Sample records for model based predictive

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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...

  6. PREDICTIVE MODELS

    SciTech Connect (OSTI)

    Ray, R.M. (DOE Bartlesville Energy Technology Center, Bartlesville, OK (United States))

    1988-10-01T23:59:59.000Z

    PREDICTIVE MODELS is a collection of five models - CFPM, CO2PM, ICPM, PFPM, and SFPM - used in the 1982-1984 National Petroleum Council study of enhanced oil recovery (EOR) potential. Each pertains to a specific EOR process designed to squeeze additional oil from aging or spent oil fields. The processes are: 1) chemical flooding; 2) carbon dioxide miscible flooding; 3) in-situ combustion; 4) polymer flooding; and 5) steamflood. CFPM, the Chemical Flood Predictive Model, models micellar (surfactant)-polymer floods in reservoirs, which have been previously waterflooded to residual oil saturation. Thus, only true tertiary floods are considered. An option allows a rough estimate of oil recovery by caustic or caustic-polymer processes. CO2PM, the Carbon Dioxide miscible flooding Predictive Model, is applicable to both secondary (mobile oil) and tertiary (residual oil) floods, and to either continuous CO2 injection or water-alternating gas processes. ICPM, the In-situ Combustion Predictive Model, computes the recovery and profitability of an in-situ combustion project from generalized performance predictive algorithms. PFPM, the Polymer Flood Predictive Model, is switch-selectable for either polymer or waterflooding, and an option allows the calculation of the incremental oil recovery and economics of polymer relative to waterflooding. SFPM, the Steamflood Predictive Model, is applicable to the steam drive process, but not to cyclic steam injection (steam soak) processes. The IBM PC/AT version includes a plotting capability to produces a graphic picture of the predictive model results.

  7. 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

  8. 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 [

  9. PREDICTIVE MODELS

    SciTech Connect (OSTI)

    Ray, R.M. (DOE Bartlesville Energy Technology Technology Center, Bartlesville, OK (United States))

    1986-12-01T23:59:59.000Z

    PREDICTIVE MODELS is a collection of five models - CFPM, CO2PM, ICPM, PFPM, and SFPM - used in the 1982-1984 National Petroleum Council study of enhanced oil recovery (EOR) potential. Each pertains to a specific EOR process designed to squeeze additional oil from aging or spent oil fields. The processes are: 1) chemical flooding, where soap-like surfactants are injected into the reservoir to wash out the oil; 2) carbon dioxide miscible flooding, where carbon dioxide mixes with the lighter hydrocarbons making the oil easier to displace; 3) in-situ combustion, which uses the heat from burning some of the underground oil to thin the product; 4) polymer flooding, where thick, cohesive material is pumped into a reservoir to push the oil through the underground rock; and 5) steamflood, where pressurized steam is injected underground to thin the oil. CFPM, the Chemical Flood Predictive Model, models micellar (surfactant)-polymer floods in reservoirs, which have been previously waterflooded to residual oil saturation. Thus, only true tertiary floods are considered. An option allows a rough estimate of oil recovery by caustic or caustic-polymer processes. CO2PM, the Carbon Dioxide miscible flooding Predictive Model, is applicable to both secondary (mobile oil) and tertiary (residual oil) floods, and to either continuous CO2 injection or water-alternating gas processes. ICPM, the In-situ Combustion Predictive Model, computes the recovery and profitability of an in-situ combustion project from generalized performance predictive algorithms. PFPM, the Polymer Flood Predictive Model, is switch-selectable for either polymer or waterflooding, and an option allows the calculation of the incremental oil recovery and economics of polymer relative to waterflooding. SFPM, the Steamflood Predictive Model, is applicable to the steam drive process, but not to cyclic steam injection (steam soak) processes.

  10. 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

  11. Validated Model-Based Performance Prediction of Multi-Core Software Routers

    E-Print Network [OSTI]

    Carle, Georg

    Terms--measurement, simulation, intra-node model, re- source contention, model validation, software components. Leveraged by high flexibility and low costs of software developments in comparison with hardwareValidated Model-Based Performance Prediction of Multi-Core Software Routers Torsten Meyer1

  12. Water Research 38 (2004) 33313339 Testing a surface tension-based model to predict the salting

    E-Print Network [OSTI]

    Herbert, Bruce

    Water Research 38 (2004) 3331­3339 Testing a surface tension-based model to predict the salting out associated with transferring solutes from water to a salt solution to the difference in surface tensions likely reflects the inability of the simple surface tension model to account for all interactions among

  13. 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.

  14. 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 where diesel gener- ator sets (a diesel engine connected to a generator) produce electrical power, which Email: torstein.bo@itk.ntnu.no, tor.arne.johansen@itk.ntnu.no Abstract--Diesel-electric propulsion

  15. MRI based diffusion and perfusion predictive model to estimate stroke Stephen E. Rosea,

    E-Print Network [OSTI]

    McLachlan, Geoff

    MRI based diffusion and perfusion predictive model to estimate stroke evolution Stephen E. Rosea and perfusion images acquired in the acute stage of stroke. The validity of this methodology was tested on novel patient data including data acquired from an independent stroke clinic. Regions-of-interest (ROIs

  16. Predictive Modeling of Mercury Speciation in Combustion Flue Gases Using GMDH-Based Abductive Networks

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    to develop. The use of modern data-based machine learning techniques has been recently introduced, including and boiler operating conditions. Prediction performance compares favourably with neural network models for future work to further improve performance. Index Terms: Mercury speciation, Flue gases, Boiler emissions

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

    E-Print Network [OSTI]

    tethered to the ground at a high velocity across the wind direction. Power can be generated by a, the first option is considered. Because it involves a much lighter structure, a major advantage of powerControl of Airborne Wind Energy Systems Based on Nonlinear Model Predictive Control & Moving

  18. Towards QoS Prediction Based on Composition Structure Analysis and Probabilistic Environment Models

    E-Print Network [OSTI]

    Politécnica de Madrid, Universidad

    Towards QoS Prediction Based on Composition Structure Analysis and Probabilistic Environment Models Dragan Ivanovi´c Universidad Polit´ecnica de Madrid idragan@clip.dia.fi.upm.es Peerachai Kaowichakorn Universidad Polit´ecnica de Madrid p.kaowichakorn@gmail.com Manuel Carro Universidad Polit´ecnica de Madrid

  19. 2014Science About the cover: A new transcriptomics-based model accurately predicts how much

    E-Print Network [OSTI]

    2014Science Frontiers #12;About the cover: A new transcriptomics-based model accurately predicts's Environmental Molecular Sciences Laboratory: Making Isoprene from Biomass Material Using Bacillus Species. Pacific Northwest National Laboratory (PNNL) is a U.S. Department of Energy (DOE), Office of Science

  20. 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.

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

    E-Print Network [OSTI]

    Qin, Xiao

    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 different machines to estimate the real-time energy consumption. The results show our model can get better

  2. 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

  3. 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.

  4. 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...

  5. 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.

  6. A data-based approach for multivariate model predictive control performance monitoring$

    E-Print Network [OSTI]

    Chen, Sheng

    of the proposed methodology is demonstrated in a case study of the Wood­Berry distillation column system. & 2010 model predictive control (MPC) controller, which systematically integrates both the assessment'' user-predefined one, this method can properly evaluate the performance of an MPC controller

  7. 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 wind power capacities are likely to take place offshore. As for onshore wind parks, short-term wind of offshore farms and their secure integration to the grid. Modeling the behavior of large wind farms

  8. 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.

  9. 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.

  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 demanding nonlinear and strongly interactive process application. A Model-on-Demand Model Predictive Control (MoD-MPC

  11. Prediction of PWSCC in nickel base alloys using crack growth rate models

    SciTech Connect (OSTI)

    Thompson, C.D.; Krasodomski, H.T.; Lewis, N.; Makar, G.L. [Knolls Atomic Power Lab., Schenectady, NY (United States)

    1995-12-31T23:59:59.000Z

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

  12. 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 ...

  13. 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.

  14. A lightning summary and decision model for thunderstorm prediction at Whiteman Air Force Base, Missouri

    E-Print Network [OSTI]

    Bass, Randall Gerald

    1996-01-01T23:59:59.000Z

    A cloud-to-ground lightning summary was developed for a 139xl85 kilometer area centered at Whiteman Air Force Base. Spatial and temporal patterns, and first stroke peak currents were analyzed from 1989-1995. Stability indices were examined...

  15. 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

  16. 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.

  17. PREDICTIVE MODELS. Enhanced Oil Recovery Model

    SciTech Connect (OSTI)

    Ray, R.M. [DOE Bartlesville Energy Technology Center, Bartlesville, OK (United States)

    1992-02-26T23:59:59.000Z

    PREDICTIVE MODELS is a collection of five models - CFPM, CO2PM, ICPM, PFPM, and SFPM - used in the 1982-1984 National Petroleum Council study of enhanced oil recovery (EOR) potential. Each pertains to a specific EOR process designed to squeeze additional oil from aging or spent oil fields. The processes are: 1 chemical flooding; 2 carbon dioxide miscible flooding; 3 in-situ combustion; 4 polymer flooding; and 5 steamflood. CFPM, the Chemical Flood Predictive Model, models micellar (surfactant)-polymer floods in reservoirs, which have been previously waterflooded to residual oil saturation. Thus, only true tertiary floods are considered. An option allows a rough estimate of oil recovery by caustic or caustic-polymer processes. CO2PM, the Carbon Dioxide miscible flooding Predictive Model, is applicable to both secondary (mobile oil) and tertiary (residual oil) floods, and to either continuous CO2 injection or water-alternating gas processes. ICPM, the In-situ Combustion Predictive Model, computes the recovery and profitability of an in-situ combustion project from generalized performance predictive algorithms. PFPM, the Polymer Flood Predictive Model, is switch-selectable for either polymer or waterflooding, and an option allows the calculation of the incremental oil recovery and economics of polymer relative to waterflooding. SFPM, the Steamflood Predictive Model, is applicable to the steam drive process, but not to cyclic steam injection (steam soak) processes. The IBM PC/AT version includes a plotting capability to produces a graphic picture of the predictive model results.

  18. 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

  19. PREDICTIVE MODELS. Enhanced Oil Recovery Model

    SciTech Connect (OSTI)

    Ray, R.M. [DOE Bartlesville Energy Technology Technology Center, Bartlesville, OK (United States)

    1992-02-26T23:59:59.000Z

    PREDICTIVE MODELS is a collection of five models - CFPM, CO2PM, ICPM, PFPM, and SFPM - used in the 1982-1984 National Petroleum Council study of enhanced oil recovery (EOR) potential. Each pertains to a specific EOR process designed to squeeze additional oil from aging or spent oil fields. The processes are: 1 chemical flooding, where soap-like surfactants are injected into the reservoir to wash out the oil; 2 carbon dioxide miscible flooding, where carbon dioxide mixes with the lighter hydrocarbons making the oil easier to displace; 3 in-situ combustion, which uses the heat from burning some of the underground oil to thin the product; 4 polymer flooding, where thick, cohesive material is pumped into a reservoir to push the oil through the underground rock; and 5 steamflood, where pressurized steam is injected underground to thin the oil. CFPM, the Chemical Flood Predictive Model, models micellar (surfactant)-polymer floods in reservoirs, which have been previously waterflooded to residual oil saturation. Thus, only true tertiary floods are considered. An option allows a rough estimate of oil recovery by caustic or caustic-polymer processes. CO2PM, the Carbon Dioxide miscible flooding Predictive Model, is applicable to both secondary (mobile oil) and tertiary (residual oil) floods, and to either continuous CO2 injection or water-alternating gas processes. ICPM, the In-situ Combustion Predictive Model, computes the recovery and profitability of an in-situ combustion project from generalized performance predictive algorithms. PFPM, the Polymer Flood Predictive Model, is switch-selectable for either polymer or waterflooding, and an option allows the calculation of the incremental oil recovery and economics of polymer relative to waterflooding. SFPM, the Steamflood Predictive Model, is applicable to the steam drive process, but not to cyclic steam injection (steam soak) processes.

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

    SciTech Connect (OSTI)

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

    1995-02-22T23:59:59.000Z

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

  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. Compatibility of Stand Basal Area Predictions Based on Forecast Combination

    E-Print Network [OSTI]

    Cao, Quang V.

    Compatibility of Stand Basal Area Predictions Based on Forecast Combination Xiongqing Zhang Carr.) in Beijing, forecast combination was used to adjust predicted stand basal areas from these three types of models. The forecast combination method combines information and disperses errors from

  5. 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.

  6. 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

  7. Standard Model Predictions for the Muon $(g-2)/2$

    E-Print Network [OSTI]

    S. I. Eidelman

    2009-04-21T23:59:59.000Z

    The current status of the Standard Model predictions for the muon anomalous magnetic moment is described. Various contributions expected in the Standard Model are discussed. After the reevaluation of the leading-order hadronic term based on the new \\ep data, the theoretical prediction is more than three standard deviations lower than the experimental value.

  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. 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

  10. 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 . . . . . .

  11. 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 ....

  12. 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.

  13. 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

  14. Model accurately predicts directional borehole trajectory

    SciTech Connect (OSTI)

    Mamedbekov, O.K. (Azerbaijan State Petroleum Academy, Baku (Azerbaijan))

    1994-08-29T23:59:59.000Z

    Theoretical investigations and field data analyses helped develop a new method of predicting the rate of inclination change in a deviated well bore to help reduce the frequency and magnitude of doglegs. Predicting borehole dogleg severity is one of the main problems in directional drilling. Predicting the tendency and magnitude of borehole deviation and comparing them to the planned well path makes it possible to improve bottom hole assembly (BHA) design and to reduce the number of correction runs. The application of adaptation models for predicting the rate of inclination change if measurement-while-drilling systems are used results in improved accuracy of prediction, and therefore a reduction in correction runs.

  15. 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

  16. ASSESSMENT OF ECONOMIC PERFORMANCE OF MODEL PREDICTIVE

    E-Print Network [OSTI]

    Huang, Biao

    ASSESSMENT OF ECONOMIC PERFORMANCE OF MODEL PREDICTIVE CONTROL THROUGH VARIANCE/CONSTRAINT TUNING advanced process control (APC) strategies to deal with multivariable constrained control problems with an ultimate objective towards economic optimization. Any attempt to evaluate MPC performance should therefore

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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...

  2. 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...

  3. 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.

  4. 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.

  5. 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

  6. Tuning Methods for Model Predictive Controllers

    E-Print Network [OSTI]

    methods for tuning of a Gas-Oil Furnace, a Wood-Berry Distillation Column and a Cement Mill Circuit. #12-M.Sc.-2012-69 #12;Summary (English) Model Predictive Control (MPC) is an optimal control strategy, and can-Berry distillations kolonne og en cement mølle proces. #12;iv #12;Preface This M. Sc. thesis was prepared

  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. Numerical Weather Prediction (NWP) and hybrid ARMA/ANN model to predict global radiation

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Numerical Weather Prediction (NWP) and hybrid ARMA/ANN model to predict global radiation Cyril a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (ALADIN). We particularly@gmail.com #12;Abstract. We propose in this paper an original technique to predict global radiation using

  10. 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

  11. 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

  12. 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

  13. 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.

