known as instantaneous

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

    SciTech Connect (OSTI)

    Rosenberg, Michael I.; Hart, Philip R.

    2014-10-01T23:59:59.000Z

    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.

  3. An integrated system for real-time Model Predictive Control of humanoid robots

    E-Print Network [OSTI]

    Todorov, Emanuel

    this goal. The automatic controller is based on real-time model-predictive control (MPC) applied to the full. The resulting composite cost is sent to the MPC machinery which constructs a new locally-optimal time- varying-based optimal control is called Model-Predictive Control (MPC), an approach that relies on real-time trajectory

  4. Stimulation Prediction Models | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro Industries Pvt LtdShawangunk,SoutheastSt.SteepStimulation Prediction Models Jump to:

  5. A minimal and predictive $T_7$ lepton flavor 331 model

    E-Print Network [OSTI]

    Hernández, A E Cárcamo

    2015-01-01T23:59:59.000Z

    We present a model based on the $SU(3)_{C}\\otimes SU(3)_{L}\\otimes U(1)_{X}$ gauge group having an extra $T_{7}\\otimes Z_{3}\\otimes Z_{14}$ flavor group, where the light active neutrino masses arise via double seesaw mechanism and the observed charged lepton mass hierarchy is a consequence of the $Z_{14}$ symmetry breaking at very high energy. In our minimal and predictive $T_7$ lepton flavor 331 model, the spectrum of neutrinos includes very light active neutrinos and heavy and very heavy sterile neutrinos. The obtained neutrino mixing parameters and neutrino mass squared splittings are compatible with the neutrino oscillation experimental data, for both normal and inverted hierarchies. The model predicts CP conservation in neutrino oscillations.

  6. Application of the Gebhart-Block Model for Predicting Vertical Temperature Distribution in a Large Space Building with Natural Ventilation

    E-Print Network [OSTI]

    Huang, C.; Song, Y.; Luo, X.

    2006-01-01T23:59:59.000Z

    Based on the Block model for predicting vertical temperature distribution in a large space, this paper describes an improved Gebhart-Block model for predicting vertical temperature distribution of a large space with natural ventilation...

  7. Performance Prediction based on Inherent Program Similarity

    E-Print Network [OSTI]

    John, Lizy Kurian

    the SPEC website. Our framework estimates per-benchmark machine ranks with a 0.89 av- erage and a 0 of a standardized benchmark suite for estimating the performance of the application of interest for two reasons,ljohn}@ece.utexas.edu ABSTRACT A key challenge in benchmarking is to predict the performance of an application of interest

  8. Designing Smart Environments: A Paradigm Based on Learning and Prediction

    E-Print Network [OSTI]

    Cook, Diane J.

    This chapter proposes a learning and prediction based paradigm for designing smart home environments and prediction based paradigm optimizes goal functions of smart home environments such as minimizing maintenance capability. MavHome implementation issues and some practical issues are also discussed. Keywords: Smart

  9. Prediction of Leptonic CP Phase in $A_4$ symmetric model

    E-Print Network [OSTI]

    Sin Kyu Kang; Morimitsu Tanimoto

    2015-01-29T23:59:59.000Z

    We consider minimal modifications to tribimaximal (TBM) mixing matrix which accommodate non-zero mixing angle $\\theta_{13}$ and CP violation. We derive four possible forms for the minimal modifications to TBM mixing in a model with $A_4$ flavor symmetry by incorporating symmetry breaking terms appropriately. We show how possible values of the Dirac-type CP phase $\\delta_D$ can be predicted with regards to two neutrino mixing angles in the standard parametrization of the neutrino mixing matrix. Carrying out numerical analysis based on the recent updated experimental results for neutrino mixing angles, we predict the values of the CP phase for all possible cases. We also confront our predictions of the CP phase with the updated fit.

  10. Spatiotemporal discrimination model predicts temporal masking functions

    E-Print Network [OSTI]

    CA 94035 a b Institute for Optical Research, Stockholm, Sweden W ABSTRACT e present a simplified dual, and masking based on local spatio­temporal contrast energy. The contras ensitivity filter parameters for the lack of space­time l s separability in contrast detection, the model has separate sustained

  11. Developing Models for Predictive Climate Science

    SciTech Connect (OSTI)

    Drake, John B [ORNL; Jones, Philip W [Los Alamos National Laboratory (LANL)

    2007-01-01T23:59:59.000Z

    The Community Climate System Model results from a multi-agency collaboration designed to construct cutting-edge climate science simulation models for a broad research community. Predictive climate simulations are currently being prepared for the petascale computers of the near future. Modeling capabilities are continuously being improved in order to provide better answers to critical questions about Earth's climate. Climate change and its implications are front page news in today's world. Could global warming be responsible for the July 2006 heat waves in Europe and the United States? Should more resources be devoted to preparing for an increase in the frequency of strong tropical storms and hurricanes like Katrina? Will coastal cities be flooded due to a rise in sea level? The National Climatic Data Center (NCDC), which archives all weather data for the nation, reports that global surface temperatures have increased over the last century, and that the rate of increase is three times greater since 1976. Will temperatures continue to climb at this rate, will they decline again, or will the rate of increase become even steeper? To address such a flurry of questions, scientists must adopt a systematic approach and develop a predictive framework. With responsibility for advising on energy and technology strategies, the DOE is dedicated to advancing climate research in order to elucidate the causes of climate change, including the role of carbon loading from fossil fuel use. Thus, climate science--which by nature involves advanced computing technology and methods--has been the focus of a number of DOE's SciDAC research projects. Dr. John Drake (ORNL) and Dr. Philip Jones (LANL) served as principal investigators on the SciDAC project, 'Collaborative Design and Development of the Community Climate System Model for Terascale Computers.' The Community Climate System Model (CCSM) is a fully-coupled global system that provides state-of-the-art computer simulations of the Earth's past, present, and future climate states. The collaborative SciDAC team--including over a dozen researchers at institutions around the country--developed, validated, documented, and optimized the performance of CCSM using the latest software engineering approaches, computational technology, and scientific knowledge. Many of the factors that must be accounted for in a comprehensive model of the climate system are illustrated in figure 1.

  12. Bayesian Models and Algorithms for Protein Beta-Sheet Prediction

    E-Print Network [OSTI]

    Erdogan, Hakan

    0 Bayesian Models and Algorithms for Protein Beta-Sheet Prediction Zafer Aydin, Student Member, IEEE, Yucel Altunbasak, Senior Member, IEEE, and Hakan Erdogan, Member, IEEE Abstract--Prediction of -sheet prediction defined as the prediction of -strand pairings, interaction types (parallel or anti

  13. A case model for predictive maintenance

    E-Print Network [OSTI]

    Li, Jiawei, M. Eng. Massachusetts Institute of Technology

    2008-01-01T23:59:59.000Z

    This project is to respond to a need by Varian Semiconductor Equipment Associates, Inc. (VSEA) to help predict failure of ion implanters. Predictive maintenance would help to reduce the unscheduled downtime of ion implanters, ...

  14. Colliding cascades model for earthquake prediction

    E-Print Network [OSTI]

    2000-10-12T23:59:59.000Z

    3 International Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences, Moscow, Russia. 4 Department of Earth ...

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

    SciTech Connect (OSTI)

    Ying, Khor Chia [Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor (Malaysia); Hin, Pooi Ah [Sunway University Business School, No. 5, Jalan Universiti, Bandar Sunway, 47500 Subang Jaya, Selangor (Malaysia)

    2014-06-19T23:59:59.000Z

    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 ?{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 ?{sup (j)}, we assume that ?{sup (j)} depends on ?{sup (j?m)}, ?{sup (j?m+1)},…, ?{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.

  16. Model Predictability-Form Lorenz System to Operational Ocean and

    E-Print Network [OSTI]

    Chu, Peter C.

    Model Predictability- Form Lorenz System to Operational Ocean and Atmospheric Models Peter C Chu. Poberezhny, 2002: Power law decay in model predictability skill. Geophysical Research Letters, 29 (15), 10 Six Months Four-Times Daily Data From July 9, 1998 for Verification #12;Model Generated Velocity

  17. Distributed state estimation and model predictive control of linear interconnected system

    E-Print Network [OSTI]

    Boyer, Edmond

    requirements, modern control systems are becoming more and more complex. For these processes, different controlDistributed state estimation and model predictive control of linear interconnected system: In this paper, a distributed and networked control system architecture based on independent Model Predictive

  18. Plug-and-play decentralized model predictive control for linear systems

    E-Print Network [OSTI]

    Ferrari-Trecate, Giancarlo

    1 Plug-and-play decentralized model predictive control for linear systems Stefano Riverso, Graduate to automatize the design of local controllers so that it can be carried out in parallel by smart actuators. In particular, local controllers exploit tube-based Model Predictive Control (MPC) in order to guarantee

  19. Exact Amplitude--Based Resummation QCD Predictions and LHC Data

    E-Print Network [OSTI]

    Ward, B F L; Yost, S A

    2014-01-01T23:59:59.000Z

    We present the current status of the comparisons with the respective data of the predictions of our approach of exact amplitude-based resummation in quantum field theory as applied to precision QCD calculations as needed for LHC physics, using the MC Herwiri1.031. The agreement between the theoretical predictions and the data exhibited continues to be encouraging.

  20. Model Predictive Control for Energy Efficient Buildings

    E-Print Network [OSTI]

    Ma, Yudong

    2012-01-01T23:59:59.000Z

    Learning Control for Thermal Energy Storage Systems”. In:Predictive Control of Thermal Energy Storage in Buildingmaking use of building thermal energy storage, and this work

  1. Advantages and Limitations of an In Vitro Lipolysis Model as a Predictive Tool in the Development of Lipid Based Oral Formulations or Lipophilic Drugs

    E-Print Network [OSTI]

    Dahan, Arik

    2006-10-26T23:59:59.000Z

    -physiological conditions In vitro dynamic lipolysis model (stage 1) In vitro dynamic lipolysis model (stage 2) #0;? Drug in formulation is dispersed in the system #0;? Experiment initiated with the insertion of pancreatic juice #0;? Throughout lipolysis, free FA... l Oil phase Aqueous phase Sediment phase Most readily available for absorption Not available for absorption May participate in absorption In vitro dynamic lipolysis model (stage 3) #0;? Following the completion of the lipolysis, aliquots...

  2. Markovian Models for Electrical Load Prediction in Smart Buildings

    E-Print Network [OSTI]

    California at Santa Barbara, University of

    Markovian Models for Electrical Load Prediction in Smart Buildings Muhammad Kumail Haider, Asad,13100004,ihsan.qazi}@lums.edu.pk Abstract. Developing energy consumption models for smart buildings is important develop parsimo- nious Markovian models of smart buildings for different periods in a day for predicting

  3. NONLINEAR MODEL PREDICTIVE CONTROL VIA FEASIBILITYPERTURBED SEQUENTIAL QUADRATIC

    E-Print Network [OSTI]

    Wright, Steve

    NONLINEAR MODEL PREDICTIVE CONTROL VIA FEASIBILITY­PERTURBED SEQUENTIAL QUADRATIC PROGRAMMING­06, AUGUST 2002, COMPUTER SCIENCES DEPT, UNIV. OF WISCONSIN TEXAS­WISCONSIN MODELING AND CONTROL CONSORTIUM REPORT TWMCC­2002­02 Abstract. Model predictive control requires the solution of a sequence of continuous

  4. age prediction models: Topics by E-print Network

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

    a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared Skogestad, Sigurd 162 On biases in the...

  5. accident prediction models: Topics by E-print Network

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

    a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared Skogestad, Sigurd 136 Title: Development of...

  6. animal models predictive: Topics by E-print Network

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

    a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared Skogestad, Sigurd 222 Title: Development of...

  7. accident prediction model: Topics by E-print Network

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

    a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared Skogestad, Sigurd 136 Title: Development of...

  8. TROPICAL DEFORESTATION MODELLING: A COMPARATIVE ANALYSIS OF DIFFERENT PREDICTIVE APPROACHES.

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    TROPICAL DEFORESTATION MODELLING: A COMPARATIVE ANALYSIS OF DIFFERENT PREDICTIVE APPROACHES-time discretisation; Remote Sensing; Neural Networks; Markov Chains; MCE; Dinamica; Risk management; Deforestation

  9. Hospital Readmission in General Medicine Patients: A Prediction Model

    E-Print Network [OSTI]

    2010-01-01T23:59:59.000Z

    to the department of medicine as a screening tool forquality of care problems. Medicine. 2008;87:294–300. 3.Readmission in General Medicine Patients: A Prediction Model

  10. Model-based tomographic reconstruction

    DOE Patents [OSTI]

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

    2012-06-26T23:59:59.000Z

    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.

  11. Hot blast stove process model and model-based controller

    SciTech Connect (OSTI)

    Muske, K.R. [Villanova Univ., PA (United States). Dept. of Chemical Engineering; Howse, J.W.; Hansen, G.A.; Cagliostro, D.J. [Los Alamos National Lab., NM (United States). Computational Science Methods Group; Chaubal, P.C. [Inland Steel Industries, Inc., East Chicago, IN (United States). Research Labs.

    1998-12-31T23:59:59.000Z

    This paper describes the process model and model-based control techniques implemented on the hot blast stoves for the No. 7 Blast Furnace at the Inland Steel facility in East Chicago, Indiana. A detailed heat transfer model of the stoves is developed and verified using plant data. This model is used as part of a predictive control scheme to determine the minimum amount of fuel necessary to achieve the blast air requirements. The model is also used to predict maximum and minimum temperature constraint violations within the stove so that the controller can take corrective actions while still achieving the required stove performance.

  12. Climate Prediction: The Limits of Ocean Models

    E-Print Network [OSTI]

    Stone, Peter H.

    We identify three major areas of ignorance which limit predictability in current ocean GCMs. One is the very crude representation of subgrid-scale mixing processes. These processes are parameterized with coefficients whose ...

  13. Bootstrap Prediction for Returns and Volatilities in GARCH Models

    E-Print Network [OSTI]

    Ortega, Esther Ruiz

    Bootstrap Prediction for Returns and Volatilities in GARCH Models Lorenzo Pascuala , Juan Romob of GARCH processes is proposed. Financial market participants have shown an increasing interest Autoregressive Conditionally Heteroscedastic (GARCH) models, originally introduced by Bollerslev (1986), provide

  14. Model Predictive Control of a Kaibel Distillation Column

    E-Print Network [OSTI]

    Skogestad, Sigurd

    Model Predictive Control of a Kaibel Distillation Column Martin Kvernland Ivar Halvorsen Sigurd (e-mail: skoge@ntnu.no) Abstract: This is a simulation study on controlling a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared

  15. Chance Constrained Model Predictive Control Alexander T. Schwarm

    E-Print Network [OSTI]

    Nikolaou, Michael

    through a simulation case study on a high-purity distillation column. Suggestions for further improvements@uh.edu #12;2 Abstract This work focuses on robustness of model predictive control (MPC) with respect such property, particularly important for constrained model predictive control (MPC) systems

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

    SciTech Connect (OSTI)

    Hemez, Francois M [Los Alamos National Laboratory; Unal, Cetin [Los Alamos National Laboratory; Atamturktur, Huriye S [CLEMSON UNIV.

    2010-01-01T23:59:59.000Z

    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.

  17. Nonlinear Model Predictive Control of Municipal Solid Waste Combustion Plants

    E-Print Network [OSTI]

    Van den Hof, Paul

    Nonlinear Model Predictive Control of Municipal Solid Waste Combustion Plants M. Leskens , R.h.Bosgra@tudelft.nl, p.m.j.vandenhof@tudelft.nl Keywords : nonlinear model predictive control, municipal solid waste combus- tion Abstract : Combustion of municipal solid waste (MSW; = household waste) is used to reduce

  18. Project Profile: Predictive Physico-Chemical Modeling of Intrinsic Degradation Mechanisms for Advanced Reflector Materials

    Broader source: Energy.gov [DOE]

    NREL, under the Physics of Reliability: Evaluating Design Insights for Component Technologies in Solar (PREDICTS) Program will be developing a physics-based computational degradation model to assess the kinetic oxidation rates; realistic model light attenuation and transport; and multi-layer treatment with variable properties Simulation based experimental design.

  19. Spatial predictive distribution for precipitation based on numerical weather predictions (NWP)

    E-Print Network [OSTI]

    Steinsland, Ingelin

    for precipitation based on NWP #12;Motivation, hydro power production How much water comes when? With uncertainty Precipitation Data Meteorological model NWP Short term optimalization Run off Hydrological model Past Future

  20. 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

    2013-09-01T23:59:59.000Z

    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.

  1. Predicting the Energy Output of Wind Farms Based on Weather Data: Important Variables and their Correlation

    E-Print Network [OSTI]

    Vladislavleva, Katya; Neumann, Frank; Wagner, Markus

    2011-01-01T23:59:59.000Z

    Wind energy plays an increasing role in the supply of energy world-wide. The energy output of a wind farm is highly dependent on the weather condition present at the wind farm. If the output can be predicted more accurately, energy suppliers can coordinate the collaborative production of different energy sources more efficiently to avoid costly overproductions. With this paper, we take a computer science perspective on energy prediction based on weather data and analyze the important parameters as well as their correlation on the energy output. To deal with the interaction of the different parameters we use symbolic regression based on the genetic programming tool DataModeler. Our studies are carried out on publicly available weather and energy data for a wind farm in Australia. We reveal the correlation of the different variables for the energy output. The model obtained for energy prediction gives a very reliable prediction of the energy output for newly given weather data.

  2. Detection and Prediction of Errors in EPCs of the SAP Reference Model

    E-Print Network [OSTI]

    van der Aalst, Wil

    as a blueprint for roll-out projects of SAP's ERP system. It reflects Version18 4.6 of SAP R/3 which was marketedDetection and Prediction of Errors in EPCs of the SAP Reference Model J. Mendling a, H.M.W. Verbeek provide empirical evidence for these questions based on the SAP reference model. This model collection

  3. ai based prediction: Topics by E-print Network

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

    implementing game artificial intelligence (AI) for video Boyer, Edmond 12 Cost-Based Abduction (CBA) is an AI model for reasoning under uncertainty. In CBA, evidence to...

  4. Estimation and prediction in spatial models with block composite likelihoods

    E-Print Network [OSTI]

    Reich, Brian J.

    Estimation and prediction in spatial models with block composite likelihoods Jo Eidsvik1 , Benjamin, IA 50011, U.S.A. (niemi@iastate.edu) 1 #12;Abstract A block composite likelihood is developed for estimation and prediction in large spatial datasets. The composite likelihood is constructed from the joint

  5. Micromechanical Modeling of Filament Wound Cement-Based Composites

    E-Print Network [OSTI]

    Mobasher, Barzin

    Micromechanical Modeling of Filament Wound Cement-Based Composites B. Mobasher, M.ASCE1 Abstract: A theoretical model to predict the response of laminated cement-based composites is developed. The micromechanical model simulates the mechanical response of a multilayer cement-based composite laminate under

  6. Hierarchical Bayesian Models for Predicting The Spread of Ecological Processes

    E-Print Network [OSTI]

    Hierarchical Bayesian Models for Predicting The Spread of Ecological Processes Christopher K. Wikle Department of Statistics, University of Missouri To appear: Ecology June 10, 2002 Key Words: Bayesian, Diffusion, Forecast, Hierarchical, House Finch, Invasive, Malthu- sian, State Space, Uncertainty Abstract

  7. Predictive capacity planning modeling with tactical and strategic applications

    E-Print Network [OSTI]

    Zeppieri, Michael A. (Michael Anthony), 1975-

    2004-01-01T23:59:59.000Z

    The focus of my internship was the development of a predictive capacity planning model to characterize the storage requirements and space utilization for Amazon's Campbellsville (SDF) Fulfillment Center (FC). Amazon currently ...

  8. On the predictive capability and stability of rubber material models

    E-Print Network [OSTI]

    Zheng, Haining

    2008-01-01T23:59:59.000Z

    Due to the high non-linearity and incompressibility constraint of rubber materials, the predictive capability and stability of rubber material models require specific attention for practical engineering analysis. In this ...

  9. Settlement Prediction, Gas Modeling and Slope Stability Analysis

    E-Print Network [OSTI]

    Politècnica de Catalunya, Universitat

    Settlement Prediction, Gas Modeling and Slope Stability Analysis in Coll Cardús Landfill Li Yu using mechanical models Simulation of gas generation, transport and extraction in MSW landfill 1 models Simulation of gas generation, transport and extraction in MSW landfill 1) Analytical solution

  10. Conformal Higgs model: predicted dark energy density

    E-Print Network [OSTI]

    R. K. Nesbet

    2014-11-03T23:59:59.000Z

    Postulated universal Weyl conformal scaling symmetry provides an alternative to the $\\Lambda$CDM paradigm for cosmology. Recent applications to galactic rotation velocities, Hubble expansion, and a model of dark galactic halos explain qualitative phenomena and fit observed data without invoking dark matter. Significant revision of theory relevant to galactic collisions and clusters is implied, but not yet tested. Dark energy is found to be a consequence of conformal symmetry for the Higgs scalar field of electroweak physics. The present paper tests this implication. The conformal Higgs model acquires a gravitational effect described by a modified Friedmann cosmic evolution equation, shown to fit cosmological data going back to the cosmic microwave background epoch. The tachyonic mass parameter of the Higgs model becomes dark energy in the Friedmann equation. A dynamical model of this parameter, analogous to the Higgs mechanism for gauge boson mass, is derived and tested here. An approximate calculation yields a result consistent with the empirical magnitude inferred from Hubble expansion.

  11. Model Predictive Control for Energy Efficient Buildings

    E-Print Network [OSTI]

    Ma, Yudong

    2012-01-01T23:59:59.000Z

    T mixed T amb d OA ?T supply Cooling Fan Heating 20 Time (models for supply fan (5.6), cooling and heating coils (5.7)Solar radiation u cooling/heating coils supply fan dampers

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

    SciTech Connect (OSTI)

    Hoffman, E.; Skidmore, E.

    2009-11-24T23:59:59.000Z

    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 higher than the estimates due to the conservative assumptions used for the model. For lower heat loads at similar ambient temperatures, seal lifetime is further increased. The preliminary model is based on several assumptions that require validation with additional experiments and longer exposures at more realistic conditions. The assumption of constant exposure at peak temperature is believed to be conservative. Cumulative damage at more realistic conditions will likely be less severe but is more difficult to assess based on available data. Arrhenius aging behavior is expected, but non-Arrhenius behavior is possible. Validation of Arrhenius behavior is ideally determined from longer tests at temperatures closer to actual service conditions. CSR experiments will therefore continue at lower temperatures to validate the model. Ultrasensitive oxygen consumption analysis has been shown to be useful in identifying non-Arrhenius behavior within reasonable test periods. Therefore, additional experiments are recommended and planned to validate the model.

  13. Model for predicting the acrosswind response of

    E-Print Network [OSTI]

    Kareem, Ahsan

    force fluctuations are formulated, based on wind tunnel measurements. A statistical integration scheme the preliminary design of tall buildings. Keywords: buildings, wind Ioadings, acrosswind response It is important to recognize the unsteady nature of wind loads in the design of buildings to ensure structural safety

  14. Predictive modeling of pedestal structure in KSTAR using EPED model

    SciTech Connect (OSTI)

    Han, Hyunsun; Kim, J. Y. [National Fusion Research Institute, Daejeon 305-806 (Korea, Republic of)] [National Fusion Research Institute, Daejeon 305-806 (Korea, Republic of); Kwon, Ohjin [Department of Physics, Daegu University, Gyeongbuk 712-714 (Korea, Republic of)] [Department of Physics, Daegu University, Gyeongbuk 712-714 (Korea, Republic of)

    2013-10-15T23:59:59.000Z

    A predictive calculation is given for the structure of edge pedestal in the H-mode plasma of the KSTAR (Korea Superconducting Tokamak Advanced Research) device using the EPED model. Particularly, the dependence of pedestal width and height on various plasma parameters is studied in detail. The two codes, ELITE and HELENA, are utilized for the stability analysis of the peeling-ballooning and kinetic ballooning modes, respectively. Summarizing the main results, the pedestal slope and height have a strong dependence on plasma current, rapidly increasing with it, while the pedestal width is almost independent of it. The plasma density or collisionality gives initially a mild stabilization, increasing the pedestal slope and height, but above some threshold value its effect turns to a destabilization, reducing the pedestal width and height. Among several plasma shape parameters, the triangularity gives the most dominant effect, rapidly increasing the pedestal width and height, while the effect of elongation and squareness appears to be relatively weak. Implication of these edge results, particularly in relation to the global plasma performance, is discussed.

  15. Bayesian calibration of a k -turbulence model for predictive jet-in-crossflow simulations

    E-Print Network [OSTI]

    Ray, Jaideep

    Bayesian calibration of a k - turbulence model for predictive jet-in-crossflow simulations Jaideep skill in jet-in-crossflow simulations. The method is based on the hypotheses that (1) informative features of jet-in-crossflow interactions and (2) one can construct surrogates of RANS models

  16. Model Based Control Refrigeration Systems

    E-Print Network [OSTI]

    Model Based Control of Refrigeration Systems Ph.D. Thesis Lars Finn Sloth Larsen Central R & D University, Denmark. The work has been carried out at the Central R&D - Refrigeration and Air Conditioning The subject for this Ph.D. thesis is model based control of refrigeration systems. Model based control covers

  17. Behavior-Based Budget Management Using Predictive Analytics

    SciTech Connect (OSTI)

    Troy Hiltbrand

    2013-03-01T23:59:59.000Z

    Historically, the mechanisms to perform forecasting have primarily used two common factors as a basis for future predictions: time and money. While time and money are very important aspects of determining future budgetary spend patterns, organizations represent a complex system of unique individuals with a myriad of associated behaviors and all of these behaviors have bearing on how budget is utilized. When looking to forecasted budgets, it becomes a guessing game about how budget managers will behave under a given set of conditions. This becomes relatively messy when human nature is introduced, as different managers will react very differently under similar circumstances. While one manager becomes ultra conservative during periods of financial austerity, another might be un-phased and continue to spend as they have in the past. Both might revert into a state of budgetary protectionism masking what is truly happening at a budget holder level, in order to keep as much budget and influence as possible while at the same time sacrificing the greater good of the organization. To more accurately predict future outcomes, the models should consider both time and money and other behavioral patterns that have been observed across the organization. The field of predictive analytics is poised to provide the tools and methodologies needed for organizations to do just this: capture and leverage behaviors of the past to predict the future.