  14. Predicting Time-Delays under Real-Time Scheduling for Linear Model Predictive Control

    E-Print Network [OSTI]

    Zhang, Fumin

    Predicting Time-Delays under Real-Time Scheduling for Linear Model Predictive Control Zhenwu Shi prediction of time-delays caused by real-time scheduling. Then, a model predictive controller is designed, the interaction between real-time scheduling and control design has received interest in the literature

  15. Numerical Weather Prediction (NWP) and hybrid ARMA/ANN model to predict global radiation

    E-Print Network [OSTI]

    Voyant, Cyril; Paoli, Christophe; Nivet, Marie Laure

    2012-01-01T23:59:59.000Z

    We propose in this paper an original technique to predict global radiation using a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (ALADIN). We particularly look at the Multi-Layer Perceptron. After optimizing our architecture with ALADIN and endogenous data previously made stationary and using an innovative pre-input layer selection method, we combined it to an ARMA model from a rule based on the analysis of hourly data series. This model has been used to forecast the hourly global radiation for five places in Mediterranean area. Our technique outperforms classical models for all the places. The nRMSE for our hybrid model ANN/ARMA is 14.9% compared to 26.2% for the na\\"ive persistence predictor. Note that in the stand alone ANN case the nRMSE is 18.4%. Finally, in order to discuss the reliability of the forecaster outputs, a complementary study concerning the confidence interval of each prediction is proposed

  16. 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.

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

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

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

  18. 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

  19. 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

  20. Statistical hadronization model predictions for charmed hadrons at LHC

    E-Print Network [OSTI]

    A Andronic; P Braun-Munzinger; K Redlich; J Stachel

    2007-07-27T23:59:59.000Z

    We present predictions of the statistical hadronization model for charmed hadrons production in Pb+Pb collisions at LHC.

  1. 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.

  2. Open problem: Dynamic Relational Models for Improved Hazardous Weather Prediction

    E-Print Network [OSTI]

    McGovern, Amy

    . Current weather radar detection and prediction sys- tems primarily rely on numerical models. We proposeOpen problem: Dynamic Relational Models for Improved Hazardous Weather Prediction Amy McGovern1, #12;Dynamic Relational Models for Improved Hazardous Weather Prediction Radar velocity Radar

  3. 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.

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

    E-Print Network [OSTI]

    Cook, Diane J.

    Designing Smart Environments: A Paradigm Based on Learning and Prediction Sajal K. Das and Diane J This chapter proposes a learning and prediction based paradigm for designing smart home environments control operations and tasks within the environment as well as to identify anomalies. Thus, the learning

  5. 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.

  6. Near quantitative agreement of model free DFT- MD predictions...

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

    Near quantitative agreement of model free DFT- MD predictions with XAFS observations of the hydration structure of highly Near quantitative agreement of model free DFT- MD...

  7. 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 UNIVERSIDAD POLITÉCNICA DE CATALUÑA April, 2007 GEOMODELS #12;Introduction to Coll Cardús landfill Prediction of settlement in Coll Cardús landfill 1) Settlement prediction by empirical method 2) Settlement prediction

  8. 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

  9. 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, ...

  10. 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.

  11. 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

    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... Progesterone What is the effect of significant presystemic metabolism in the gut wall on the IVIVC of the lipolysis model? 6 In vitro dynamic lipolysis model Progesterone Conclusion: Performance rank order: MCT > LCT > SCT Dahan and Hoffman, Pharm Res 2006 0...

  12. Defect site prediction based upon statistical analysis of fault signatures

    E-Print Network [OSTI]

    Trinka, Michael Robert

    2004-09-30T23:59:59.000Z

    Good failure analysis is the ability to determine the site of a circuit defect quickly and accurately. We propose a method for defect site prediction that is based on a site's probability of excitation, making no assumptions about the type...

  13. Wind Speed Prediction Via Time Series Modeling.

    E-Print Network [OSTI]

    Alexander, Daniel

    2009-01-01T23:59:59.000Z

    ??Projected construction of nearby wind farms motivates this study of statistical forecasting of wind speed, for which accurate prediction is critically important to the fluid… (more)

  14. 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

  15. A high-resolution, cloud-assimilating numerical weather prediction model for solar irradiance forecasting

    E-Print Network [OSTI]

    Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

    2013-01-01T23:59:59.000Z

    Multiscale Numerical Weather Prediction Model.   Progress assimilating numerical weather prediction model for solar customizable  numerical weather prediction model that is 

  16. Fast prediction and evaluation of gravitational waveforms using surrogate models

    E-Print Network [OSTI]

    Scott E. Field; Chad R. Galley; Jan S. Hesthaven; Jason Kaye; Manuel Tiglio

    2014-02-28T23:59:59.000Z

    [Abridged] We propose a solution to the problem of quickly and accurately predicting gravitational waveforms within any given physical model. The method is relevant for both real-time applications and in more traditional scenarios where the generation of waveforms using standard methods can be prohibitively expensive. Our approach is based on three offline steps resulting in an accurate reduced-order model that can be used as a surrogate for the true/fiducial waveform family. First, a set of m parameter values is determined using a greedy algorithm from which a reduced basis representation is constructed. Second, these m parameters induce the selection of m time values for interpolating a waveform time series using an empirical interpolant. Third, a fit in the parameter dimension is performed for the waveform's value at each of these m times. The cost of predicting L waveform time samples for a generic parameter choice is of order m L + m c_f online operations where c_f denotes the fitting function operation count and, typically, m standard ways. Surrogate model building for other waveform models follow the same steps and have the same low online scaling cost. For expensive numerical simulations of binary black hole coalescences we thus anticipate large speedups in generating new waveforms with a surrogate. As waveform generation is one of the dominant costs in parameter estimation algorithms and parameter space exploration, surrogate models offer a new and practical way to dramatically accelerate such studies without impacting accuracy.

  17. 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

  18. Supporting technology for enhanced oil recovery: Polymer predictive model

    SciTech Connect (OSTI)

    Not Available

    1986-12-01T23:59:59.000Z

    The Polymer Flood Predictive Model (PFPM) was developed by Scientific Software-Intercomp for the National Petroleum Council's (NPC) 1984 survey of US enhanced oil recovery potential (NPC, 1984). The PFPM is switch-selectable for either polymer or waterflooding, and an option in the model allows the calculation of the incremental oil recovery and economics of polymer relative to waterflooding. The architecture of the PFPM is similar to that of the other predictive models in the series: in-situ combustion, steam drive (Aydelotte and Pope, 1983), chemical flooding (Paul et al., 1982) and CO/sub 2/ miscible flooding (Paul et al., 1984). In the PFPM, an oil rate versus time function for a single pattern is computed and then is passed to the economic calculations. Data for reservoir and process development, operating costs, and a pattern schedule (if multiple patterns are desired) allow the computation of discounted cash flow and other measures of profitability. The PFPM is a three-dimensional (stratified, five-spot), two-phase (water and oil) model which computes water from breakthrough and oil recovery using fractional flow theory, and models areal and vertical sweeps using a streamtube approach. A correlation based on numerical simulation results is used to model the polymer slug size effect. The physical properties of polymer fluids, such as adsorption, permeability reduction, and non-Newtonian effects, are included in the model. Pressure drop between the injector and producer is kept constant, and the injectivity at each time step is calculated based on the mobility in each streamtube. Heterogeneity is accounted for by either entering detailed layer data or using the Dykstra-Parsons coefficient for a reservoir with a log-normal permeability distribution. 24 refs., 27 figs., 59 tabs.

  19. 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.

  20. 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

  1. Economic and Distributed Model Predictive Control of Nonlinear Systems

    E-Print Network [OSTI]

    Heidarinejad, Mohsen

    2012-01-01T23:59:59.000Z

    R. Amrit. Optimizing process economic performance us- ing2 Economic Model Predictive Control of Nonlinear Processof MPC and economic optimization of processes (e.g. , [2,

  2. 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...

  3. 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...

  4. 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...

  5. Data Assimilation for Idealised Mathematical Models of Numerical Weather Prediction

    E-Print Network [OSTI]

    Wirosoetisno, Djoko

    Data Assimilation for Idealised Mathematical Models of Numerical Weather Prediction Supervisors). Background: Numerical Weather Prediction (NWP) has seen significant gains in accuracy in recent years due is directed at achieving real-world impact in numerical weather prediction by addressing fundamental issues

  6. 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 ...

  7. Connecting Peptide Physicochemical and Antimicrobial Properties by a Rational Prediction Model

    E-Print Network [OSTI]

    Pompeu Fabra, Universitat

    Connecting Peptide Physicochemical and Antimicrobial Properties by a Rational Prediction Model Marc network approach, based on the AMP's physicochemical characteristics, that is able not only to identify active peptides but also to assess its antimicrobial potency. The physicochemical properties considered

  8. Grid-based modeling in "Wissensnetz Energiemeteorologie" Jan Ploski1

    E-Print Network [OSTI]

    Heinemann, Detlev

    -Grid) for running numerical weather prediction models. Based on experience with our introductory implementation resources of the German Grid [3] for running NWP (Numerical Weather Prediction) models. This paper its prediction quality and on overcoming the technical challenges to establish numerical weather

  9. 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

  10. Web Page Rank Prediction with Markov Models Michalis Vazirgiannis

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Web Page Rank Prediction with Markov Models Michalis Vazirgiannis INRIA Futurs Orsay, France a method for predicting the rank- ing position of a Web page. Assuming a set of successive past top-k rankings, we study the evolution of Web pages in terms of ranking trend sequences used for Markov Models

  11. Forecasting wave height probabilities with numerical weather prediction models

    E-Print Network [OSTI]

    Stevenson, Paul

    Forecasting wave height probabilities with numerical weather prediction models Mark S. Roulstona; Numerical weather prediction 1. Introduction Wave forecasting is now an integral part of operational weather methods for generating such forecasts from numerical model output from the European Centre for Medium

  12. 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

  13. 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

  14. Model Predictive Control of a Kaibel Distillation Column

    E-Print Network [OSTI]

    Skogestad, Sigurd

    column with model predictive control (MPC). A Kaibel distillation column has several advantages comparedModel Predictive Control of a Kaibel Distillation Column Martin Kvernland Ivar Halvorsen Sigurd only a single column shell. The distillation process is a multivariable process which leads

  15. 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.

  16. Hamiltonian-based numerical methods for forced-dissipative climate prediction

    E-Print Network [OSTI]

    Al Hanbali, Ahmad

    Hamiltonian-based numerical methods for forced-dissipative climate prediction Bob Peeters1 , Onno long-term weather forecast models fail at this point. But the question remains, however: Question: Is it advantageous to use numerical schemes with a Hamil- tonian core for realistic climate modeling? The primitive

  17. The Dynamics of Deterministic Chaos in Numerical Weather Prediction Models

    E-Print Network [OSTI]

    A. Mary Selvam

    2003-10-07T23:59:59.000Z

    Atmospheric weather systems are coherent structures consisting of discrete cloud cells forming patterns of rows/streets, mesoscale clusters and spiral bands which maintain their identity for the duration of their appreciable life times in the turbulent shear flow of the planetary Atmospheric Boundary Layer. The existence of coherent structures (seemingly systematic motion) in turbulent flows has been well established during the last 20 years of research in turbulence. Numerical weather prediction models based on the inherently non-linear Navier-Stokes equations do not give realistic forecasts because of the following inherent limitations: (1) the non-linear governing equations for atmospheric flows do not have exact analytic solutions and being sensitive to initial conditions give chaotic solutions characteristic of deterministic chaos (2) the governing equations do not incorporate the dynamical interactions and co-existence of the complete spectrum of turbulent fluctuations which form an integral part of the large coherent weather systems (3) limitations of available computer capacity necessitates severe truncation of the governing equations, thereby generating errors of approximations (4) the computer precision related roundoff errors magnify the earlier mentioned uncertainties exponentially with time and the model predictions become unrealistic. The accurate modelling of weather phenomena therefore requires alternative concepts and computational techniques. In this paper a universal theory of deterministic chaos applicable to the formation of coherent weather structures in the ABL is presented.

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

    SciTech Connect (OSTI)

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

    2013-09-01T23:59:59.000Z

    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.

  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. 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.

  1. 24 More Years of Numerical Weather Prediction: A Model Performance Model

    E-Print Network [OSTI]

    Stoffelen, Ad

    24 More Years of Numerical Weather Prediction: A Model Performance Model Gerard Cats May 26, 2008 Abstract For two formulations of currently usual numerical weather prediction models the evolution in such a model is much 1 #12;24 More Years of Numerical Weather Prediction Gerard Cats higher than in a sis

  2. 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.

  3. Supporting technology for enhanced oil recovery: Chemical flood predictive model

    SciTech Connect (OSTI)

    Ray, R.M.; Munoz, J.D.

    1986-12-01T23:59:59.000Z

    The Chemical Flood Predictive Model (CFPM) 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 CFPM models micellar (surfactant)-polymer (MP) floods in reservoirs which have been previously waterflooded to residual oil saturation. Thus, only true tertiary floods are considered. An option is available in the model which allows a rough estimate of oil recovery by caustic (alkaline) or caustic-polymer processes. This ''caustic'' option, added for the NPC survey, is not modeled as a separate process. Rather, the caustic and caustic-polymer oil recoveries are computed simply as 15% and 40%, respectively, of the MP oil recovery. In the CFPM, an oil rate versus time function for a single pattern is computed and the results are passed to the economic routines. To estimate multi-pattern project behavior, a pattern development schedule must be specified. After-tax cash flow is computed by combining revenues with capital costs for drilling, conversion and upgrading of wells, chemical handling costs, fixed and variable operating costs, injectant costs, depreciation, royalties, severance, state, federal, and windfall profit taxes, cost and price inflation rates, and the discount rate. A lumped parameter uncertainty routine is used to estimate risk, and allows for variation in computed project performance within an 80% confidence interval. The CFPM uses theory and the results of numerical simulation to predict MP oil recovery in five-spot patterns. Oil-bank and surfactant breakthrough and project life are determined from fractional flow theory. A Koval-type factor, based on the Dykstra-Parsons (1950) coefficient, is used to account for the effects of reservoir heterogeneity on surfactant and oil bank velocities. 18 refs., 17 figs., 27 tabs.

  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. 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.

  6. 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

  7. Interactive software for model predictive control with simultaneous identification

    E-Print Network [OSTI]

    Echeverria Del Rio, Pablo

    2000-01-01T23:59:59.000Z

    This thesis is a unified practical framework in the theory of Model Predictive Control with Simultaneous Identification. The ability to change and visualize parameters on-line makes this toolbox attractive for control engineers, and for anyone...

  8. Standard Model Prediction of the Muon Anomalous Magnetic Moment

    E-Print Network [OSTI]

    Joaquim Prades

    2010-02-18T23:59:59.000Z

    I review the present Standard Model prediction of the muon anomalous magnetic moment. The discrepancy with its experimental determination is (25.5 +- 8.0) x 10^-10, i.e., 3.2 standard deviations.

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

    E-Print Network [OSTI]

    2010-01-01T23:59:59.000Z

    J Med. 1985;313: JGIM Hasan et al. : Hospital ReadmissionA Prediction Model Omar Hasan, MBBS, MPH 1,2 , David O.online December 15, 2009 Hasan et al. : Hospital Readmission

  10. 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

  11. 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.

  12. 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.

  13. Occupancy Modeling and Prediction for Building Energy Management VARICK L. ERICKSON, University of California, Merced

    E-Print Network [OSTI]

    Carreira-Perpiñán, Miguel Á.

    42 Occupancy Modeling and Prediction for Building Energy Management VARICK L. ERICKSON, University, University of California, Merced Heating, cooling and ventilation accounts for 35% energy usage in the United into building conditioning system for usage-based demand control conditioning strategies. Using strategies based

  14. The Isospin Model prediction for multi-pion tau decays

    E-Print Network [OSTI]

    Randall J. Sobie

    1998-10-19T23:59:59.000Z

    The predictions of an isospin model are compared with the branching ratios of the 5 and 6 pion decays of the tau lepton. In both cases, the isospin model suggests that the tau favours decays in which there is an omega resonance. Recent measurements of such tau decays confirm this hypothesis. If the decay of the tau to 7 pions also proceeds through an intermediate omega, then the isospin model predicts that the branching ratio of the tau to seven charged pions should be small when compared with other 7 pion decays. New limits on this mode appear to support this argument.

  15. 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

  16. 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.

  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. 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.

  19. 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 ...

  20. 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.

  1. 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

  2. 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

  3. RESEARCH ARTICLE Climate change model predicts 33 % rice yield decrease

    E-Print Network [OSTI]

    Boyer, Edmond

    RESEARCH ARTICLE Climate change model predicts 33 % rice yield decrease in 2100 in Bangladesh parameters on rice. The effects of climate change on yield of a popular winter rice cultivar in Bangladesh online: 12 June 2012 # INRA and Springer-Verlag, France 2012 Abstract In Bangladesh, projected climate

  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. 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.

  6. 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.

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

    SciTech Connect (OSTI)

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

    2011-06-01T23:59:59.000Z

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

  8. 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

  9. 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

  10. PREDICTIONS FOR STRESS-STRAIN BEHAVIOR OF PANKI FLY-ASH USING MODIFIED CAM CLAY MODEL

    E-Print Network [OSTI]

    Prashant, Amit

    the fact that fly-ash is a granular material and its mechanical response may be similar to that of soils) is based on critical state soil mechanics, and today it is one of the most widely used constitutive model for predicting the mechanical behavior of geo-materials. In critical state soil mechanics, it is proposed

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

    SciTech Connect (OSTI)

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

    2014-09-01T23:59:59.000Z

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

  12. 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...

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

    E-Print Network [OSTI]

    Garcia, Gonzalo Andres

    2013-05-31T23:59:59.000Z

    Measurement Unit LFT : Linear Fractional Transformation LPV : Linear Parameter-Varying LTI : Linear Time-Invariant LTV : Linear Time-Varying NED : North-East-Down (N)MPC : (Nonlinear) Model Predictive Controller MIMO : Multi Input Multi Output..., showing superior tracking performance over conventional multi-loop proportional-derivative controllers. Ref. [50] applied linear MPC to a small helicopter, easily incorporating control and state constraints, and reducing the typical computational burden...

  14. 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.

  15. 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 ...

  16. 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, Paris-Erdogan law, rotor blade, wind turbine SUMMARY & CONCLUSIONS Based on the modeling and the better quality of the wind resource in the sea, the installation of wind turbines is shifting from

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. Predictive Modeling of fMRI Brain States using Functional Canonical Correlation Analysis

    E-Print Network [OSTI]

    Smeulders, Arnold

    Predictive Modeling of fMRI Brain States using Functional Canonical Correlation Analysis S Abstract. We present a novel method for predictive modeling of human brain states from functional for prediction of naturalistic stimuli from unknown fMRI data shows that the method nds highly predictive brain

  5. 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.

  6. Segmentation of speech based on adaptive pitch prediction

    E-Print Network [OSTI]

    Ødega?rd, Jan Erik

    1990-01-01T23:59:59.000Z

    - 38 mant frame. 48 IV V VI SNR for F ? P cascaded prediction applying the AMD pitch predictor. 49 SNR for P ? F cascaded prediction applying the AMD pitch predictor. 49 SNR for exponentially weighted pitch measurement in an F ? P cascaded... configuration. 50 VII SNR for exponentially weighted pitch measurement in an P ? F cascaded configuration. VIII IX SNR for unstabilized P ? F cascaded configuration. . SNR for stabilized P ? F cascaded configuration. 60 LIST OF FIGURES FIGURE Page...

  7. 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.

  8. E-Print Network 3.0 - area prediction models Sample Search Results

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

    for: area prediction models Page: << < 1 2 3 4 5 > >> 1 The Quality of a 48-Hours Wind Power Forecast Using the German and Danish Weather Prediction Model Summary: The Quality...

  9. 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

  10. 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...TM based operator interface was developed by Praxair to make the system usable in our operations. 174 ESL-IE-96-04-24 Proceedings from the Eighteenth Industrial Energy Technology Conference, Houston, TX, April 17-18, 1996 Benefits overview MPC has...

  11. 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

  12. Hybrid fuzzy predictive control based on genetic algorithms for the temperature control of a batch reactor .

    E-Print Network [OSTI]

    Causa, Javier

    2008-01-01T23:59:59.000Z

    ??In this paper we describe the design of hybrid fuzzy predictive control based on a genetic algorithm (GA). We also present a simulation test of… (more)

  13. 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 

  14. 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 ...

  15. 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.

  16. Evaluating the ability of a numerical weather prediction model to forecast tracer concentrations during ETEX 2

    E-Print Network [OSTI]

    Dacre, Helen

    Evaluating the ability of a numerical weather prediction model to forecast tracer concentrations an operational numerical weather prediction model to forecast air quality are also investigated. These potential a numerical weather prediction (NWP) model independently of the CTM. The NWP output is typically archived

  17. Probabilistic fatigue life prediction model for alloys with defects: applied to A206

    SciTech Connect (OSTI)

    Kapoor, Rajeev; Sree Hari Rao, V.; Mishra, Rajiv S.; Baumann, John A.; Grant, Glenn J.

    2011-05-31T23:59:59.000Z

    Presented here is a model for the prediction of fatigue life based on the statistical distribution of pores, intermetallic particles and grains. This has been applied to a cast Al alloy A206, before and after friction stir processing (FSP). The model computes the probability to initiate a small crack based on the probability of finding combinations of defects and grains on the surface. The crack initiation and propagation life of small cracks due to these defect and grain combinations are computed and summed to obtain the total fatigue life. The defect and grain combinations are ranked according to total fatigue life and the failure probability computed. Bending fatigue experiments were carried out on A206 before and after FSP. FSP eliminated the porosity, broke down the particles and refined the microstructure. The model predicted the fatigue life of A206 before and after FSP well. The cumulative probability distribution vs. fatigue life was fitted to a three parameter Weibull distribution function. The scatter reduced after FSP and the threshold of fatigue life increased. The potential improvement in the fatigue life of A206 for a microstructure consisting of a finer distribution of particle sizes after FSP was predicted using the model.

  18. 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

  19. 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

  20. 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...

  1. 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.

  2. ZEPHYR THE PREDICTION MODELS T.S. Nielsen, H. Madsen, H. Aa. Nielsen

    E-Print Network [OSTI]

    models and methods for predicting the wind power output from wind farms. The system is being developed Modelling (IMM) as the modelling team and all the Danish utilities as partners and users. The new models INTRODUCTION Historically there has been two models used in Denmark to predict the power production from wind

  3. Hybrid coupled models of the tropical Paci c | II ENSO prediction

    E-Print Network [OSTI]

    Hsieh, William

    Hybrid coupled models of the tropical Paci#12;c | II ENSO prediction by Youmin Tang 1 , William W: ytang@cims.nyu.edu #12; Abstract Two hybrid coupled models (HCMs), a dynamical ocean model coupled Introduction Models for ENSO prediction can be categorized into purely statistical models, hybrid coupled

  4. 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)

  5. A multivariate quadrature based moment method for LES based modeling of supersonic combustion

    E-Print Network [OSTI]

    Raman, Venkat

    function (PDF) approach is a powerful technique for large eddy simulation (LES) based modeling of scramjet and robust scramjet engine is critical for the1 realization of hypersonic flight. Availability of predictive computational models will provide2 a fast and efficient means for designing and optimizing scramjet engines

  6. 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.

  7. 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.

  8. 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

  9. HEART MOTION PREDICTION BASED ON ADAPTIVE ESTIMATION ALGORITHMS FOR ROBOTIC-ASSISTED

    E-Print Network [OSTI]

    Cavusoglu, Cenk

    HEART MOTION PREDICTION BASED ON ADAPTIVE ESTIMATION ALGORITHMS FOR ROBOTIC-ASSISTED BEATING HEART of the Graduate School of Engineering and Science ii #12;ABSTRACT HEART MOTION PREDICTION BASED ON ADAPTIVE ESTIMATION ALGORITHMS FOR ROBOTIC-ASSISTED BEATING HEART SURGERY Eser Erdem Tuna M.S. in Electrical

  10. 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

  11. An Association Rule-based CLIPS Program for Interactive Prediction of MSC Differentiation in vitro

    E-Print Network [OSTI]

    Coenen, Frans

    @liverpool.ac.uk Abstract-- In this paper, a software toolkit has been developed for in silica prediction the rules obtained from previous experimental data via data mining techniques, based on which the prediction (Classification based on Multiple Association Rules) [10] has been successfully used to obtain rules with useful

  12. The Dark Gravity model predictions for Gravity Probe B

    E-Print Network [OSTI]

    Frederic Henry-Couannier

    2007-10-23T23:59:59.000Z

    The previous version of this article gave erroneous predictions. The correct uptodate predictions can be found in the section devoted to gravitomagnetism in the living review of the Dark Gravity theory: gr-qc/0610079 The most natural prediction is zero frame dragging and the same geodetic effect as predicted by GR. However, a straightforward extension of the theory could lead to the same frame-dragging as in GR.

  13. 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

  14. 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.

  15. 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).

  16. Bayesian methods for discontinuity detection in climate model predictions.

    SciTech Connect (OSTI)

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

    2010-06-01T23:59:59.000Z

    Discontinuity detection is an important component in many fields: Image recognition, Digital signal processing, and Climate change research. Current methods shortcomings are: Restricted to one- or two-dimensional setting, Require uniformly spaced and/or dense input data, and Give deterministic answers without quantifying the uncertainty. Spectral methods for Uncertainty Quantification with global, smooth bases are challenged by discontinuities in model simulation results. Domain decomposition reduces the impact of nonlinearities and discontinuities. However, while gaining more smoothness in each subdomain, the current domain refinement methods require prohibitively many simulations. Therefore, detecting discontinuities up front and refining accordingly provides huge improvement to the current methodologies.

  17. 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 ...

  18. 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 ...

  19. 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

  20. Modeling and life prediction methodology for titanium matrix composites subjected to mission profiles

    SciTech Connect (OSTI)

    Mirdamadi, M. [Analytical Services and Materials Inc., Hampton, VA (United States); Johnson, W.S. [Georgia Inst. of Tech., Atlanta, GA (United States). School of Materials Science and Engineering

    1996-12-31T23:59:59.000Z

    Titanium matrix composites (TMCs) are being evaluated as structural materials for elevated temperature applications in future generation hypersonic vehicles. In such applications, TMC components are subjected to complex thermomechanical loading profiles at various elevated temperatures. Therefore, thermomechanical fatigue (TMF) testing, using a simulated mission profile, is essential for evaluation and development of life prediction methodologies. The objective of the research presented in this paper was to evaluate the TMF response of the [0/90]{sub 2s} SCS-6/TIMETAL-21S subjected to a generic hypersonic flight profile and its portions with a temperature ranging from {minus}130 to 816 C. It was found that the composite modulus, prior to rapid degradation, had consistent values for all the profiles tested. The accumulated minimum strain was also found to be the same for all the profiles tested. A micromechanics-based analysis was used to predict the stress-strain response of the laminate and of the constituents in each ply during thermomechanical loading conditions by using only constituent properties as input. The fiber was modeled as elastic with transverse orthotropic and temperature-dependent properties. The matrix was modeled using a thermoviscoplastic constitutive relationship. In the analysis, the composite modulus degradation was assumed to result from matrix cracking and was modeled by reducing the matrix modulus. Fatigue lives of the composite subjected to the complex generic hypersonic flight profiles were well correlated using the predicted stress in 0{degree} fibers.

  1. Modeling and life prediction methodology for Titanium Matrix Composites subjected to mission profiles

    SciTech Connect (OSTI)

    Mirdamadi, M.; Johnson, W.S.

    1994-08-01T23:59:59.000Z

    Titanium matrix composites (TMC) are being evaluated as structural materials for elevated temperature applications in future generation hypersonic vehicles. In such applications, TMC components are subjected to complex thermomechanical loading profiles at various elevated temperatures. Therefore, thermomechanical fatigue (TMF) testing, using a simulated mission profile, is essential for evaluation and development of life prediction methodologies. The objective of the research presented in this paper was to evaluate the TMF response of the (0/90)2s SCS-6/Timetal-21S subjected to a generic hypersonic flight profile and its portions with a temperature ranging from -130 C to 816 C. It was found that the composite modulus, prior to rapid degradation, had consistent values for all the profiles tested. A micromechanics based analysis was used to predict the stress-strain response of the laminate and of the constituents in each ply during thermomechanical loading conditions by using only constituent properties as input. The fiber was modeled as elastic with transverse orthotropic and temperature dependent properties. The matrix was modeled using a thermoviscoplastic constitutive relation. In the analysis, the composite modulus degradation was assumed to result from matrix cracking and was modeled by reducing the matrix modulus. Fatigue lives of the composite subjected to the complex generic hypersonic flight profile were well correlated using the predicted stress in 0 degree fibers.

  2. 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...

  3. 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 buildingpredictive control of thermal energy storage in buildingsystems which use thermal energy storage. In particular the

  4. 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.

  5. 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

  6. Autobiography based prediction in a situated Ladislau Boloni

    E-Print Network [OSTI]

    Bölöni, Ladislau L

    and engineering from books and lectures and the setup and results of experiments can also be described as stories Engineering and Computer Science University of Central Florida 4000 Central Florida Blvd, Orlando FL 32816 feature of any situated AGI system. The most widely used approach is to create a model of the world

  7. A turbulence model for buoyant flows based on vorticity generation.

    SciTech Connect (OSTI)

    Domino, Stefan Paul; Nicolette, Vernon F.; O'Hern, Timothy John; Tieszen, Sheldon R.; Black, Amalia Rebecca

    2005-10-01T23:59:59.000Z

    A turbulence model for buoyant flows has been developed in the context of a k-{var_epsilon} turbulence modeling approach. A production term is added to the turbulent kinetic energy equation based on dimensional reasoning using an appropriate time scale for buoyancy-induced turbulence taken from the vorticity conservation equation. The resulting turbulence model is calibrated against far field helium-air spread rate data, and validated with near source, strongly buoyant helium plume data sets. This model is more numerically stable and gives better predictions over a much broader range of mesh densities than the standard k-{var_epsilon} model for these strongly buoyant flows.

  8. 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

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

    E-Print Network [OSTI]

    Huang, Yinlun

    . Index Terms--Control system design, fuzzy logic, model predic- tive control. I. INTRODUCTION MODELIEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 8, NO. 6, DECEMBER 2000 665 Fuzzy Model Predictive Control computational effort that may prohibit its on-line applications. In this paper, a fuzzy model predictive control

  10. Evaluation of Location-Specific Predictions by a Detailed Simulation Model of Aedes aegypti Populations

    E-Print Network [OSTI]

    Lloyd, Alun

    Evaluation of Location-Specific Predictions by a Detailed Simulation Model of Aedes aegypti Buster is a stochastic, spatially explicit simulation model of Aedes aegypti populations, designed of Location-Specific Predictions by a Detailed Simulation Model of Aedes aegypti Populations. PLoS ONE 6(7): e

  11. 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

  12. 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

  13. 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

  14. 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.

  15. 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 

  16. 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...

  17. 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...

  18. 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

  19. Robust UAV Coordination for Target Tracking using Output-Feedback Model Predictive Control with Moving Horizon Estimation

    E-Print Network [OSTI]

    Hespanha, João Pedro

    Robust UAV Coordination for Target Tracking using Output-Feedback Model Predictive Control consider the control of two UAVs tracking an evasive moving ground vehicle. The UAVs are small fixed to maintain visibility. The control inputs to the UAVs are computed based on noisy measurements of the UAVs

  20. 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

  1. 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

  2. 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.