  18. Predicting Vehicle Crashworthiness: Validation of Computer Models for

    E-Print Network [OSTI]

    Berger, Jim

    Predicting Vehicle Crashworthiness: Validation of Computer Models for Functional and Hierarchical. Cafeo, Chin-Hsu Lin, and Jian Tu Abstract The CRASH computer model simulates the effect of a vehicle colliding against different barrier types. If it accurately represents real vehicle crash- worthiness

  19. Modelling Monsoons: Understanding and Predicting Current and Future Behaviour

    SciTech Connect (OSTI)

    Turner, A; Sperber, K R; Slingo, J M; Meehl, G A; Mechoso, C R; Kimoto, M; Giannini, A

    2008-09-16T23:59:59.000Z

    The global monsoon system is so varied and complex that understanding and predicting its diverse behaviour remains a challenge that will occupy modellers for many years to come. Despite the difficult task ahead, an improved monsoon modelling capability has been realized through the inclusion of more detailed physics of the climate system and higher resolution in our numerical models. Perhaps the most crucial improvement to date has been the development of coupled ocean-atmosphere models. From subseasonal to interdecadal timescales, only through the inclusion of air-sea interaction can the proper phasing and teleconnections of convection be attained with respect to sea surface temperature variations. Even then, the response to slow variations in remote forcings (e.g., El Nino-Southern Oscillation) does not result in a robust solution, as there are a host of competing modes of variability that must be represented, including those that appear to be chaotic. Understanding the links between monsoons and land surface processes is not as mature as that explored regarding air-sea interactions. A land surface forcing signal appears to dominate the onset of wet season rainfall over the North American monsoon region, though the relative role of ocean versus land forcing remains a topic of investigation in all the monsoon systems. Also, improved forecasts have been made during periods in which additional sounding observations are available for data assimilation. Thus, there is untapped predictability that can only be attained through the development of a more comprehensive observing system for all monsoon regions. Additionally, improved parameterizations - for example, of convection, cloud, radiation, and boundary layer schemes as well as land surface processes - are essential to realize the full potential of monsoon predictability. Dynamical considerations require ever increased horizontal resolution (probably to 0.5 degree or higher) in order to resolve many monsoon features including, but not limited to, the Mei-Yu/Baiu sudden onset and withdrawal, low-level jet orientation and variability, and orographic forced rainfall. Under anthropogenic climate change many competing factors complicate making robust projections of monsoon changes. Without aerosol effects, increased land-sea temperature contrast suggests strengthened monsoon circulation due to climate change. However, increased aerosol emissions will reflect more solar radiation back to space, which may temper or even reduce the strength of monsoon circulations compared to the present day. A more comprehensive assessment is needed of the impact of black carbon aerosols, which may modulate that of other anthropogenic greenhouse gases. Precipitation may behave independently from the circulation under warming conditions in which an increased atmospheric moisture loading, based purely on thermodynamic considerations, could result in increased monsoon rainfall under climate change. The challenge to improve model parameterizations and include more complex processes and feedbacks pushes computing resources to their limit, thus requiring continuous upgrades of computational infrastructure to ensure progress in understanding and predicting the current and future behavior of monsoons.

  20. A physics-based emissions model for aircraft gas turbine combustors

    E-Print Network [OSTI]

    Allaire, Douglas L

    2006-01-01T23:59:59.000Z

    In this thesis, a physics-based model of an aircraft gas turbine combustor is developed for predicting NO. and CO emissions. The objective of the model is to predict the emissions of current and potential future gas turbine ...

  1. Lepton Flavor Violation in Predictive SUSY-GUT Models

    SciTech Connect (OSTI)

    Albright, Carl H.; /Northern Illinois U. /Fermilab; Chen, Mu-Chun; /UC, Irvine

    2008-02-01T23:59:59.000Z

    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.

  2. Predictability and reduced order modeling in stochastic reaction networks.

    SciTech Connect (OSTI)

    Najm, Habib N.; Debusschere, Bert J.; Sargsyan, Khachik

    2008-10-01T23:59:59.000Z

    Many systems involving chemical reactions between small numbers of molecules exhibit inherent stochastic variability. Such stochastic reaction networks are at the heart of processes such as gene transcription, cell signaling or surface catalytic reactions, which are critical to bioenergy, biomedical, and electrical storage applications. The underlying molecular reactions are commonly modeled with chemical master equations (CMEs), representing jump Markov processes, or stochastic differential equations (SDEs), rather than ordinary differential equations (ODEs). As such reaction networks are often inferred from noisy experimental data, it is not uncommon to encounter large parametric uncertainties in these systems. Further, a wide range of time scales introduces the need for reduced order representations. Despite the availability of mature tools for uncertainty/sensitivity analysis and reduced order modeling in deterministic systems, there is a lack of robust algorithms for such analyses in stochastic systems. In this talk, we present advances in algorithms for predictability and reduced order representations for stochastic reaction networks and apply them to bistable systems of biochemical interest. To study the predictability of a stochastic reaction network in the presence of both parametric uncertainty and intrinsic variability, an algorithm was developed to represent the system state with a spectral polynomial chaos (PC) expansion in the stochastic space representing parametric uncertainty and intrinsic variability. Rather than relying on a non-intrusive collocation-based Galerkin projection [1], this PC expansion is obtained using Bayesian inference, which is ideally suited to handle noisy systems through its probabilistic formulation. To accommodate state variables with multimodal distributions, an adaptive multiresolution representation is used [2]. As the PC expansion directly relates the state variables to the uncertain parameters, the formulation lends itself readily to sensitivity analysis. Reduced order modeling in the time dimension is accomplished using a Karhunen-Loeve (KL) decomposition of the stochastic process in terms of the eigenmodes of its covariance matrix. Subsequently, a Rosenblatt transformation relates the random variables in the KL decomposition to a set of independent random variables, allowing the representation of the system state with a PC expansion in those independent random variables. An adaptive clustering method is used to handle multimodal distributions efficiently, and is well suited for high-dimensional spaces. The spectral representation of the stochastic reaction networks makes these systems more amenable to analysis, enabling a detailed understanding of their functionality, and robustness under experimental data uncertainty and inherent variability.

  3. 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 (Massachusetts Institute of Technology, Cambridge, MA); Armstrong, Robert C.; Vanderveen, Keith

    2008-09-01T23:59:59.000Z

    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.

  4. Model to predict the mechanical behaviour of oriented rigid PVC

    E-Print Network [OSTI]

    Miroshnychenko, Dmitri

    Model to predict the mechanical behaviour of oriented rigid PVC D. J. Hitt*1 and D. Miroshnychenko2 The mechanical properties of PVC sheets can be modified substantially by both uniaxial and biaxial stretching pattern in the relationship between tensile properties of oriented PVC products and imposed strains

  5. Penetration rate prediction for percussive drilling via dry friction model

    E-Print Network [OSTI]

    Krivtsov, Anton M.

    Penetration rate prediction for percussive drilling via dry friction model Anton M. Krivtsov a of percussive drilling assuming a dry friction mechanism to explain the experimentally observed drop in pene as a frictional pair, and this can generate the pattern of the impact forces close to reality. Despite quite

  6. Reference wind farm selection for regional wind power prediction models

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Reference wind farm selection for regional wind power prediction models Nils Siebert George.siebert@ensmp.fr, georges.kariniotakis@ensmp.fr Abstract Short-term wind power forecasting is recognized today as a major requirement for a secure and economic integration of wind generation in power systems. This paper deals

  7. Fast Nonconvex Model Predictive Control for Commercial Refrigeration

    E-Print Network [OSTI]

    Fast Nonconvex Model Predictive Control for Commercial Refrigeration Tobias Gybel Hovgard , Lars F multi-zone refrigeration system, consisting of several cooling units that share a common compressor. This corresponds roughly to 2% of the entire electricity consumption in the country. Refrigerated goods constitute

  8. Model Predictive Control For Wind Excited Buildings: A Benchmark Problem

    E-Print Network [OSTI]

    Kareem, Ahsan

    control force; W is the wind excitation vector of dimension 24; and are control output vec- tor , , , , , , , and were given by Yang et al (1999) and have appropriate dimensions. The wind force data acting1 Model Predictive Control For Wind Excited Buildings: A Benchmark Problem Gang Mei, Student M

  9. 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

    2008-03-20T23:59:59.000Z

    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.

  10. A distributed accelerated gradient algorithm for distributed model predictive

    E-Print Network [OSTI]

    Como, Giacomo

    of hydro power plants is to manage the available water resources efficiently, while following an optimal is applied to the power reference tracking problem of a hydro power valley (HPV) system. The applied power control, Distributed optimization, Accelerated gradient algorithm, Model predictive control

  11. Predicting solar cycle 24 with a solar dynamo model

    E-Print Network [OSTI]

    Arnab Rai Choudhuri; Piyali Chatterjee; Jie Jiang

    2007-01-18T23:59:59.000Z

    Whether the upcoming cycle 24 of solar activity will be strong or not is being hotly debated. The solar cycle is produced by a complex dynamo mechanism. We model the last few solar cycles by `feeding' observational data of the Sun's polar magnetic field into our solar dynamo model. Our results fit the observed sunspot numbers of cycles 21-23 extremely well and predict that cycle~24 will be about 35% weaker than cycle~23.

  12. A Graphical Model for Predicting Protein Molecular Function Barbara E. Engelhardt bee@cs.berkeley.edu

    E-Print Network [OSTI]

    function within the homologous proteins, despite the lack of a direct connection between sequenceA Graphical Model for Predicting Protein Molecular Function Barbara E. Engelhardt bee function evolves within a phylogenetic tree based on the proteins' sequence. Inputs are a phylogeny

  13. A graphical model for predicting protein molecular function Barbara E Engelhardt bee@cs.berkeley.edu

    E-Print Network [OSTI]

    Stephens, Matthew

    function within the homologous proteins, despite the lack of a direct connection between sequenceA graphical model for predicting protein molecular function Barbara E Engelhardt bee function evolves within a phylogenetic tree based on the proteins' sequence. Inputs are a phylogeny

  14. Application of a spatially referenced water quality model to predict E. coli flux in two Texas river basins

    E-Print Network [OSTI]

    , Deepti

    2009-05-15T23:59:59.000Z

    Water quality models are applied to assess the various processes affecting the concentrations of contaminants in a watershed. SPAtially Referenced Regression On Watershed attributes (SPARROW) is a nonlinear regression based approach to predict...

  15. Model Predictability Depends on Model Fidelity: Challenges in...

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

    and climate, and projections of climate change, show that current climate and Earth-system models continue to have stubborn irreducible errors. It is unlikely that the...

  16. Stochastic Models Predict User Behavior in Social Media

    E-Print Network [OSTI]

    Hogg, Tad; Smith, Laura M

    2013-01-01T23:59:59.000Z

    User response to contributed content in online social media depends on many factors. These include how the site lays out new content, how frequently the user visits the site, how many friends the user follows, how active these friends are, as well as how interesting or useful the content is to the user. We present a stochastic modeling framework that relates a user's behavior to details of the site's user interface and user activity and describe a procedure for estimating model parameters from available data. We apply the model to study discussions of controversial topics on Twitter, specifically, to predict how followers of an advocate for a topic respond to the advocate's posts. We show that a model of user behavior that explicitly accounts for a user transitioning through a series of states before responding to an advocate's post better predicts response than models that fail to take these states into account. We demonstrate other benefits of stochastic models, such as their ability to identify users who a...

  17. Risk prediction models for melanoma: A systematic review

    E-Print Network [OSTI]

    Usher-Smith, Juliet A.; Emery, Jon; Kassianos, Angelos P.; Walter, Fiona M.

    2014-06-03T23:59:59.000Z

    of Cambridge, Cambridge, UK. 2 General Practice and Primary Care Academic Centre, University of Melbourne, Australia. 3 School of Primary, Aboriginal and Rural Health Care, University of Western Australia, Australia. Running title: Risk prediction models... :1000129. 35. English, DR, Armstrong, BK. Identifying people at high risk of cutaneous malignant melanoma: Results from a case-control study in Western Australia. Br. Med. J. (Clin. Res. Ed). 1988; 296: 1285–1288. 36. Amir, E, Freedman, OC, Seruga...

  18. Carbon-cycle models for better long-term predictions | EMSL

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

    Carbon-cycle models for better long-term predictions Carbon-cycle models for better long-term predictions Released: November 04, 2014 Reduced variation among models should improve...

  19. Development of a scalable model for predicting arsenic transport coupled with oxidation and adsorption reactions

    E-Print Network [OSTI]

    Clement, Prabhakar

    modeling; Contaminant transport; Scaling; Numerical modeling 1. Introduction Management of groundwaterDevelopment of a scalable model for predicting arsenic transport coupled with oxidation is critical for predicting its transport dynamics in groundwater systems. We completed batch experiments

  20. Hybrid model predictive control of induction of Escherichia coli A. Agung Julius, M. Selman Sakar, Alberto Bemporad and George J. Pappas

    E-Print Network [OSTI]

    Pappas, George J.

    regulating the fraction of induction of a colony of Escherichia coli. We use the abstract model to designHybrid model predictive control of induction of Escherichia coli A. Agung Julius, M. Selman Sakar a feedback controller based on model predictive control strategy. Upon simulation, we show that the model

  1. Neutrino minimal standard model predictions for neutrinoless double beta decay

    SciTech Connect (OSTI)

    Bezrukov, F. [Institute for Nuclear Research of the Russian Academy of Sciences, 60th October Anniversary prospect 7a, Moscow 117312 (Russian Federation) and Institut de Theorie des Phenomenes Physiques, Ecole Polytechnique Federale de Lausanne, CH-1015 Lausanne (Switzerland)

    2005-10-01T23:59:59.000Z

    Prediction of the effective Majorana mass for neutrinoless double {beta} decay in a simple extension of the standard model ({nu}MSM) is given. The model adds three right-handed neutrinos with masses smaller than the electroweak scale and explains dark matter of the Universe. This leads to constraints 1.3

  2. Fuel Conditioning Facility Electrorefiner Model Predictions versus Measurements

    SciTech Connect (OSTI)

    D Vaden

    2007-10-01T23:59:59.000Z

    Electrometallurgical treatment of spent nuclear fuel is performed in the Fuel Conditioning Facility (FCF) at the Idaho National Laboratory (INL) by electrochemically separating uranium from the fission products and structural materials in a vessel called an electrorefiner (ER). To continue processing without waiting for sample analyses to assess process conditions, an ER process model predicts the composition of the ER inventory and effluent streams via multicomponent, multi-phase chemical equilibrium for chemical reactions and a numerical solution to differential equations for electro-chemical transport. The results of the process model were compared to the electrorefiner measured data.

  3. A prediction based control scheme for networked systems with delays and packet dropouts

    E-Print Network [OSTI]

    Knobloch,Jürgen

    A prediction based control scheme for networked systems with delays and packet dropouts Lars Gr based prediction and time-stamps in order to compensate for delays and packet dropouts to analyze the properties of our scheme, we introduce the notion of prediction consistency which enables us

  4. Predictive models for power dissipation in optical transceivers

    E-Print Network [OSTI]

    Butler, Katherine, 1981-

    2004-01-01T23:59:59.000Z

    Power dissipation in optical networks is a significant problem for the telecommunications industry. The optical transceiver was selected as a representative device of the network, and a component based power model is ...

  5. Unified model of voltage/current mode control to predict subharmonic oscillation

    E-Print Network [OSTI]

    Fang, Chung-Chieh

    2012-01-01T23:59:59.000Z

    A unified model of voltage mode control (VMC) and current mode control (CMC) is proposed to predict the subharmonic oscillation. In the unified model, based on the sampled-data slope-based analysis, the subharmonic oscillation boundary conditions for VMC/CMC have similar forms. The boundary conditions are exact, and can be further simplified in various approximate closed forms for design purpose. Harmonic balance analysis is also applied. Both the slope-based and harmonic balance analysis are applied to analyze five different VMC/CMC control schemes. A new "HB plot" and an equivalent "M plot" are proposed to accurately predict the subharmonic oscillation. The relation between the crossover frequency and the subharmonic oscillation is also analyzed.

  6. Predicting Land-Ice Retreat and Sea-Level Rise with the Community Earth System Model

    SciTech Connect (OSTI)

    Lipscomb, William [Los Alamos National Laboratory

    2012-06-19T23:59:59.000Z

    Coastal stakeholders need defensible predictions of 21st century sea-level rise (SLR). IPCC assessments suggest 21st century SLR of {approx}0.5 m under aggressive emission scenarios. Semi-empirical models project SLR of {approx}1 m or more by 2100. Although some sea-level contributions are fairly well constrained by models, others are highly uncertain. Recent studies suggest a potential large contribution ({approx}0.5 m/century) from the marine-based West Antarctic Ice Sheet, linked to changes in Southern Ocean wind stress. To assess the likelihood of fast retreat of marine ice sheets, we need coupled ice-sheet/ocean models that do not yet exist (but are well under way). CESM is uniquely positioned to provide integrated, physics based sea-level predictions.

  7. A Molecular Mechanics Knowledge Base Applied to Template Based Structure Prediction

    E-Print Network [OSTI]

    Qu, Xiaotao

    2011-02-22T23:59:59.000Z

    -residue hairpin. It contains a 4:4 type IV turn 69,70 making up by residues 47-50 (sequence DATK), seven possible main-chain-to-main-chain hydrogen bonds, a hydrophobic core involves residue Trp43, Tyr45, Phe52 and Val 54 and a possible ion pair... the conclusion that our simulated dataset as well as our packing?oriented prediction method are useful for template based structure prediction. v DEDICATION To my wife Miao whom I love with all my heart and my parents who support me all the way here...

  8. Virtual Models for Prediction of Wind Turbine Parameters

    E-Print Network [OSTI]

    Andrew Kusiak

    Abstract—In this paper, a data-driven methodology for the development of virtual models of a wind turbine is presented. To demonstrate the proposed methodology, two parameters of the wind turbine have been selected for modeling, namely, power output and rotor speed. A virtual model for each of the two parameters is developed and tested with data collected at a wind farm. Both models consider controllable and noncontrollable parameters of the wind turbine, as well as the delay effect of wind speed and other parameters. To mitigate data bias of each virtual model and ensure its robustness, a training set is assembled from ten randomly selected turbines. The performance of a virtual model is largely determined by the input parameters selected and the data mining algorithms used to extract the model. Several data mining algorithms for parameter selection and model extraction are analyzed. The research presented in the paper is illustrated with computational results. Index Terms—Data mining, parameter selection, power prediction, virtual model, wind turbine. I.

  9. Predicting spin of compact objects from their QPOs: A global QPO model

    E-Print Network [OSTI]

    Banibrata Mukhopadhyay

    2008-09-19T23:59:59.000Z

    We establish a unified model to explain Quasi-Periodic-Oscillation (QPO) observed from black hole and neutron star systems globally. This is based on the accreting systems thought to be damped harmonic oscillators with higher order nonlinearity. The model explains multiple properties parallelly independent of the nature of the compact object. It describes QPOs successfully for several compact sources. Based on it, we predict the spin frequency of the neutron star Sco X-1 and the specific angular momentum of black holes GRO J1655-40, GRS 1915+105.

  10. Prediction of risk-based screening levels for infiltration of volatile subsurface contaminants into buildings

    SciTech Connect (OSTI)

    Hers, I.; Zapf-Gilje, R.; Petrovic, S. [Golder Associates Ltd., Burnaby, British Columbia (Canada); Macfarlane, M.; McLenehan, R. [British Columbia Ministry of Environment, Lands and Parks, Victoria, British Columbia (Canada)

    1997-09-01T23:59:59.000Z

    A Risk-Based Corrective Action (RBCA) approach is increasingly being used for the management of contaminated sites. Fundamental to this approach is the prediction of risk-based screening levels (RBSL) for operable exposure pathways. Screening level models currently used indicate that RBSLs for the indoor inhalation pathway can be significantly lower than other pathways typically considered. This paper presents the results of a screening level spreadsheet model used to predict human health risks resulting from infiltration of volatile organic compounds (VOCs) into buildings. The model was developed to derive RBSLs for soil and groundwater for possible future incorporation into the regulation of contaminated sites in British Columbia. Key features of the semi-analytical VOC infiltration model are steady-state diffusive mass transfer through soil coupled with advective and diffusive mass transfer through a cracked building floor slab or wall, source mass depletion of soil contaminants present using a mass balance approach, and the capability to incorporate multi-component chemical partitioning for soils containing non-aqueous phase liquid (NAPL). The critical factors affecting VOC infiltration and resulting health risks are presented.

  11. Feature-Based Prediction of Trajectories for Socially Compliant Navigation

    E-Print Network [OSTI]

    Teschner, Matthias

    in a shared environment with humans need the ability to predict the movements of people to better plan and unexpected evasive movements. In this paper, we present an algorithm for learning typical human navigation behavior. Predicting human behavior and the ability to react in a natural way will enable robots to become

  12. Physically-based demand modeling 

    E-Print Network [OSTI]

    Calloway, Terry Marshall

    1980-01-01T23:59:59.000Z

    Transactions on Automatic Control, vol. AC-19, December 1974, pp. 887-893. L3] |4] LS] [6] [7] LB] C. W. Brice and S. K. Jones, MPhysically-Based Demand Modeling, d EC-77-5-01-5057, RF 3673, Electric Power Institute, Texas A&M University, October 1978.... C. W. Br ice and 5, K, Jones, MStochastically-Based Physical Load Models Topical Report, " EC-77-5-01-5057, RF 3673, Electric Power Institute, Texas A&M University, May 1979. S. K. Jones and C. W. Brice, "Point Process Models for Power System...

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

    SciTech Connect (OSTI)

    B. Wayne Bequette; Priyadarshi Mahapatra

    2010-08-31T23:59:59.000Z

    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.

  14. Predictive modeling of reactive wetting and metal joining.

    SciTech Connect (OSTI)

    van Swol, Frank B.

    2013-09-01T23:59:59.000Z

    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.

  15. Physics-based damage predictions for simulating testing and evaluation (T and E) experiments

    SciTech Connect (OSTI)

    Addessio, F.L.; Schraad, M.W.; Lewis, M.W.

    1999-03-01T23:59:59.000Z

    This is the final report of a two-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). This report addresses the need to develop computational techniques and physics-based material models for simulating damage to weapons systems resulting from ballistic threats. Modern weapons systems, such as fighter aircraft, are becoming more dependent upon composite materials to reduce weight, to increase strength and stiffness, and to resist adverse conditions resulting from high temperatures and corrosion. Unfortunately, damaged components can have severe and detrimental effects, as evidenced by statistics from Desert Storm indicating that 75% of aircraft losses were attributable to fuel system vulnerability with hydrodynamic ram being the primary kill mechanism. Therefore, this project addresses damage predictions for composite systems that are subjected to ballistic threats involving hydrodynamic ram. A computational technique for simulating fluid-solid interaction phenomena and physics-based material models have been developed for this purpose.

  16. Crucial stages of protein folding through a solvable model: Predicting target sites

    E-Print Network [OSTI]

    Cecconi, Fabio

    Crucial stages of protein folding through a solvable model: Predicting target sites for enzyme. Keywords: Protein-folding modeling; prediction of key folding sites; HIV-1 protease; drug resistance One

  17. A Scenario-based Predictive Control Approach to Building HVAC Management Systems

    E-Print Network [OSTI]

    Johansson, Karl Henrik

    A Scenario-based Predictive Control Approach to Building HVAC Management Systems Alessandra Parisio and Air Conditioning (HVAC) systems while minimizing the overall energy use. The strategy uses

  18. ForestGALES A PC-based wind risk model

    E-Print Network [OSTI]

    be needed to uproot or break the tree? 3.1 What wind speed would create the force required to damageForestGALES A PC-based wind risk model for British Forests User's Guide Version 2.0 June 2004 Barry by strong winds in Britain 1.1 Historical context ­ Previous predictive windthrow model 1.1 What does Forest

  19. Real-time solar wind prediction based on SDO/AIA coronal hole data

    E-Print Network [OSTI]

    Rotter, T; Temmer, M; Vrsnak, B

    2015-01-01T23:59:59.000Z

    We present an empirical model based on the visible area covered by coronal holes close to the central meridian in order to predict the solar wind speed at 1 AU with a lead time up to four days in advance with a 1hr time resolution. Linear prediction functions are used to relate coronal hole areas to solar wind speed. The function parameters are automatically adapted by using the information from the previous 3 Carrington Rotations. Thus the algorithm automatically reacts on the changes of the solar wind speed during different phases of the solar cycle. The adaptive algorithm has been applied to and tested on SDO/AIA-193A observations and ACE measurements during the years 2011-2013, covering 41 Carrington Rotations. The solar wind speed arrival time is delayed and needs on average 4.02 +/- 0.5 days to reach Earth. The algorithm produces good predictions for the 156 solar wind high speed streams peak amplitudes with correlation coefficients of cc~0.60. For 80% of the peaks, the predicted arrival matches within ...

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

    E-Print Network [OSTI]

    Haves, Phillip

    2010-01-01T23:59:59.000Z

    heat  exchangers,  the  models  calibrated  using  the  manufacturer  performance  curves  predicted  power  consumption  within 10%.  The data 

  1. Subsidence prediction for the forthcoming TONO UCG project. [Rubble model and block model

    SciTech Connect (OSTI)

    Sutherland, H.R.; Hommert, P.J.; Taylor, L.M.; Benzley, S.E.

    1983-01-01T23:59:59.000Z

    The motion of the strata that overlie the TONO UCG Project partial-seam test is calculated using the analyses that have been developed for the prediction of subsidence above coal mines. This purely mechanical analysis of the overburden response to the formation of a void in the underlying coal seam is based on the analysis of two codes. The first is a finite-element code that uses a nonlinear rubble model to describe both the kinematics of roof fall and the continuum behavior of broken and unbroken strata. The second is a block code that treats the overburden as an assemblage of blocks. The equations of motion are solved for each block using an explicit integration operator. As both of these calculations are two-dimensional in nature, they are used to calibrate the semi-empirical, complementary influence function model. This model permits the extension of the two-dimensional analyses to three dimensions by using computationally efficient algorithms. These techniques are calibrated to UCG projects by analyzing the Hoe Creek 3 burn. Their application to the TONO project required the estimation of the lateral extent of the cavity for the partial-seam test. The estimates utilized the projected tons of coal to be removed and two scenarios for the burn sequence. The subsidence analytical techniques were combined with the expected patterns of coal removal to place an upper bound on the surface subsidence that can be anticipated at the TONO UCG site. 9 figures.

  2. PREDICTION OF TEMPERATURE-DEPENDENT PROPERTIES BY CORRELATIONS BASED ON SIMILARITY OF MOLECULAR STRUCTURES

    E-Print Network [OSTI]

    Brauner, Neima

    PREDICTION OF TEMPERATURE-DEPENDENT PROPERTIES BY CORRELATIONS BASED ON SIMILARITY OF MOLECULAR and environmental impact assessment, hazard and operability analysis. Therefore, methods for reliable prediction of property data are needed. In particular, prediction of temperature-dependent properties (like vapor

  3. Prediction of Transcription Start Sites Based on Feature Selection Using AMOSA

    E-Print Network [OSTI]

    1 Prediction of Transcription Start Sites Based on Feature Selection Using AMOSA Xi Wang1 sites (TSSs) is a primary and important step. With the aim to improve the computational prediction are extracted. Effective feature selection can minimize the noise, improve the prediction accuracy, and also

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

    SciTech Connect (OSTI)

    Nikabdullah, N. [Department of Mechanical and Materials Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia and Institute of Space Science (ANGKASA), Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (Malaysia); Singh, S. S. K.; Alebrahim, R.; Azizi, M. A. [Department of Mechanical and Materials Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (Malaysia); K, Elwaleed A. [Institute of Space Science (ANGKASA), Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (Malaysia); Noorani, M. S. M. [School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia (Malaysia)

    2014-06-19T23:59:59.000Z

    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.

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

    E-Print Network [OSTI]

    Haves, Phillip

    2010-01-01T23:59:59.000Z

    13]  Wetter,  M..  2009.   “Modelica?based  Modeling  and 14]  Wetter,  M..  2009.   “Modelica?based  Modeling  and modeling  language  Modelica.   Steady  state  models  of 

  6. Trajectory Free Linear Model Predictive Control for Stable Walking in the Presence of Strong

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Trajectory Free Linear Model Predictive Control for Stable Walking in the Presence of Strong of the dynamics of the robot and propose a new Linear Model Predictive Control scheme which is an improvement are unfortunately severely limited. Model Predictive Control, also known as Receding Horizon Control, is a general

  7. Static Load Balancing using Non-Uniform Mesh Partitioning based on Ray Density Prediction for the Parallel Wavefront Construction Method

    E-Print Network [OSTI]

    Alyabes, Abdullah Fahad

    2014-08-01T23:59:59.000Z

    owing to load imbalances between multiple processors.This paper applies a static load balancing approach based on a method for predicting future loads for a synthetic salt dome model, in order to improve the performance.The approach utilizes a...