  3. 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...

  4. 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...

  5. 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.

  6. 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 ...

  7. 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

  8. 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

  9. EVALUATION OF NUMERICAL WEATHER PREDICTION IN MODELING CLOUD-RADIATION INTERACTIONS OVER THE SOUTHERN GREAT PLAINS

    E-Print Network [OSTI]

    Johnson, Peter D.

    EVALUATION OF NUMERICAL WEATHER PREDICTION IN MODELING CLOUD- RADIATION INTERACTIONS OVER.bnl.gov ABSTRACT Numerical weather prediction (NWP) is the basis for present-day weather forecasts, and NWP for Medium-Range Weather Forecasts, the US North American Model, and the US Global Forecast System. Attempts

  10. EXPLICIT SIMULATION OF ICE PARTICLE HABITS IN A NUMERICAL WEATHER PREDICTION MODEL

    E-Print Network [OSTI]

    Wisconsin at Madison, University of

    EXPLICIT SIMULATION OF ICE PARTICLE HABITS IN A NUMERICAL WEATHER PREDICTION MODEL by Tempei This study develops a scheme for explicit simulation of ice particle habits in Cloud Resolving Models (CRMs is called Spectral Ice Habit Prediction System (SHIPS), which represents a continuous-property approach

  11. 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

  12. 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

  13. 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

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    -FATIGUE-OXIDATION DAMAGE A. M. ALAM1 and L. REMY2 1 ALSTOM (Power), Gas Turbine Design Department, Brown Boveri Strasse 7A LIFETIME PREDICTION MODEL FOR SINGLE CRYSTAL SUPERALLOYS SUBJECTED TO THERMOMECHANICAL CREEP 91003, Evry, France ABSTRACT This paper contains a brief description of a lifetime prediction model

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

    SciTech Connect (OSTI)

    Yunovich, M.; Thompson, N.G. [CC Technologies Labs., Inc., Dublin, OH (United States)

    1998-12-31T23:59:59.000Z

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

  16. 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

  17. 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...

  18. 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.

  19. 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

  20. 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

  1. Experimental Evaluation of Inventory-Based Discrete-Updating Market Maker for Intra-Firm Prediction

    E-Print Network [OSTI]

    Boyer, Edmond

    an inventory-based updating logic according to the transactions in the market. Laboratory experimentsExperimental Evaluation of Inventory-Based Discrete- Updating Market Maker for Intra-Firm Prediction Market System Using VIPS Hajime Mizuyama1 , Morio Ueda, Katsunobu Asada and Yu Tagaya 1 Department

  2. 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 consumption plays an important role in the total energy consumption of end use. Energy efficiency in building

  3. Image-based Prediction of Landmark Features for Mobile Robot Navigation

    E-Print Network [OSTI]

    Jaffe, Jules

    -based prediction of point and line features for a mobile system operating on a planar surface. Preliminary-based navigation system. The central idea in this design is to constantly track im- age features used as landmarks. This pro- vides constant and accurate control of position, yet avoids the overhead of computing an explicit

  4. 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

  5. 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, ...

  6. Soil-landscape model helps predict potassium supply in vineyards

    E-Print Network [OSTI]

    O'Geen, Anthony T; Pettygrove, Stuart; Southard, Randal; Minoshima, Hideomi; Verdegaal, Paul S.

    2008-01-01T23:59:59.000Z

    Australia: Winetitles. Marchand DE, Allwardt A. 1981. LateGeologic ages based on Marchand and Allwardt (1981). †

  7. 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.

  8. A Novel Ab-initio Genetic-Based Approach for Protein Folding Prediction

    E-Print Network [OSTI]

    Sergio R. Duarte; David C. Becerra; Fernando Nino; Yoan J. Pinzón

    In this paper, a model based on genetic algorithms for protein folding prediction is proposed. The most important features of the proposed approach are: i) Heuristic secondary structure information is used in the initialization of the genetic algorithm; ii) An enhanced 3D spatial representation called cube-octahedron is used, also, an expansion technique is proposed in order to reduce the computational complexity and spatial constraints; iii) Data preprocessing of geometric features to characterize the cubeoctahedron using twelve basic vectors to define the nodes. Additionally, biological information (torsion angles, bond angles and secondary structure conformations) was pre-processed through an analysis of all possible combinations of the basic vectors which satisfy the biological constrains defined by the spatial representation; and iv) Hashing techniques were used to improve the computational efficiency. The pre-processed information was stored in hash tables, which are intensively used by the genetic algorithm. Some experiments were carried out to validate the proposed model obtaining very promising results.

  9. Copula Based Hierarchical Bayesian Models

    E-Print Network [OSTI]

    Ghosh, Souparno

    2010-10-12T23:59:59.000Z

    WITH THE SAME MARGINAL AND CONDITIONAL LINK . 9 III.1. Random effects model . . . . . . . . . . . . . . . . . . . . 12 III.1.1. Logistic link with bridge random effects . . . . . 15 III.1.2. Log-log link with positive stable random effects . 19 III.1.3. Logistic... probabilities for models of various order . . . . . . . . . . . 58 8. Comparison among various mixture-copula models . . . . . . . . . . 59 9. DIC, AAPE and AAD for the two competing models . . . . . . . . . 93 10. Posterior summary of parameters for the two...

  10. Roadway pollutant dispersion: development of a data base and a model and evaluation of five models

    E-Print Network [OSTI]

    Green, Nicholas Joseph

    1980-01-01T23:59:59.000Z

    ROADWAY POLLUTANT D1SPERSION: DEVELOPMENT OF A DATA 3ASE AND A MODEL AND EVALUATION OF FIVE MODELS A Thesis by NICHOLAS JOSEPH GREEN Submitted to the Graduate College of Texas A&M University in partial fulfillment of the requirement... previous dispersion models, as well as the present model. The emission rates for a portion of the Texas ASM data base included those predicted by MOBILE 1, an EPA computer model, and those calcul- ated by a mass balance technique using experimental data...

  11. 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

  12. 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...

  13. 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.

  14. Putting Nonlinear Model Predictive Control Bjarne A. Foss1

    E-Print Network [OSTI]

    Foss, Bjarne A.

    estimation. Finally, we consider the design of the optimization problem itself and implementation issues. 1 for optimization of suspension PVC polymerization processes has been implemented on two large (140 m3) autoclaves: It contains a rather detailed nonlinear model of the polymerization reactor. The reactor model includes

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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.

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

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

    - TOUGH family codes have been widely used in modeling EGS and CCS processes. The fracture-matrix feature can be handled through the MINC module; however, at considerable cost....

  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. 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.

  6. 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.

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

    E-Print Network [OSTI]

    Joshi, Praveen Sudhakar

    2012-06-07T23:59:59.000Z

    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. 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...

  9. Model predictive control with application to real-time hardware and guided parafoil

    E-Print Network [OSTI]

    Alaniz, Abran, 1980-

    2004-01-01T23:59:59.000Z

    Model Predictive Control (MPC) is a control strategy that is suitable for optimizing the performance of constrained systems. Constraints are present in all control systems due to the physical and environmental limits on ...

  10. 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...

  11. Sensors and Actuators B 106 (2005) 122127 Eulerian-Lagrangian model for predicting odor dispersion using

    E-Print Network [OSTI]

    Katul, Gabriel

    Sensors and Actuators B 106 (2005) 122­127 Eulerian-Lagrangian model for predicting odor dispersion-level heating from solar short wave radiation, and (2) during the evening when deep surface cooling through long

  12. 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

  13. 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 ...

  14. 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

  15. 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

  16. 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

  17. 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.

  18. 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

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

    E-Print Network [OSTI]

    in rural areas. Now BSs that harvest renewable energy, such as solar and wind, are gradually deployed are powered by solar energy. This reveals the potential of energy harvesting techniques to be applied in ruralSolar Radiation Prediction and Energy Allocation for Energy Harvesting Base Stations Yanan Bao

  20. ECG Compression Algorithms Comparisons among EZW, Modified EZW and Wavelet Based Linear Prediction

    E-Print Network [OSTI]

    Fowler, Mark

    ECG Compression Algorithms Comparisons among EZW, Modified EZW and Wavelet Based Linear Prediction 74 6 Recommendation for Future Research 78 List of References 79 Appendices 81 Appendix 1 ECG Signal.............................................87 #12;iv List of Tables 2.1 Variance Comparisons (ECG 16265

  1. A Regression-Based Approach for Improving the Association Rule Mining through Predicting

    E-Print Network [OSTI]

    Zhang, Minjie

    rules for credit evaluation in the domain of farmers'credit his- tory. Li et al. [6] specifically of Rules on General Datasets Dien Tuan Le, Fenghui Ren, and Minjie Zhang School of Computer Science to create concrete models in particular domains for predicting the potential number of association rules

  2. 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...

  3. 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...

  4. 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.

  5. 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

  6. Lurking Pathway Prediction And Pathway ODE Model Dynamic Analysis

    E-Print Network [OSTI]

    Zhang, Rengjing

    2013-11-18T23:59:59.000Z

    regulated proteins in the transduction pro- cess. And by modeling the CCL2 pathway in MTB infected cells, J N K , cM Y C and P LC showed as the most significant modules. Hence, the drug treatments inhibit- ing J N K , cM Y C and P LC would effectively...

  7. 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

  8. Random Forest-Based Protein Model Quality Assessment (RFMQA) Using Structural Features and Potential Energy

    E-Print Network [OSTI]

    Lee, Jooyoung

    Random Forest-Based Protein Model Quality Assessment (RFMQA) Using Structural Features and Potential Energy Terms Balachandran Manavalan, Juyong Lee, Jooyoung Lee* Center for In Silico Protein in protein structure prediction. In this study, we present the first application of random forest based model

  9. 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

  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. A soil moisture availability model for crop stress prediction

    E-Print Network [OSTI]

    Gay, Roger Franklin

    1983-01-01T23:59:59.000Z

    is composed of three major components, which are, a) calcul ation of evapotranspiration, b) infiltration of moisture into the soil, c) redistribution of the soil moisture. Other edaphic models have been developed by Hill [1974], Bai er and Robertson... inputs could result in the development of moist layers in the lower soil layer that would not be accounted for if the moisture were uniformly redistributed. As the cycle progesses, redistribution and moisture depletion do occur, until there 1s less...

  12. 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.

  13. SimTable helps firefighters model and predict fire direction

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

    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:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas ConchasPassiveSubmitted forHighlightsSeminarsSilicon sponge improvesSimTable models and

  14. A PHYSICALLY-BASED SCHEME FOR THE URBAN ENERGY BUDGET IN ATMOSPHERIC MODELS

    E-Print Network [OSTI]

    Ribes, Aurélien

    A PHYSICALLY-BASED SCHEME FOR THE URBAN ENERGY BUDGET IN ATMOSPHERIC MODELS VALÉRY MASSON Centre published data. Firstly, it is shown that the evolution of the model-predicted fluxes during a night. These two validations show that the radiative energy input to the urban surface model is realistic

  15. 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...

  16. 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.

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

    E-Print Network [OSTI]

    Foss, Bjarne A.

    -estimation and prediction in a MPC scheme. The controller has been applied to quality control of a FCCU fractionator IFAC Keywords: Nonlinear Model Predictive Control, Multi-Model, FCCU fractionator 1. INTRDUCTION Model is investigated through simulation of a rigorous model of a typical refining unit, a FCCU (Fluidized Catalytic

  18. A Two Step Model for Linear Prediction, with Connections to PLS

    E-Print Network [OSTI]

    A Two Step Model for Linear Prediction, with Connections to PLS Ying Li Faculty of Natural ISSN, 1654-9406 ISBN, 978-91-576-9055-5 c 2011 Ying Li, Uppsala Print: SLU Service/Repro, Uppsala 2011 Model, Krylov Space, MLE, PLS. Author's address: Ying Li SLU, Department of Energy and Technology, Box

  19. 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

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

    E-Print Network [OSTI]

    A Model for Predicting Daily Peak Visitation and Implications for Recreation Management and Water carrying capacity. Keywords Visitation model Á Recreation management Á Water quality Á River visitation Á Clark, Fort Collins, Colorado 80523, USA 123 Environmental Management DOI 10.1007/s00267-008-9079-5 #12

  1. 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

  2. Critical Fracture Stress and Fracture Strain Models for the Prediction of Lower and

    E-Print Network [OSTI]

    Ritchie, Robert

    Critical Fracture Stress and Fracture Strain Models for the Prediction of Lower and Upper Shelf fracture stress and stress modified fracture strain models are utilized to describe the variation of lower and upper shelf fracture toughness with temperature and strain rate for two alloy steels used

  3. 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

  4. 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

  5. Nonlinear Model Predictive Control of an Aircraft Gas Turbine Engine Brent. J. Brunell

    E-Print Network [OSTI]

    Bitmead, Bob

    Nonlinear Model Predictive Control of an Aircraft Gas Turbine Engine Brent. J. Brunell , Robert R the potential to achieve better performance than the production controller. 1 Introduction Gas turbines can turbine model considered is a low bypass, two rotor, turbojet with a variable exhaust area typical

  6. 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

  7. 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

  8. 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.

  9. 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

  10. Individual-based modeling of fish: Linking to physical models and water quality.

    SciTech Connect (OSTI)

    Rose, K.A.

    1997-08-01T23:59:59.000Z

    The individual-based modeling approach for the simulating fish population and community dynamics is gaining popularity. Individual-based modeling has been used in many other fields, such as forest succession and astronomy. The popularity of the individual-based approach is partly a result of the lack of success of the more aggregate modeling approaches traditionally used for simulating fish population and community dynamics. Also, recent recognition that it is often the atypical individual that survives has fostered interest in the individual-based approach. Two general types of individual-based models are distribution and configuration. Distribution models follow the probability distributions of individual characteristics, such as length and age. Configuration models explicitly simulate each individual; the sum over individuals being the population. DeAngelis et al (1992) showed that, when distribution and configuration models were formulated from the same common pool of information, both approaches generated similar predictions. The distribution approach was more compact and general, while the configuration approach was more flexible. Simple biological changes, such as making growth rate dependent on previous days growth rates, were easy to implement in the configuration version but prevented simple analytical solution of the distribution version.

  11. 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 .

  12. Estimation of the mean depth of boreal lakes for use in numerical weather prediction and climate modelling

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    in the numerical weather prediction (NWP) and climate models through parameterisation. For parameterisation, data. The effect of lakes should be parameterised in numerical weather prediction (NWP) and climate modellingEstimation of the mean depth of boreal lakes for use in numerical weather prediction and climate

  13. Model-Based Testing : The Test of Formal Models

    E-Print Network [OSTI]

    Model-Based Testing : The Test of Formal Models Jan Tretmans ESI & Radboud University Nijmegen #12;2 Testing (Software) Testing: checking or measuring some quality characteristics of an executing object by performing experiments in a controlled way w.r.t. a specification tester specification SUT System Under Test

  14. A predictive model for the combustion process in dual fuel engines

    SciTech Connect (OSTI)

    Liu, Z.; Karim, G.A. [Univ. of Calgary, Alberta (Canada)

    1995-12-31T23:59:59.000Z

    A multi-zone model has been developed for the prediction of the combustion processes in dual fuel engines and some of their performance features. The consequences of the interaction between the gaseous and the diesel fuels and the resulting modification to the combustion processes are considered. A reacting zone has been incorporated in the model to describe the partial oxidation of the gaseous fuel-air mixture while detailed kinetic schemes are employed to describe the oxidation of the gaseous fuel, right from the start of compression to the end of the expansion process. The associated formation and concentrations of exhaust emissions are correspondingly established. The model can predict the onset of knock as well as the operating features and emissions for the more demanding case of light load performance. Predicted values for methane operation show good agreement with corresponding experimental values.