  8. Crowdtuning: systematizing auto-tuning using predictive modeling and

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    in a public repository to initiate systematic, reproducible and collaborative R&D with a new publication model, reliability and cost. We present our novel long-term holistic and practical solution to this problem basedTuning.org for collaborative explanation, top-down complexity reduction, incremental problem decomposition and detection

  9. Probe measurements and numerical model predictions of evolving size distributions in premixed flames

    SciTech Connect (OSTI)

    De Filippo, A.; Sgro, L.A.; Lanzuolo, G.; D'Alessio, A. [Dipartimento di Ingegneria Chimica, Universita degli Studi di Napoli Federico II, Piazzale Tecchio 80, 80125 Napoli (Italy)

    2009-09-15T23:59:59.000Z

    Particle size distributions (PSDs), measured with a dilution probe and a Differential Mobility Analyzer (DMA), and numerical predictions of these PSDs, based on a model that includes only coagulation or alternatively inception and coagulation, are compared to investigate particle growth processes and possible sampling artifacts in the post-flame region of a C/O = 0.65 premixed laminar ethylene-air flame. Inputs to the numerical model are the PSD measured early in the flame (the initial condition for the aerosol population) and the temperature profile measured along the flame's axial centerline. The measured PSDs are initially unimodal, with a modal mobility diameter of 2.2 nm, and become bimodal later in the post-flame region. The smaller mode is best predicted with a size-dependent coagulation model, which allows some fraction of the smallest particles to escape collisions without resulting in coalescence or coagulation through the size-dependent coagulation efficiency ({gamma}{sub SD}). Instead, when {gamma} = 1 and the coagulation rate is equal to the collision rate for all particles regardless of their size, the coagulation model significantly under predicts the number concentration of both modes and over predicts the size of the largest particles in the distribution compared to the measured size distributions at various heights above the burner. The coagulation ({gamma}{sub SD}) model alone is unable to reproduce well the larger particle mode (mode II). Combining persistent nucleation with size-dependent coagulation brings the predicted PSDs to within experimental error of the measurements, which seems to suggest that surface growth processes are relatively insignificant in these flames. Shifting measured PSDs a few mm closer to the burner surface, generally adopted to correct for probe perturbations, does not produce a better matching between the experimental and the numerical results. (author)

  10. Elemental Solubility Tendency for the Phases of Uranium by Classical Models Used to Predict Alloy Behavior

    SciTech Connect (OSTI)

    Van Blackwood; Travis Koenig; Saleem Drera; Brajenda Mishra; Davis Olson; Doug Porter; Robert Mariani

    2012-03-01T23:59:59.000Z

    Traditional alloy theory models, specifically Darken-Gurry and Miedema’s analyses, that characterize solutes in solid solvents relative to physical properties of the elements have been used to assist in predicting alloy behavior. These models will be applied relative to the three solid phases of uranium: alpha (orthorhombic), beta (tetragonal), and gamma (bcc). These phases have different solubilities for specific alloy additions as a function of temperature. The Darken-Gurry and Miedema models, with modifications based on concepts of Waber, Gschneider, and Brewer will be used to predict the behavior of four types of solutes: 1) Transition metals that are used for various purposes associated with the containment as alloy additions in the uranium fuel 2) Transuranic elements in the uranium 3) Rare earth fission products (lanthanides) 4) Transition metals and other fission products Using these solute map criteria, elemental behavior will be predicted as highly soluble, marginally soluble, or immiscible (compound formers) and will be used to compare solute effects during uranium phase transformations. The overlapping of these solute maps are convenient first approximation tools for predicting alloy behavior.

  11. Data-based Motion Prediction Julian J. Faraway

    E-Print Network [OSTI]

    Faraway, Julian

    prediction. Many vehicle interiors and workplaces are first designed using a CAD system. Physical prototypes an authentically moving virtual human within soft- ware such as Jack ([2]) helps the designer detect prob- lems of motion capture data required. Even so, the methodology pre- 1 #12;sented below is generalizable and would

  12. Prediction Based Task Scheduling in Distributed Computing \\Lambda

    E-Print Network [OSTI]

    Kaltofen, Erich

    on the timely identification of the least loaded nodes. Whether the issue of interest is load­sharing a systematic and statistically sound method for uncovering the information present in the past load data and using that information to predict the future processor load. Using time series statistical methods we

  13. Algorithms for Green Buildings: Learning-Based Techniques for Energy Prediction and Fault Diagnosis

    E-Print Network [OSTI]

    Seshia, Sanjit A.

    Algorithms for Green Buildings: Learning-Based Techniques for Energy Prediction and Fault Diagnosis on servers or to redistribute to lists, requires prior specific permission. #12;Algorithms for Green Buildings: Learning-Based Techniques for Energy Prediction and Fault Diagnosis Daniel Holcomb Wenchao Li

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

    SciTech Connect (OSTI)

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

    2002-05-01T23:59:59.000Z

    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.

  15. 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

    2012-07-22T23:59:59.000Z

    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.

  16. Adaptive model predictive process control using neural networks

    DOE Patents [OSTI]

    Buescher, Kevin L. (Los Alamos, NM); Baum, Christopher C. (Mazomanie, WI); Jones, Roger D. (Espanola, NM)

    1997-01-01T23:59:59.000Z

    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.

  17. Adaptive model predictive process control using neural networks

    DOE Patents [OSTI]

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

    1997-08-19T23:59:59.000Z

    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.

  18. Optimal Model-Based Production Planning

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    1 Optimal Model-Based Production Planning for Refinery Operation Abdulrahman Alattas Advisor;2 Outline Introduction Problem Statement Refinery Planning Model Development LP Planning Models NLP Planning Models Conclusion #12;3 Introduction Refinery production planning models Optimizing refinery

  19. Predicted impacts of future water level decline on monitoring wells using a ground-water model of the Hanford Site

    SciTech Connect (OSTI)

    Wurstner, S.K.; Freshley, M.D.

    1994-12-01T23:59:59.000Z

    A ground-water flow model was used to predict water level decline in selected wells in the operating areas (100, 200, 300, and 400 Areas) and the 600 Area. To predict future water levels, the unconfined aquifer system was stimulated with the two-dimensional version of a ground-water model of the Hanford Site, which is based on the Coupled Fluid, Energy, and Solute Transport (CFEST) Code in conjunction with the Geographic Information Systems (GIS) software package. The model was developed using the assumption that artificial recharge to the unconfined aquifer system from Site operations was much greater than any natural recharge from precipitation or from the basalt aquifers below. However, artificial recharge is presently decreasing and projected to decrease even more in the future. Wells currently used for monitoring at the Hanford Site are beginning to go dry or are difficult to sample, and as the water table declines over the next 5 to 10 years, a larger number of wells is expected to be impacted. The water levels predicted by the ground-water model were compared with monitoring well completion intervals to determine which wells will become dry in the future. Predictions of wells that will go dry within the next 5 years have less uncertainty than predictions for wells that will become dry within 5 to 10 years. Each prediction is an estimate based on assumed future Hanford Site operating conditions and model assumptions.

  20. Prediction of tree diameter growth using quantile regression and mixed-effects models

    E-Print Network [OSTI]

    Cao, Quang V.

    Prediction of tree diameter growth using quantile regression and mixed-effects models Som B. Bohora diameter predictions for the same tree in the future. Another approach considered in this study involved and mixed-effects models in predicting tree diameter growth. Tree diameter at the end of each growth period

  1. Segmentation of speech based on adaptive pitch prediction

    E-Print Network [OSTI]

    Ødega?rd, Jan Erik

    1990-01-01T23:59:59.000Z

    on periodicity tends to reduce prediction gain due to the frame/energy distribution, and therefore using the SNR as a measure of filter performance has to be evaluated in light of how well pitch peaks are removed in the speech signal. ACKNOWLEDGMENTS I wish.... Stability of LPC synthesis filters D. Pitch predictor II SPEECH SEGMENTATION 5 7 8 11 12 14 19 A. Derivation of Algorithms 1. Optimum and sub-optimum pitch analysis frame 2. Minimum deviation pitch frame estimation 3. Adaptive minimum deviation...

  2. A Bayesian Approach for Parameter Estimation and Prediction using a Computationally Intensive Model

    E-Print Network [OSTI]

    Dave Higdon; Jordan D. McDonnell; Nicolas Schunck; Jason Sarich; Stefan M. Wild

    2014-09-17T23:59:59.000Z

    Bayesian methods have been very successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best fit of a physics-based model $\\eta(\\theta)$ where $\\theta$ denotes the uncertain, best input setting. Hence the statistical model is of the form $y = \\eta(\\theta) + \\epsilon$, where $\\epsilon$ accounts for measurement, and possibly other error sources. When non-linearity is present in $\\eta(\\cdot)$, the resulting posterior distribution for the unknown parameters in the Bayesian formulation is typically complex and non-standard, requiring computationally demanding computational approaches such as Markov chain Monte Carlo (MCMC) to produce multivariate draws from the posterior. While quite generally applicable, MCMC requires thousands, or even millions of evaluations of the physics model $\\eta(\\cdot)$. This is problematic if the model takes hours or days to evaluate. To overcome this computational bottleneck, we present an approach adapted from Bayesian model calibration. This approach combines output from an ensemble of computational model runs with physical measurements, within a statistical formulation, to carry out inference. A key component of this approach is a statistical response surface, or emulator, estimated from the ensemble of model runs. We demonstrate this approach with a case study in estimating parameters for a density functional theory (DFT) model, using experimental mass/binding energy measurements from a collection of atomic nuclei. We also demonstrate how this approach produces uncertainties in predictions for recent mass measurements obtained at Argonne National Laboratory (ANL).

  3. Physics-based models of the plasmasphere

    SciTech Connect (OSTI)

    Jordanova, Vania K [Los Alamos National Laboratory; Pierrard, Vivane [BELGIUM; Goldstein, Jerry [SWRI; Andr'e, Nicolas [ESTEC/ESA; Kotova, Galina A [SRI, RUSSIA; Lemaire, Joseph F [BELGIUM; Liemohn, Mike W [U OF MICHIGAN; Matsui, H [UNIV OF NEW HAMPSHIRE

    2008-01-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov [Science and Research Staff, Office of Pharmaceutical Science, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993–0002 (United States); Cross, Kevin P. [Leadscope, Inc., 1393 Dublin Road, Columbus, OH, 43215–1084 (United States)] [Leadscope, Inc., 1393 Dublin Road, Columbus, OH, 43215–1084 (United States)

    2012-05-01T23:59:59.000Z

    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 structure–activity 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.

  5. A Forward Looking Version of the MIT Emissions Prediction and Policy Analysis (EPPA) Model

    E-Print Network [OSTI]

    Babiker, Mustafa M.H.

    This paper documents a forward looking multi-regional general equilibrium model developed from the latest version of the recursive-dynamic MIT Emissions Prediction and Policy Analysis (EPPA) model. The model represents ...

  6. The MIT Emissions Prediction and Policy Analysis (EPPA) model : revisions, sensitivities, and comparisons of results

    E-Print Network [OSTI]

    Babiker, Mustafa H.M.; Reilly, John M.; Mayer, Monika.; Eckaus, Richard S.; Sue Wing, Ian.; Hyman, Robert C.

    The Emissions Prediction and Policy Analysis (EPPA) model is a component of the MIT Integrated Earth Systems Model (IGSM). Here, we provide an overview of the model accessible to a broad audience and present the detailed ...

  7. The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4

    E-Print Network [OSTI]

    Paltsev, Sergey.

    The Emissions Prediction and Policy Analysis (EPPA) model is the part of the MIT Integrated Global Systems Model (IGSM) that represents the human systems. EPPA is a recursive-dynamic multi-regional general equilibrium model ...

  8. NONLINEAR MPC BASED ON MULTI-MODEL FOR DISTILLATION COLUMNS

    E-Print Network [OSTI]

    Foss, Bjarne A.

    NONLINEAR MPC BASED ON MULTI-MODEL FOR DISTILLATION COLUMNS Bjarne A. Foss1 , Song-Bo Cong established for a petroleum distillation column through first principle analysis, and its parameters have been-estimation and prediction in a MPC scheme. The controller has been applied to quality control of a FCCU fractionator

  9. Model based dependability evaluation for automotive control functions

    E-Print Network [OSTI]

    Schlingloff, Holger

    Model based dependability evaluation for automotive control functions Sasa Vulinovic 1 , Bernd@informatik.hu-berlin.de Abstract In this paper, we study the evaluation of reliability for embedded functions in automotive. In order to assess fault tolerant designs for automotive software it is essential to be able to predict

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

    E-Print Network [OSTI]

    Ma, Yudong

    2010-01-01T23:59:59.000Z

    predictive control of thermal energy storage in buildingsystems which use thermal energy storage. In particular thepredictive control of thermal energy storage in building

  11. Toward understanding predictability of climate: a linear stochastic modeling approach

    E-Print Network [OSTI]

    Wang, Faming

    2004-11-15T23:59:59.000Z

    (E?) ? ; (2.29) which represents the predictable information(Schneider and Gri?es, 1999). In our case here, it is convenient to work with a derived quantity which we call predictive power loss (PPL) PPL(?) = e? 2nI(?x; x) = det ?E?C?1?1=n (2.30) after... the predictive power (PP) of Schneider and Gri?es (1999). Using the properties of positive de?nite matrix, one can show 0 6 PPL 6 1. It is consistent with ?(?) in the sense that PPL(0) = 0 and PPL(?1) = 1. The predictive power loss has some nice mathematical...

  12. Sequence-Based Prediction of Protein Folding Rates Using Contacts, Secondary Structures and Support Vector Machines

    E-Print Network [OSTI]

    Cheng, Jianlin Jack

    Sequence-Based Prediction of Protein Folding Rates Using Contacts, Secondary Structures and Support, Columbia, Missouri * Corresponding author: chengji@missouri.edu Abstract Predicting protein folding rate is useful for understanding protein folding process and guiding protein design. Here we developed a method

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

    SciTech Connect (OSTI)

    Fok, Alex

    2013-10-30T23:59:59.000Z

    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.

  14. An Analytical Model for Predicting the Remaining Battery Capacity of Lithium-Ion Batteries

    E-Print Network [OSTI]

    Pedram, Massoud

    An Analytical Model for Predicting the Remaining Battery Capacity of Lithium-Ion Batteries Peng cycle-life tends to shrink significantly. The capacities of commercial lithium-ion batteries fade by 10 prediction model to estimate the remaining capacity of a Lithium-Ion battery. The proposed analytical model

  15. Model for the prediction of 3D surface topography in 5-axis milling

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Model for the prediction of 3D surface topography in 5-axis milling Sylvain Lavernhe LURPA - ENS surface topography obtained in 5-axis milling in function of the machining conditions. For this purpose to a feed rate prediction model. Thanks to the simulation model of 3D surface topography, the influence

  16. Local approach to fracture based prediction of the and

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    -ductility reference temperature 45(76987@ due to irradiation is equal to the shift of (0)2123 . A material model on the Charpy data obtained on an unirradiated A508 Cl.3 steel. It is then applied to irradiated materials. 1 Introduction Reactor pressure vessels (RPV) of commercial nuclear power plants are subjected

  17. Comparisons of Exact Amplitude--Based Resummation Predictions and LHC Data

    E-Print Network [OSTI]

    Ward, B F L; Yost, S A

    2014-01-01T23:59:59.000Z

    Using the MC Herwiri1.031, we present the current status of the comparisons with LHC data of the predictions of our approach of exact amplitude-based resummation for precision QCD calculations.

  18. Evaluation of a case-based Reasoning Energy Prediction Tool for Commercial Buildings 

    E-Print Network [OSTI]

    Monfet, D.; Arkhipova, E.; Choiniere, D.

    2013-01-01T23:59:59.000Z

    This paper presents the results of an energy predictor that predicts the energy demand of commercial buildings using Case Based Reasoning (CBR). The proposed approach is evaluated using monitored data in a real office building located in Varennes...

  19. 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...

  20. Health Monitoring in an Agent-Based Smart Home by Activity Prediction

    E-Print Network [OSTI]

    Cook, Diane J.

    Health Monitoring in an Agent-Based Smart Home by Activity Prediction Sajal K. Das and Diane J objective of this paper is to investigate techniques for using agent-based smart home technologies-based smart home project funded by NSF. 1 Introduction and Motivation We live in an increasingly connected

  1. Modeling Metal Fatigue As a Key Step in PV Module Life Time Prediction (Presentation)

    SciTech Connect (OSTI)

    Bosco, N.

    2012-02-01T23:59:59.000Z

    This presentation covers modeling metal fatigue as a key step in photovoltaic (PV) module lifetime predictions. Described are time-dependent and time-independent case studies.

  2. Influence of two dynamic predictive clothing insulation models on building energy performance

    E-Print Network [OSTI]

    Lee, Kwang Ho; Schiavon, Stefano

    2013-01-01T23:59:59.000Z

    Predictive Clothing Insulation Models on Building Energyunnecessarily higher clothing insulation and lower heatingthat the constant clothing insulation assumption lead to the

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

    E-Print Network [OSTI]

    Haves, Phillip

    2010-01-01T23:59:59.000Z

    Model Predictive Control of HVAC Systems:    Implementation and  air  conditioning  (HVAC)  account  for  27%  of  the reduction potential of HVAC systems with  active thermal 

  4. The rapidly evolving field of decadal climate prediction, using initialized climate models to produce time-evolving predictions of regional climate, is producing new results for

    E-Print Network [OSTI]

    , and it is on those time scales of interest to water managers that decadal climate prediction is being appliedThe rapidly evolving field of decadal climate prediction, using initialized climate models to produce time-evolving predictions of regional climate, is producing new results for predictions

  5. Model Proton-Coupled Electron Transfer Reactions in Solution: Predictions of Rates, Mechanisms, and Kinetic Isotope Effects

    E-Print Network [OSTI]

    Hammes-Schiffer, Sharon

    Model Proton-Coupled Electron Transfer Reactions in Solution: Predictions of Rates, Mechanisms isotope effects for proton-coupled electron transfer (PCET) reactions. These studies are based, the solvent is represented as a dielectric continuum, and the active electrons and transferring protons

  6. Prediction of Channel State for Cognitive Radio Using Higher-Order Hidden Markov Model

    E-Print Network [OSTI]

    Qiu, Robert Caiming

    Prediction of Channel State for Cognitive Radio Using Higher-Order Hidden Markov Model Zhe Chen implementation. Prediction can be utilized to diminish the negative effect of such latency. In this paper, this latency is illustrated, and an approach for prediction of channel state using higher-order hidden Markov

  7. Optimal Model-Based Production Planning

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    1 Optimal Model-Based Production Planning for Refinery Operation Abdulrahman Alattas Advisor Steam distillation column Conclusion #12;3 Introduction Refinery production planning models Optimizing refinery operation Crude selection Maximizing profit; minimizing cost LP-based, linear process unit

  8. Predicting Coupled Ocean-Atmosphere Modes with a Climate Modeling Hierarchy -- Final Report

    SciTech Connect (OSTI)

    Michael Ghil, UCLA; Andrew W. Robertson, IRI, Columbia Univ.; Sergey Kravtsov, U. of Wisconsin, Milwaukee; Padhraic Smyth, UC Irvine

    2006-08-04T23:59:59.000Z

    The goal of the project was to determine midlatitude climate predictability associated with tropical-extratropical interactions on interannual-to-interdecadal time scales. Our strategy was to develop and test a hierarchy of climate models, bringing together large GCM-based climate models with simple fluid-dynamical coupled ocean-ice-atmosphere models, through the use of advanced probabilistic network (PN) models. PN models were used to develop a new diagnostic methodology for analyzing coupled ocean-atmosphere interactions in large climate simulations made with the NCAR Parallel Climate Model (PCM), and to make these tools user-friendly and available to other researchers. We focused on interactions between the tropics and extratropics through atmospheric teleconnections (the Hadley cell, Rossby waves and nonlinear circulation regimes) over both the North Atlantic and North Pacific, and the ocean’s thermohaline circulation (THC) in the Atlantic. We tested the hypothesis that variations in the strength of the THC alter sea surface temperatures in the tropical Atlantic, and that the latter influence the atmosphere in high latitudes through an atmospheric teleconnection, feeding back onto the THC. The PN model framework was used to mediate between the understanding gained with simplified primitive equations models and multi-century simulations made with the PCM. The project team is interdisciplinary and built on an existing synergy between atmospheric and ocean scientists at UCLA, computer scientists at UCI, and climate researchers at the IRI.

  9. A Mathematical Model for Predicting the Life of PEM Fuel Cell Membranes Subjected to Hydration Cycling

    E-Print Network [OSTI]

    Burlatsky, S F; O'Neill, J; Atrazhev, V V; Varyukhin, A N; Dmitriev, D V; Erikhman, N S

    2013-01-01T23:59:59.000Z

    Under typical PEM fuel cell operating conditions, part of membrane electrode assembly is subjected to humidity cycling due to variation of inlet gas RH and/or flow rate. Cyclic membrane hydration/dehydration would cause cyclic swelling/shrinking of the unconstrained membrane. In a constrained membrane, it causes cyclic stress resulting in mechanical failure in the area adjacent to the gas inlet. A mathematical modeling framework for prediction of the lifetime of a PEM FC membrane subjected to hydration cycling is developed in this paper. The model predicts membrane lifetime as a function of RH cycling amplitude and membrane mechanical properties. The modeling framework consists of three model components: a fuel cell RH distribution model, a hydration/dehydration induced stress model that predicts stress distribution in the membrane, and a damage accrual model that predicts membrane life-time. Short descriptions of the model components along with overall framework are presented in the paper. The model was used...

  10. Locating Pleistocene refugia: Comparing phylogeographic and ecological niche model predictions

    E-Print Network [OSTI]

    Waltari, Eric; Hijmans, Robert J.; Peterson, A. Townsend; Nyá ri, Á rpá d S.; Perkins, Susan L.; Guralnick, Robert P.

    2007-07-11T23:59:59.000Z

    , American Museum of Natural History, New York, New York, United States of America, 2 International Rice Research Institute, Los Ban˜os, Laguna, Philippines, 3Natural History Museum & Biodiversity Research Center, University of Kansas, Lawrence, Kansas.... Refugia identified in phylogeographic studies are shown as black outlines. Areas predicted to be refugia are in green, areas not predicted are in gray, and hatching indicates approximate locations of ice sheets [68]. Gray lines indicate present day...

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

    SciTech Connect (OSTI)

    Tippett, Michael K. [Columbia University

    2014-04-09T23:59:59.000Z

    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.

  12. Optimal Model-Based Production Planning

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    Optimal Model-Based Production Planning for Refinery Operation Abdulrahman Alattas Advisor: Ignacio;Outline Introduction Refinery Planning Model Development LP Planning Models NLP Planning Models FI Model Aggregate Model Conclusion & Future work 2 #12;3 Introduction Refinery production planning

  13. A Benchmark of Computational Models of Saliency to Predict Human Fixations

    E-Print Network [OSTI]

    Judd, Tilke

    2012-01-13T23:59:59.000Z

    Many computational models of visual attention have been created from a wide variety of different approaches to predict where people look in images. Each model is usually introduced by demonstrating performances on new ...

  14. Predicting regeneration establishment with the prognosis model. Forest Service research paper

    SciTech Connect (OSTI)

    Ferguson, D.E.; Carlson, C.E.

    1993-08-01T23:59:59.000Z

    The conifer establishment following regeneration timber harvests is predicted by version 2 of the Regeneration Establishment Model, a submodel of the Prognosis Model. The regeneration model covers 10 species for forests in Montana, central Idaho, and northern Idaho. Most harvest and site preparation methods can be simulated so that alternative treatments can be evaluated. Also included in the model is the influence of western spruce budworm (Choristoneura occidentalis) on regeneration success. The model predicts the probability of stocking, seedling density, species composition, and seedling heights 2 to 20 years after harvest. The paper describes the study design, equation development, model formulation, and model behavior for the Regeneration Establishment Model.

  15. A New Empirical Model for Predicting Single-Sided, Wind-Driven Natural Ventilation in Buildings

    E-Print Network [OSTI]

    Chen, Qingyan "Yan"

    A New Empirical Model for Predicting Single-Sided, Wind-Driven Natural Ventilation in Buildings-sided natural ventilation is difficult due to the bi-directional flow at the opening and the complex flow around buildings. A new empirical model was developed that can predict the mean ventilation rate and fluctuating

  16. Statistical prediction of aircraft trajectory: regression methods vs point-mass model

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    the altitude of climbing aircraft. In addition to the standard linear regression model, two common non-linear, BADA, linear regression, neural networks, Loess. INTRODUCTION Predicting aircraft trajectoriesStatistical prediction of aircraft trajectory: regression methods vs point-mass model M. Ghasemi

  17. Model Predictive Tracking Control for a Head-Positioning in a Hard-Disk-Drive

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Model Predictive Tracking Control for a Head-Positioning in a Hard-Disk-Drive M. Taktak-Meziou, A generated from Model Predictive Control (MPC). The first approach consists of a classical linear MPC without/Write (R/W) head of a Hard-Disk-Drive (HDD) servo-system, which is resolved with two control algorithms

  18. Axis control using model predictive control: identification and friction effect reduction

    E-Print Network [OSTI]

    Boyer, Edmond

    Axis control using model predictive control: identification and friction effect reduction Pedro this numerical model is used to synthetize a predictive GPC controller reducing the impact of the friction Rodriguez-Ayerbe, Didier Dumur, Sylvain Lavernhe** * SUPELEC- E3S, Automatic Control, 3 rue Joliot Curie

  19. A graphical model approach for predicting free energies of association for protein-protein

    E-Print Network [OSTI]

    Langmead, Christopher James

    A graphical model approach for predicting free energies of association for protein University, Pittsburgh, PA 1 Corresponding Author: cjl@cs.cmu.edu #12;Keywords: Graphical Models, Free Energy in free energy, and the ability to predict binding free energies provides both better understanding

  20. Matchstick: A Room-to-Room Thermal Model for Predicting Indoor Temperature from Wireless Sensor Data

    E-Print Network [OSTI]

    Hazas, Mike

    that our model can predict future indoor temperature trends with a 90th percentile aggregate error between thermo- stat actuates the heating, ventilation, and air condition- ing (HVAC) infrastructure to bring and these energy approaches, a heating model could allow future temperature trends to be predicted using

  1. A Predictive Model for Slip Resistance Using Artificial Neural Networks Janet M. Twomey, IIE Student Member

    E-Print Network [OSTI]

    Smith, Alice E.

    A Predictive Model for Slip Resistance Using Artificial Neural Networks Janet M. Twomey, IIE Artificial Neural Networks Why This Paper is Important Slips and falls are a serious ergonomic problem a slip resistance testing device were used to develop an artificial neural network model which predicts

  2. Genetic Algorithm for Predicting Protein Folding in the 2D HP Model

    E-Print Network [OSTI]

    Emmerich, Michael

    Genetic Algorithm for Predicting Protein Folding in the 2D HP Model A Parameter Tuning Case Study of a protein, predicting its tertiary structure is known as the protein folding problem. This problem has been. The protein folding problem in the HP model is to find a conformation (a folded sequence) with the lowest

  3. Fault-tolerant model predictive control of a wind turbine benchmark

    E-Print Network [OSTI]

    Cambridge, University of

    Fault-tolerant model predictive control of a wind turbine benchmark X. Yang J.M. Maciejowski tolerant control problem of a wind turbine benchmark. A hierarchical controller with model predictive pre component of the wind turbine. The global MPC is used to schedule the operation of the components

  4. A forward microphysical model to predict the size-distribution parameters of laboratory generated (mimic)

    E-Print Network [OSTI]

    Oxford, University of

    A forward microphysical model to predict the size- distribution parameters of laboratory generated Interactions ­ Condensational Growth and Coagulation, Submitted for Indian Aerosol Science and Technology Microphysical Model for the UTLS (FAMMUS) is applied to predict the size-distribution parameters of laboratory

  5. The US National Multi-Model Ensemble ISI Prediction System Ben Kirtman (University of Miami)

    E-Print Network [OSTI]

    Miami, University of

    The US National Multi-Model Ensemble ISI Prediction System Ben Kirtman (University of Miami) The newly emerging US National Multi-Model Ensemble (NMME) sub-seasonal to interannual (ISI) prediction includes experimental real-time ISI forecasting that leverages existing CTB partner activities. The NMME

  6. Proton Exchange Membrane Fuel Cell degradation prediction based on Adaptive Neuro Fuzzy Inference Systems

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Proton Exchange Membrane Fuel Cell degradation prediction based on Adaptive Neuro Fuzzy Inference online XX XX XXXX Keywords: Proton Exchange Membrane fuel cell degradation, Prognostic and Health nominal operating condition of a PEM fuel cell stack. It proposes a methodology based on Adaptive Neuro

  7. Structure based chemical shift prediction using Random Forests non-linear regression

    E-Print Network [OSTI]

    Langmead, Christopher James

    Structure based chemical shift prediction using Random Forests non-linear regression K. Arun-ordinates will permit close study of this relationship. This paper presents a novel non-linear regression based ap, regression, Random Forests #12;Abstract Protein nuclear magnetic resonance (NMR) chemical shifts are among

  8. A Parallel Statistical Learning Approach to the Prediction of Building Energy Consumption Based on Large Datasets

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    A Parallel Statistical Learning Approach to the Prediction of Building Energy Consumption Based consumption of buildings based on historical performances is an important approach to achieve energy efficiency. A simulation method is here introduced to obtain sufficient clean historical consumption data

  9. LS-SVM based regression and spectral clustering for predicting maintenance of machines

    E-Print Network [OSTI]

    with sensory3 faults have been used [? ],[? ],[? ]: corrective maintenance, preventive main-4 tenance, manual the machine fails, it is expensive and6 safety and environmental issues arise. Preventive maintenance is basedLS-SVM based regression and spectral clustering for predicting maintenance of machines Rocco

  10. Model Structure Analysis for Model-based Operation of

    E-Print Network [OSTI]

    Van den Hof, Paul

    conducted in the framework of the "Integrated System Approach Petroleum Production" (ISAPP) programmeModel Structure Analysis for Model-based Operation of Petroleum Reservoirs #12;#12;MODEL STRUCTURE ANALYSIS FOR MODEL-BASED OPERATION OF PETROLEUM RESERVOIRS PROEFSCHRIFT ter verkrijging van de graad van

  11. A Business Intelligence Model to Predict Bankruptcy using Financial Domain Ontology with Association Rule Mining Algorithm

    E-Print Network [OSTI]

    Martin, A; Venkatesan, Dr V Prasanna

    2011-01-01T23:59:59.000Z

    Today in every organization financial analysis provides the basis for understanding and evaluating the results of business operations and delivering how well a business is doing. This means that the organizations can control the operational activities primarily related to corporate finance. One way that doing this is by analysis of bankruptcy prediction. This paper develops an ontological model from financial information of an organization by analyzing the Semantics of the financial statement of a business. One of the best bankruptcy prediction models is Altman Z-score model. Altman Z-score method uses financial rations to predict bankruptcy. From the financial ontological model the relation between financial data is discovered by using data mining algorithm. By combining financial domain ontological model with association rule mining algorithm and Zscore model a new business intelligence model is developed to predict the bankruptcy.

  12. Kitaev models based on unitary quantum groupoids

    SciTech Connect (OSTI)

    Chang, Liang, E-mail: liangchang@math.tamu.edu [Department of Mathematics, Texas A and M University, College Station, Texas 77843-3368 (United States)] [Department of Mathematics, Texas A and M University, College Station, Texas 77843-3368 (United States)

    2014-04-15T23:59:59.000Z

    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.

  13. Overview of Neutrino Mixing Models and Their Mixing Angle Predictions

    SciTech Connect (OSTI)

    Albright, Carl H.

    2009-11-01T23:59:59.000Z

    An overview of neutrino-mixing models is presented with emphasis on the types of horizontal flavor and vertical family symmetries that have been invoked. Distributions for the mixing angles of many models are displayed. Ways to differentiate among the models and to narrow the list of viable models are discussed.

  14. Numerical and analytical modeling of sanding onset prediction

    E-Print Network [OSTI]

    Yi, Xianjie

    2004-09-30T23:59:59.000Z

    results vary with the selection of one or another rock strength criterion. In this work, we present four commonly used rock strength criteria in sanding onset prediction and wellbore stability studies: Mohr-Coulomb, Hoek-Brown, Drucker-Prager, and Modified...

  15. Predictive Linear Regression Model for Microinverter Internal Temperature

    E-Print Network [OSTI]

    Rollins, Andrew M.

    , photovoltaic (PV) module temperature, irradiance and AC power data. Time-series environmental, temperature prediction, reliabil- ity, photovoltaic systems. I. INTRODUCTION PV modules equipped with microinverters have system. Reliability of microinverters in harsh and extreme real- world outdoor operating conditions has

  16. MOLECULAR MODELING OF PROTEINS AND MATHEMATICAL PREDICTION OF PROTEIN STRUCTURE

    E-Print Network [OSTI]

    Neumaier, Arnold

    ­called protein folding problem. The static aspect is concerned with how to predict the folded (native, tertiary at solutions to the protein folding problem. Key words. protein folding, molecular mechanics, transition states. This so­called protein folding problem is one of the most challenging problems in current bio­ chemistry

  17. MOLECULAR MODELING OF PROTEINS AND MATHEMATICAL PREDICTION OF PROTEIN STRUCTURE

    E-Print Network [OSTI]

    Neumaier, Arnold

    -called protein folding problem. The static aspect is concerned with how to predict the folded (native, tertiary at solutions to the protein folding problem. Key words. protein folding, molecular mechanics, transition states. This so-called protein folding problem is one of the most challenging problems in current bio- chemistry

  18. Application of bi-linear loglog SN model to strain-controlled fatigue data of aluminum alloys and its effect on life predictions

    E-Print Network [OSTI]

    Fatemi, Ali

    Application of bi-linear log­log S­N model to strain-controlled fatigue data of aluminum alloys­log model is applied to stress amplitude versus fatigue life data of 14 aluminum alloys. It is shown-life curves are discussed. Life predictions of aluminum alloys based on linear and bi-linear models are also

  19. A physically-based abrasive wear model for composite materials

    SciTech Connect (OSTI)

    Lee, Gun Y.; Dharan, C.K.H.; Ritchie, Robert O.

    2001-05-01T23:59:59.000Z

    A simple physically-based model for the abrasive wear of composite materials is presented based on the mechanics and mechanisms associated with sliding wear in soft (ductile) matrix composites containing hard (brittle) reinforcement particles. The model is based on the assumption that any portion of the reinforcement that is removed as wear debris cannot contribute to the wear resistance of the matrix material. The size of this non-contributing portion of the reinforcement is estimated by modeling the three primary wear mechanisms, specifically plowing, interfacial cracking and particle removal. Critical variables describing the role of the reinforcement, such as its relative size and the nature of the matrix/reinforcement interface, are characterized by a single contribution coefficient, C. Predictions are compared with the results of experimental two-body (pin-on drum) abrasive wear tests performed on a model aluminum particulate-reinforced epoxy matrix composite material.

  20. A machine learning approach to modeling and predicting training effectiveness

    E-Print Network [OSTI]

    Stimpson, Alexander J. (Alexander James)

    2015-01-01T23:59:59.000Z

    Developments in online and computer-based training (CBT) technologies have enabled improvements in efficiency, efficacy, and scalability of modern training programs. The use of computer-based methods in training programs ...

  1. Optimal Model-Based Production Planning

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    1 Optimal Model-Based Production Planning for Refinery Operation Abdulrahman Alattas Advisor Distillation Column FI Model Conclusion #12;3 Introduction Refinery production planning models Optimizing refinery operation Crude selection Maximizing profit; minimizing cost LP-based, linear process unit

  2. Abstract--Eventually, prediction of transformer thermal performance for dynamic loading will be made using models

    E-Print Network [OSTI]

    1 Abstract--Eventually, prediction of transformer thermal performance for dynamic loading will be made using models distilled from measure data, rather than models derived from transformer heat for measuring the acceptability of transformer thermal models. For a model to be acceptable, it must have

  3. Predictive Simulation of Bidirectional Glenn Shunt Using a Hybrid Blood Vessel Model

    E-Print Network [OSTI]

    Leow, Wee Kheng

    Predictive Simulation of Bidirectional Glenn Shunt Using a Hybrid Blood Vessel Model Hao Li1 to model the deformation of blood vessels. The hybrid blood vessel model consists of a reference Cosserat rod and a surface mesh. The reference Cosserat rod models the blood vessel's global bending

  4. Human walking model predicts joint mechanics, electromyography and mechanical economy

    E-Print Network [OSTI]

    Endo, Ken

    In this paper, we present an under-actuated model of human walking, comprising only a soleus muscle and flexion/extension monoarticular hip muscles. The remaining muscle groups of the human leg are modeled using quasi-passive, ...

  5. On the Predictive Uncertainty of a Distributed Hydrologic Model

    E-Print Network [OSTI]

    Cho, Huidae

    2009-05-15T23:59:59.000Z

    .2.2. Sampling strategy for high diversity . . . . . . . . . . 34 3.2.3. Isolated speciation . . . . . . . . . . . . . . . . . . . 36 3.2.4. Fitness assimilation . . . . . . . . . . . . . . . . . . . 39 3.2.5. Nesting criteria for global and local optima... unique optimal solution Beven (2006a). There may exist even mathematically inferior solutions, often referred to as local optima, that provide more realistic predictions. However, it is not straight- forward to find local optima using global optimization...

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

    SciTech Connect (OSTI)

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

    2012-05-01T23:59:59.000Z

    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.

  7. A Molecular Mechanics Knowledge Base Applied to Template Based Structure Prediction 

    E-Print Network [OSTI]

    Qu, Xiaotao

    2011-02-22T23:59:59.000Z

    Predicting protein structure using its primary sequence has always been a challenging topic in biochemistry. Although it seems as simple as finding the minimal energy conformation, it has been quite difficult to provide ...

  8. 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

    2013-12-18T23:59:59.000Z

    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.

  9. Correlation and prediction of liquid-phase adsorption on zeolites using group contributions based on adsorbate-solid solution theory

    SciTech Connect (OSTI)

    Berti, C.; Ulbig, P.; Burdorf, A.; Seippel, J.; Schulz, S.

    1999-08-31T23:59:59.000Z

    Both correlation as well as prediction of experimental data for the adsorption of various binary liquid mixtures of alkanes and alkenes on NaX at different temperatures are presented. The theoretical background is based on the adsorbate-solid solution theory which conceives the adsorbed phase to be a mixture of the adsorbed species (adsorbate) and the adsorbent as an additional component. With the introduction of the Gibbs excess energy G{sup E*} for this hypothetical mixture, activity coefficients and composition of the adsorbed phase may be calculated. The Biggs excess energy and thus the activity coefficient of the adsorbed species depend strongly on the energetic heterogeneity of the solid surface which may be described by use of so-called group contribution models. These approaches, until now widely applied to predict fluid-phase equilibrium, are derived from statistical thermodynamics and take into account the energetic interactions between the respective components. For the application of this approach on thermodynamics of adsorption zeolites have to be divided into different functional groups such as SiO{sub 2}, AlO{sub 2}{sup {minus}}, and the respective cations. The interaction energies between these active sites and the functional groups of the adsorbed liquid molecules represent fundamental parameters of activity coefficient models based on group contributions such as UNIFAC. These parameters were determined by fitting four different adsorption systems. With the fitted values, six other systems were predicted. Both correlation and prediction include adsorption data at different temperatures. All calculations show excellent results with a mean relative deviation of 4.2% for the correlation and a mean deviation in the range of 8--17% for the predictions.

  10. Predicting hurricane regional landfall rates: comparing local and basin-wide track model approaches

    E-Print Network [OSTI]

    Hall, T; Hall, Tim; Jewson, Stephen

    2006-01-01T23:59:59.000Z

    We compare two methods for making predictions of the climatological distribution of the number of hurricanes making landfall along short sections of the North American coastline. The first method uses local data, and the second method uses a basin-wide track model. Using cross-validation we show that the basin-wide track model gives better predictions for almost all parts of the coastline. This is the first time such a comparison has been made, and is the first rigourous justification for the use of basin-wide track models for predicting hurricane landfall rates and hurricane risk.

  11. Agent-Based Modeling and Simulation for Hydrogen Transition Analysis...

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

    Agent-Based Modeling and Simulation for Hydrogen Transition Analysis Agent-Based Modeling and Simulation for Hydrogen Transition Analysis Presentation on Agent-Based Modeling and...

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

    SciTech Connect (OSTI)

    Drover, Damion, Ryan

    2011-12-01T23:59:59.000Z

    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 laser altimetry remote sensing method, obtained from the USDA Forest Service at Savannah River Site. The specific DEM resolutions were chosen because they are common grid cell sizes (10m, 30m, and 50m) used in mapping for management applications and in research. The finer resolutions (2m and 5m) were chosen for the purpose of determining how finer resolutions performed compared with coarser resolutions at predicting wetness and related soil attributes. The wetness indices were compared across DEMs and with each other in terms of quantile and distribution differences, then in terms of how well they each correlated with measured soil attributes. Spatial and non-spatial analyses were performed, and predictions using regression and geostatistics were examined for efficacy relative to each DEM resolution. Trends in the raw data and analysis results were also revealed.

  13. Embedded Online Optimization for Model Predictive Control at ...

    E-Print Network [OSTI]

    2013-03-05T23:59:59.000Z

    optimization-based control systems on low cost embedded platforms. ..... Modern computing platforms must allow for a wide range of applications that operate on.

  14. Topic-based mixture language modelling

    E-Print Network [OSTI]

    Gotoh, Yoshihiko; Renals, Steve

    1999-01-01T23:59:59.000Z

    This paper describes an approach for constructing a mixture of language models based on simple statistical notions of semantics using probabilistic models developed for information retrieval. The approach encapsulates corpus-derived semantic...

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

    E-Print Network [OSTI]

    Ma, Yudong

    2010-01-01T23:59:59.000Z

    of the cooling towers while consuming less energy. Duringtowers, the thermal storage tank and the electricity energytowers, the thermal storage tank, the campus model and the electricity energy

  16. Development of Chemical Model to Predict the Interactions between...

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

    large domain size and multiple realizations. * Model calibration and verification (End of project) - We will collect data from literature, extrapolate existing data and conduct...

  17. 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)

    2013-01-01T23:59:59.000Z

    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.

  18. Prediction of Solid Polycyclic Aromatic Hydrocarbons Solubility in Water with the NRTL-PR Model

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Prediction of Solid Polycyclic Aromatic Hydrocarbons Solubility in Water with the NRTL-PR Model of solid polycyclic aromatic hydrocarbons in water. For this purpose, we first validate our methodology for fluid phase equilibria predictions of aromatic hydrocarbons and gas (CO2, C2H6) mixtures. Finally, we

  19. Predicting the net carbon exchanges of crop rotations in Europe with an agro-ecosystem model

    E-Print Network [OSTI]

    Boyer, Edmond

    Predicting the net carbon exchanges of crop rotations in Europe with an agro-ecosystem model S.Lehuger@art.admin.ch. Fax: (+41) 44 377 72 01. Phone: (+41) 44 377 75 13. hal-00414342,version2-1Sep2010 #12;Abstract Carbon and measuring land-atmosphere carbon exchanges from arable lands are important tasks to predict the influence

  20. Ventilation performance prediction for buildings: Model Assessment Qingyan Chena,b,*

    E-Print Network [OSTI]

    Chen, Qingyan "Yan"

    1 Ventilation performance prediction for buildings: Model Assessment Qingyan Chena,b,* , Kisup Leeb ventilation systems for buildings requires a suitable tool to assess the system performance-scale experimental, multizone network, zonal, and CFD) for predicting ventilation performance in buildings, which can

  1. Occupancy Modeling and Prediction for Building Energy Varick L. Erickson, University of California, Merced

    E-Print Network [OSTI]

    Cerpa, Alberto E.

    A Occupancy Modeling and Prediction for Building Energy Management Varick L. Erickson, University.Cerpa, University of California, Merced Heating, cooling and ventilation accounts for 35% energy usage in the United and Prediction for Building Energy Management and Auditing. ACM Trans. Sensor Netw. V, N, Article A (August 2012

  2. Non-asymptotic Adaptive Prediction in Functional Linear Models Elodie Brunel, Andre Mas, and Angelina Roche

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Non-asymptotic Adaptive Prediction in Functional Linear Models ´Elodie Brunel, Andr´e Mas, and Angelina Roche I3M, Universit´e Montpellier II Abstract Functional linear regression has recently attracted. Functional linear regression, functional principal components analysis, mean squared prediction error

  3. USING LEARNING MACHINES TO CREATE SOLAR RADIATION MAPS FROM NUMERICAL WEATHER PREDICTION MODELS,

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    USING LEARNING MACHINES TO CREATE SOLAR RADIATION MAPS FROM NUMERICAL WEATHER PREDICTION MODELS to develop a methodology to generate solar radiation maps using information from different sources. First with conclusions and next works in the last section. Keywords: Solar Radiation maps, Numerical Weather Predictions

  4. `TVLSI-00029-2003.R1 An Analytical Model for Predicting the Remaining Battery

    E-Print Network [OSTI]

    Pedram, Massoud

    . Reference [7] studied the battery discharge efficiency under different loading conditions and approximated`TVLSI-00029-2003.R1 1 An Analytical Model for Predicting the Remaining Battery Capacity of Lithium-Ion Batteries Peng Rong, Student Member, IEEE and Massoud Pedram, Fellow, IEEE Abstract -- Predicting

  5. Discrepancies in the Prediction of Solar Wind using Potential Field Source Surface Model: An

    E-Print Network [OSTI]

    Zhao, Xuepu

    Discrepancies in the Prediction of Solar Wind using Potential Field Source Surface Model. This inverse relation has been made use of in the prediction of solar wind speed at 1 AU using a potential between the magnetic flux tube expansion factor (FTE) at the source surface and the solar wind speed

  6. Model Formulation and Predictions for a Pyrotechnically Actuated Pin Puller*

    E-Print Network [OSTI]

    ) actuated pin puller. The conservation principles are written as a set of ordinary differential equations-stirred reactor is simulated. These assumptions generally restrict the validity of the model to regimes near a formulation of the model in terms of the mass, momentum, and energy principles supplemented by appropriate

  7. Direct comparison of Neural Network, Fuzzy Logic and Model Prediction Variable Structure vortex flow controllers

    E-Print Network [OSTI]

    Joshi, Praveen Sudhakar

    1999-01-01T23:59:59.000Z

    Predictive Variable Structure and Fuzzy Logic based controllers for the same benchmark problem. Evaluation criteria consist of closed-loop system performance, activity level of the VFC nozzles, ease of controller synthesis, time required to synthesize...

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

    DOE Patents [OSTI]

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

    2013-04-09T23:59:59.000Z

    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.

  9. PREDICTION OF REMAINING LIFE OF POWER TRANSFORMERS BASED ON LEFT TRUNCATED AND RIGHT

    E-Print Network [OSTI]

    PREDICTION OF REMAINING LIFE OF POWER TRANSFORMERS BASED ON LEFT TRUNCATED AND RIGHT CENSORED of the remaining life of high-voltage power transform- ers is an important issue for energy companies because of the need for planning maintenance and capital expenditures. Lifetime data for such transformers

  10. Improving objective intelligibility prediction by combining correlation and coherence based methods with a measure

    E-Print Network [OSTI]

    objective method for intelligibility prediction of enhanced speech which is based on the negative distortion clean speech signal, likely due to a bad noise estimate during the speech enhancement procedure. While Elsevier B.V. All rights reserved. Keywords: Speech intelligibility; Objective measures; Speech enhancement

  11. Using Trust-Based Information Aggregation for Predicting Security Level of Systems

    E-Print Network [OSTI]

    Ray, Indrakshi

    Using Trust-Based Information Aggregation for Predicting Security Level of Systems Siv Hilde Houmb1 level of a security solution using information sources who are trusted to varying degrees. We show how}@cs.colostate.edu Abstract. Sometimes developers must design innovative security solutions that have a rapid development

  12. Using Trust-Based Information Aggregation for Predicting Security Level of Systems

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Using Trust-Based Information Aggregation for Predicting Security Level of Systems Siv Hilde Houmb1 level of a security solution using information sources who are trusted to varying degrees. We show how.colostate.edu Abstract. Sometimes developers must design innovative security solutions that have a rapid development

  13. An Integrated Development Environment for Building Predictable Component-Based Embedded Systems

    E-Print Network [OSTI]

    Becker, Steffen

    Save-IDE An Integrated Development Environment for Building Predictable Component-Based Embedded-- In this paper we present an Integrated Development Environment Save-IDE, a toolset that embraces several tools-time properties, such as timing properties, and transforming the components to real-time execution elements. Save

  14. Job-Scheduling with Resource Availability Prediction for Volunteer-Based Grid Computing

    E-Print Network [OSTI]

    Haddadi, Hamed

    Job-Scheduling with Resource Availability Prediction for Volunteer-Based Grid Computing Jun Zhang environment, one big challenge for effective job allocation is resource availability. As resources in this environment are volatile and may become frequently unavailable, matching guest jobs to suitable resources

  15. Evaluation of short-term climate change prediction in multi-model CMIP5 decadal hindcasts

    E-Print Network [OSTI]

    Webster, Peter J.

    events such as trop- ical cyclone activity. On decadal timescales, some aspects of internal climate skill of individual models have been analyzed separately for multi-year prediction horizons over

  16. Reconfigurable autopilot design for a high performance aircraft using model predictive control

    E-Print Network [OSTI]

    Ruiz, Jose Pedro, 1980-

    2004-01-01T23:59:59.000Z

    The losses of military and civilian aircraft due to control surface failures have prompted research into controllers with a degree of reconfiguration. This thesis will describe a design approach incorporating Model Predictive ...

  17. Application of the cumulative risk model in predicting school readiness in Head Start children

    E-Print Network [OSTI]

    Rodriguez-Escobar, Olga Lydia

    2009-05-15T23:59:59.000Z

    outcomes. This study built on this literature by investigating how child, parent, and family risk factors predicted school readiness in Head Start children using two statistical models. Specific aims of this study included identifying 1) to what degree...

  18. Evaluating Importance Ratings as an Alternative to Mental Models in Predicting Driving Crashes and Moving Violations

    E-Print Network [OSTI]

    McDonald, Jennifer Nicole

    2012-07-16T23:59:59.000Z

    The present study investigated the extent to which importance ratings (i.e., a measure of perceived importance for driving-related concepts) are a viable alternative to traditional mental model assessment methods in predicting driving performance...

  19. Energy Savings Through Application of Model Predictive Control to an Air Separation Facility

    E-Print Network [OSTI]

    Hanson, T. C.; Scharf, P. F.

    Energy Savings Through Application of Model Predictive Control to an Air Separation Facility Thomas C. Hanson PauiF. Scharf Manager Senior Engineering Associate Process Development Process Control Technology Praxair, Inc., Tonawanda, New York...

  20. Image Segmentation for the Application of the Neugebauer Colour Prediction Model on Inkjet Printed

    E-Print Network [OSTI]

    Figueiredo, Mário A. T.

    are reported in Section 5. The paper is concluded in Section 6. 2 The Neugebauer Color Prediction Model overlaps (CM, CY, MY, CK, MK, YK); all ternary overlaps (CMY, CMK, CYK, MYK), the single full overlap (CMYK

  1. PREDICTIVE THERMAL MODEL FOR INDIRECT TEMPERATURE MEASUREMENT INSIDE ATOMIC CELL OF NUCLEAR MAGNETIC RESONANCE GYROSCOPE

    E-Print Network [OSTI]

    Tang, William C

    , atomic MEMS, compact thermal model. INTRODUCTION We present a two-step process for predicting and the VCSEL, active heating and cooling was included in the presented prototype through an external heater

  2. A Mathematical Model for Predicting the Life of PEM Fuel Cell Membranes Subjected to Hydration Cycling

    E-Print Network [OSTI]

    S. F. Burlatsky; M. Gummalla; J. O'Neill; V. V. Atrazhev; A. N. Varyukhin; D. V. Dmitriev; N. S. Erikhman

    2013-06-19T23:59:59.000Z

    Under typical PEM fuel cell operating conditions, part of membrane electrode assembly is subjected to humidity cycling due to variation of inlet gas RH and/or flow rate. Cyclic membrane hydration/dehydration would cause cyclic swelling/shrinking of the unconstrained membrane. In a constrained membrane, it causes cyclic stress resulting in mechanical failure in the area adjacent to the gas inlet. A mathematical modeling framework for prediction of the lifetime of a PEM FC membrane subjected to hydration cycling is developed in this paper. The model predicts membrane lifetime as a function of RH cycling amplitude and membrane mechanical properties. The modeling framework consists of three model components: a fuel cell RH distribution model, a hydration/dehydration induced stress model that predicts stress distribution in the membrane, and a damage accrual model that predicts membrane life-time. Short descriptions of the model components along with overall framework are presented in the paper. The model was used for lifetime prediction of a GORE-SELECT membrane.

  3. Wake models are used to improve predictions of Annual Energy Production (AEP) of wind farms.

    E-Print Network [OSTI]

    Daraio, Chiara

    ·Wake models are used to improve predictions of Annual Energy Production (AEP) of wind farms. ·Wake measurements in the ETHZ facility compare well with measurements at the Horns Rev offshore wind farm models take account of the effects of wakes on downstream wind turbines. ·Wake models used in the wind

  4. Sunshine-Factor Model with Treshold GARCH for Predicting Temperature of Weather Contracts

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Sunshine-Factor Model with Treshold GARCH for Predicting Temperature of Weather Contracts Hélène of the shocks on the volatility by estimating a structural model with a periodic threshold GARCH. We show model, Markov chain, threshold GARCH, Monte- Carlo simulations, pricing, Value-at-Risk. JEL

  5. Power law decay in model predictability skill Peter C. Chu,1

    E-Print Network [OSTI]

    Chu, Peter C.

    Power law decay in model predictability skill Peter C. Chu,1 Leonid M. Ivanov,1,2 Lakshmi H. Kantha a Gulf of Mexico nowcast/forecast model. Power law scaling is found in the mean square error of displacement between drifting buoy and model trajectories (both at 50 m depth). The probability density

  6. Artificial Neural Networks and Hidden Markov Models for Predicting the Protein Structures: The Secondary Structure

    E-Print Network [OSTI]

    1 Artificial Neural Networks and Hidden Markov Models for Predicting the Protein Structures advice on the development of this project #12;2 Artificial Neural Networks and Hidden Markov Models learning methods: artificial neural networks (ANN) and hidden Markov models (HMM) (Rost 2002; Karplus et al

  7. Modeling, Analysis, Predictions, and Projections Email: oar.cpo.mapp@noaa.gov

    E-Print Network [OSTI]

    Earth system models to better simulate the climate system? Can we improve intraseasonal to seasonal mission, MAPP supports the development of advanced Earth system models that can predict climate variations, and the external research community. MAPP Objectives · Improve Earth system models · Achieve an integrated Earth

  8. An Advanced Induction Machine Model for Predicting Inverter-Machine Interaction

    E-Print Network [OSTI]

    Chapman, Patrick

    An Advanced Induction Machine Model for Predicting Inverter-Machine Interaction [31 [41 [51 [6] [7 saturntion d d d d d d d d d d d d d d d d d d d d d d d Leakage inductance saturation as a function of flux- tion machine model specifically designed for use with inverter models to study machin

  9. Evaluation of SWAT model - subdaily runoff prediction in Texas watersheds

    E-Print Network [OSTI]

    Palanisamy, Bakkiyalakshmi

    2007-09-17T23:59:59.000Z

    Spatial variability of rainfall is a significant factor in hydrologic and water quality modeling. In recent years, characterizing and analyzing the effect of spatial variability of rainfall in hydrologic applications has become vital with the advent...