  15. Comparison of model predicted to observed winds in the coastal zone

    SciTech Connect (OSTI)

    Garstang, M.; Pielke, R.A.; Snow, J.W.

    1982-06-01T23:59:59.000Z

    Predictions of near-surface (10 to 100 m) wind velocities made by a mesoscale numerical model on a 10 km grid over and near the coastline are checked against observations. Two comparisons are made. The first is between observed and model-estimated mean annual wind power density at locations where surface observations exist in three coastal areas: the Chesapeake Bay, the Apalachee Bay and the South Texas coastal area. The second comparison is made between model predictions over the Delmarva Peninsula and adjacent ocean and observations made over a 120 x 30 km rectangle extending across the peninsula and out to sea. It is concluded that the unbiased error analysis skill ratings of 81% and 76% are attained for two days of prediction-observation comparisons. In the meantime, the skill of the model in duplicating individual coastal wind fields is taken as 78%. In addition, a qualitative comparison is made between the predicted fields of wind and the observed wind field. The predicted wind field unquestionably reproduces the observed field.

  16. 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.

  17. 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

  18. COBRA-WC model and predictions for a fast-reactor natural-circulation transient. [LMFBR

    SciTech Connect (OSTI)

    George, T.L.; Basehore, K.L.; Prather, W.A.

    1980-01-01T23:59:59.000Z

    The COBRA-WC (Whole Core) code has been used to predict the core-wide coolant and rod temperature distribution in a liquid metal fast reactor during the early part (first 220 seconds) of a natural circulation transient. Approximately one-sixth of the core was modeled including bypass flows and the pressure losses above and below the core region. Detailed temperature and flow distributions were obtained for the two test fuel assemblies. The COBRA-WC model, the approach, and predictions of core-wide transient coolant and rod temperatures during a natural circulation transient are presented in this paper.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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 ...

  4. 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

  5. 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...

  6. 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.

  7. 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

  8. 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

  9. 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 ...

  10. 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

  11. 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

  12. Predictive Inner-Outer Model for Turbulent Boundary Layers Applied to Hypersonic DNS Data

    E-Print Network [OSTI]

    Martín, Pino

    Predictive Inner-Outer Model for Turbulent Boundary Layers Applied to Hypersonic DNS Data Clara numerical simulation (DNS) data of supersonic and hypersonic turbulent boundaries with Mach 3 and Mach 7, and Martin12­14 on DNS of hypersonic turbulent boundary layers demonstrates the existence of large scale

  13. 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

  14. Human Leg Model Predicts Ankle Muscle-Tendon Morphology, State, Roles and Energetics in Walking

    E-Print Network [OSTI]

    Herr, Hugh

    Human Leg Model Predicts Ankle Muscle-Tendon Morphology, State, Roles and Energetics in Walking to be established. Here we develop a computational framework to address how the ankle joint actuation problem-tendon morphology and neural activations enable a metabolically optimal realization of biological ankle mechanics

  15. A probabilistic model to predict the formation and propagation of crack networks in thermal

    E-Print Network [OSTI]

    . In the case of cooling systems in nuclear power plants, observations revealed the presence of thermal crazing loading even if thermal fatigue is multiaxial. However, the first simulations on a uniaxial mechanicalA probabilistic model to predict the formation and propagation of crack networks in thermal fatigue

  16. A Novel Virtual Age Reliability Model for Time-to-Failure Prediction

    E-Print Network [OSTI]

    Kuzmanov, Georgi

    counts, devices approaching physical feature size limits and nuclear plant comparable power densityA Novel Virtual Age Reliability Model for Time-to-Failure Prediction Yao Wang, Sorin Cotofana their relatively short operating lifetime. To overcome the MTTF weakness, this paper proposes a novel virtual age

  17. 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

  18. 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-scaled kinetic energy are all consistent with the available observations in the regions of significant wind

  19. 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

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

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    Economic Nonlinear Model Predictive Control for the Optimization of Gas Pipeline Networks EWO University Oct 12, 2011 Ajit Gopalakrishnan (CMU) Economic NMPC for gas pipeline optimization Oct 12, 2011 1 Gopalakrishnan (CMU) Economic NMPC for gas pipeline optimization Oct 12, 2011 4 / 24 #12;Natural Gas Industry

  3. 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

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

    E-Print Network [OSTI]

    Daraio, Chiara

    deficit in the near field, Proceedings of the European Wind Energy Conference, Madrid, Spain, European, Boundary Layer Meteorology 132, pp. 129-149, 2009. [3] G. Larsen, H. Madsen and N. Sørensen, Mean wake·Wake models are used to improve predictions of Annual Energy Production (AEP) of wind farms. ·Wake

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    processes of PAH with subcritical water [5,6] since it provides the extractability limit which can be used groups, for the representation of the solubility of solid PAH in subcritical water. These hal-00872639Prediction of Solid Polycyclic Aromatic Hydrocarbons Solubility in Water with the NRTL-PR Model

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. Microstructure Based Modeling of ? Phase Influence on Mechanical...

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

    Based Modeling of ? Phase Influence on Mechanical Response of Cast AM Series Mg Alloys. Microstructure Based Modeling of ? Phase Influence on Mechanical Response of Cast...

  12. 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...

  13. 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...

  14. 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...

  15. 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

  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. An individual-based instream flow model for coexisting populations of brown and rainbow trout

    SciTech Connect (OSTI)

    Van Winkle, W.; Jager, H.I.; Holcomb, B.D.

    1996-03-01T23:59:59.000Z

    This report describes an individual-based model for sympatric populations of brown and rainbow trout in a stream habitat. Hatchery rainbow trout are included as a third species. The model provides a tool for predicting flow effects on trout populations by linking the hydraulic component of the Physical Habitat Simulation (PHABSIM) methodology and an individual-based population modeling approach. PHABSIM simulates the spatial distribution of depth and velocity at different flows. The individual-based model simulates the reproduction, foraging, consumption, energetic costs, growth, habitat utilization, movement, and mortality of individual fish, and enables population attributes to be determined from relevant attributes of individual fish. The spatially explicit nature of the model permits evaluation of behavioral responses used by fish to mitigate temporary setbacks in habitat quality. This linked mechanistic modeling approach readily lends itself to the iterative process of making predictions, testing against field data, improving the model, and making more predictions. The model has been applied to a stream segment in the Tule River, California. Physical and biological data from this site are used as input to the model. Calibrating the model to abundance data was relatively easy because values for mortality parameters were not strongly constrained by empirical data. Calibrating the model to observed growth rates and habitat use was more challenging. The primary reason for developing this model has been to provide a new and complementary tool to PHABSIM that can be used in instream-flow assessments.

  18. Demand Response-Enabled Model Predictive HVAC Load Control in Buildings using Real-Time Electricity Pricing.

    E-Print Network [OSTI]

    Avci, Mesut

    2013-01-01T23:59:59.000Z

    ??A practical cost and energy efficient model predictive control (MPC) strategy is proposed for HVAC load control under dynamic real-time electricity pricing. The MPC strategy… (more)

  19. Regression Model Predicting Appraised Unit Value of Land in San Francisco County from Number of and Distance to Public Transit Stops using GIS

    E-Print Network [OSTI]

    Son, Kiyoung

    2012-07-16T23:59:59.000Z

    The objective of this study is to develop a quantifying model that predicts the appraised unit value of parcels in San Francisco County based on number of LEED-NC Public Transportation Access (PTA) qualified bus, light rail and commuter rail stops...

  20. 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.

  1. A Model for Predicting Magnetic Targeting of Multifunctional Particles in the Microvasculature

    E-Print Network [OSTI]

    Furlani, E J

    2006-01-01T23:59:59.000Z

    A mathematical model is presented for predicting magnetic targeting of multifunctional carrier particles that are designed to deliver therapeutic agents to malignant tissue in vivo. These particles consist of a nonmagnetic core material that contains embedded magnetic nanoparticles and therapeutic agents such as photodynamic sensitizers. For in vivo therapy, the particles are injected into the vascular system upstream from malignant tissue, and captured at the tumor using an applied magnetic field. The applied field couples to the magnetic nanoparticles inside the carrier particle and produces a force that attracts the particle to the tumor. In noninvasive therapy the applied field is produced by a permanent magnet positioned outside the body. In this paper a mathematical model is developed for predicting noninvasive magnetic targeting of therapeutic carrier particles in the microvasculature. The model takes into account the dominant magnetic and fluidic forces on the particles and leads to an analytical expr...

  2. 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

  3. Use of a predictive model for the impact of cofiring coal/biomass blends on slagging and fouling propensity

    SciTech Connect (OSTI)

    Piotr Plaza; Anthony J. Griffiths; Nick Syred; Thomas Rees-Gralton [Cardiff University, Cardiff (United Kingdom). Centre for Research in Energy

    2009-07-15T23:59:59.000Z

    The paper describes an investigation of slagging and fouling effects when cofiring coal/biomass blends by using a predictive model for large utility boilers. This model is based on the use a zone computational method to determine the midsection temperature profile throughout a boiler, coupled with a thermo-chemical model, to define and assess the risk of elevated slagging and fouling levels during cofiring of solid fuels. The application of this prediction tool was made for a 618 MW thermal wall-fired pulverized coal boiler, cofired with a typical medium volatile bituminous coal and two substitute fuels, sewage sludge and sawdust. Associated changes in boiler efficiency as well as various heat transfer and thermodynamic parameters of the system were analyzed with slagging and fouling effects for different cofiring ratios. The results of the modeling revealed that, for increased cofiring of sewage sludge, an elevated risk of slagging and high-temperature fouling occurred, in complete contrast to the effects occurring with the utilization of sawdust as a substitute fuel. 30 refs., 9 figs.,1 tab.

  4. 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.

  5. 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...

  6. Predicting relative permeability from water retention: A direct approach based on fractal geometry

    E-Print Network [OSTI]

    Perfect, Ed

    various configu- rations of the pore size distribution and interconnectivity can match those predicted

  7. 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...

  8. 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. ...

  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. 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

  11. Statistical Model Predictions for p-p and Pb-Pb collisions at LHC

    E-Print Network [OSTI]

    I Kraus; J Cleymans; H Oeschler; K Redlich; S Wheaton

    2007-07-09T23:59:59.000Z

    Predictions for particle production at LHC are discussed in the context of the statistical model. Moreover, the capability of particle ratios to determine the freeze-out point experimentally is studied, and the best suited ratios are specified. Finally, canonical suppression in p-p collisions at LHC energies is discussed in a cluster framework. Measurements with p-p collisions will allow us to estimate the strangeness correlation volume and to study its evolution over a large range of incident energies.

  12. A new thermodynamic model to predict wax deposition from crude oils

    E-Print Network [OSTI]

    Loganathan, Narayanan

    1993-01-01T23:59:59.000Z

    Hydrocarbons 5 Comparison of Experimental and Predicted Onset Temperatures using this Model at 1 Atm. 30 31 37 6 Component Data for Oil Mixture l. 7 Characterization for Oil Mixture l. 8 Characterization for Oil Mixture 2. 9 Characterization for Oil... for Flash Calculations . . 34 4 Variation of Onset Temperature with Pressure for Oil Mixture l. . . 5 Variation of Onset Temperature with Pressure for Oil Mixture 2 . . 51 52 6 Wax Precipitation Curves for Oil Mixture 1 at 1 Atm. . . 7 Wax...

  13. 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? . . . . . .

  14. 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.

  15. 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.

  16. 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...

  17. 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.

  18. semble Prediction Lizzie S. R. Froude1

    E-Print Network [OSTI]

    Froude, Lizzie

    by numerical weather prediction (NWP). Operational NWP models are based on a set of equations known for Medium Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP will grow rapidly, resulting in a total loss of predictability at higher forecast times. Today's models

  19. 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....

  20. 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.

  1. Jack Rabbit Pretest Data For TATB Based IHE Model Development

    SciTech Connect (OSTI)

    Hart, M M; Strand, O T; Bosson, S T

    2008-06-18T23:59:59.000Z

    The Jack Rabbit Pretest series consisted of 5 focused hydrodynamic experiments, 2021E PT3, PT4, PT5, PT6, and PT7. They were fired in March and April of 2008 at the Contained Firing Facility, Site 300, Lawrence Livermore National Laboratory, Livermore, California. These experiments measured dead-zone formation and impulse gradients created during the detonation of TATB based insensitive high explosive. This document contains reference data tables for all 5 experiments. These data tables include: (1) Measured laser velocimetry of the experiment diagnostic plate (2) Computed diagnostic plate profile contours through velocity integration (3) Computed center axis pressures through velocity differentiation. All times are in microseconds, referenced from detonator circuit current start. All dimensions are in millimeters. Schematic axi-symmetric cross sections are shown for each experiment. These schematics detail the materials used and dimensions of the experiment and component parts. This should allow anyone wanting to evaluate their TATB based insensitive high explosive detonation model against experiment. These data are particularly relevant in examining reactive flow detonation model prediction in computational simulation of dead-zone formation and resulting impulse gradients produced by detonating TATB based explosive.

  2. 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.

  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. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. A warranty forecasting model based on piecewise statistical distributions and stochastic simulation

    E-Print Network [OSTI]

    Sandborn, Peter

    industry and has a specific application to automotive electronics. The warranty prediction model is based is demonstrated using a case study of automotive electronics warranty returns. The approach developed b CALCE Electronic Products and Systems Center, Department of Mechanical Engineering, University

  12. 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

  13. 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.

  14. 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...

  15. A GIS-based atmospheric dispersion model

    E-Print Network [OSTI]

    Boyer, Edmond

    pollution due to the use of agricultural pesticide is a major concern to- day, regarding both public health dispersion and to propose an useful air pollution prediction tool, using fluid mechanics equations and open un outil de prediction de la pollution de l'air . Ce travail concerne la modélisation de la dérive

  16. Lagrangian and Control Volume Models for Prediction of Cooling Lake Performance at SRP

    SciTech Connect (OSTI)

    Garrett, A.J.

    2001-06-26T23:59:59.000Z

    The model validation described in this document indicates that the methods described here and by Cooper (1984) for predicting the performance of the proposed L-Area cooling lake are reliable. Extensive observations from the Par Pond system show that lake surface temperatures exceeding 32.2 degrees C (90 degrees F) are attained occasionally in the summer in areas where there is little or no heating from the P-Area Reactor. Regulations which restrict lake surface temperatures to less than 32.2 degrees C should be structured to allow for these naturally-occurring thermal excursions.

  17. A difference based approach to the semiparametric partial linear model

    E-Print Network [OSTI]

    Wang, Lie

    2011-01-01T23:59:59.000Z

    A commonly used semiparametric partial linear model is considered. We propose analyzing this model using a difference based approach. The procedure estimates the linear component based on the differences of the observations ...

  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. 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.

  1. 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...

  2. 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.