  10. DECENTRALIZED ROBUST NONLINEAR MODEL PREDICTIVE CONTROLLER FOR UNMANNED AERIAL SYSTEMS

    E-Print Network [OSTI]

    Garcia, Gonzalo Andres

    2013-05-31T23:59:59.000Z

    that enables the vehicle to follow an arbitrary trajectory shaped by moving points; 2 A formulation that embeds the guidance logic and trajectory information in the aircraft model, avoiding cross coupling and control degradation; 3 An artificial neural network...

  11. How predictable : modeling rates of change in individuals and populations

    E-Print Network [OSTI]

    Krumme, Katherine

    2013-01-01T23:59:59.000Z

    This thesis develops methodologies to measure rates of change in individual human behavior, and to capture statistical regularities in change at the population level, in three pieces: i) a model of individual rate of change ...

  12. Robust Constrained Model Predictive Control using Linear Matrix Inequalities \\Lambda

    E-Print Network [OSTI]

    Balakrishnan, Venkataramanan "Ragu"

    dynamical systems, such as those encountered in chemical process control in the petrochemical, pulp process models as well as many performance criteria of significance to the process industries can

  13. Robust Constrained Model Predictive Control using Linear Matrix Inequalities

    E-Print Network [OSTI]

    Balakrishnan, Venkataramanan "Ragu"

    , such as those encountered in chemical process control in the petrochemical, pulp and paper industries, several process models as well as many performance criteria of significance to the process industries can

  14. Dispersion modeling for prediction of emission factors for cattle feedyards

    E-Print Network [OSTI]

    Parnell, Sarah Elizabeth

    1994-01-01T23:59:59.000Z

    of state air pollution regulatory agencies will require accurate EPA AP-42 emission factors. A protocol was developed so that accurate emission factors can be determined using both source sampling data and dispersion modeling. In this study, an emission...

  15. Validating agent based models through virtual worlds.

    SciTech Connect (OSTI)

    Lakkaraju, Kiran; Whetzel, Jonathan H.; Lee, Jina [Sandia National Laboratories, Livermore, CA; Bier, Asmeret Brooke; Cardona-Rivera, Rogelio E. [North Carolina State University, Raleigh, NC; Bernstein, Jeremy Ray Rhythm [Gaikai, Inc., Aliso Viejo, CA

    2014-01-01T23:59:59.000Z

    As the US continues its vigilance against distributed, embedded threats, understanding the political and social structure of these groups becomes paramount for predicting and dis- rupting their attacks. Agent-based models (ABMs) serve as a powerful tool to study these groups. While the popularity of social network tools (e.g., Facebook, Twitter) has provided extensive communication data, there is a lack of ne-grained behavioral data with which to inform and validate existing ABMs. Virtual worlds, in particular massively multiplayer online games (MMOG), where large numbers of people interact within a complex environ- ment for long periods of time provide an alternative source of data. These environments provide a rich social environment where players engage in a variety of activities observed between real-world groups: collaborating and/or competing with other groups, conducting battles for scarce resources, and trading in a market economy. Strategies employed by player groups surprisingly re ect those seen in present-day con icts, where players use diplomacy or espionage as their means for accomplishing their goals. In this project, we propose to address the need for ne-grained behavioral data by acquiring and analyzing game data a commercial MMOG, referred to within this report as Game X. The goals of this research were: (1) devising toolsets for analyzing virtual world data to better inform the rules that govern a social ABM and (2) exploring how virtual worlds could serve as a source of data to validate ABMs established for analogous real-world phenomena. During this research, we studied certain patterns of group behavior to compliment social modeling e orts where a signi cant lack of detailed examples of observed phenomena exists. This report outlines our work examining group behaviors that underly what we have termed the Expression-To-Action (E2A) problem: determining the changes in social contact that lead individuals/groups to engage in a particular behavior. Results from our work indicate that virtual worlds have the potential for serving as a proxy in allocating and populating behaviors that would be used within further agent-based modeling studies.

  16. Flow Control of Real Time Multimedia Applications Using Model Predictive Control with a Feed Forward Term

    E-Print Network [OSTI]

    Duong, Thien Chi

    2011-02-22T23:59:59.000Z

    FLOW CONTROL OF REAL TIME MULTIMEDIA APPLICATIONS USING MODEL PREDICTIVE CONTROL WITH A FEED FORWARD TERM A Thesis by THIEN CHI DUONG Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment... of the requirements for the degree of MASTER OF SCIENCE December 2010 Major Subject: Mechanical Engineering Flow Control of Real Time Multimedia Applications Using Model Predictive Control with Feed Forward Term...

  17. Evaluation of a mathematical model in predicting intake of growing and finishing cattle

    E-Print Network [OSTI]

    Bourg, Brandi Marie

    2009-05-15T23:59:59.000Z

    EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment... of the requirements for the degree of MASTER OF SCIENCE December 2007 Major Subject: Animal Science EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG Submitted...

  18. Evaluation of a mathematical model in predicting intake of growing and finishing cattle

    E-Print Network [OSTI]

    Bourg, Brandi Marie

    2008-10-10T23:59:59.000Z

    EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment... of the requirements for the degree of MASTER OF SCIENCE December 2007 Major Subject: Animal Science EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG Submitted...

  19. A quantitative model to predict the cost of quality nonconformance in the construction industry

    E-Print Network [OSTI]

    Opara, Ethelbert Okechukwu

    1993-01-01T23:59:59.000Z

    A QUANTITATIVE MODEL TO PREDICT THE COST OF QUALITY NONCONFORMANCE IN THE CONSTRUCTION INDUSTRY A Thesis by ETHELBERT OKECHUKWU OPARA Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of requirements... for the degree of MASTER OF SCIENCE August 1993 Major Subject: Construction Management A QUANTITATIVE MODEL TO PREDICT THE COST OF QUALITY NONCONFORMANCE IN THE CONSTRUCTION INDUSTRY A Thesis by ETHELBERT OKECHUKWU OPARA Submitted to Texas A&M University...

  20. Development of a new model for predicting sucker-rod pumping system performance

    E-Print Network [OSTI]

    Garcia, Julian Perez

    1988-01-01T23:59:59.000Z

    DEVELOPMENT OF A NEW MODEL FOR PREDICTING SUCKER-ROD PUMPING SYSTEM PERFORMANCE A Thesis by JULIAN PEREZ GARCIA, JR. Submitted to the Graduate College of Texas A&M University in partial fulfillment of the requirements for the degree... of MASTER OF SCIENCE August 1988 Major Subject: Petroleum Engineering DEVELOPMENT OF A NEW MODEL FOR PREDICTING SUCKER-ROD PUMPING SYSTEM PERFORMANCE A Thesis by JULIAN PEREZ GARCIA, JR. Approved as to style and content by: J. . Jen in s (Cha...

  1. A computer simulation model for the prediction of temperature distributions in radiofrequency hyperthermia treatment

    E-Print Network [OSTI]

    Rothe, Jeanne Marie

    1983-01-01T23:59:59.000Z

    A COMPUTER SIMULATION MODEL FOR THE PREDICTION OF . EMPERATURE DISTRIBUTIONS IN RADIOFREQUENCY HYPERTHERMIA TREATMENT A Thesis by JEANNE MARIE ROTHE Submitted to the Graduate College of Texas ASM University in Partial fulfillment... of the requirement for the degree of MASTER OF SCIENCE DECEMBER 1983 Major Subject: Bioengineering A COMPUTER SIMULATION MODEL FOR THE PREDICTION OF TEMPERATURE DISTRIBUTIONS IN RADIOFREQUENCY HYPERTHERMIA TREATMENT A Thesis by JEANNE MARIE ROTHE Approved...

  2. A new, efficient computational model for the prediction of fluid seal flowfields

    E-Print Network [OSTI]

    Hibbs, Robert Irwin

    1988-01-01T23:59:59.000Z

    A NEW) EFFICIENT COMPUTATIONAL MODEL FOR THE PREDICTION OF FLUID SEAL FLOWFIELDS A Thesis by ROBERT IRWIN HIBBS, JR. Submitted to the Office of Graduate Studies of Texas ASM University in partial fulfillment of the requirement for the degree... of MASTER OF SCIENCE December 1988 Major Subject: Mechanical Engineering A NEW, EFFICIENT COMPUTATIONAL MODEL FOR THE PREDICTION OF FLUID SEAL FLOWFIELDS A Thesis by ROBERT IRWIN HIBBS, JR. Approved as to style and content by: David L. Rhode...

  3. Structure-Based Predictive model for Coal Char Combustion.

    SciTech Connect (OSTI)

    Hurt, R.; Calo, J. [Brown Univ., Providence, RI (United States). Div. of Engineering; Essenhigh, R.; Hadad, C [Ohio State Univ., Columbus, OH (United States). Dept. of Chemistry; Stanley, E. [Boston Univ., MA (United States). Dept. of Physics

    1997-03-28T23:59:59.000Z

    The first quarter of this project was used to carry out a detailed planning process to coordinate the various aspects of this collaborative effort. A workshop was held at Brown University on December 4, 1996, attended by all project participants and key visitors, in which presentations were given by the principal investigators on their respective subtasks. The planning process culminated in the completion of a comprehensive document submitted to DOE / FETC under separate cover. Following the planning exercise, research work was initiated and will be continued in the second project quarter.

  4. Coordinated Dynamic Voltage Stabilization based on Model Predictive Control

    E-Print Network [OSTI]

    Kumar, Ratnesh

    is very important for power system operations. This paper presents an approach for optimal coordination and operation [1], [2]. The deregulation of power industry has created an economical incentive to operate power devices, generator reactive power control, transformer tap changer control and load shedding. As shown

  5. Modeling cyclic ratcheting based fatigue life of HSLA steels using crystal plasticity FEM simulations and experiments

    E-Print Network [OSTI]

    Ghosh, Somnath

    Modeling cyclic ratcheting based fatigue life of HSLA steels using crystal plasticity FEM This paper develops a plastic ratcheting based fatigue failure model for HSLA steels from a combination. It predicts the nucleation of major cracks in the microstruc- ture in ratcheting. Subsequently, the total life

  6. 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.

    2013-02-01T23:59:59.000Z

    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.

  7. Evaluating the Applicability of Current Models of Workload to Peer-based Human-robot Teams

    E-Print Network [OSTI]

    Zhang, Tao

    -off possibility into a reality. Human Performance Moderator Functions (HPMFs) can be used to predict human. This trend was predicted by the IMPRINT Pro models. These results are the first to indicate that existing Terms Performance, Experimentation, Human Factors Keywords human-robot peer-based teams, human-performance

  8. Model Refinement Needs A model developed by Peters and Marmorek (2003) will be used to generate predictions for

    E-Print Network [OSTI]

    449 Model Refinement Needs A model developed by Peters and Marmorek (2003) will be used to generate primarily an energy sink or primarily a source of food? More information is needed as to interactions predictions for comparison with observed variations in kokanee production. As with most models

  9. Comparisons of Predictions from Exact Amplitude-Based Resummation Methods with LHC and Cosmological Data

    E-Print Network [OSTI]

    Ward, B F L; Yost, S A

    2013-01-01T23:59:59.000Z

    We present the current status of the comparisons with the respective data of the predictions of our approach of exact amplitude-based resummation in quantum field theory in two areas of investigation: precision QCD calculations of all four of us as needed for LHC physics and the resummed quantum gravity realization by one of us (B.F.L.W.) of Einstein's theory of general relativity as formulated by Feynman. The agreement between the theoretical predictions and the data exhibited continues to be encouraging.

  10. 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.

    2014-02-01T23:59:59.000Z

    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.

  11. Land Surface Model Data Assimilation for Atmospheric Prediction

    E-Print Network [OSTI]

    Walker, Jeff

    remote sensing studies, using visible, thermal infrared (surface temperature) and microwave (passive, the first passive microwave sensor in space with appropriate frequencies for measuring near-surface soil of concurrent data has made evaluation of SMMR-based studies effectively impossible (Walker et al., 2003

  12. 3D Rigid Body Impact Burial Prediction Model

    E-Print Network [OSTI]

    Chu, Peter C.

    -fixed coordinate (E-coordinate) · cylinder's main-axis following coordinate (M-coordinate) · hydrodynamic force-Coordiante Hydrodynamic forces (drag and lift) are easily calculated. #12;Moment of Momentum Equations #12;Interfacial;Experiment · Hydrodynamic Model Development · Behavior of Falling Cylinder in Water Column (Chaotic

  13. Prediction under uncertainty in reservoir modeling S. Subbeya,*, M. Christiea

    E-Print Network [OSTI]

    Sambridge, Malcolm

    a Institute of Petroleum Engineering, Heriot-Watt University, Edinburgh EH14 4AS, UK b Research School to production data, is obtained. The model is then used to forecast future production profiles. Because the history match is non-unique, the forecast production profiles are therefore uncertain, although

  14. A NEW MODEL FOR PERFORMANCE PREDICTION OF HARD ROCK TBMS.

    E-Print Network [OSTI]

    TBMs. The model uses information on the rock properties and cutting geometry to calculate TBM rate on data collected in the field and is merely a regression between machine parameters, rock properties is introduced to provide an estimate of disc cutting forces as a function of rock properties and the cutting

  15. Optimal Model-Based Production Planning for

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    1 1 Optimal Model-Based Production Planning for Refinery Operation Abdulrahman Alattas Advisor to refinery profit and economics Refinery production planning models Operation optimization Crude selection Integrate scheduling into planning model Current Project collaboration with BP Goal: develop a refinery

  16. Prediction of Emerging Technologies Based on Analysis of the U.S. Patent Citation Network

    E-Print Network [OSTI]

    Érdi, Péter; Somogyvári, Zoltán; Strandburg, Katherine; Tobochnik, Jan; Volf, Péter; Zalányi, László

    2012-01-01T23:59:59.000Z

    The network of patents connected by citations is an evolving graph, which provides a representation of the innovation process. A patent citing another implies that the cited patent reflects a piece of previously existing knowledge that the citing patent builds upon. A methodology presented here (i) identifies actual clusters of patents: i.e. technological branches, and (ii) gives predictions about the temporal changes of the structure of the clusters. A predictor, called the {citation vector}, is defined for characterizing technological development to show how a patent cited by other patents belongs to various industrial fields. The clustering technique adopted is able to detect the new emerging recombinations, and predicts emerging new technology clusters. The predictive ability of our new method is illustrated on the example of USPTO subcategory 11, Agriculture, Food, Textiles. A cluster of patents is determined based on citation data up to 1991, which shows significant overlap of the class 442 formed at th...

  17. Interactive software for model predictive control with simultaneous identification

    E-Print Network [OSTI]

    Echeverria Del Rio, Pablo

    2000-01-01T23:59:59.000Z

    and Internal Model Control (IMC) by Garcia and Morari (Garcia and Morari, 1982); the other one was about the stability of constrained MPC by Rawlings and Muske (Rawlings and Muske, 1993). Among the research papers and thesis that have been written about MPC... making process (Garcia, Prett and Morari, 1989). In order to obtain the maximum benefit from a process, several performance objectives should be specified and attained in the design and actual implementation of the plant. However, this condition...

  18. 2007 IEEE International Conference on Signal Processing and Communications (ICSPC 2007), 24-27 November 2007, Dubai, United Arab Emirates IMPROVED INTER PREDICTION BASED ON

    E-Print Network [OSTI]

    Po, Lai-Man

    -27 November 2007, Dubai, United Arab Emirates IMPROVED INTER PREDICTION BASED ON STRUCTURAL SIMILARITY IN H

  19. A soil moisture availability model for crop stress prediction

    E-Print Network [OSTI]

    Gay, Roger Franklin

    1983-01-01T23:59:59.000Z

    wet so11 profile [Ritch1e et al. , 1972] . . . . . . . . . . . . . . 12 Relationships between the ratio of actual evaporation (Ea) to pan evaporat1on (E an) as a function of the available soil water in Rule and Bragg soybean [Burch et al. , 1978...] F1gure Interact1ons between soil-moisture status and other components of a general crop yield model . . . . . . . . . . . . . . . 16 Figure Root densit1es for ra1nfed Ruse and Bragg soybean, 98 days after planting [Burch et al. , 1978...

  20. Gamma-ray Burst Models: General Requirements and Predictions

    E-Print Network [OSTI]

    P. Meszaros

    1995-02-21T23:59:59.000Z

    Whatever the ultimate energy source of gamma-ray bursts turns out to be, the resulting sequence of physical events is likely to lead to a fairly generic, almost unavoidable scenario: a relativistic fireball that dissipates its energy after it has become optically thin. This is expected both for cosmological and halo distances. Here we explore the observational motivation of this scenario, and the consequences of the resulting models for the photon production in different wavebands, the energetics and the time structure of classical gamma-ray bursters.

  1. Development and Validation of an Advanced Stimulation Prediction Model for

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOE Facility DatabaseMichigan: EnergyKansas:DetroitOpen Energy1987)

  2. Development of Chemical Model to Predict the Interactions between

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOE Facility DatabaseMichigan: EnergyKansas:DetroitOpen

  3. 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

    2010-06-29T23:59:59.000Z

    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 report describes the development and testing of the algorithm and evaluates the resulting performance, concluding with a discussion of next steps in further research. The experimental results show a small improvement in COP over the baseline policy but it is difficult to draw any strong conclusions about the energy savings potential for MPC with this system only four days of suitable experimental data were obtained once correct operation of the MPC system had been achieved. These data show an improvement in COP of 3.1% {+-} 2.2% relative to a baseline established immediately prior to the period when the MPC was run in its final form. This baseline includes control policy improvements that the plant operators learned by observing the earlier implementations of MPC, including increasing the temperature of the water supplied to the chiller condensers from the cooling towers. The process of data collection and model development, necessary for any MPC project, resulted in the team uncovering various problems with the chilled water system. Although it is difficult to quantify the energy savings resulting from these problems being remedied, they were likely on the same order as the energy savings from the MPC itself. Although the types of problems uncovered and the level of energy savings may differ significantly from other projects, some of the benefits of detecting and diagnosing problems are expected from the use of MPC for any chilled water plant. The degree of chiller loading was found to be a key factor for efficiency. It is more efficient to operate the chillers at or near full load. In order to maximize the chiller load, one would maximize the temperature difference across chillers and the chilled water flow rate through the chillers. Thus, the CHWS set-point and the chilled water flow-rate can be used to limit the chiller loading to prevent chiller surging. Since the flow rate has an upper bound and the CHWS set point has a lower bound, the chiller loading is constrained and often determined by the chilled water return temperature (CHWR). The CHWR temperature

  4. Quantification and prediction of extreme events in a one-dimensional nonlinear dispersive wave model

    E-Print Network [OSTI]

    Will Cousins; Themistoklis P. Sapsis

    2014-01-15T23:59:59.000Z

    The aim of this work is the quantification and prediction of rare events characterized by extreme intensity in nonlinear waves with broad spectra. We consider a one-dimensional non- linear model with deep-water waves dispersion relation, the Majda-McLaughlin-Tabak (MMT) model, in a dynamical regime that is characterized by broadband spectrum and strong non- linear energy transfers during the development of intermittent events with finite-lifetime. To understand the energy transfers that occur during the development of an extreme event we perform a spatially localized analysis of the energy distribution along different wavenumbers by means of the Gabor transform. A stochastic analysis of the Gabor coefficients reveals i) the low-dimensionality of the intermittent structures, ii) the interplay between non-Gaussian statis- tical properties and nonlinear energy transfers between modes, as well as iii) the critical scales (or critical Gabor coefficients) where a critical amount of energy can trigger the formation of an extreme event. We analyze the unstable character of these special localized modes directly through the system equation and show that these intermittent events are due to the interplay of the system nonlinearity, the wave dispersion, and the wave dissipation which mimics wave breaking. These localized instabilities are triggered by random localizations of energy in space, created by the dispersive propagation of low-amplitude waves with random phase. Based on these properties, we design low-dimensional functionals of these Gabor coefficients that allow for the prediction of the extreme event well before the nonlinear interactions begin to occur.

  5. Air Leakage of U.S. Homes: Model Prediction

    SciTech Connect (OSTI)

    Sherman, Max H.; McWilliams, Jennifer A.

    2007-01-01T23:59:59.000Z

    Air tightness is an important property of building envelopes. It is a key factor in determining infiltration and related wall-performance properties such as indoor air quality, maintainability and moisture balance. Air leakage in U.S. houses consumes roughly 1/3 of the HVAC energy but provides most of the ventilation used to control IAQ. The Lawrence Berkeley National Laboratory has been gathering residential air leakage data from many sources and now has a database of more than 100,000 raw measurements. This paper uses a model developed from that database in conjunction with US Census Bureau data for estimating air leakage as a function of location throughout the US.

  6. Prediction of oxy-coal flame stand-off using high-fidelity thermochemical models

    E-Print Network [OSTI]

    Prediction of oxy-coal flame stand-off using high-fidelity thermochemical models and the one Abstract An Eulerian one-dimensional turbulence (ODT) model is applied to simulate oxy-coal combustion temperature and mixing rate on oxy-coal flame is simulated and discussed where flame stand-off is used

  7. An Efficient Genetic Algorithm for Predicting Protein Tertiary Structures in the 2D HP Model

    E-Print Network [OSTI]

    Istrail, Sorin

    , predicting its tertiary structure is known as the protein folding problem. This problem has been widely genetic algo- rithm for the protein folding problem under the HP model in the two-dimensional square Genetic Algorithm, Protein Folding Problem, 2D HP Model 1. INTRODUCTION Amino acids are the building

  8. User-click Modeling for Understanding and Predicting Search-behavior

    E-Print Network [OSTI]

    Yang, Qiang

    . Categories and Subject Descriptors H.3.3 [Information Search and Retrieval]: General Terms AlgorithmsUser-click Modeling for Understanding and Predicting Search-behavior Yuchen Zhang1 , Weizhu Chen1 advances in search users' click modeling consider both users' search queries and click/skip behavior

  9. Development of a new model to predict indoor daylighting : integration in CODYRUN software and validation

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Development of a new model to predict indoor daylighting : integration in CODYRUN software in the scientific literature for determining indoor daylighting values. They are classified in three categories. The originality of our paper relies on the coupling of several simplified models of indoor daylighting

  10. Predicting Response to Political Blog Posts with Topic Models Language Technologies Institute

    E-Print Network [OSTI]

    Cohen, William W.

    - tent Dirichlet Allocation, introduced by Blei et al. (2003), in various ways to capture different char a blog site. The model is an extension of Latent Dirichlet Allocation (LDA) introduced by Blei et al for learning and/or prediction (Blei et al., 2003). Different models can be compared to explore

  11. PAVEMENT PREDICTION PERFORMANCE MODELS AND RELATION WITH TRAFFIC FATALITIES AND INJURIES

    E-Print Network [OSTI]

    Boyer, Edmond

    PAVEMENT PREDICTION PERFORMANCE MODELS AND RELATION WITH TRAFFIC FATALITIES AND INJURIES V. CEREZO.gothie@developpement-durable.gouv.fr ABSTRACT This paper presents some results of a study, which aimed at modelling pavement evolution, pavement characteristics and age. In a second part, non-linear regressions were used in view of obtaining

  12. Predictive Modeling of Transient Storage and Nutrient Uptake: Implications for Stream Restoration

    E-Print Network [OSTI]

    Predictive Modeling of Transient Storage and Nutrient Uptake: Implications for Stream Restoration of reactive transport modeling for stream restoration purposes: the accuracy of the nutrient spiraling geomorphology and hydraulics influence nu- trient uptake is vital for stream restoration projects that modify

  13. A Model for Predicting Daily Peak Visitation and Implications for Recreation Management and Water Quality: Evidence

    E-Print Network [OSTI]

    carrying capacity. Keywords Visitation model Á Recreation management Á Water quality Á River visitation ÁA Model for Predicting Daily Peak Visitation and Implications for Recreation Management and Water Quality: Evidence from Two Rivers in Puerto Rico Luis E. Santiago � Armando Gonzalez-Caban � John Loomis

  14. A simplified approach to quantifying predictive and parametric uncertainty in artificial neural network hydrologic models

    E-Print Network [OSTI]

    Chaubey, Indrajeet

    considerable interest in developing methods for uncertainty analysis of artificial neural network (ANN) models and parametric uncertainty in artificial neural network hydrologic models, Water Resour. Res., 43, W10407, doi:10A simplified approach to quantifying predictive and parametric uncertainty in artificial neural

  15. IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 8, NO. 6, DECEMBER 2000 665 Fuzzy Model Predictive Control

    E-Print Network [OSTI]

    Huang, Yinlun

    and petrochemical industries during the past decade. In MPC, a process dynamic model is used to predict future (FMPC) approach is introduced to design a control system for a highly nonlinear process. In this approach, a process system is described by a fuzzy convolution model that consists of a number of quasi

  16. Atomistic Modeling of Macromolecular Crowding Predicts Modest Increases in Protein Folding and Binding Stability

    E-Print Network [OSTI]

    Weston, Ken

    Atomistic Modeling of Macromolecular Crowding Predicts Modest Increases in Protein Folding that macromolecular crowding can increase protein folding stability, but depending on details of the models (e.g., how on the effects of macro- molecular crowding on protein folding and binding stability has been reached. Crowders

  17. The 1D Iterative Model for Predicting Thermal Radiation from a Jet Fire

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    manuscript, published in "6. International Seminar on Fire and Explosion Hazards (FEH), Leeds : UnitedThe 1D Iterative Model for Predicting Thermal Radiation from a Jet Fire Leroy, G.* and Duplantier of the current jet fire models used in the accidental fire risks department are semi- empirical. They depend

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

    SciTech Connect (OSTI)

    Cao Yue, E-mail: yuecao@umich.edu [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Department of Radiology, University of Michigan, Ann Arbor, Michigan (United States); Wang Hesheng [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States)] [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Johnson, Timothy D. [Department of Biostatistics, University of Michigan, Ann Arbor, Michigan (United States)] [Department of Biostatistics, University of Michigan, Ann Arbor, Michigan (United States); Pan, Charlie [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States)] [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Hussain, Hero [Department of Radiology, University of Michigan, Ann Arbor, Michigan (United States)] [Department of Radiology, University of Michigan, Ann Arbor, Michigan (United States); Balter, James M.; Normolle, Daniel; Ben-Josef, Edgar; Ten Haken, Randall K.; Lawrence, Theodore S.; Feng, Mary [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States)] [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States)

    2013-01-01T23:59:59.000Z

    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 could aid in individualizing therapy, particularly for patients at risk for liver injury after RT.

  19. 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

    2013-07-21T23:59:59.000Z

    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 .

  20. Evaluation of Transport and Dispersion Models: A Controlled Comparison of HPAC and NARAC Predictions

    SciTech Connect (OSTI)

    Warner, S; Heagy, J F; Platt, N; Larson, D; Sugiyama, G; Nasstrom, J S; Foster, K T; Bradley, S; Bieberbach, G

    2001-05-01T23:59:59.000Z

    During fiscal year 2000, a series of studies in support of the Defense Threat Reduction Agency (DTRA) was begun. The goal of these studies is to improve the verification, validation, and accreditation (VV&A) of hazard prediction and assessment models and capabilities. These studies are part of a larger joint VV&A collaborative effort that DTRA and the Department of Energy (DOE), via the Lawrence Livermore National Laboratory (LLNL), are conducting. This joint effort includes comparisons of the LLNL and DTRA transport and dispersion (T&D) modeling systems, NARAC and HPAC, respectively. The purpose of this work is to compare, in a systematic way, HPAC and NARAC model predictions for a set of controlled hypothetical release scenarios. Only ''model-versus-model'' comparisons are addressed in this work. Model-to-field trial comparisons for HPAC and NARAC have been addressed in a recent companion study, in support of the same joint VV&A effort.