  3. Weather Regime Prediction Using Statistical Learning

    E-Print Network [OSTI]

    A. Deloncle; R. Berk; F. D'Andrea; M. Ghil

    2011-01-01T23:59:59.000Z

    most advanced numerical weather prediction models still havefor numerical weather prediction models. Acknowledgements It

  4. Model-based Quality Assurance of Automotive Software

    E-Print Network [OSTI]

    Jurjens, Jan

    Model-based Quality Assurance of Automotive Software Jan Jürjens1 , Daniel Reiss2 , David (Germany) #12;Jan Jürjens et al.: Model-based Quality Assurance of Automotive Software 2 The Problem (Meta. #12;Jan Jürjens et al.: Model-based Quality Assurance of Automotive Software 3 The Problem (Meta

  5. 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

  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. Utilization of Smart Materials and Predictive Modeling to Integrate Intracellular Dynamics with Cell Biomechanics and Collective Tissue Behavior

    E-Print Network [OSTI]

    Mather, Patrick T.

    Utilization of Smart Materials and Predictive Modeling to Integrate Intracellular Dynamics important structures inside cells. New "smart" material will be used to trigger changes to cell movement Medical University Control of Cell Polarization by Smart Material Substrates Multiscale Imaging Multiscale

  9. 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

  10. 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

  11. Standard Model Predictions and New Physics Sensitivity in B->DD Decays

    E-Print Network [OSTI]

    Jung, Martin

    2014-01-01T23:59:59.000Z

    An extensive model-independent analysis of B->DD decays is carried out employing SU(3) flavour symmetry, including symmetry-breaking corrections. Several theoretically clean observables are identified which allow for testing the Standard Model. These include the known time-dependent CP asymmetries, the penguin pollution of which can be controlled in this framework, but notably also quasi-isospin relations which are experimentally well accessible and unaffected by symmetry-breaking corrections. Theoretical assumptions can be kept to a minimum and controlled by additional sum rules. Available data are used in global fits to predict the branching ratio for the B0->DsDs decay as well as several CP asymmetries which have not been measured so far, and future prospects are analyzed.

  12. 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...

  13. 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

    THE APPLICATION OI' A CHEMICAL EQUILIBRIUM MODEL, SOLTEQ, TO PREDICT THK CHEMICAL SPKCIATIONS IN STABILIZED/SOLIDIFIED WASTE FORMS A Thesis by JOO-YANG PARK 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 1994 Major Subject: Civil Engineering THE APPLICATION OF A CHEMICAL EQUILIBRIUM MODEL, SOLTEQ, TO PREDICT THE CHEMICAL SPECIATIONS IN STABILIZED/SOLIDIFIED WASTE FORMS A Thesis...

  14. 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.

  15. 3D Model Retrieval based on Adaptive Views Clustering

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    3D Model Retrieval based on Adaptive Views Clustering Tarik Filali Ansary1 , Mohamed Daoudi2 , Jean.daoudi@univ-tours.fr http://www-rech.enic.fr/miire Abstract. In this paper, we propose a method for 3D model indexing based selection of 2D views from a 3D model, and a probabilistic Bayesian method for 3D model retrieval from

  16. 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

  17. 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.

  18. 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.

  19. Society of Petroleum Engineers A New Approach to Predict Bit Life Based on Tooth or Bearing Failures

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    ms m . . . Society of Petroleum Engineers SPE 51082 A New Approach to Predict Bit Life Based. Aminian, SPE, West Virginia U. Copyright 1998, Society of Petroleum Engineers Inc. This paper was prepared by the Society .of Petroleum Engineers and are subject to correction by the author(s). The material, as presented

  20. Transition Prediction for Scramjet Intakes Using the \\gamma-Re_\\theta_t Model Coupled to Two Turbulence Models

    E-Print Network [OSTI]

    Frauholz, Sarah; Müller, Siegfried; Behr, Marek

    2014-01-01T23:59:59.000Z

    Due to the thick boundary layers in hypersonic flows, the state of the boundary layer significantly influences the whole flow field as well as surface heat loads. Hence, for engineering applications the efficient numerical prediction of laminar-to-turbulent transition is a challenging and important task. Within the framework of the Reynolds averaged Navier-Stokes equations, Langtry/Menter [1] proposed the -Re?t transition model using two transport equations for the intermittency and Re?t combined with the Shear Stress Transport turbulence model (SST) [2]. The transition model contains two empirical correlations for onset and length of transition. Langtry/Menter [1] designed and validated the correlations for the subsonic and transonic flow regime. For our applications in the hypersonic flow regime, the development of a new set of correlations proved necessary, even when using the same SST turbulence model [3]. Within this paper, we propose a next step and couple the transition model with the SSG/LRR-! Reynold...

  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. 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...

  3. 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.

  4. A Simple Path Loss Prediction Model for HVAC Systems O. K. Tonguz, D. D. Stancil, A. E. Xhafa, A. G. Cepni, P. V. Nikitin

    E-Print Network [OSTI]

    Stancil, Daniel D.

    1 A Simple Path Loss Prediction Model for HVAC Systems O. K. Tonguz, D. D. Stancil, A. E. Xhafa, A, and air conditioning (HVAC) cylindrical ducts in 2.4-2.5 GHz frequency band. The model we propose predicts the average power loss between a transmitter-receiver pair in an HVAC duct network. This prediction model

  5. 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.

  6. 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...

  7. 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...

  8. 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.

  9. 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.

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

    SciTech Connect (OSTI)

    Salloum, Maher N.; Gharagozloo, Patricia E.

    2013-10-01T23:59:59.000Z

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

  11. 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.

  12. 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.

  13. Quasi-steady model for predicting temperature of aqueous foams circulating in geothermal wellbores

    SciTech Connect (OSTI)

    Blackwell, B.F.; Ortega, A.

    1983-01-01T23:59:59.000Z

    A quasi-steady model has been developed for predicting the temperature profiles of aqueous foams circulating in geothermal wellbores. The model assumes steady one-dimensional incompressible flow in the wellbore; heat transfer by conduction from the geologic formation to the foam is one-dimensional radially and time-dependent. The vertical temperature distribution in the undisturbed geologic formation is assumed to be composed of two linear segments. For constant values of the convective heat-transfer coefficient, a closed-form analytical solution is obtained. It is demonstrated that the Prandtl number of aqueous foams is large (1000 to 5000); hence, a fully developed temperature profile may not exist for representative drilling applications. Existing convective heat-transfer-coefficient solutions are adapted to aqueous foams. The simplified quasi-steady model is successfully compared with a more-sophisticated finite-difference computer code. Sample temperature-profile calculations are presented for representative values of the primary parameters. For a 5000-ft wellbore with a bottom hole temperature of 375{sup 0}F, the maximum foam temperature can be as high as 300{sup 0}F.

  14. Variance, Skewness & Kurtosis: results from the APM Cluster Redshift Survey and model predictions

    E-Print Network [OSTI]

    Enrique Gaztañaga; Rupert Croft; Gavin Dalton

    1995-01-31T23:59:59.000Z

    We estimate the variance $\\xibar_2$, the skewness $\\xibar_3$ and the kurtosis $\\xibar_4$ in the distribution of density fluctuations in a complete sample from the APM Cluster Redshift Survey with 339 clusters and a mean depth $ \\sim 250\\Mpc$. We are able to measure the statistics of fluctuations in spheres of radius $R \\simeq 5-80 \\Mpc$, with reasonable errorbars. The statistics in the cluster distribution follow the hierarchical pattern $\\xibar_J=S_J~\\xibar_2^{J-1}$ with $S_J$ roughly constant, $S_3 \\simeq 2$ and $S_4 \\sim 8$. We analyse the distribution of clusters taken from N-body simulations of different dark matter models. The results are compared with an alternative method of simulating clusters which uses the truncated Zel'dovich approximation. We argue that this alternative method is not reliable enough for making quantitative predictions of $\\xibar$. The N-body simulation results follow similar hierarchical relations to the observations, with $S_J$ almost unaffected by redshift distortions from peculiar motions. The standard $\\Omega=1$ Cold Dark Matter (CDM) model is inconsistent with either the second, third or fourth order statistics at all scales. However both a hybrid Mixed Dark Matter model and a low density CDM variant agree with the $\\xibar_J$ observations.

  15. 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.

  16. 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.

  17. Engineering Process Coordination based on A Service Event Notification Model

    E-Print Network [OSTI]

    Stanford University

    Engineering Process Coordination based on A Service Event Notification Model Jian Cao1, Jie Wang2 the project lifecycle process. Grid-based engineering service is a potentially useful technology for process coordination. Thus we propose a Grid service based event notification model to support engineering process

  18. Net Balanced Floorplanning Based on Elastic Energy Model

    E-Print Network [OSTI]

    Nannarelli, Alberto

    Net Balanced Floorplanning Based on Elastic Energy Model Wei Liu and Alberto Nannarelli Dept variations can introduce extra signal skew, it is desirable to have floorplans with balanced net delays based on the elastic energy model. The B*-tree, which is based on an ordered binary tree, is used

  19. MODELING AND CONTROLLING PARALLEL TASKS IN DROPLET-BASED MICROFLUIDIC

    E-Print Network [OSTI]

    Chapter 12 MODELING AND CONTROLLING PARALLEL TASKS IN DROPLET-BASED MICROFLUIDIC SYSTEMS Karl F-independent models and algorithms to automate the operation of droplet-based microfluidic systems. In these systems mapping of a biochemical analysis task onto a droplet-based microfluidic system is investigated. Achieving

  20. Fuel Cell System Improvement for Model-Based Diagnosis Analysis

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Fuel Cell System Improvement for Model-Based Diagnosis Analysis Philippe Fiani & Michel Batteux of a model of a fuel cell system, in order to make it usable for model- based diagnosis methods. A fuel cell for the fuel cell stack but also for the system environment. In this paper, we present an adapted library which

  1. PARAMETER ESTIMATION BASED MODELS OF WATER SOURCE HEAT PUMPS

    E-Print Network [OSTI]

    PARAMETER ESTIMATION BASED MODELS OF WATER SOURCE HEAT PUMPS By HUI JIN Bachelor of Science validation of the water-to-air heat pump model. It's hard to find any words to express the thanks to my BASED MODELS OF WATER SLOURCE HEAT PUMPS Thesis Approved: Thesis Adviser Dean of the Graduate College ii

  2. 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.

  3. Optimization of the GB/SA Solvation Model for Predicting the Structure of Surface Loops in Proteins

    E-Print Network [OSTI]

    Meirovitch, Hagai

    Optimization of the GB/SA Solvation Model for Predicting the Structure of Surface Loops in ProteinsVed: October 10, 2005; In Final Form: December 1, 2005 Implicit solvation models are commonly optimized the force field is sometimes not considered. In previous studies, we have developed an optimization

  4. Real-Time Track Prediction of Tropical Cyclones over the North Indian Ocean Using the ARW Model

    E-Print Network [OSTI]

    Real-Time Track Prediction of Tropical Cyclones over the North Indian Ocean Using the ARW Model of Technology Bhubaneswar, Odisha, India A. ROUTRAY National Centre for Medium Range Weather Forecasting, Noida The performance of the Advanced Research version of the Weather Research and Forecasting (ARW) model in real

  5. Conclusions The results show that the models are able to predict the response of the FETi motor

    E-Print Network [OSTI]

    Sóbester, András

    Conclusions The results show that the models are able to predict the response of the FETi motor just one animal might over-fit the noise of that particular animal. However, a model designed strand transmit the movement to the sensory neurons in the FeCO, which excite the motor neurons. Design

  6. 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.

  7. Elements of a pragmatic approach for dealing with bias and uncertainty in experiments through predictions : experiment design and data conditioning; %22real space%22 model validation and conditioning; hierarchical modeling and extrapolative prediction.

    SciTech Connect (OSTI)

    Romero, Vicente Jose

    2011-11-01T23:59:59.000Z

    This report explores some important considerations in devising a practical and consistent framework and methodology for utilizing experiments and experimental data to support modeling and prediction. A pragmatic and versatile 'Real Space' approach is outlined for confronting experimental and modeling bias and uncertainty to mitigate risk in modeling and prediction. The elements of experiment design and data analysis, data conditioning, model conditioning, model validation, hierarchical modeling, and extrapolative prediction under uncertainty are examined. An appreciation can be gained for the constraints and difficulties at play in devising a viable end-to-end methodology. Rationale is given for the various choices underlying the Real Space end-to-end approach. The approach adopts and refines some elements and constructs from the literature and adds pivotal new elements and constructs. Crucially, the approach reflects a pragmatism and versatility derived from working many industrial-scale problems involving complex physics and constitutive models, steady-state and time-varying nonlinear behavior and boundary conditions, and various types of uncertainty in experiments and models. The framework benefits from a broad exposure to integrated experimental and modeling activities in the areas of heat transfer, solid and structural mechanics, irradiated electronics, and combustion in fluids and solids.

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

    SciTech Connect (OSTI)

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

    2010-09-01T23:59:59.000Z

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

  9. SEISMIC RESPONSE PREDICTION OF NUPEC'S FIELD MODEL TESTS OF NPP STRUCTURES WITH ADJACENT BUILDING EFFECT.

    SciTech Connect (OSTI)

    XU,J.COSTANTINO,C.HOFMAYER,C.ALI,S.

    2004-03-04T23:59:59.000Z

    As part of a verification test program for seismic analysis computer codes for Nuclear Power Plant (NPP) structures, the Nuclear Power Engineering Corporation (NUPEC) of Japan has conducted a series of field model tests to address the dynamic cross interaction (DCI) effect on the seismic response of NPP structures built in close proximity to each other. The program provided field data to study the methodologies commonly associated with seismic analyses considering the DCI effect. As part of a collaborative program between the United States and Japan on seismic issues related to NPP applications, the U.S. Nuclear Regulatory Commission sponsored a program at Brookhaven National Laboratory (BNL) to perform independent seismic analyses which applied common analysis procedures to predict the building response to recorded earthquake events for the test models with DCI effect. In this study, two large-scale DCI test model configurations were analyzed: (1) twin reactor buildings in close proximity and (2) adjacent reactor and turbine buildings. This paper describes the NUPEC DCI test models, the BNL analysis using the SASSI 2000 program, and comparisons between the BNL analysis results and recorded field responses. To account for large variability in the soil properties, the conventional approach of computing seismic responses with the mean, mean plus and minus one-standard deviation soil profiles is adopted in the BNL analysis and the three sets of analysis results were used in the comparisons with the test data. A discussion is also provided in the paper to address (1) the capability of the analysis methods to capture the DCI effect, and (2) the conservatism of the practice for considering soil variability in seismic response analysis for adjacent NPP structures.

  10. MIT Big Data Challenge: Transportation in the City of Boston Model of Prediction Challenge

    E-Print Network [OSTI]

    Oliva, Aude

    and for periods before and after the prediction interval. When available, the number of MBTA T rides at nearby

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

    SciTech Connect (OSTI)

    Laskowski, Gregory Michael

    2005-12-01T23:59:59.000Z

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

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

    SciTech Connect (OSTI)

    Garten Jr, Charles T [ORNL

    2012-01-01T23:59:59.000Z

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

  13. A prediction of meander migration based on large-scale flume tests in clay

    E-Print Network [OSTI]

    Park, Namgyu

    2009-05-15T23:59:59.000Z

    great ideas or useful hints for new research concerning the same type of problem. The past research works related to the prediction of meander migration were studied in order to have a better understanding of the existing techniques and an idea of a...

  14. RISK PREDICTION OF A BEHAVIOR-BASED ADHESION CONTROL NETWORK FOR ONLINE SAFETY ANALYSIS OF

    E-Print Network [OSTI]

    Berns, Karsten

    by default. But for wheeled driving on concrete walls via negative pressure adhesion a prediction of risks- ited payload. Also the impact of features like surface roughness, sheathing defects, porous areas is de- signed to be used for inspections of large concrete buildings as depicted in figure 1

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

    SciTech Connect (OSTI)

    Maguire, J.; Burch, J.

    2013-08-01T23:59:59.000Z

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

  16. A bridge-functional-based classical mapping method for predicting the correlation functions of uniform electron gases at finite temperature

    SciTech Connect (OSTI)

    Liu, Yu; Wu, Jianzhong, E-mail: jwu@engr.ucr.edu [Department of Chemical and Environmental Engineering and Department of Mathematics, University of California, Riverside, California 92521 (United States)] [Department of Chemical and Environmental Engineering and Department of Mathematics, University of California, Riverside, California 92521 (United States)

    2014-02-28T23:59:59.000Z

    Efficient and accurate prediction of the correlation functions of uniform electron gases is of great importance for both practical and theoretical applications. This paper presents a bridge-functional-based classical mapping method for calculating the correlation functions of uniform spin-unpolarized electron gases at finite temperature. The bridge functional is formulated by following Rosenfeld's universality ansatz in combination with the modified fundamental measure theory. The theoretical predictions are in good agreement with recent quantum Monte Carlo results but with negligible computational cost, and the accuracy is better than a previous attempt based on the hypernetted-chain approximation. We find that the classical mapping method is most accurate if the effective mass of electrons increases as the density falls.

  17. Brain-Based Learning Theory: An Online Course Design Model.

    E-Print Network [OSTI]

    Tompkins, Abreena Walker

    2007-01-01T23:59:59.000Z

    ??Abstract Abreena W. Tompkins. BRAIN-BASED LEARNING THEORY: AN ONLINE COURSE DESIGN MODEL (Under the direction of Dr. Steven Deckard) School of Education, February, 2006. The… (more)

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

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

    between Geothermal Rocks, Supercritical Carbon Dioxide and Water Experiment-Based Model for the Chemical Interactions between Geothermal Rocks, Supercritical Carbon Dioxide...

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

    SciTech Connect (OSTI)

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

    2014-08-01T23:59:59.000Z

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

  20. Molecular adsorption of alkanes on platinum surfaces: A predictive theoretical model

    SciTech Connect (OSTI)

    Stinnett, J.A.; Madix, R.J. [Department of Chemical Engineering, Stanford University, Stanford, California 94305 (United States)] [Department of Chemical Engineering, Stanford University, Stanford, California 94305 (United States)

    1996-07-01T23:59:59.000Z

    The adsorption probabilities of methane and propane on Pt(111), and propane on Pt(110)-(1{times}2) have been successfully predicted for a wide range of incident energies and angles with classical stochastic trajectory simulations, using a pairwise additive Morse methyl{endash}platinum potential previously developed from the measured trapping probabilities of ethane on Pt(111). These predictions, along with those for ethane adsorption on Pt(110){endash}(1{times}2), comprise a unified model for the molecular adsorption of alkanes on platinum surfaces. The simulations show the initial trapping probabilities of methane and propane on Pt(111) are determined to within approximately 10{percent} by the fate of the first bounce. They also indicate that at normal incidence on Pt(111) energy conversions from perpendicular translational motion to both cartwheeling rotation and lattice phonons play increasingly important roles in increasing the trapping probability as the alkane increases in size and molecular weight. For methane itself excitation of parallel translational momentum after the first bounce serves as the most effective energy storage mechanism which facilitates trapping, whereas for propane cartwheel rotational motion plays the dominant role. Excessive excitation of these modes of motion, however, can cause scattering on subsequent bounces by reconversion of the energy into perpendicular translational energy. Collisions of methane with the hollow and bridge sites on the Pt(111) surface appear less effective in trapping than do atop sites. The simulations also suggest excitation of the C{endash}C{endash}C bending mode of propane has little effect on the trapping of propane on platinum surfaces for beam energies below 55 kJ/mol. {copyright} {ital 1996 American Institute of Physics.}

  1. Development and verification of simplified prediction models for enhanced oil recovery applications. CO/sub 2/ (miscible flood) predictive model. Final report

    SciTech Connect (OSTI)

    Paul, G.W.

    1984-10-01T23:59:59.000Z

    A screening model for CO/sub 2/ miscible flooding has been developed consisting of a reservoir model for oil rate and recovery and an economic model. The reservoir model includes the effects of viscous fingering, reservoir heterogeneity, gravity segregation and areal sweep. The economic model includes methods to calculate various profitability indices, the windfall profits tax, and provides for CO/sub 2/ recycle. The model is applicable to secondary or tertiary floods, and to solvent slug or WAG processes. The model does not require detailed oil-CO/sub 2/ PVT data for execution, and is limited to five-spot patterns. A pattern schedule may be specified to allow economic calculations for an entire project to be made. Models of similar architecture have been developed for steam drive, in-situ combustion, surfactant-polymer flooding, polymer flooding and waterflooding. 36 references, 41 figures, 4 tables.

  2. Time irreversible copula-based Markov Models

    E-Print Network [OSTI]

    Beare, Brendan K.; Seo, Juwon

    2012-01-01T23:59:59.000Z

    retail gasoline markets exhibit prominent Edgeworth priceaverage retail price across a sample of gasoline stations inprice cycles, cost-based pricing and sticky pricing in retail gasoline

  3. Topology-Based Vehicle Systems Modelling.

    E-Print Network [OSTI]

    Yam, Edward

    2013-01-01T23:59:59.000Z

    ??The simulation tools that are used to model vehicle systems have not been advancing as quickly as the growth of research and technology surrounding the… (more)

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

    SciTech Connect (OSTI)

    Langton, C.; Kosson, D.

    2009-11-30T23:59:59.000Z

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

  5. Template-Based Modeling of Protein Structure David Constant

    E-Print Network [OSTI]

    will obviously have an effect on the quality of the ultimate model that is predicted. In recent years, the line this method. Simple BLAST searches comparing sequences to sequences can be sufficient for very easy queries the query to templates using sequence profiles generated by PSI- BLAST or HMM can result

  6. Objective Intelligibility Prediction of Speech by Combining Correlation and Distortion based Techniques

    E-Print Network [OSTI]

    of these techniques has not been found satisfactory for measuring the speech intelligibility of speech enhancement of speech enhancement. We then propose to com- bine these correlation-based techniques with spectral enhancement, correlation-based techniques, spectral distance-based techniques. 1. Introduction In speech

  7. Attribute-based Mining Process for the Organization-Based Access Control Model

    E-Print Network [OSTI]

    Garcia-Alfaro, Joaquin

    to analyze and evaluate the access control systems. A model is a formal presentation of the security policyAttribute-based Mining Process for the Organization-Based Access Control Model Ahmad Samer Wazan}@telecom-sudparis.eu Abstract--Since the late 60's, different security access control models have been proposed. Their rationale

  8. Do Ecological Niche Model Predictions Reflect the Adaptive Landscape of Species?: A Test Using Myristica malabarica Lam., an Endemic Tree in the Western Ghats, India

    E-Print Network [OSTI]

    Nagaraju, Shivaprakash K.; Gudasalamani, Ravikanth; Barve, Narayani; Ghazoul, Jaboury; Narayangowda, Ganeshaiah Kotiganahalli; Ramanan, Uma Shaanker

    2013-11-29T23:59:59.000Z

    Ecological niche models (ENM) have become a popular tool to define and predict the “ecological niche” of a species. An implicit assumption of the ENMs is that the predicted ecological niche of a species actually reflects ...

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

    SciTech Connect (OSTI)

    Yock, Adam D., E-mail: ADYock@mdanderson.org; Kudchadker, Rajat J. [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States)] [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States); Rao, Arvind [Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and the Graduate School of Biomedical Sciences, the University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States)] [Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and the Graduate School of Biomedical Sciences, the University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States); Dong, Lei [Scripps Proton Therapy Center, San Diego, California 92121 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States)] [Scripps Proton Therapy Center, San Diego, California 92121 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States); Beadle, Beth M.; Garden, Adam S. [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 (United States)] [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 (United States); Court, Laurence E. [Department of Radiation Physics and Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States)] [Department of Radiation Physics and Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas 77030 (United States)

    2014-05-15T23:59:59.000Z

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

  10. Comprehensive Thermodynamics of Nickel Hydride Bis(Diphosphine) Complexes: A Predictive Model through Computations

    SciTech Connect (OSTI)

    Chen, Shentan; Rousseau, Roger J.; Raugei, Simone; Dupuis, Michel; DuBois, Daniel L.; Bullock, R. Morris

    2011-11-28T23:59:59.000Z

    Prediction of thermodynamic quantities such as redox potentials and homolytic and heterolytic metal hydrogen bond energies is critical to the a priori design of molecular catalysts. In this paper we expound upon a density functional theory (DFT)-based isodesmic methodology for the accurate computation of the above quantities across a series of Ni(diphosphine)2 complexes compounds that are potential catalysts for production of H2 from protons and electrons, or oxidation of H2 to electrons and protons. Isodesmic schemes give relative free energies between the complex of interest and a reference system. A natural choice is to use as a reference a compound that shares similarities with the chemical species under study and for which the properties of interest have been measured with accuracy. However, this is not always possible as in the case of the Ni complexes considered here where data are experimentally available for only some species. To overcome this difficulty we employed a theoretical reference compound, Ni(PH3)4, which is amenable to highly accurate electron-correlated calculations, which allows one to explore thermodynamics properties even when no experimental input is accessible. The reliability of this reference is validated against the available thermodynamics data in acetonitrile solution. Overall the proposed protocol yields excellent accuracy for redox potentials (~ 0.10 eV of accuracy), for acidities (~1.5 pKa units of accuracy), for hydricities (~2 kcal/mol of accuracy), and for homolytic bond dissociation free energies (~ 1-2 kcal/mol of accuracy). The calculated thermodynamic properties are then analyzed for a broad set of Ni complexes. The power of the approach is demonstrated through the validation of previously reported linear correlations among properties. New correlations are revealed. It emerges that only two quantities, the Ni(II)/Ni(I) and Ni(I)/Ni(0) redox potentials (which are easily accessible experimentally), suffice to predict with high confidence the energetics of all relevant species involved in the catalytic cycles for H2 oxidation and production. The approach is extendable to other transition metal complexes. This material is based upon work supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the US Department of Energy, Office of Science, Office of Basic Energy Sciences.

  11. Virginia Tech Comprehensive Power-Based Fuel Consumption Model: Modeling Diesel1 and Hybrid Buses2

    E-Print Network [OSTI]

    Rakha, Hesham A.

    Virginia Tech Comprehensive Power-Based Fuel Consumption Model: Modeling Diesel1 and Hybrid Buses2 is to extend the Virginia Tech Comprehensive Power-Based9 Fuel Consumption Model (VT-CPFM) to include diesel There are currently very few models for estimating diesel and hybrid bus fuel consumption and2 CO2 emission levels

  12. Modelling Business Energy Consumption using Agent-based Simulation Modelling Jason Wong and Kay Cao1

    E-Print Network [OSTI]

    Modelling Business Energy Consumption using Agent-based Simulation Modelling Jason Wong and Kay Cao to develop a prototype agent based simulation model for business energy consumption, using data from the 2008 presents a framework of the model for estimating business energy consumption. Section V discusses the data

  13. SEMANTIC LEARNING MODEL AND EXTENDED STUDENT MODEL: TOWARDS AN AHAM-BASED ADAPTIVE SYSTEM

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    SEMANTIC LEARNING MODEL AND EXTENDED STUDENT MODEL: TOWARDS AN AHAM-BASED ADAPTIVE SYSTEM Hend hypermedia systems, we distinguish AHAM as the most popular reference model which is based on the Dexter hoc integration of the AHAM's user's model as well as the IMS/LIP and IEEE/PAPI standards. KEY WORDS

  14. A Mechanism-Based Approach to Predict the Relative Biological Effectiveness of Protons and Carbon Ions in Radiation Therapy

    SciTech Connect (OSTI)

    Frese, Malte C. [Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut (United States); Department of Medical Physics in Radiation Oncology, German Cancer Research Center, Heidelberg (Germany); Yu, Victor K. [Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut (United States); Stewart, Robert D. [Department of Radiation Oncology, University of Washington, Seattle, Washington (United States); Carlson, David J., E-mail: david.j.carlson@yale.edu [Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut (United States)

    2012-05-01T23:59:59.000Z

    Purpose: The physical and potential biological advantages of proton and carbon ions have not been fully exploited in radiation therapy for the treatment of cancer. In this work, an approach to predict proton and carbon ion relative biological effectiveness (RBE) in a representative spread-out Bragg peak (SOBP) is derived using the repair-misrepair-fixation (RMF) model. Methods and Materials: Formulas linking dose-averaged linear-quadratic parameters to DSB induction and processing are derived from the RMF model. The Monte Carlo Damage Simulation (MCDS) software is used to quantify the effects of radiation quality on the induction of DNA double-strand breaks (DSB). Trends in parameters {alpha} and {beta} for clinically relevant proton and carbon ion kinetic energies are determined. Results: Proton and carbon ion RBE are shown to increase as particle energy, dose, and tissue {alpha}/{beta} ratios decrease. Entrance RBE is {approx}1.0 and {approx}1.3 for protons and carbon ions, respectively. For doses in the range of 0.5 to 10 Gy, proton RBE ranges from 1.02 (proximal edge) to 1.4 (distal edge). Over the same dose range, the RBE for carbon ions ranges from 1.5 on the proximal edge to 6.7 on the distal edge. Conclusions: The proposed approach is advantageous because the RBE for clinically relevant particle distributions is guided by well-established physical and biological (track structure) considerations. The use of an independently tested Monte Carlo model to predict the effects of radiation quality on DSB induction also minimizes the number of ad hoc biological parameters that must be determined to predict RBE. Large variations in predicted RBE across an SOBP may produce undesirable biological hot and cold spots. These results highlight the potential for the optimization of physical dose for a uniform biological effect.

  15. Institute for Software Technology Model-Based Testing

    E-Print Network [OSTI]

    t Institute for Software Technology Model-Based Testing Ausgewählte Kapitel Softwaretechnologie 2 2013/14 B.K. Aichernig Model-Based Testing 1 / 38 #12;t Institute for Software Technology Testing Testing: checking or measuring some quality characteristics of an executing system by performing

  16. Analysis and Model-Based Control of Servomechanisms With Friction

    E-Print Network [OSTI]

    Papadopoulos, Evangelos

    Analysis and Model-Based Control of Servomechanisms With Friction Evangelos G. Papadopoulos e Engineering, National Technical University of Athens, 15780 Athens, Greece Friction is responsible for several, model-based feedback compensation is studied for servomechanism tracking tasks. Several kinetic friction

  17. Integration of the predictions of two models with dose measurements in a1 case study of children exposed to the emissions of a lead smelter2

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    exposed to the emissions of a lead smelter2 Abstract3 The predictions of two source-to-dose models lead smelter. Both5 models were built up from several sub-models linked together and run using Monte

  18. Vapor pressure and boiling point elevation of slash pine black liquors: Predictive models with statistical approach

    SciTech Connect (OSTI)

    Zaman, A.A.; McNally, T.W.; Fricke, A.L. [Univ. of Florida, Gainesville, FL (United States)] [Univ. of Florida, Gainesville, FL (United States)

    1998-01-01T23:59:59.000Z

    Vapor-liquid equilibria and boiling point elevation of slash pine kraft black liquors over a wide range of solid concentrations (up to 85% solids) has been studied. The liquors are from a statistically designed pulping experiment for pulping slash pine in a pilot scale digester with four cooking variables of effective alkali, sulfidity, cooking time, and cooking temperature. It was found that boiling point elevation of black liquors is pressure dependent, and this dependency is more significant at higher solids concentrations. The boiling point elevation data at different solids contents (at a fixed pressure) were correlated to the dissolved solids (S/(1 {minus} S)) in black liquor. Due to the solubility limit of some of the salts in black liquor, a change in the slope of the boiling point elevation as a function of the dissolved solids was observed at a concentration of around 65% solids. An empirical method was developed to describe the boiling point elevation of each liquor as a function of pressure and solids mass fraction. The boiling point elevation of slash pine black liquors was correlated quantitatively to the pulping variables, using different statistical procedures. These predictive models can be applied to determine the boiling point rise (and boiling point) of slash pine black liquors at processing conditions from the knowledge of pulping variables. The results are presented, and their utility is discussed.