  1. Impact of rainstorm and runoff modeling on predicted consequences of atmospheric releases from nuclear reactor accidents

    SciTech Connect (OSTI)

    Ritchie, L.T.; Brown, W.D.; Wayland, J.R.

    1980-05-01T23:59:59.000Z

    A general temperate latitude cyclonic rainstorm model is presented which describes the effects of washout and runoff on consequences of atmospheric releases of radioactive material from potential nuclear reactor accidents. The model treats the temporal and spatial variability of precipitation processes. Predicted air and ground concentrations of radioactive material and resultant health consequences for the new model are compared to those of the original WASH-1400 model under invariant meteorological conditions and for realistic weather events using observed meteorological sequences. For a specific accident under a particular set of meteorological conditions, the new model can give significantly different results from those predicted by the WASH-1400 model, but the aggregate consequences produced for a large number of meteorological conditions are similar.

  2. OPTIMAL DIFFERENTIATION BASED ON STOCHASTIC SIGNAL MODELS

    E-Print Network [OSTI]

    OPTIMAL DIFFERENTIATION BASED ON STOCHASTIC SIGNAL MODELS Bengt Carlsson, Anders Ahl'en and Mikael Sternad \\Lambda November 1989 Abstract The problem of estimating the time derivative of a signal from sam is to use stochastic models of the signal to be differentiated and of the measurement noise. Two approaches

  3. RESIDUAL PREDICTION BASED ON UNIT SELECTION David Sundermann1,2,3

    E-Print Network [OSTI]

    Black, Alan W

    Bonafonte2 , Hermann Ney4 , Alan W Black5 1 Siemens Corporate Technology, Munich, Germany 2 Universitat@suendermann.com, harald.hoege@siemens.com, antonio.bonafonte@upc.edu, ney@cs.rwth-aachen.de, awb@cs.cmu.edu ABSTRACT based on lin- ear transformation or hidden Markov model-based speech synthesis. Our voice conversion

  4. Dynamic Modeling of Aerobic Growth of Shewanella oneidensis. Predicting Triauxic Growth, Flux Distributions and Energy Requirement for Growth

    SciTech Connect (OSTI)

    Song, Hyun-Seob; Ramkrishna, Doraiswami; Pinchuk, Grigoriy E.; Beliaev, Alex S.; Konopka, Allan; Fredrickson, Jim K.

    2013-01-01T23:59:59.000Z

    A model-based analysis is conducted to investigate metabolism of Shewanella oneidensis MR-1 strain in aerobic batch culture, which exhibits an intriguing growth pattern by sequentially consuming substrate (i.e., lactate) and by-products (i.e., pyruvate and acetate). A general protocol is presented for developing a detailed network-based dynamic model for S. oneidensis based on the Lumped Hybrid Cybernetic Model (LHCM) framework. The L-HCM, although developed from only limited data, is shown to accurately reproduce exacting dynamic metabolic shifts, and provide reasonable estimates of energy requirement for growth. Flux distributions in S. oneidensis predicted by the L-HCM compare very favorably with 13C-metabolic flux analysis results reported in the literature. Predictive accuracy is enhanced by incorporating measurements of only a few intracellular fluxes, in addition to extracellular metabolites. The L-HCM developed here for S. oneidensis is consequently a promising tool for the analysis of intracellular flux distribution and metabolic engineering.

  5. Prediction and measurement of transient responses of first difference based chaos control for 1-dimensional maps

    E-Print Network [OSTI]

    Edward H. Hellen; J. Keith Thomas

    2010-01-14T23:59:59.000Z

    Chaotic behavior can be produced from difference equations with unstable fixed points. Difference equations can be used for algorithms to control the chaotic behavior by perturbing a system parameter using feedback based on the first difference of the system value. This results in a system of nonlinear first order difference equations whose stable fixed point is the controlled chaotic behavior. Basing the feedback on the first difference produces distinctly different transient responses than when basing feedback on the error from the fixed point. Analog electronic circuits provide the experimental system for testing the chaos control algorithm. The circuits are low-cost, relatively easy to construct, and therefore provide a useful transition towards more specialized real-world applications. Here we present predictions and experimental results for the transient responses of a first difference based feedback control method applied to a chaotic finite difference 1-dimensional map. The experimental results are in good agreement with predictions, showing a variety of behaviors for the transient response, including erratic appearing non-steady convergence.

  6. The application of a chemical equilibrium model, SOLTEQ, to predict the chemical speciations in stabilized/solidified waste forms 

    E-Print Network [OSTI]

    Park, Joo-Yang

    1994-01-01T23:59:59.000Z

    . . . . . . . . . . . . . . . . . ?. .. , . . . . . . . . . . . . 55 10 Prediction of porewater pH . 11 Effects of pH on predictions of various species . . . 12 Prediction of Al concentration 13 Prediction of Fe concentration 14 Prediction of SO4 concentration . 15 Prediction of Ca concentration . 16...A hydration (16). However, Reardon (9) indicated that equilibrium models using current K, ?values of these minerals tend to predict the thermodynamic stability of ettringite over monosulfate. Because the hydration of C4AF is analogous to that of CsA, C4AF...

  7. Springback prediction in sheet metal forming process based on the hybrid SA

    SciTech Connect (OSTI)

    Guo Yuqin; Jiang Hong; Wang Xiaochun [School of Mechanical Engineering, Xi' an Jiaotong University, Xi' an 710049 (China); Li Fuzhu [Technology Institute, Xuzhou Normal University, XuZhou 221011 (China)

    2005-08-05T23:59:59.000Z

    In terms of the intensive similarity between the sheet metal forming-springback process and that of the annealing of metals, it is suggested that the simulation of the sheet metal forming process is performed with the Nonlinear FEM and the springback prediction is implemented by solving the large-scale combinational optimum problem established on the base of the energy descending and balancing in deformed part. The BFGS-SA hybrid SA approach is proposed to solve this problem and improve the computing efficiency of the traditional SA and its capability of obtaining the global optimum solution. At the same time, the correlative annealing strategies for the SA algorithm are determined in here. By comparing the calculation results of sample part with those of experiment measurement at the specified sections, the rationality of the schedule of springback prediction used and the validity of the BFGS-SA algorithm proposed are verified.

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

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

    developed models to predict the reliability of hybrid gas bearing (HGB) and dry gas seal (DGS) components in the turboexpander of a supercritical CO2 turbine. The...

  9. A probabilistic graphical model based stochastic input model construction

    SciTech Connect (OSTI)

    Wan, Jiang [Materials Process Design and Control Laboratory, Sibley School of Mechanical and Aerospace Engineering, 101 Frank H.T. Rhodes Hall, Cornell University, Ithaca, NY 14853-3801 (United States); Zabaras, Nicholas, E-mail: nzabaras@gmail.com [Materials Process Design and Control Laboratory, Sibley School of Mechanical and Aerospace Engineering, 101 Frank H.T. Rhodes Hall, Cornell University, Ithaca, NY 14853-3801 (United States); Center for Applied Mathematics, 657 Frank H.T. Rhodes Hall, Cornell University, Ithaca, NY 14853-3801 (United States)

    2014-09-01T23:59:59.000Z

    Model reduction techniques have been widely used in modeling of high-dimensional stochastic input in uncertainty quantification tasks. However, the probabilistic modeling of random variables projected into reduced-order spaces presents a number of computational challenges. Due to the curse of dimensionality, the underlying dependence relationships between these random variables are difficult to capture. In this work, a probabilistic graphical model based approach is employed to learn the dependence by running a number of conditional independence tests using observation data. Thus a probabilistic model of the joint PDF is obtained and the PDF is factorized into a set of conditional distributions based on the dependence structure of the variables. The estimation of the joint PDF from data is then transformed to estimating conditional distributions under reduced dimensions. To improve the computational efficiency, a polynomial chaos expansion is further applied to represent the random field in terms of a set of standard random variables. This technique is combined with both linear and nonlinear model reduction methods. Numerical examples are presented to demonstrate the accuracy and efficiency of the probabilistic graphical model based stochastic input models. - Highlights: • Data-driven stochastic input models without the assumption of independence of the reduced random variables. • The problem is transformed to a Bayesian network structure learning problem. • Examples are given in flows in random media.

  10. Final Report Coupling in silico microbial models with reactive transport models to predict the fate of contaminants in the subsurface.

    SciTech Connect (OSTI)

    Lovley, Derek R.

    2012-10-31T23:59:59.000Z

    This project successfully accomplished its goal of coupling genome-scale metabolic models with hydrological and geochemical models to predict the activity of subsurface microorganisms during uranium bioremediation. Furthermore, it was demonstrated how this modeling approach can be used to develop new strategies to optimize bioremediation. The approach of coupling genome-scale metabolic models with reactive transport modeling is now well enough established that it has been adopted by other DOE investigators studying uranium bioremediation. Furthermore, the basic principles developed during our studies will be applicable to much broader investigations of microbial activities, not only for other types of bioremediation, but microbial metabolism in diversity of environments. This approach has the potential to make an important contribution to predicting the impact of environmental perturbations on the cycling of carbon and other biogeochemical cycles.

  11. Supersonic combustion studies using a multivariate quadrature based method for combustion modeling

    E-Print Network [OSTI]

    Raman, Venkat

    Supersonic combustion studies using a multivariate quadrature based method for combustion modeling function (PDF) of thermochemical variables can be used for accurately computing the combustion source term of predictive models for supersonic combustion is a critical step in design and development of scramjet engines

  12. Physiologically Based Pharmacokinetic Modeling of Benzene Metabolism in Mice through Extrapolation

    E-Print Network [OSTI]

    metabolic constants for humans can subsequently be extrapolated to predict the dosimetry of benzene and itsPhysiologically Based Pharmacokinetic Modeling of Benzene Metabolism in Mice through Extrapolation parameters are also available for humans. Unknown parameters were estimated by fitting the model to published

  13. Improving the Fanger model's thermal comfort predictions for naturally ventilated spaces

    E-Print Network [OSTI]

    Truong, Phan Hue

    2010-01-01T23:59:59.000Z

    The Fanger model is the official thermal comfort model in U.S. and international standards and is based on the heat balance of the human body with the environment. This investigation focuses on re-specifying the parameters ...

  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

    2009-03-03T23:59:59.000Z

    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. Total and Peak Energy Consumption Minimization of Building HVAC Systems Using Model Predictive Control

    E-Print Network [OSTI]

    Maasoumy, Mehdi; Sangiovanni-Vincentelli, Alberto

    2012-01-01T23:59:59.000Z

    optimal control design for HVAC systems,’’ in Proc. Dynamicelectricity consumption in hvac using learning- based model-algorithm design for hvac systems in energy efficient

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

    SciTech Connect (OSTI)

    Jaroslav Solc

    2009-06-01T23:59:59.000Z

    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.

  17. Dynamics of Cell Shape and Forces on Micropatterned Substrates Predicted by a Cellular Potts Model

    E-Print Network [OSTI]

    Philipp J. Albert; Ulrich S. Schwarz

    2014-05-19T23:59:59.000Z

    Micropatterned substrates are often used to standardize cell experiments and to quantitatively study the relation between cell shape and function. Moreover, they are increasingly used in combination with traction force microscopy on soft elastic substrates. To predict the dynamics and steady states of cell shape and forces without any a priori knowledge of how the cell will spread on a given micropattern, here we extend earlier formulations of the two-dimensional cellular Potts model. The third dimension is treated as an area reservoir for spreading. To account for local contour reinforcement by peripheral bundles, we augment the cellular Potts model by elements of the tension-elasticity model. We first parameterize our model and show that it accounts for momentum conservation. We then demonstrate that it is in good agreement with experimental data for shape, spreading dynamics, and traction force patterns of cells on micropatterned substrates. We finally predict shapes and forces for micropatterns that have not yet been experimentally studied.

  18. Predicting effective magnetoelectric response in magnetic-ferroelectric composites via phase-field modeling

    E-Print Network [OSTI]

    Chen, Long-Qing

    Predicting effective magnetoelectric response in magnetic-ferroelectric composites via phase Articles you may be interested in Stress magnetization model for magnetostriction in multiferroic composite circular fibrous multiferroic composites J. Appl. Phys. 109, 104901 (2011); 10.1063/1.3583580 Effect

  19. Molecular Constraints on Synaptic Tagging and Maintenance of Long-Term Potentiation: A Predictive Model

    E-Print Network [OSTI]

    Paul Smolen; Douglas A. Baxter; John H. Byrne

    2012-08-03T23:59:59.000Z

    Protein synthesis-dependent, late long-term potentiation (LTP) and depression (LTD) at glutamatergic hippocampal synapses are well characterized examples of long-term synaptic plasticity. Persistent increased activity of the enzyme protein kinase M (PKM) is thought essential for maintaining LTP. Additional spatial and temporal features that govern LTP and LTD induction are embodied in the synaptic tagging and capture (STC) and cross capture hypotheses. Only synapses that have been "tagged" by an stimulus sufficient for LTP and learning can "capture" PKM. A model was developed to simulate the dynamics of key molecules required for LTP and LTD. The model concisely represents relationships between tagging, capture, LTD, and LTP maintenance. The model successfully simulated LTP maintained by persistent synaptic PKM, STC, LTD, and cross capture, and makes testable predictions concerning the dynamics of PKM. The maintenance of LTP, and consequently of at least some forms of long-term memory, is predicted to require continual positive feedback in which PKM enhances its own synthesis only at potentiated synapses. This feedback underlies bistability in the activity of PKM. Second, cross capture requires the induction of LTD to induce dendritic PKM synthesis, although this may require tagging of a nearby synapse for LTP. The model also simulates the effects of PKM inhibition, and makes additional predictions for the dynamics of CaM kinases. Experiments testing the above predictions would significantly advance the understanding of memory maintenance.

  20. Prediction of the tool displacement for robot milling applications using coupled models of an industrial

    E-Print Network [OSTI]

    Stryk, Oskar von

    . INTRODUCTION The major fields of machining applications for industrial robots are automated pre- machining an industrial robot for milling applications inaccuracies of the serial robot kinematic, the low structuralPrediction of the tool displacement for robot milling applications using coupled models

  1. Motion Control of Tetrahymena pyriformis Cells with Artificial Magnetotaxis: Model Predictive Control (MPC) Approach

    E-Print Network [OSTI]

    Julius, Anak Agung

    -- The use of live microbial cells as microscale robots is an attractive premise, primarily because eukaryotic cell. Whitesides et al [10] demonstrated the biological propul- sion of microscale loadsMotion Control of Tetrahymena pyriformis Cells with Artificial Magnetotaxis: Model Predictive

  2. Three-Dimensional Hydrodynamic Model for Prediction of Falling Cylinder Through Water Column

    E-Print Network [OSTI]

    Chu, Peter C.

    1 1 Three-Dimensional Hydrodynamic Model for Prediction of Falling Cylinder Through Water Column-coordinate), cylinder's main-axis following coordinate (M-coordinate), and hydrodynamic force following coordinate (F-coordinate system. The hydrodynamic forces (such as the drag and lift forces) and their moments are easily computed

  3. Adaptive Model Predictive Control of the Hybrid Dynamics of a Fuel Cell System.

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Adaptive Model Predictive Control of the Hybrid Dynamics of a Fuel Cell System. M. Fiacchini, T operation of a fuel cell system is presented. The aim of the control design is to guarantee that the oxygen control to a fuel cell plant is presented. The fuel cell, located in the laboratory of the Department

  4. A comparison of various models in predicting ignition delay in single-particle coal combustion

    E-Print Network [OSTI]

    A comparison of various models in predicting ignition delay in single-particle coal combustion November 2013 Accepted 7 January 2014 Available online xxxx Keywords: Coal Devolatilization Ignition delay a b s t r a c t In this paper, individual coal particle combustion under laminar conditions

  5. Predicting Protein Folds with Structural Repeats Using a Chain Graph Model

    E-Print Network [OSTI]

    Xing, Eric P.

    Predicting Protein Folds with Structural Repeats Using a Chain Graph Model Yan Liu yanliu, Carnegie Mellon University, Pittsburgh, PA 15213 USA Abstract Protein fold recognition is a key step to to accurately identify protein folds aris- ing from typical spatial arrangements of well-defined secondary

  6. Structural health monitoring with piezoelectric wafer active sensors predictive modeling and simulation

    E-Print Network [OSTI]

    Giurgiutiu, Victor

    Structural health monitoring with piezoelectric wafer active sensors ­ predictive modeling of the state of the art in structural health monitoring with piezoelectric wafer active sensors and follows with conclusions and suggestions for further work Key Words: structural health monitoring, SHM, nondestructive

  7. Towards a Generalized Regression Model for On-body Energy Prediction from Treadmill Walking

    E-Print Network [OSTI]

    Sukhatme, Gaurav S.

    Towards a Generalized Regression Model for On-body Energy Prediction from Treadmill Walking sensor data to energy expenditure is the ques- tion of normalizating across physiological parameters. Common approaches such as weight scaling require validation for each new population. An alternative

  8. A Prediction Model for Adiabatic and Diabatic Capillary Tubes with Alternative Refrigerants

    E-Print Network [OSTI]

    Zhang, Yupeng

    2014-12-05T23:59:59.000Z

    line) that exits the evaporator, which creates the so called capillary tube/suction line heat exchanger. Models to predict the mass flow in both adiabatic capillary tubes and capillary tube/suction line heat exchangers are developed in this thesis...

  9. Model-predicted distribution of wind-induced internal wave energy in the world's oceans

    E-Print Network [OSTI]

    Miami, University of

    Model-predicted distribution of wind-induced internal wave energy in the world's oceans Naoki 9 July 2008; published 30 September 2008. [1] The distribution of wind-induced internal wave energy-induced internal wave energy in the world's oceans, J. Geophys. Res., 113, C09034, doi:10.1029/2008JC004768. 1

  10. Virtual Electrodes Mechanisms Predictions with a Current-Lifted Monodomain Model

    E-Print Network [OSTI]

    Boyer, Edmond

    Virtual Electrodes Mechanisms Predictions with a Current-Lifted Monodomain Model Yves Coudi`ere1 cost. The source term is derived from a lifting principle ap- plied to the resolution, and an excitation part, that remains unchanged. Equivalently, we make a lifting of the stimula- tion functions

  11. Predictive Modeling for Glass-Side Laser Scribing of Thin Film Photovoltaic Cells

    E-Print Network [OSTI]

    Yao, Y. Lawrence

    with reduced thermal effect. Film side laser scribing is governed by heating, melting and vaporizing of selective films. Glass side laser scribing is a thermal-mechanical process which involves stress inducedPredictive Modeling for Glass-Side Laser Scribing of Thin Film Photovoltaic Cells Hongliang Wang

  12. Model predictive control of a pilot-scale distillation column using a programmable automation controller

    E-Print Network [OSTI]

    Model predictive control of a pilot-scale distillation column using a programmable automation). The controller is tested on a pilot-scale binary distillation column to track reference temperatures. A majorRIO) to control a pilot-scale binary distillation col- umn. Both the PI-controllers and the supervising online MPC

  13. Supervisory hybrid model predictive control for voltage stability of power networks

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Supervisory hybrid model predictive control for voltage stability of power networks R.R. Negenborn voltage control problems in electric power networks have stimulated the interest for the imple- mentation dynamics to restore power consumption beyond the capability of the transmission and generation system

  14. Prediction Intervals for NAR Model Structures Using a Bootstrap De Brabanter J.,

    E-Print Network [OSTI]

    Prediction Intervals for NAR Model Structures Using a Bootstrap Method De Brabanter J structure. Our approach relies on the external bootstrap procedure [1]. This method is contrasted. In this paper, an external bootstrap method will be proposed for this purpose. The bootstrap is a computer

  15. Predicting pesticide fate in the hive (part 2): development of a dynamic hive model

    E-Print Network [OSTI]

    .g. bees, wax and honey). The proposed model is validated using empirical data on -fluvalinate residues in bees, wax and honey. It predicts with good approximation both the trends over time to measured data. A honeybee hive is a micro-ecosystem com- posed of several components (e.g. bees, wax, honey

  16. Accurate Modeling and Prediction of Energy Availability in Energy Harvesting Real-Time Embedded Systems

    E-Print Network [OSTI]

    Qiu, Qinru

    Binghamton University, State University of New York Binghamton, New York, USA {jlu5, sliu5, qwu, qqiuAccurate Modeling and Prediction of Energy Availability in Energy Harvesting Real-Time Embedded}@binghamton.edu Abstract -- Energy availability is the primary subject that drives the research innovations in energy

  17. Comparison of Machine Learning Techniques with Classical Statistical Models in Predicting Health Outcomes

    E-Print Network [OSTI]

    Mitnitski, Arnold B.

    ,5]. The aim of our report is to compare the performance of sev- eral well known machine learning techniquesComparison of Machine Learning Techniques with Classical Statistical Models in Predicting Health Faculty of Computer Science, Dalhousie University, Canada Abstract Several machine learning techniques

  18. Nonparametric Variable Selection for Predictive Models and Subpopulations in Clinical Trials

    E-Print Network [OSTI]

    Xie, Jun

    Introduction In most clinical trials, there is much heterogeneity among individual outcomes and the treat- mentNonparametric Variable Selection for Predictive Models and Subpopulations in Clinical Trials Jingyi, IN 47907 Abstract Most clinical trials have heterogeneous treatment effect among patient individuals

  19. Blood Glucose Level Prediction using Physiological Models and Support Vector Regression

    E-Print Network [OSTI]

    Bunescu, Razvan C.

    Blood Glucose Level Prediction using Physiological Models and Support Vector Regression Razvan continually monitor their blood glucose levels and adjust insulin doses, striving to keep blood glucose levels as close to normal as possible. Blood glucose levels that deviate from the normal range can lead to serious

  20. Technical Report -DTU -Informatics and Mathematical Modeling (May 31, 2007) Temperature Prediction in District

    E-Print Network [OSTI]

    Prediction in District Heating Systems with cFIR models Pierre Pinson , Torben S. Nielsen, Henrik Aa. Nielsen, Lyngby, Denmark Abstract Current methodologies for the optimal operation of district heating systems regularization. Results are given for the test case of the Roskilde district heating system, over a period

  1. A LIFETIME PREDICTION MODEL FOR SINGLE CRYSTAL SUPERALLOYS SUBJECTED TO THERMOMECHANICAL

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    materials tensile, creep and LCF test data at different temperatures. Some parameters, independentA LIFETIME PREDICTION MODEL FOR SINGLE CRYSTAL SUPERALLOYS SUBJECTED TO THERMOMECHANICAL CREEP for Single Crystal Superalloys operated at high temperatures and subjected to creep, fatigue and oxidation

  2. Exploiting Two Intelligent Models to Predict Water Level: A field study of Urmia lake, Iran

    E-Print Network [OSTI]

    Fernandez, Thomas

    Exploiting Two Intelligent Models to Predict Water Level: A field study of Urmia lake, Iran Shahab. The measurements from a single tide gauge at Urmia Lake, Northwest Iran, were used to train and validate the GP of Tabriz, Tabriz, Iran. Tel: 0098-411-3392786 Fax: 0098-411-3345332, (e-mail: sha- hab kvk66@yahoo

  3. Randomized Model Predictive Control for HVAC Systems Alessandra Parisio, Damiano Varagnolo, Daniel Risberg,

    E-Print Network [OSTI]

    Johansson, Karl Henrik

    Randomized Model Predictive Control for HVAC Systems Alessandra Parisio, Damiano Varagnolo, Daniel Conditioning (HVAC) sys- tems play a fundamental role in maintaining acceptable ther- mal comfort and Indoor. A possible solu- tion is to develop effective control strategies for HVAC sys- tems, but this is complicated

  4. Economic Nonlinear Model Predictive Control for the Optimization of Gas Pipeline Networks

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    / 24 #12;Natural Gas Industry Motivation Natural Gas Industry Globally increasing demand & production of natural gas. Demand distribution (as of 2008) 21 % residential, 13 % Commercial, 34 % Industrial, 29 - Regulated, Deregulated markets Applying Economic Model Predictive Control to gas transportation. 1Zheng et

  5. A multivalued knowledge-base model

    E-Print Network [OSTI]

    Achs, Agnes

    2010-01-01T23:59:59.000Z

    The basic aim of our study is to give a possible model for handling uncertain information. This model is worked out in the framework of DATALOG. At first the concept of fuzzy Datalog will be summarized, then its extensions for intuitionistic- and interval-valued fuzzy logic is given and the concept of bipolar fuzzy Datalog is introduced. Based on these ideas the concept of multivalued knowledge-base will be defined as a quadruple of any background knowledge; a deduction mechanism; a connecting algorithm, and a function set of the program, which help us to determine the uncertainty levels of the results. At last a possible evaluation strategy is given.

  6. Perception Based Character Modeling and Animation

    E-Print Network [OSTI]

    Higa, Mitsutoshi

    procedure Page RESULTS 32 Perceived sex 3 Perceived masculinity 4 Perceived femininity 6 Perceived attractiveness 38 DISCUSSION 40 Perceived sex Perceived masculinity and femininity 41 Perceived attractiveness 42 Summary 43 PERCEPTION BASED MODELING... the WHR and walk motion 4 Modeling the WHR 49 Animating the walk 51 SUMMARY AND CONCLUSION 3 REFERENCES 55 APPENDIX A 8 APPENDIX B 61 APPENDIX C 9 APPENDIX D.... 72 APPENDIX E 120 Page VITA 121 LIST OF FIGURES FIGURE Page 1 A complete cycle...

  7. Key challenges to model-based design : distinguishing model confidence from model validation

    E-Print Network [OSTI]

    Flanagan, Genevieve (Genevieve Elise Cregar)

    2012-01-01T23:59:59.000Z

    Model-based design is becoming more prevalent in industry due to increasing complexities in technology while schedules shorten and budgets tighten. Model-based design is a means to substantiate good design under these ...

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

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

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

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

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

    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...

  10. application models based: Topics by E-print Network

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

    the potentials and limits Bryson, Joanna J. 2 Model-Based Vulnerability Testing for Web Applications Physics Websites Summary: Model-Based Vulnerability Testing for Web...

  11. Model-Inspired Research. TES research uses modeling, prediction, and synthesis to identify

    E-Print Network [OSTI]

    in Earth system models (ESMs). TES supports research to advance fundamental understanding of terrestrial-process models, ecosystem models, and the Community Earth System Model). This emphasis on the capture of advanced in Earth system models to increase the quality of climate model projections and to provide the scientific

  12. Brief Articles A Swift All-Atom Energy-Based Computational Protocol to Predict DNA-Ligand Binding

    E-Print Network [OSTI]

    Jayaram, Bhyravabotla

    atomic charges on the DNA and ligand atoms calculated from Coulomb's law, employing a sigmoidal dielecBrief Articles A Swift All-Atom Energy-Based Computational Protocol to Predict DNA-Ligand Binding

  13. Predictions and measurements of isothermal airflow in a model once-through steam generator

    SciTech Connect (OSTI)

    Carter, H R; Promey, G J; Rush, G C

    1982-11-01T23:59:59.000Z

    Once-Through Steam Generators (OTSGs) are used in the Nuclear Steam Supply Systems marketed by The Babcock and Wilcox Company (B and W). To analytically predict the three-dimensional, steady-state thermohydraulic conditions in the OTSG, B and W has developed a proprietary code THEDA-1 and is working in cooperation with EPRI to develop an improved version, THEDA-2. Confident application of THEDA requires experimental verification to demonstrate that the code can accurately describe the thermohydraulic conditions in geometries characteristic of the OTSG. The first step in the THEDA verification process is the subject of this report. A full-scale, partial-section model of two OTSG spans was constructed and tested using isothermal air as the working fluid. Model local velocities and pressure profiles were measured and compared to THEDA prediction for five model configurations. Over 3000 velocity measurements were taken and the results were compared to THEDA predictions. Agreement between measured and predicted velocity data was generally better than +-12.5%.

  14. Left-right models with light neutrino mass prediction and dominant neutrinoless double beta decay rate

    E-Print Network [OSTI]

    M. K. Parida; Sudhanwa Patra

    2013-01-14T23:59:59.000Z

    In TeV scale left-right symmetric models, new dominant predictions to neutrinoless double beta decay and light neutrino masses are in mutual contradiction because of large contribution to the latter through popular seesaw mechanisms. We show that in a class of left-right models with high-scale parity restoration, these results coexist without any contravention with neutrino oscillation data and the relevant formula for light neutrino masses is obtained via gauged inverse seesaw mechanism. The most dominant contribution to the double beta decay is shown to be via $W^-_L- W^-_R$ mediation involving both light and heavy neutrino exchanges, and the model predictions are found to discriminate whether the Dirac neutrino mass is of quark-lepton symmetric origin or without it. We also discuss associated lepton flavor violating decays.

  15. A Simplified Residential Base-Case Model

    E-Print Network [OSTI]

    Do, S. L.; Choi, J. H.; Haberl, J. S.

    2013-01-01T23:59:59.000Z

    This study was for the DOE-2.1e program to develop a simplified residential ASHP house model in Houston, Texas. The house characteristics were based on the standard reference design and requirements as defined in Chapter 4 of the 2009 IECC...

  16. Multiscale Agent-Based Consumer Market Modeling

    E-Print Network [OSTI]

    Kemner, Ken

    , and Visualization Group; and 3 Center for Energy, Environmental, and Economic Systems Analysis, Argonne NationalMultiscale Agent-Based Consumer Market Modeling MICHAEL J. NORTH,1 CHARLES M. MACAL,1 JAMES ST 8, 2009; revised August 19, 2009; accepted September 8, 2009 Consumer markets have been studied

  17. Physics-Based Mathematical Models for Nanotechnology

    E-Print Network [OSTI]

    Melnik, Roderick

    Physics-Based Mathematical Models for Nanotechnology 2008 J. Phys.: Conf. Ser. 107, 011001, doi: 10 for their excellent support during the workshop. Nanotechnology is the study and application of phenomena at or below. This workshop put strong emphasis on discussions of the new mathematics needed in nanotechnology especially

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

    SciTech Connect (OSTI)

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

    2010-09-01T23:59:59.000Z

    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, Bayesian methods for optimal testing in the QMU framework were developed. This completion of this project represent an increased understanding of how to apply and use the QMU process as a means for improving model predictions of the behavior of complex systems. 4

  19. A model for predicting the costs of research and development in the Post Office Department

    E-Print Network [OSTI]

    Watts, David Eli

    1970-01-01T23:59:59.000Z

    coefficients relating Y and 4. e is an n x 1 vector of the random errors c which are 2 normally distributed with mean 0 and variance a The least squares solution to this model is I ] I B ~ (K X) X Y Linear Cost Models The general philosophy behind linear... of Committee) ~ g QAr4 (Member) (Head of Department) ( er) January 1970 ABSTRACT A Model for Predicting the Costs of Research and Development in the Post Office Department. (January 1970) David E. Vatts, B. S. , Texas A&M University; Directed by: Dr...

  20. Interim Models Developed to Predict Key Hanford Waste Glass Properties Using Composition

    SciTech Connect (OSTI)

    Vienna, John D.; Kim, Dong-Sang; Hrma, Pavel R.

    2003-08-08T23:59:59.000Z

    Over the past several years the amount of waste glass property data available in the open literature has increased markedly. We have compiled the data from over 2000 glass compositions, evaluated the data for consistency, and fit glass property models to portions of this database.[1] The properties modeled include normalized releases of boron (rB), sodium (rNa), and lithium (rLi) from glass exposed to the product consistency test (PCT), liquidus temperature (TL) of glasses in the spinel and zircon primary phase field, viscosity (?) at 1150°C (?1150) and as a function of temperature (?T), and molar volume (V). These models were compared to some of the previously available models and were found to predict the properties of glasses not used in model fitting better and covered broader glass composition regions than the previous ones. This paper summarizes the data collected and the models that resulted from this effort.

  1. Fast and accurate prediction of numerical relativity waveforms from binary black hole mergers using surrogate models

    E-Print Network [OSTI]

    Blackman, Jonathan; Galley, Chad R; Szilagyi, Bela; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A

    2015-01-01T23:59:59.000Z

    Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. In this paper, we construct an accurate and fast-to-evaluate surrogate model for numerical relativity (NR) waveforms from non-spinning binary black hole coalescences with mass ratios from $1$ to $10$ and durations corresponding to about $15$ orbits before merger. Our surrogate, which is built using reduced order modeling techniques, is distinct from traditional modeling efforts. We find that the full multi-mode surrogate model agrees with waveforms generated by NR to within the numerical error of the NR code. In particular, we show that our modeling strategy produces surrogates which can correctly predict NR waveforms that were {\\em not} used for the surrogate's training. For all practical purposes, then, the surrogate waveform model is equivalent to the high-accuracy, large-scale simulation waveform but can be evaluated in a millisecond to a second dependin...

  2. Earthquake prediction: Simple methods for complex phenomena

    E-Print Network [OSTI]

    Luen, Bradley

    2010-01-01T23:59:59.000Z

    and predictions . . . . . . . . . . . . . . . . . . . . .6.1 Assessing models and predictions . . . . . . .What are earthquake predictions and forecasts? . . . . . .

  3. Constraint-Based Runtime Prediction of SLA Violations in Service Orchestrations

    E-Print Network [OSTI]

    Politécnica de Madrid, Universidad

    Prediction of SLA Violations in Service Orchestrations. In Gerti Kappel, Hamid Motahari, and Zakaria Maamar

  4. Predictions for the abundance and colours of galaxies in high redshift clusters in hierarchical models

    E-Print Network [OSTI]

    Merson, Alexander I; Abdalla, Filipe B; Gonzalez-Perez, Violeta; Lagos, Claudia del P; Mei, Simona

    2015-01-01T23:59:59.000Z

    High redshift galaxy clusters allow us to examine galaxy formation in extreme environments. Here we compile data for $z>1$ galaxy clusters to test the predictions from one of the latest semi-analytical models of galaxy formation. The model gives a good match to the slope and zero-point of the cluster red sequence. The model is able to match the cluster galaxy luminosity function at faint and bright magnitudes, but under-estimates the number of galaxies around the break in the luminosity function. We find that simply assuming a weaker dust attenuation improves the model predictions for the cluster galaxy luminosity function, but worsens the predictions for the red sequence at bright magnitudes. Examination of the properties of the bright cluster galaxies suggests that the default dust attenuation is very large due to these galaxies having large reservoirs of cold gas as well as small radii. We find that matching the luminosity function and colours of high redshift cluster galaxies, whilst remaining consistent ...

  5. Evaluation of the Highway Safety Manual Crash Prediction Model for Rural Two-Lane Highway Segments in Kansas

    E-Print Network [OSTI]

    Lubliner, Howard

    2011-12-31T23:59:59.000Z

    for states other than those the model was developed for. To address this gap the Kansas Department of Transportation (KDOT) commissioned this study to analyze both the accuracy and the practicality of using these crash prediction models on Kansas highways...

  6. Impact of emissions, chemistry, and climate on atmospheric carbon monoxide : 100-year predictions from a global chemistry-climate model

    E-Print Network [OSTI]

    Wang, Chien.; Prinn, Ronald G.

    The possible trends for atmospheric carbon monoxide in the next 100 yr have been illustrated using a coupled atmospheric chemistry and climate model driven by emissions predicted by a global economic development model. ...

  7. Energy Band Model Based on Effective Mass

    E-Print Network [OSTI]

    Viktor Ariel

    2012-09-06T23:59:59.000Z

    In this work, we demonstrate an alternative method of deriving an isotropic energy band model using a one-dimensional definition of the effective mass and experimentally observed dependence of mass on energy. We extend the effective mass definition to anti-particles and particles with zero rest mass. We assume an often observed linear dependence of mass on energy and derive a generalized non-parabolic energy-momentum relation. The resulting non-parabolicity leads to velocity saturation at high particle energies. We apply the energy band model to free relativistic particles and carriers in solid state materials and obtain commonly used dispersion relations and experimentally confirmed effective masses. We apply the model to zero rest mass particles in graphene and propose using the effective mass for photons. Therefore, it appears that the new energy band model based on the effective mass can be applied to relativistic particles and carriers in solid state materials.

  8. Comparing GIS-based habitat models for applications in EIA and SEA

    SciTech Connect (OSTI)

    Gontier, Mikael, E-mail: gontier@kth.s [Department of Land and Water Resources Engineering, Royal Institute of Technology, SE-100 44 Stockholm (Sweden); Moertberg, Ulla, E-mail: mortberg@kth.s [Department of Land and Water Resources Engineering, Royal Institute of Technology, SE-100 44 Stockholm (Sweden); Balfors, Berit, E-mail: balfors@kth.s [Department of Land and Water Resources Engineering, Royal Institute of Technology, SE-100 44 Stockholm (Sweden)

    2010-01-15T23:59:59.000Z

    Land use changes, urbanisation and infrastructure developments in particular, cause fragmentation of natural habitats and threaten biodiversity. Tools and measures must be adapted to assess and remedy the potential effects on biodiversity caused by human activities and developments. Within physical planning, environmental impact assessment (EIA) and strategic environmental assessment (SEA) play important roles in the prediction and assessment of biodiversity-related impacts from planned developments. However, adapted prediction tools to forecast and quantify potential impacts on biodiversity components are lacking. This study tested and compared four different GIS-based habitat models and assessed their relevance for applications in environmental assessment. The models were implemented in the Stockholm region in central Sweden and applied to data on the crested tit (Parus cristatus), a sedentary bird species of coniferous forest. All four models performed well and allowed the distribution of suitable habitats for the crested tit in the Stockholm region to be predicted. The models were also used to predict and quantify habitat loss for two regional development scenarios. The study highlighted the importance of model selection in impact prediction. Criteria that are relevant for the choice of model for predicting impacts on biodiversity were identified and discussed. Finally, the importance of environmental assessment for the preservation of biodiversity within the general frame of biodiversity conservation is emphasised.

  9. Reduced model prediction of electron temperature profiles in microtearing-dominated National Spherical Torus eXperiment plasmas

    SciTech Connect (OSTI)

    Kaye, S. M., E-mail: skaye@pppl.gov; Guttenfelder, W.; Bell, R. E.; Gerhardt, S. P.; LeBlanc, B. P.; Maingi, R. [Princeton Plasma Physics Laboratory, Princeton University, Princeton, New Jersey 08543 (United States)

    2014-08-15T23:59:59.000Z

    A representative H-mode discharge from the National Spherical Torus eXperiment is studied in detail to utilize it as a basis for a time-evolving prediction of the electron temperature profile using an appropriate reduced transport model. The time evolution of characteristic plasma variables such as ?{sub e},??{sub e}{sup ?}, the MHD ? parameter, and the gradient scale lengths of T{sub e}, T{sub i}, and n{sub e} were examined as a prelude to performing linear gyrokinetic calculations to determine the fastest growing micro instability at various times and locations throughout the discharge. The inferences from the parameter evolutions and the linear stability calculations were consistent. Early in the discharge, when ?{sub e} and ?{sub e}{sup ?} were relatively low, ballooning parity modes were dominant. As time progressed and both ?{sub e} and ?{sub e}{sup ?} increased, microtearing became the dominant low-k{sub ?} mode, especially in the outer half of the plasma. There are instances in time and radius, however, where other modes, at higher-k{sub ?}, may, in addition to microtearing, be important for driving electron transport. Given these results, the Rebut-Lallia-Watkins (RLW) electron thermal diffusivity model, which is based on microtearing-induced transport, was used to predict the time-evolving electron temperature across most of the profile. The results indicate that RLW does a good job of predicting T{sub e} for times and locations where microtearing was determined to be important, but not as well when microtearing was predicted to be stable or subdominant.

  10. Predicting bid prices in construction projects using non-parametric statistical models

    E-Print Network [OSTI]

    Pawar, Roshan

    2009-05-15T23:59:59.000Z

    of Department, David Rosowsky August 2007 Major Subject: Civil Engineering iii ABSTRACT Predicting Bid Prices in Construction Projects Using Non-parametric Statistical Models. (August 2007) Roshan Pawar, B.E., University of Mumbai Chair... neural networks. v DEDICATION Dedicated to my parents Suresh and Sharayu Pawar and brother Abhishek Pawar. vi ACKNOWLEDGEMENTS I would like to thank the committee chair Dr. Seth Guikema for providing his assistance...

  11. PREV'AIR, a modeling platform for the air quality predictability study , C. Honor2

    E-Print Network [OSTI]

    Menut, Laurent

    PREV'AIR, a modeling platform for the air quality predictability study Menut L.1 , C. Honoré2 , L Ministère de l'écologie et du développement durable, Paris, France This platform is proposed by the PREV'AIR about PREV'AIR ? please send an e-mail to cecile.honore@ineris.fr 1. Introduction Since 2002, the PREV'AIR

  12. Modeling of diffusive mass transport in micropores in cement based materials

    SciTech Connect (OSTI)

    Yamaguchi, Tetsuji, E-mail: yamaguchi.tetsuji@jaea.go.j [Japan Atomic Energy Agency, Shirakata, Tokai, Ibaraki 319-1195 (Japan); Negishi, Kumi [Japan Atomic Energy Agency, Shirakata, Tokai, Ibaraki 319-1195 (Japan); Taiheiyo Consultant Company Limited, 2-4-2, Osaku, Sakura, Chiba 285-8655 (Japan); Hoshino, Seiichi; Tanaka, Tadao [Japan Atomic Energy Agency, Shirakata, Tokai, Ibaraki 319-1195 (Japan)

    2009-12-15T23:59:59.000Z

    In order to predict long-term leaching behavior of cement constituents for safety assessments of radioactive waste disposal, we modeled diffusive mass transport in micropores in cement based materials. Based on available knowledge on the pore structure, we developed a transport porosity model that enables us to estimate effective porosity available for diffusion (transport porosity) in cement based materials. We microscopically examined the pore structure of hardened cement pastes to partially verify the model. Effective diffusivities of tritiated water in hardened cement pastes were also obtained experimentally, and were shown to be proportional to the estimated transport porosity.

  13. Predictive Reactor Pressure Vessel Steel Irradiation Embrittlement Models: Issues and Opportunities

    SciTech Connect (OSTI)

    Odette, George Robert [UCSB; Nanstad, Randy K [ORNL

    2009-01-01T23:59:59.000Z

    Nuclear plant life extension to 80 years will require accurate predictions of neutron irradiation-induced increases in the ductile-brittle transition temperature ( T) of reactor pressure vessel (RPV) steels at high fluence conditions that are far outside the existing database. Remarkable progress in mechanistic understanding of irradiation embrittlement has led to physically motivated T correlation models that provide excellent statistical fi ts to the existing surveillance database. However, an important challenge is developing advanced embrittlement models for low fl ux-high fl uence conditions pertinent to extended life. These new models must also provide better treatment of key variables and variable combinations and account for possible delayed formation of late blooming phases in low copper steels. Other issues include uncertainties in the compositions of actual vessel steels, methods to predict T attenuation away from the reactor core, verifi cation of the master curve method to directly measure the fracture toughness with small specimens and predicting T for vessel annealing remediation and re-irradiation cycles.

  14. 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.

    1983-04-01T23:59:59.000Z

    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.

  15. A model for predicting the evolution of damage in the plastic bonded explosive LX17

    E-Print Network [OSTI]

    Seidel, Gary Don

    2002-01-01T23:59:59.000Z

    . Of particular interest, Chan et al. (1997a, 1997b) observed grain boundary fracture in argillaceous salt. Along the same lines, Helms et al. (1999) employed the Tvergaard (1990) cohesive zone model in an implicit finite element code to predict grain boundary... implemented into a finite element code. The model, developed in part by Yoon and Allen (1999) and Allen and Searcy (2000, 2001a, 2001b), will use material parameters for the plastic bonded explosive LX17 in order to compare computational results...

  16. Phenomenological Model for Predicting the Energy Resolution of Neutron-Damaged Coaxial HPGe Detectors

    SciTech Connect (OSTI)

    C. DeW. Van Siclen; E. H. Seabury; C. J. Wharton; A. J. Caffrey

    2012-10-01T23:59:59.000Z

    The peak energy resolution of germanium detectors deteriorates with increasing neutron fluence. This is due to hole capture at neutron-created defects in the crystal which prevents the full energy of the gamma-ray from being recorded by the detector. A phenomenological model of coaxial HPGe detectors is developed that relies on a single, dimensionless parameter that is related to the probability for immediate trapping of a mobile hole in the damaged crystal. As this trap parameter is independent of detector dimensions and type, the model is useful for predicting energy resolution as a function of neutron fluence.

  17. NEAR FIELD MODELING OF SPE1 EXPERIMENT AND PREDICTION OF THE SECOND SOURCE PHYSICS EXPERIMENTS (SPE2)

    SciTech Connect (OSTI)

    Antoun, T; Xu, H; Vorobiev, O; Lomov, I

    2011-10-20T23:59:59.000Z

    Motion along joints and fractures in the rock has been proposed as one of the sources of near-source shear wave generation, and demonstrating the validity of this hypothesis is a focal scientific objective of the source physics experimental campaign in the Climax Stock granitic outcrop. A modeling effort has been undertaken by LLNL to complement the experimental campaign, and over the long term provide a validated computation capability for the nuclear explosion monitoring community. The approach involves performing the near-field nonlinear modeling with hydrodynamic codes (e.g., GEODYN, GEODYN-L), and the far-field seismic propagation with an elastic wave propagation code (e.g., WPP). the codes will be coupled together to provide a comprehensive source-to-sensor modeling capability. The technical approach involves pre-test predictions of each of the SPE experiments using their state of the art modeling capabilities, followed by code improvements to alleviate deficiencies identified in the pre-test predictions. This spiral development cycle wherein simulations are used to guide experimental design and the data from the experiment used to improve the models is the most effective approach to enable a transition from the descriptive phenomenological models in current use to the predictive, hybrid physics models needed for a science-based modeling capability for nuclear explosion monitoring. The objective of this report is to describe initial results of non-linear motion predictions of the first two SPE shots in the Climax Stock: a 220-lb shot at a depth of 180 ft (SPE No.1), and a 2570-lb shot at a depth of 150 ft (SPE No.2). The simulations were performed using the LLNL ensemble granite model, a model developed to match velocity and displacement attenuation from HARDHAT, PILE DRIVER, and SHOAL, as well as Russian and French nuclear test data in granitic rocks. This model represents the state of the art modeling capabilities as they existed when the SPE campaign was launched in 2010, and the simulation results presented here will establish a baseline that will be used for gauging progress as planned modeling improvements are implemented during the remainder of the SPE program. The initial simulations were performed under 2D axisymmetric conditions assuming the geologic medium to be a homogeneous half space. However, logging data obtained from the emplacement hole reveal two major faults that intersect the borehole at two different depth intervals (NSTec report, 2011) and four major joint sets. To evaluate the effect of these discrete structures on the wave forms generated they have performed 2D and 3D analysis with a Lagrangian hydrocode, GEODYN-L that shares the same material models with GEODYN but can explicitly take joints and fault into consideration. They discuss results obtained using these two different approaches in this report.

  18. Sensor and model integration for the rapid prediction of concurrent flow flame spread 

    E-Print Network [OSTI]

    Cowlard, Adam

    Fire Safety Engineering is required at every stage in the life cycle of modern-day buildings. Fire safety design, detection and suppression, and emergency response are all vital components of Structural Fire Safety but are usually perceived...Issues of accuracy aside, these models demand heavy resources and computational time periods that are far greater than the time associated with the processes being simulated. To be of use to emergency responders, the output would need to be produced faster than the event itself with lead time to enable planning of an intervention strategy. Therefore in isolation, model output is not robust or fast enough to be implemented in an emergency response scenario. The concept of super-real time predictions steered by measurements is studied in the simple yet meaningful scenario of concurrent flow flame spread. Experiments have been conducted with PMMA slabs to feed sensor data into a simple analytical model. Numerous sensing techniques have been adapted to feed a simple algebraic expression from the literature linking flame spread, flame characteristics and pyrolysis evolution in order to model upward flame spread. The measurements are continuously fed to the computations so that projections of the flame spread velocity and flame characteristics can be established at each instant in time, ahead of the real flame. It was observed that as the input parameters in the analytical models were optimised to the scenario, rapid convergence between the evolving experiment and the predictions was attained....

  19. 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.

    2006-01-01T23:59:59.000Z

    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.

  20. Improving filtering and prediction of spatially extended turbulent systems with model errors through stochastic parameter estimation

    SciTech Connect (OSTI)

    Gershgorin, B. [Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute of Mathematical Sciences, New York University, NY 10012 (United States); Harlim, J. [Department of Mathematics, North Carolina State University, NC 27695 (United States)], E-mail: jharlim@ncsu.edu; Majda, A.J. [Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute of Mathematical Sciences, New York University, NY 10012 (United States)

    2010-01-01T23:59:59.000Z

    The filtering and predictive skill for turbulent signals is often limited by the lack of information about the true dynamics of the system and by our inability to resolve the assumed dynamics with sufficiently high resolution using the current computing power. The standard approach is to use a simple yet rich family of constant parameters to account for model errors through parameterization. This approach can have significant skill by fitting the parameters to some statistical feature of the true signal; however in the context of real-time prediction, such a strategy performs poorly when intermittent transitions to instability occur. Alternatively, we need a set of dynamic parameters. One strategy for estimating parameters on the fly is a stochastic parameter estimation through partial observations of the true signal. In this paper, we extend our newly developed stochastic parameter estimation strategy, the Stochastic Parameterization Extended Kalman Filter (SPEKF), to filtering sparsely observed spatially extended turbulent systems which exhibit abrupt stability transition from time to time despite a stable average behavior. For our primary numerical example, we consider a turbulent system of externally forced barotropic Rossby waves with instability introduced through intermittent negative damping. We find high filtering skill of SPEKF applied to this toy model even in the case of very sparse observations (with only 15 out of the 105 grid points observed) and with unspecified external forcing and damping. Additive and multiplicative bias corrections are used to learn the unknown features of the true dynamics from observations. We also present a comprehensive study of predictive skill in the one-mode context including the robustness toward variation of stochastic parameters, imperfect initial conditions and finite ensemble effect. Furthermore, the proposed stochastic parameter estimation scheme applied to the same spatially extended Rossby wave system demonstrates high predictive skill, comparable with the skill of the perfect model for a duration of many eddy turnover times especially in the unstable regime.

  1. Accuracy Test for Link Prediction in terms of Similarity Index: The Case of WS and BA Models

    E-Print Network [OSTI]

    Ahn, Min-Woo

    2015-01-01T23:59:59.000Z

    Link prediction is a technique that uses the topological information in a given network to infer the missing links in it. Since past research on link prediction has primarily focused on enhancing performance for given empirical systems, negligible attention has been devoted to link prediction with regard to network models. In this paper, we thus apply link prediction to two network models: The Watts-Strogatz (WS) model and Barab\\'asi-Albert (BA) model. We attempt to gain a better understanding of the relation between accuracy and each network parameter (mean degree, the number of nodes and the rewiring probability in the WS model) through network models. Six similarity indices are used, with precision and area under the ROC curve (AUC) value as the accuracy metrics. We observe a positive correlation between mean degree and accuracy, and size independence of the AUC value.

  2. Machine Learning Based Online Performance Prediction for Runtime Parallelization and Task Scheduling

    SciTech Connect (OSTI)

    Li, J; Ma, X; Singh, K; Schulz, M; de Supinski, B R; McKee, S A

    2008-10-09T23:59:59.000Z

    With the emerging many-core paradigm, parallel programming must extend beyond its traditional realm of scientific applications. Converting existing sequential applications as well as developing next-generation software requires assistance from hardware, compilers and runtime systems to exploit parallelism transparently within applications. These systems must decompose applications into tasks that can be executed in parallel and then schedule those tasks to minimize load imbalance. However, many systems lack a priori knowledge about the execution time of all tasks to perform effective load balancing with low scheduling overhead. In this paper, we approach this fundamental problem using machine learning techniques first to generate performance models for all tasks and then applying those models to perform automatic performance prediction across program executions. We also extend an existing scheduling algorithm to use generated task cost estimates for online task partitioning and scheduling. We implement the above techniques in the pR framework, which transparently parallelizes scripts in the popular R language, and evaluate their performance and overhead with both a real-world application and a large number of synthetic representative test scripts. Our experimental results show that our proposed approach significantly improves task partitioning and scheduling, with maximum improvements of 21.8%, 40.3% and 22.1% and average improvements of 15.9%, 16.9% and 4.2% for LMM (a real R application) and synthetic test cases with independent and dependent tasks, respectively.

  3. Predicting the Frequency of Water Quality Standard Violations Using Bayesian Calibration of Eutrophication Models

    E-Print Network [OSTI]

    Arhonditsis, George B.

    of Eutrophication Models Weitao Zhang1 and George B. Arhonditsis1, 2,* 1Department of Geography University using three synthetic datasets that represent oligo-, meso- and eutrophic lake conditions. Scientific in the Laurentian Great Lakes region. INDEX WORDS: Environmental management, process-based models, eutrophication

  4. OFS model-based adaptive control for block-oriented non-linear Systems

    E-Print Network [OSTI]

    Cambridge, University of

    ) and a heavy oil distillation column (Zhang et al., 2004b). Meanwhile, he has also made some theoretical processes such as distillation, pH neutralization control, hydro-control and chemical reactions linear model predictive control (MPC) based on a Laguerre series and successfully applied the scheme to p

  5. A Multicompartment LiverBased Pharmacokinetic Model for Benzene and Its Metabolites in Mice

    E-Print Network [OSTI]

    extrapolated to predict in vivo data for benzene metabolism and dosimetry. 1 Introduction and Problem in a variety of blood and bone marrow disorders in both humans and laboratory animals [9, 18]. IncreasedA Multicompartment Liver­Based Pharmacokinetic Model for Benzene and Its Metabolites in Mice Cammey

  6. A Multicompartment Liver-Based Pharmacokinetic Model for Benzene and Its Metabolites in Mice

    E-Print Network [OSTI]

    extrapolated to predict in vivo data for benzene metabolism and dosimetry. 1 Introduction and Problem in a variety of blood and bone marrow disorders in both humans and laboratory animals [9, 18]. IncreasedA Multicompartment Liver-Based Pharmacokinetic Model for Benzene and Its Metabolites in Mice Cammey

  7. The Microwave Thermal Emission from the Zodiacal Dust Cloud Predicted with Contemporary Meteoroid Models

    E-Print Network [OSTI]

    Dikarev, Valery V

    2015-01-01T23:59:59.000Z

    Predictions of the microwave thermal emission from the interplanetary dust cloud are made using several contemporary meteoroid models to construct the distributions of cross-section area of dust in space, and applying the Mie light-scattering theory to estimate the temperatures and emissivities of dust particles in broad size and heliocentric distance ranges. In particular, the model of the interplanetary dust cloud by Kelsall et al. (1998, ApJ 508: 44-73), the five populations of interplanetary meteoroids of Divine (1993, JGR 98(E9): 17,029-17,048) and the Interplanetary Meteoroid Engineering Model (IMEM) by Dikarev et al. (2004, EMP 95: 109-122) are used in combination with the optical properties of olivine, carbonaceous and iron spherical particles. The Kelsall model has been widely accepted by the Cosmic Microwave Background (CMB) community. We show, however, that it predicts the microwave emission from interplanetary dust remarkably different from the results of application of the meteoroid engineering m...