  19. E-Print Network 3.0 - ai based prediction Sample Search Results

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

    Computer Technologies and Information Sciences 32 A Semantic Navigation Model for Video Games Leonard van Driel and Rafael Bidarra Summary: . In this paper we develop a generic...

  20. 48 OCTOBER | 2010 Near Term Power PredicTioN

    E-Print Network [OSTI]

    Kusiak, Andrew

    48 OCTOBER | 2010 Near Term Power PredicTioN wiNd eNergy is becomiNg a sigNificaNT player are presented. The first model for power prediction is developed based on the power curve equation [1 equation, data-mining algorithms can be directly applied to predict the power based on parameters

  1. An ignition and combustion model based on the level-set method for spark ignition engine multidimensional modeling

    SciTech Connect (OSTI)

    Tan, Zhichao; Reitz, Rolf D. [Engine Research Center, University of Wisconsin-Madison, 1500 Engineering Drive, Madison, WI 53706 (United States)

    2006-04-15T23:59:59.000Z

    To improve the prediction accuracy of the spark ignition and combustion processes in spark ignition engines, improved ignition and flame propagation models have been developed and implemented in the CFD code, KIVA-3V. An equation to calculate the spark ignition kernel growth rate is derived that considers the effects of the spark ignition discharge energy and flow turbulence on the ignition kernel growth. In addition, a flamelet combustion model based on the G equation combustion model was developed and implemented. To test the ignition and combustion models, they were applied to a homogeneous charge pancake-shaped-combustion-chamber engine, in which experimental heat flux data from probes in the engine head and cylinder liner were available. By comparing the flame arrival timings with the simulation predictions, the ignition and combustion models were validated. In addition, the models were also applied to a homogeneous charge propane-fueled SI engine. Good agreement with experimental cylinder pressures and NO{sub x} data was obtained as a function of ignition timing, engine speed, and EGR levels. (author)

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

    SciTech Connect (OSTI)

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

    1996-08-09T23:59:59.000Z

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

  3. Modeling the Ductile Brittle Fracture Transition in Reactor Pressure Vessel Steels using a Cohesive Zone Model based approach

    SciTech Connect (OSTI)

    Pritam Chakraborty; S. Bulent Biner

    2013-10-01T23:59:59.000Z

    Fracture properties of Reactor Pressure Vessel (RPV) steels show large variations with changes in temperature and irradiation levels. Brittle behavior is observed at lower temperatures and/or higher irradiation levels whereas ductile mode of failure is predominant at higher temperatures and/or lower irradiation levels. In addition to such temperature and radiation dependent fracture behavior, significant scatter in fracture toughness has also been observed. As a consequence of such variability in fracture behavior, accurate estimates of fracture properties of RPV steels are of utmost importance for safe and reliable operation of reactor pressure vessels. A cohesive zone based approach is being pursued in the present study where an attempt is made to obtain a unified law capturing both stable crack growth (ductile fracture) and unstable failure (cleavage fracture). The parameters of the constitutive model are dependent on both temperature and failure probability. The effect of irradiation has not been considered in the present study. The use of such a cohesive zone based approach would allow the modeling of explicit crack growth at both stable and unstable regimes of fracture. Also it would provide the possibility to incorporate more physical lower length scale models to predict DBT. Such a multi-scale approach would significantly improve the predictive capabilities of the model, which is still largely empirical.

  4. Action Selection and Mental Transformation Based on a Chain of Forward Models

    E-Print Network [OSTI]

    Hoffmann, Heiko

    are internal sensorimotor models that predict how the sensory situation changes as a result of an agent- motor models and specifically forward models are sup- posed to be involved. Wolpert et al. (2003) for using a chain of forward models for prediction). Instead of trying to model hu- mans or animals, we

  5. Cross-comparison of spacecraft-environment interaction model predictions applied to Solar Probe Plus near perihelion

    SciTech Connect (OSTI)

    Marchand, R. [Department of Physics, University of Alberta, Edmonton, Alberta T6G 2E1 (Canada); Miyake, Y.; Usui, H. [Graduate School of System Informatics, Kobe University, Kobe 657-8501 (Japan); Deca, J.; Lapenta, G. [Centre for Mathematical Plasma Astrophysics, Mathematics Department, KU Leuven, Celestijnenlaan 200B bus 2400, 3001 Leuven (Belgium); Matéo-Vélez, J. C. [Department of Space Environment, Onera—The French Aerospace Lab, Toulouse (France); Ergun, R. E.; Sturner, A. [Department of Astrophysical and Planetary Science, University of Colorado, Boulder, Colorado 80309 (United States); Génot, V. [Institut de Recherche en Astrophysique et Planétologie, Université de Toulouse, France and CNRS, IRAP, 9 Av. colonel Roche, BP 44346, 31028 Toulouse cedex 4 (France); Hilgers, A. [ESA, ESTEC, Keplerlaan 1, PO Box 299, 2200 AG Noordwijk (Netherlands); Markidis, S. [High Performance Computing and Visualization Department, KTH Royal Institute of Technology, Stockholm (Sweden)

    2014-06-15T23:59:59.000Z

    Five spacecraft-plasma models are used to simulate the interaction of a simplified geometry Solar Probe Plus (SPP) satellite with the space environment under representative solar wind conditions near perihelion. By considering similarities and differences between results obtained with different numerical approaches under well defined conditions, the consistency and validity of our models can be assessed. The impact on model predictions of physical effects of importance in the SPP mission is also considered by comparing results obtained with and without these effects. Simulation results are presented and compared with increasing levels of complexity in the physics of interaction between solar environment and the SPP spacecraft. The comparisons focus particularly on spacecraft floating potentials, contributions to the currents collected and emitted by the spacecraft, and on the potential and density spatial profiles near the satellite. The physical effects considered include spacecraft charging, photoelectron and secondary electron emission, and the presence of a background magnetic field. Model predictions obtained with our different computational approaches are found to be in agreement within 2% when the same physical processes are taken into account and treated similarly. The comparisons thus indicate that, with the correct description of important physical effects, our simulation models should have the required skill to predict details of satellite-plasma interaction physics under relevant conditions, with a good level of confidence. Our models concur in predicting a negative floating potential V{sub fl}??10V for SPP at perihelion. They also predict a “saturated emission regime” whereby most emitted photo- and secondary electron will be reflected by a potential barrier near the surface, back to the spacecraft where they will be recollected.

  6. Kinetic data base for combustion modeling

    SciTech Connect (OSTI)

    Tsang, W.; Herron, J.T. [National Institute of Standards and Technology, Gaithersburg, MD (United States)

    1993-12-01T23:59:59.000Z

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

  7. Development of a cell-based stream flow routing model

    E-Print Network [OSTI]

    Raina, Rajeev

    2005-08-29T23:59:59.000Z

    al. (1994) developed a 2.00x2.50 resolution river routing model for a number of World Rivers, coupled with an atmospheric-ocean model. The GCM of NASA/Goddard Institute for Space Studies (GISS) (Hansen et al., 1983) was used to calculate the runoff... resolution of 2.00 X 2.50 using the coarse river network developed by Miller et al. (1994). Input to each of the grid cell was derived from the improved GISS GCM (Hansen et al., 1983), which improved the model prediction of discharge. Costa and Foley (1997...

  8. Stroke Fragmentation based on Geometry Features and Hidden Markov Model

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Stroke Fragmentation based on Geometry Features and Hidden Markov Model Guihuan Feng, Christian Viard-Gaudin, Technical Report, IRCCyN Nantes/IVC ABSTRACT Stroke fragmentation is one of the key steps in pen-based interaction. In this letter, we present a unified HMM-based stroke fragmentation technique

  9. Kinetic model for predicting the concentrations of active halogens species in chlorinated saline cooling waters. Final report

    SciTech Connect (OSTI)

    Haag, W.R.; Lietzke, M.H.

    1981-08-01T23:59:59.000Z

    A kinetic model has been developed for describing the speciation of chlorine-produced oxidants in seawater as a function of time. The model is applicable under a broad variety of conditions, including all pH range, salinities, temperatures, ammonia concentrations, organic amine concentrations, and chlorine doses likely to be encountered during power plant cooling water chlorination. However, the effects of sunlight are not considered. The model can also be applied to freshwater and recirculating water systems with cooling towers. The results of the model agree with expectation, however, complete verification is not feasible at the present because analytical methods for some of the predicted species are lacking.

  10. Extracting Business Rules from COBOL: A Model-Based Tool

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Extracting Business Rules from COBOL: A Model-Based Tool Valerio Cosentino AtlanMod, INRIA, EMN and we provide a set of model transformations to identify and visualize the embedded business rules at this point. This model will be then manipulated in the next steps to extract the business rules

  11. Prediction of the Tool Displacement by Coupled Models of the Compliant Industrial Robot and the Milling Process

    E-Print Network [OSTI]

    Stryk, Oskar von

    Prediction of the Tool Displacement by Coupled Models of the Compliant Industrial Robot@sim.tu-darmstadt.de Abstract Using an industrial robot for machining parts provides a cost-saving and flexible alternative Interaction, Milling Process, Robot Structure 1 INTRODUCTION The major field of cutting applications

  12. The Quality of a 48-Hours Wind Power Forecast Using the German and Danish Weather Prediction Model

    E-Print Network [OSTI]

    Heinemann, Detlev

    numerical weather prediction models operated by the weather services are refined by taking into account stock exchange. The typical predic- tion time horizon which is needed for these purposes is 3 to 48 are applied taking into account the effects from lo- cal roughness, thermal stratification of the atmosphere

  13. Using Wild Oat Growth and Development to Develop a Predictive Model for Spring Wheat Growers and Consultants

    E-Print Network [OSTI]

    Minnesota, University of

    Using Wild Oat Growth and Development to Develop a Predictive Model for Spring Wheat Growers Introduction: Wild oat has become an invasive and economically important weedy species in most cereal growing% of the wheat and 72% of barley acres seeded in northwestern Minnesota are infested with wild oat. In the past

  14. Artificial neural networks: Principle and application to model based control of drying systems -- A review

    SciTech Connect (OSTI)

    Thyagarajan, T.; Ponnavaikko, M. [Crescent Engineering Coll., Madras (India); Shanmugam, J. [Madras Inst. of Tech. (India); Panda, R.C.; Rao, P.G. [Central Leather Research Inst., Madras (India)

    1998-07-01T23:59:59.000Z

    This paper reviews the developments in the model based control of drying systems using Artificial Neural Networks (ANNs). Survey of current research works reveals the growing interest in the application of ANN in modeling and control of non-linear, dynamic and time-variant systems. Over 115 articles published in this area are reviewed. All landmark papers are systematically classified in chronological order, in three distinct categories; namely, conventional feedback controllers, model based controllers using conventional methods and model based controllers using ANN for drying process. The principles of ANN are presented in detail. The problems and issues of the drying system and the features of various ANN models are dealt with up-to-date. ANN based controllers lead to smoother controller outputs, which would increase actuator life. The paper concludes with suggestions for improving the existing modeling techniques as applied to predicting the performance characteristics of dryers. The hybridization techniques, namely, neural with fuzzy logic and genetic algorithms, presented, provide, directions for pursuing further research for the implementation of appropriate control strategies. The authors opine that the information presented here would be highly beneficial for pursuing research in modeling and control of drying process using ANN. 118 refs.

  15. Model-based Safety Risk Assessment

    E-Print Network [OSTI]

    Lindsay, Peter

    development life-cycle, in order to identify critical system requirements, such as safety requirements their effectiveness, early in the system development life-cycle, on models derived directly from natural language of functional requirements of arbitrary detail ­ whether it is very early in the life-cycle when functions

  16. IC performance prediction system

    E-Print Network [OSTI]

    Ramakrishnan, Venkatakrishnan

    1996-01-01T23:59:59.000Z

    electrical test data, supplemented with in-line and in-situ data to make performance predictions. Based on the waterlevel parametric test, we will predict chip performance in order to select the appropriate package. Predictions that fall outside acceptable...

  17. Bayesian merging of multiple climate model forecasts for seasonal hydrological predictions

    E-Print Network [OSTI]

    Pan, Ming

    manage- ment, and energy and transportation sectors are a few among many others that will benefit through, such as the National Centers for Environmental Prediction (NCEP) [Kanamitsu et al., 2002], International Research predictions of soil moisture and streamflow, can have great values to our society. Agriculture, water resource

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

    SciTech Connect (OSTI)

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

    2003-07-01T23:59:59.000Z

    A Chemical-structure-based PolyUrethane Foam (CPUF) decomposition model has been developed to predict the fire-induced response of rigid, closed-cell polyurethane foam-filled systems. The model, developed for the B-61 and W-80 fireset foam, is based on a cascade of bondbreaking reactions that produce CO2. Percolation theory is used to dynamically quantify polymer fragment populations of the thermally degrading foam. The partition between condensed-phase polymer fragments and gas-phase polymer fragments (i.e. vapor-liquid split) was determined using a vapor-liquid equilibrium model. The CPUF decomposition model was implemented into the finite element (FE) heat conduction codes COYOTE and CALORE, which support chemical kinetics and enclosure radiation. Elements were removed from the computational domain when the calculated solid mass fractions within the individual finite element decrease below a set criterion. Element removal, referred to as ?element death,? creates a radiation enclosure (assumed to be non-participating) as well as a decomposition front, which separates the condensed-phase encapsulant from the gas-filled enclosure. All of the chemistry parameters as well as thermophysical properties for the CPUF model were obtained from small-scale laboratory experiments. The CPUF model was evaluated by comparing predictions to measurements. The validation experiments included several thermogravimetric experiments at pressures ranging from ambient pressure to 30 bars. Larger, component-scale experiments were also used to validate the foam response model. The effects of heat flux, bulk density, orientation, embedded components, confinement and pressure were measured and compared to model predictions. Uncertainties in the model results were evaluated using a mean value approach. The measured mass loss in the TGA experiments and the measured location of the decomposition front were within the 95% prediction limit determined using the CPUF model for all of the experiments where the decomposition gases were vented sufficiently. The CPUF model results were not as good for the partially confined radiant heat experiments where the vent area was regulated to maintain pressure. Liquefaction and flow effects, which are not considered in the CPUF model, become important when the decomposition gases are confined.

  19. Simulink Based Model of Photovoltaic Cell

    E-Print Network [OSTI]

    Mr. G. Venkateswarlu; Dr. Psangameswar Raju

    ABSTRACT: The potential for solar energy as a sustainable source of energy is well understood. With the ever increasing use of solar power the necessity of a model is accentuated. The aim of this work is to study the variation of PV module main characteristic parameters as a function of shading, with a special attention to the relationship between output power lowering due to shading.

  20. Numerical Modeling of Thermal EOR: Comprehensive Coupling of an AMR-Based Model

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Numerical Modeling of Thermal EOR: Comprehensive Coupling of an AMR-Based Model of Thermal Fluid.renard@ifpen.fr * Corresponding author Résumé -- Modélisation numérique d'EOR thermique : couplage complet entre un modèle d of Thermal EOR: Comprehensive Coupling of an AMR-Based Model of Thermal Fluid Flow and Geomechanics