  8. 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

    2014-04-23T23:59:59.000Z

    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).

  9. On Model Based Synthesis of Embedded Control Software Vadim Alimguzhin

    E-Print Network [OSTI]

    Tronci, Enrico

    Model Based Design approaches for control software. Given the formal model of a plant as a Discrete Time addresses model based synthesis of control software by trading system level non-functional requirementsOn Model Based Synthesis of Embedded Control Software Vadim Alimguzhin Federico Mari Igor Melatti

  10. Fast and accurate prediction of numerical relativity waveforms from binary black hole mergers using surrogate models

    E-Print Network [OSTI]

    Jonathan Blackman; Scott E. Field; Chad R. Galley; Bela Szilagyi; Mark A. Scheel; Manuel Tiglio; Daniel A. Hemberger

    2015-02-26T23:59:59.000Z

    Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. In this paper, we construct an accurate and fast-to-evaluate surrogate model for numerical relativity (NR) waveforms from non-spinning binary black hole coalescences with mass ratios from $1$ to $10$ and durations corresponding to about $15$ orbits before merger. Our surrogate, which is built using reduced order modeling techniques, is distinct from traditional modeling efforts. We find that the full multi-mode surrogate model agrees with waveforms generated by NR to within the numerical error of the NR code. In particular, we show that our modeling strategy produces surrogates which can correctly predict NR waveforms that were {\\em not} used for the surrogate's training. For all practical purposes, then, the surrogate waveform model is equivalent to the high-accuracy, large-scale simulation waveform but can be evaluated in a millisecond to a second depending on the number of output modes and the sampling rate. Our model includes all spherical-harmonic ${}_{-2}Y_{\\ell m}$ waveform modes that can be resolved by the NR code up to $\\ell=8$, including modes that are typically difficult to model with other approaches. We assess the model's uncertainty, which could be useful in parameter estimation studies seeking to incorporate model error. We anticipate NR surrogate models to be useful for rapid NR waveform generation in multiple-query applications like parameter estimation, template bank construction, and testing the fidelity of other waveform models.

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

    SciTech Connect (OSTI)

    Watney, W.L.

    1994-12-01T23:59:59.000Z

    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.

  12. An Equilibrium-Based Model of Gas Reaction and Detonation

    SciTech Connect (OSTI)

    Trowbridge, L.D.

    2000-04-01T23:59:59.000Z

    During gaseous diffusion plant operations, conditions leading to the formation of flammable gas mixtures may occasionally arise. Currently, these could consist of the evaporative coolant CFC-114 and fluorinating agents such as F2 and ClF3. Replacement of CFC-114 with a non-ozone-depleting substitute is planned. Consequently, in the future, the substitute coolant must also be considered as a potential fuel in flammable gas mixtures. Two questions of practical interest arise: (1) can a particular mixture sustain and propagate a flame if ignited, and (2) what is the maximum pressure that can be generated by the burning (and possibly exploding) gas mixture, should it ignite? Experimental data on these systems, particularly for the newer coolant candidates, are limited. To assist in answering these questions, a mathematical model was developed to serve as a tool for predicting the potential detonation pressures and for estimating the composition limits of flammability for these systems based on empirical correlations between gas mixture thermodynamics and flammability for known systems. The present model uses the thermodynamic equilibrium to determine the reaction endpoint of a reactive gas mixture and uses detonation theory to estimate an upper bound to the pressure that could be generated upon ignition. The model described and documented in this report is an extended version of related models developed in 1992 and 1999.

  13. Model based control of a coke battery

    SciTech Connect (OSTI)

    Stone, P.M.; Srour, J.M.; Zulli, P. [BHP Research, Mulgrave (Australia). Melbourne Labs.; Cunningham, R.; Hockings, K. [BHP Steel, Pt Kembla, New South Wales (Australia). Coal and Coke Technical Development Group

    1997-12-31T23:59:59.000Z

    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.

  14. Model-Based Sampling and Inference

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for On-Highway4,1,50022,3,,,,6,1,9,1,50022,3,,,,6,1,Decade1 Source: Office of Fossil Energy,off)Thousand CubicWellheadModel-Based

  15. A Comparison of Measured Crab and Vela Glitch Healing Parameters with Predictions of Neutron Star Models

    E-Print Network [OSTI]

    Fronefield Crawford; Marek Demianski

    2003-06-11T23:59:59.000Z

    There are currently two well-accepted models that explain how pulsars exhibit glitches, sudden changes in their regular rotational spin-down. According to the starquake model, the glitch healing parameter, Q, which is measurable in some cases from pulsar timing, should be equal to the ratio of the moment of inertia of the superfluid core of a neutron star (NS) to its total moment of inertia. Measured values of the healing parameter from pulsar glitches can therefore be used in combination with realistic NS structure models as one test of the feasibility of the starquake model as a glitch mechanism. We have constructed NS models using seven representative equations of state of superdense matter to test whether starquakes can account for glitches observed in the Crab and Vela pulsars, for which the most extensive and accurate glitch data are available. We also present a compilation of all measured values of Q for Crab and Vela glitches to date which have been separately published in the literature. We have computed the fractional core moment of inertia for stellar models covering a range of NS masses and find that for stable NSs in the realistic mass range 1.4 +/- 0.2 solar masses, the fraction is greater than 0.55 in all cases. This range is not consistent with the observational restriction Q 0.7) are consistent with the starquake model predictions and support previous conclusions that starquakes can be the cause of Crab glitches.

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

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

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

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

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

    Model for the Chemical Interactions between Geothermal Rocks, Supercritical Carbon Dioxide and Water Experiment-Based Model for the Chemical Interactions between...

  18. Discrepancies in the prediction of solar wind using potential field source surface model: An investigation of possible sources

    E-Print Network [OSTI]

    California at Berkeley, University of

    Discrepancies in the prediction of solar wind using potential field source surface model expansion factor (FTE) at the source surface and the solar wind speed (SWS) observed at Earth, which has been made use of in the prediction of solar wind speed near the Earth with reasonable accuracy. However

  19. Journal of Energy and Power Engineering 5 (2011) 554-561 Load Torque Compensator for Model Predictive Direct

    E-Print Network [OSTI]

    Schaltz, Erik

    Predictive Direct Current Control in High Power PMSM Drive Systems M. Preindl1, 2 and E. Schaltz2 1. Power Magnet Synchronous Machine (PMSM), it contains an inner current i.e. torque control loop and an outer for Model Predictive Direct Current Control in High Power PMSM Drive Systems 555 Fig. 1 Block diagram

  20. Evaluation of a case-based Reasoning Energy Prediction Tool for Commercial Buildings

    E-Print Network [OSTI]

    Monfet, D.; Arkhipova, E.; Choiniere, D.

    2013-01-01T23:59:59.000Z

    demand of the building such as whole building energy simulation, regression analysis, and black-box models (e.g., artificial neural networks). In this paper, Case-Based Reasoning (CBR), a machine-learning artificial intelligence technique, is used... area of 5300 m2 (57 050 ft2) and consists of two main sections of roughly equal size: (1) offices and conference rooms and (2) testing laboratories. The HVAC equipment consists of seven air handling units served by an air cooled chiller, ice...

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

    DOE Patents [OSTI]

    Pao, Hsueh-Yuan (San Jose, CA); Dvorak, Steven L. (Tucson, AZ)

    2010-09-14T23:59:59.000Z

    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.

  2. Models for the Prediction of Fouling in Crude Oil Pre-Heat Trains

    E-Print Network [OSTI]

    Yeap, B. L.; Wilson, D. I.; Polley, G. T.

    Models for the Prediction of Fouling in Crude Oil Pre-Heat Trains B.L. Yeap D.I. Wilson G.T. PoUey Dept. of Chern. Engng. Dept. of Chern. Engng. ESDU International Ltd University of Cambridge University of Cambridge Fouling has two significant... across a unit. Extended fouling can affect the throughput of the train. The impetus behind exchanger cleaning is often the need to maintain throughput rather than save energy. If we are to be able to consider fouling in the design of crude oil pre...

  3. Development of bias in analytical predictions based on behavior of platforms during hurricanes

    SciTech Connect (OSTI)

    Aggarwal, R.K.; Dolan, D.K.; Cornell, C.A.

    1996-12-31T23:59:59.000Z

    A Joint Industry Project (JIP) was initiated by 13 oil companies and the US Minerals Management Service (MMS), wherein a methodology was developed to use information from observed platform conditions resulting from Andrew and the hurricane hindcast data with capacity, reliability, and Bayesian updating analyses to determine a measure of differences (biases) in the analytical predictions and field observations. The procedures used for structural integrity analysis were also improved as a result of this study. Phase 1 of this project completed in October 1993 defined a global bias factor. A study of foundation behavior was completed following Phase 1 and determined bias factors specific to foundation failure modes. This paper presents the approach followed in the most recent phase of this project in which bias factors specific to jacket and two foundation failure modes (lateral and axial) were developed. This study utilized an updated storm hindcast, improved analysis models, and a more detailed calibration procedure. The three bias factors were developed and were found to differ significantly. The bias factors developed through this study have provided means to further improve procedures used in the assessment of existing platforms. The proper use of these new analytical methodologies and bias factors will produce more appropriate and cost-effective mitigation measures for safe platform operations. The methodology for establishing bias factors developed and proven in these projects is applicable to other offshore regions and production systems with specific environmental, geotechnical, material and structure features.

  4. 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...

  5. Nellis Air Force Base solar array provides model for renewable...

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

    Nellis Air Force Base solar array provides model for renewable projects Nellis Air Force Base solar array provides model for renewable projects March 24, 2010 - 4:58pm Addthis The...

  6. The use of a distributed hydrologic model to predict dynamic landslide susceptibility for a humid basin in Puerto Rico

    E-Print Network [OSTI]

    Kamal, Sameer A. (Sameer Ahmed)

    2009-01-01T23:59:59.000Z

    This thesis describes the use of a distributed hydrology model in conjunction with a Factor of Safety (FS) algorithm to predict dynamic landslide susceptibility for a humid basin in Puerto Rico. The Mameyes basin, located ...

  7. Prediction of continental shelf sediment transport using a theoretical model of the wave-current boundary layer

    E-Print Network [OSTI]

    Goud, Margaret R

    1987-01-01T23:59:59.000Z

    This thesis presents an application of the Grant-Madsen-Glenn bottom boundary layer model (Grant and Madsen, 1979; Glenn and Grant, 1987) to predictions of sediment transport on the continental shelf. The analysis is a ...

  8. Evaluation of the accuracy of the EPA model for BOD5 prediction in various climatic regions of Texas

    E-Print Network [OSTI]

    Koutny, Jessica Leigh

    2000-01-01T23:59:59.000Z

    This project focused on evaluating the effectiveness of the EPA's first-order BOD? removal model for predicting BOD? reductions in residential constructed wetlands. Monthly grab sample data from nine constructed wetlands designed using the EPA BOD5...

  9. Predictions of monthly energy consumption and annual patterns of energy usage for convenience stores by using multiple and nonlinear regression models

    E-Print Network [OSTI]

    Muendej, Krisanee

    2004-11-15T23:59:59.000Z

    Thirty convenience stores in College Station, Texas, have been selected as the samples for an energy consumption prediction. The predicted models assist facility energy managers for making decisions of energy demand/supply plans. The models...

  10. 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

    2014-05-01T23:59:59.000Z

    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.

  11. IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 7, NO. 3, JUNE 1999 319 Model Predictive Satisficing Fuzzy Logic Control

    E-Print Network [OSTI]

    Goodrich, Michael A.

    Logic Control Michael A. Goodrich, Wynn C. Stirling, and Richard L. Frost Abstract-- Model constrained and nonlinear control problems. However, even when a good model is available, it may be necessary employs a fuzzy description of system consequences via model predictions. This controller considers

  12. Gas Metal Arc Welding Process Modeling and Prediction of Weld Microstructure in MIL A46100 Armor-Grade

    E-Print Network [OSTI]

    Grujicic, Mica

    Gas Metal Arc Welding Process Modeling and Prediction of Weld Microstructure in MIL A46100 Armor metal arc welding (GMAW) butt-joining process has been modeled using a two-way fully coupled, transient in the form of heat, and the mechanical material model of the workpiece and the weld is made temperature

  13. Finite Mixture of ARMA-GARCH Model for Stock Price Prediction Him Tang, Kai-Chun Chiu and Lei Xu

    E-Print Network [OSTI]

    Xu, Lei

    Finite Mixture of ARMA-GARCH Model for Stock Price Prediction Him Tang, Kai-Chun Chiu and Lei Xu mixture of autore- gressive generalized autoregressive conditional het- eroscedasticity (AR-GARCH) models to extend the mixture of AR-GARCH model (W.C. Wong, F. Yip and L. Xu, 1998) to the mixture of ARMA- GARCH

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

    SciTech Connect (OSTI)

    Munafò, A., E-mail: munafo@vki.ac.be; Magin, T. E., E-mail: magin@vki.ac.be [Aeronautics and Aerospace Department, von Karman Institute for Fluid Dynamics, 1640 Rhode-Saint-Genèse (Belgium)

    2014-09-15T23:59:59.000Z

    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.

  15. ModelBased Information Integration in a Neuroscience Mediator System

    E-Print Network [OSTI]

    Ludäscher, Bertram

    Model­Based Information Integration in a Neuroscience Mediator System Bertram Lud¨ascher ? Amarnath

  16. Prediction-Based Recovery from Link Outages in On-Board Mobile Communication Networks

    E-Print Network [OSTI]

    Libman, Lavy

    , such as those pro- posed for (and employed in) public transport vehicles, users are connected to a local network transport routes, and their repetitive nature, allows a certain degree of prediction of impending link extension known as Freeze-TCP, we study how the performance of the protocol depends on the outage prediction

  17. Bioenergetics-Based Modeling of Individual PCB Congeners in

    E-Print Network [OSTI]

    McCarty, John P.

    Bioenergetics-Based Modeling of Individual PCB Congeners in Nestling Tree Swallows from Two 14850 A bioenergetics-based model was used to simulate the accumulation of total PCBs and 20 PCB of sediment- associated contaminants to sediment-dwelling organisms. A bioenergetics-based model was developed

  18. Real-time capable first principle based modelling of tokamak turbulent transport

    E-Print Network [OSTI]

    Breton, S; Felici, F; Imbeaux, F; Aniel, T; Artaud, J F; Baiocchi, B; Bourdelle, C; Camenen, Y; Garcia, J

    2015-01-01T23:59:59.000Z

    A real-time capable core turbulence tokamak transport model is developed. This model is constructed from the regularized nonlinear regression of quasilinear gyrokinetic transport code output. The regression is performed with a multilayer perceptron neural network. The transport code input for the neural network training set consists of five dimensions, and is limited to adiabatic electrons. The neural network model successfully reproduces transport fluxes predicted by the original quasilinear model, while gaining five orders of magnitude in computation time. The model is implemented in a real-time capable tokamak simulator, and simulates a 300s ITER discharge in 10s. This proof-of-principle for regression based transport models anticipates a significant widening of input space dimensionality and physics realism for future training sets. This aims to provide unprecedented computational speed coupled with first-principle based physics for real-time control and integrated modelling applications.

  19. A Predictive Maintenance Policy Based on the Blade of Offshore Wind Wenjin Zhu, Troyes University of Technology

    E-Print Network [OSTI]

    McCalley, James D.

    A Predictive Maintenance Policy Based on the Blade of Offshore Wind Turbine Wenjin Zhu, Troyes onshore to offshore locations [1]. As offshore wind turbines are located at remote sites withlimited]. Operation and maintenance (O&M) costs of off-shore wind turbines contribute about 25-30% to the total energy

  20. Interface modeling to predict well casing damage for big hill strategic petroleum reserve.

    SciTech Connect (OSTI)

    Ehgartner, Brian L.; Park, Byoung Yoon

    2012-02-01T23:59:59.000Z

    Oil leaks were found in well casings of Caverns 105 and 109 at the Big Hill Strategic Petroleum Reserve site. According to the field observations, two instances of casing damage occurred at the depth of the interface between the caprock and top of salt. This damage could be caused by interface movement induced by cavern volume closure due to salt creep. A three dimensional finite element model, which allows each cavern to be configured individually, was constructed to investigate shear and vertical displacements across each interface. The model contains interfaces between each lithology and a shear zone to examine the interface behavior in a realistic manner. This analysis results indicate that the casings of Caverns 105 and 109 failed by shear stress that exceeded shear strength due to the horizontal movement of the top of salt relative to the caprock, and tensile stress due to the downward movement of the top of salt from the caprock, respectively. The casings of Caverns 101, 110, 111 and 114, located at the far ends of the field, are predicted to be failed by shear stress in the near future. The casings of inmost Caverns 107 and 108 are predicted to be failed by tensile stress in the near future.

  1. Predicting the future of forests in the Mediterranean under climate change, with niche-and process-based

    E-Print Network [OSTI]

    Keenan, Trevor

    Predicting the future of forests in the Mediterranean under climate change, with niche- and process important future climatic changes are expected. Here, we assess and compare two commonly used modeling, 2004), and the potential response of these distributions to future climatic change (e.g. Thomas et al

  2. Development of a cell-based stream flow routing model 

    E-Print Network [OSTI]

    Raina, Rajeev

    2005-08-29T23:59:59.000Z

    This study presents the development of a cell-based routing model. The model developed is a two parameter hydrological routing model that uses a coarse resolution stream network to route runoff from each cell in the watershed ...

  3. A market-power based model of business groups

    E-Print Network [OSTI]

    Feenstra, Robert C; Huang, D S; Hamilton, G G

    2003-01-01T23:59:59.000Z

    complicated. In our model, business groups not only sellof Indian groups. 3. A Model of Business Groups We willa market-power based model of business groups. This We

  4. Stress-induced patterns in ion-irradiated Silicon: a model based on anisotropic plastic flow

    E-Print Network [OSTI]

    Scott A. Norris

    2012-07-24T23:59:59.000Z

    We present a model for the effect of stress on thin amorphous films that develop atop ion-irradiated silicon, based on the mechanism of ion-induced anisotropic plastic flow. Using only parameters directly measured or known to high accuracy, the model exhibits remarkably good agreement with the wavelengths of experimentally-observed patterns, and agrees qualitatively with limited data on ripple propagation speed. The predictions of the model are discussed in the context of other mechanisms recently theorized to explain the wavelengths, including extensive comparison with an alternate model of stress.

  5. Predicting Fate and Transport of Contaminants in the Vadose Zone using a Soil Screening Model

    SciTech Connect (OSTI)

    Rucker, G.

    2002-08-14T23:59:59.000Z

    Soil Screening Levels (SSLs) are threshold concentrations below which there is no concern for the migration of residual soil contaminants to the aquifer above maximum contaminant levels (MCLs). At sites where contaminant concentrations exceed SSLs, further study maybe warranted under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA). SSLs are based upon simplified fate and transport assumptions, but the guidance allows the flexibility to develop a detailed modeling approach that accounts for complex site variables such as degradation and thickness of the vadose zone. The distinct advantage of the detailed modeling is that individual sites may calculate a less restrictive, but still protective SSL. A Multi-Layer Vadose Zone Contaminant Migration Model [VZCOMML(C)] was developed at the Savannah River Site to allay the higher costs of detailed modeling and achieve a higher clean-up level. The software model is faster, simpler, and less expensive to us e than other commercially available codes.

  6. A finite difference model for predicting sediment oxygen demand in streams 

    E-Print Network [OSTI]

    Charbonnet, Danielle Andrea

    2003-01-01T23:59:59.000Z

    in the representative river system using benthic chambers. A finite difference model was developed based on Fick's Law of Diffusion. Mass transfer principles are used to perform a mass balance on the oxygen concentrations in the sediment in order to determine SOD...

  7. Predicting the steady state thickness of passive films with the Point Defect Model in fretting corrosion experiments

    E-Print Network [OSTI]

    Geringer, Jean; Taylor, Mathew L

    2013-01-01T23:59:59.000Z

    Some implants have approximately a lifetime of 15 years. The femoral stem, for example, should be made of 316L/316LN stainless steel. Fretting corrosion, friction under small displacements, should occur during human gait, due to repeated loadings and un-loadings, between stainless steel and bone for instance. Some experimental investigations of fretting corrosion have been practiced. As well known, metallic alloys and especially stainless steels are covered with a passive film that prevents from the corrosion and degradation. This passive layer of few nanometers, at ambient temperature, is the key of our civilization according to some authors. This work is dedicated to predict the passive layer thicknesses of stainless steel under fretting corrosion with a specific emphasis on the role of proteins. The model is based on the Point Defect Model (micro scale) and an update of the model on the friction process (micro-macro scale). Genetic algorithm was used for finding solution of the problem. The major results a...

  8. Prediction of buried mine-like target radar signatures using wideband electromagnetic modeling

    SciTech Connect (OSTI)

    Warrick, A.L.; Azevedo, S.G.; Mast, J.E.

    1998-04-06T23:59:59.000Z

    Current ground penetrating radars (GPR) have been tested for land mine detection, but they have generally been costly and have poor performance. Comprehensive modeling and experimentation must be done to predict the electromagnetic (EM) signatures of mines to access the effect of clutter on the EM signature of the mine, and to understand the merit and limitations of using radar for various mine detection scenarios. This modeling can provide a basis for advanced radar design and detection techniques leading to superior performance. Lawrence Livermore National Laboratory (LLNL) has developed a radar technology that when combined with comprehensive modeling and detection methodologies could be the basis of an advanced mine detection system. Micropower Impulse Radar (MIR) technology exhibits a combination of properties, including wideband operation, extremely low power consumption, extremely small size and low cost, array configurability, and noise encoded pulse generation. LLNL is in the process of developing an optimal processing algorithm to use with the MIR sensor. In this paper, we use classical numerical models to obtain the signature of mine-like targets and examine the effect of surface roughness on the reconstructed signals. These results are then qualitatively compared to experimental data.

  9. Seismic transient deconvolution with model-based signal processing

    SciTech Connect (OSTI)

    Tague, J.A.; Schutz, K.D. [Ohio Univ., Athens, OH (United States). Dept. of Electrical and Computer Engineering] [Ohio Univ., Athens, OH (United States). Dept. of Electrical and Computer Engineering

    1997-07-01T23:59:59.000Z

    Short duration seismic disturbances, obscured by earth noise and distorted by the seismometers used to measure them, can be reconstructed using model-based signal processing. Model based means that mathematical models of the seismic transient, earth noise, and seismometer dynamics are infused into the signal processor that estimates the disturbance. The processor imposes no predetermined structure on the transient and the earth noise need not be white. Model-based processors produce good quality estimates for a broad class of transient waveforms.

  10. 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

    2012-10-01T23:59:59.000Z

    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.

  11. 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.

    2013-01-01T23:59:59.000Z

    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.

  12. 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, E-mail: zhangp@mskcc.org [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Yorke, Ellen; Hu, Yu-Chi; Mageras, Gig [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Rimner, Andreas [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Deasy, Joseph O. [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States)

    2014-02-01T23:59:59.000Z

    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.

  13. Modeling Cortical Plasticity Based on Adapting Lateral Interaction

    E-Print Network [OSTI]

    A neural network model called LISSOM for the cooperative self-organization of afferent and lateral connections in cortical maps is applied to modeling cortical plasticity. After self-organization, the LISSOM maps are in a dynamic equilibrium with the input, and reorganize like the cortex in response to simulated cortical lesions and intracortical microstimulation. The model predicts that adapting lateral interactions are fundamental to cortical reorganization, and suggests techniques to hasten recovery following sensory cortical surgery.

  14. Predictive Modelling of Toxicity Resulting from Radiotherapy Treatments of Head and Neck Cancer

    E-Print Network [OSTI]

    Dean, Jamie A; Harrington, Kevin J; Nutting, Christopher M; Gulliford, Sarah L

    2014-01-01T23:59:59.000Z

    In radiotherapy for head and neck cancer, the radiation dose delivered to the pharyngeal mucosa (mucosal lining of the throat) is thought to be a major contributing factor to dysphagia (swallowing dysfunction), the most commonly reported severe toxicity. There is a variation in the severity of dysphagia experienced by patients. Understanding the role of the dose distribution in dysphagia would allow improvements in the radiotherapy technique to be explored. The 3D dose distributions delivered to the pharyngeal mucosa of 249 patients treated as part of clinical trials were reconstructed. Pydicom was used to extract DICOM (digital imaging and communications in medicine) data (the standard file formats for medical imaging and radiotherapy data). NumPy and SciPy were used to manipulate the data to generate 3D maps of the dose distribution delivered to the pharyngeal mucosa and calculate metrics describing the dose distribution. Multivariate predictive modelling of severe dysphagia, including descriptions of the d...

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

    SciTech Connect (OSTI)

    Watney, W.L.

    1992-01-01T23:59:59.000Z

    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.

  16. Prediction Space Weather Using an Asymmetric Cone Model for Halo CMEs

    E-Print Network [OSTI]

    G. Michalek; N. Gopalswamy; S. Yashiro

    2007-10-24T23:59:59.000Z

    Halo coronal mass ejections (HCMEs) are responsible of the most severe geomagnetic storms. A prediction of their geoeffectiveness and travel time to Earth's vicinity is crucial to forecast space weather. Unfortunately coronagraphic observations are subjected to projection effects and do not provide true characteristics of CMEs. Recently, Michalek (2006, {\\it Solar Phys.}, {\\bf237}, 101) developed an asymmetric cone model to obtain the space speed, width and source location of HCMEs. We applied this technique to obtain the parameters of all front-sided HCMEs observed by the SOHO/LASCO experiment during a period from the beginning of 2001 until the end of 2002 (solar cycle 23). These parameters were applied for the space weather forecast. Our study determined that the space speeds are strongly correlated with the travel times of HCMEs within Earth's vicinity and with the magnitudes related to geomagnetic disturbances.

  17. Comparison of Chiller Models for Use in Model-Based Fault Detection

    E-Print Network [OSTI]

    Sreedhara, P.; Haves, P.

    2001-01-01T23:59:59.000Z

    , 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...

  18. 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.

    2014-06-01T23:59:59.000Z

    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.

  19. Supporting technology for enhanced oil recovery: CO/sub 2/ miscible flood predictive model

    SciTech Connect (OSTI)

    Ray, R.M.; Munoz, J.D.

    1986-12-01T23:59:59.000Z

    The CO/sub 2/ Miscible Flood Predictive Model (CO2PM) was developed by Scientific Software-Intercomp for the US Department of Energy and was used in the National Petroleum Council's (NPC) 1984 survey of US enhanced oil recovery potential (NPC, 1984). The CO2PM is applicable to both secondary (mobile oil) and tertiary (residual oil) floods, and to either continuous CO/sub 2/ injection or water-alternating-gas (WAG) processes. In the CO2PM, an oil rate versus time function for a single pattern is computed, the results of which are passed to the economic calculations. To estimate multi-pattern project behavior a pattern development schedule is required. After-tax cash flow is computed by combining revenues with costs for drilling, conversion and well workovers, CO/sub 2/ compression and recycle, fixed and variable operating costs, water treating and disposal costs, depreciation, royalties, severance, state, federal and windfall profit taxes, cost and price inflation rates, and the discount rate. A lumped parameter uncertainty model is used to estimate risk, allowing for variation in computed project performance within an 80% confidence interval. The CO2PM is a three-dimensional (layered, five-spot), two-phase (aqueous and oleic), three component (oil, water, and CO/sub 2/) model. It computes oil and CO/sub 2/ breakthrough and recovery from fractional theory modified for the effects of viscous fingering, areal sweep, vertical heterogeneity and gravity segregation. 23 refs., 19 figs., 57 tabs.

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

    SciTech Connect (OSTI)

    Duffy, Stephen

    2013-09-09T23:59:59.000Z

    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.