National Library of Energy BETA

Sample records for model predictive control

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

    SciTech Connect (OSTI)

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

    2012-07-22

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

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

    SciTech Connect (OSTI)

    B. Wayne Bequette; Priyadarshi Mahapatra

    2010-08-31

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

  3. Adaptive model predictive process control using neural networks

    DOE Patents [OSTI]

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

    1997-01-01

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

  4. Adaptive model predictive process control using neural networks

    DOE Patents [OSTI]

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

    1997-08-19

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

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

    SciTech Connect (OSTI)

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

    2010-06-29

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

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

    SciTech Connect (OSTI)

    Xavier, MA; Trimboli, MS

    2015-07-01

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

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

    SciTech Connect (OSTI)

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

    2014-02-01

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

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

    DOE Patents [OSTI]

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

    2013-04-09

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

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

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

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

    2015-07-14

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

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

    SciTech Connect (OSTI)

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

    2015-06-02

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

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

    SciTech Connect (OSTI)

    Kohler, Christian

    2012-08-01

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

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

    SciTech Connect (OSTI)

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

    2013-01-07

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

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

    SciTech Connect (OSTI)

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

    2013-04-03

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

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

    SciTech Connect (OSTI)

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

    2010-06-29

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

  15. Battery Life Predictive Model

    Energy Science and Technology Software Center (OSTI)

    2009-12-31

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

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

    SciTech Connect (OSTI)

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

    2014-05-01

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

  17. predictive modeling | National Nuclear Security Administration

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

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

  18. predictive-models | netl.doe.gov

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

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

  19. Towards feasible and effective predictive wavefront control for...

    Office of Scientific and Technical Information (OSTI)

    predictive wavefront control for adaptive optics Citation Details In-Document Search Title: Towards feasible and effective predictive wavefront control for adaptive optics We ...

  20. Towards feasible and effective predictive wavefront control for...

    Office of Scientific and Technical Information (OSTI)

    Service, Springfield, VA at www.ntis.gov. We have recently proposed Predictive Fourier Control, a computationally efficient and adaptive algorithm for predictive wavefront...

  1. Dynamic model predicts well bore surge and swab pressures

    SciTech Connect (OSTI)

    Bing, Z.; Kaiji, Z.

    1996-12-30

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

  2. Integrated Environmental Control Model

    Energy Science and Technology Software Center (OSTI)

    1999-09-03

    IECM is a powerful multimedia engineering software program for simulating an integrated coal-fired power plant. It provides a capability to model various conventional and advanced processes for controlling air pollutant emissions from coal-fired power plants before, during, or after combustion. The principal purpose of the model is to calculate the performance, emissions, and cost of power plant configurations employing alternative environmental control methods. The model consists of various control technology modules, which may be integratedmore » into a complete utility plant in any desired combination. In contrast to conventional deterministic models, the IECM offers the unique capability to assign probabilistic values to all model input parameters, and to obtain probabilistic outputs in the form of cumulative distribution functions indicating the likelihood of dofferent costs and performance results. A Graphical Use Interface (GUI) facilitates the configuration of the technologies, entry of data, and retrieval of results.« less

  3. Predictive Models of Li-ion Battery Lifetime

    SciTech Connect (OSTI)

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

    2015-06-15

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

  4. Voltage control in pulsed system by predict-ahead control

    DOE Patents [OSTI]

    Payne, Anthony N.; Watson, James A.; Sampayan, Stephen E.

    1994-01-01

    A method and apparatus for predict-ahead pulse-to-pulse voltage control in a pulsed power supply system is disclosed. A DC power supply network is coupled to a resonant charging network via a first switch. The resonant charging network is coupled at a node to a storage capacitor. An output load is coupled to the storage capacitor via a second switch. A de-Q-ing network is coupled to the resonant charging network via a third switch. The trigger for the third switch is a derived function of the initial voltage of the power supply network, the initial voltage of the storage capacitor, and the present voltage of the storage capacitor. A first trigger closes the first switch and charges the capacitor. The third trigger is asserted according to the derived function to close the third switch. When the third switch is closed, the first switch opens and voltage on the node is regulated. The second trigger may be thereafter asserted to discharge the capacitor into the output load.

  5. Voltage control in pulsed system by predict-ahead control

    DOE Patents [OSTI]

    Payne, A.N.; Watson, J.A.; Sampayan, S.E.

    1994-09-13

    A method and apparatus for predict-ahead pulse-to-pulse voltage control in a pulsed power supply system is disclosed. A DC power supply network is coupled to a resonant charging network via a first switch. The resonant charging network is coupled at a node to a storage capacitor. An output load is coupled to the storage capacitor via a second switch. A de-Q-ing network is coupled to the resonant charging network via a third switch. The trigger for the third switch is a derived function of the initial voltage of the power supply network, the initial voltage of the storage capacitor, and the present voltage of the storage capacitor. A first trigger closes the first switch and charges the capacitor. The third trigger is asserted according to the derived function to close the third switch. When the third switch is closed, the first switch opens and voltage on the node is regulated. The second trigger may be thereafter asserted to discharge the capacitor into the output load. 4 figs.

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

  11. Testing model for predicting spillway cavitation damage

    SciTech Connect (OSTI)

    Lee, W.; Hoopes, J.A.

    1995-12-31

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

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

    SciTech Connect (OSTI)

    Nielsen, P.V.

    1998-10-01

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

  13. New model accurately predicts reformate composition

    SciTech Connect (OSTI)

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

    1994-01-31

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

  14. Progress towards a PETN Lifetime Prediction Model

    SciTech Connect (OSTI)

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

    2006-09-11

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

  15. An Anisotropic Hardening Model for Springback Prediction

    SciTech Connect (OSTI)

    Zeng, Danielle; Xia, Z. Cedric

    2005-08-05

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

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

    SciTech Connect (OSTI)

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

    2007-10-01

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

  17. Using micro saint to predict performance in a nuclear power plant control room

    SciTech Connect (OSTI)

    Lawless, M.T.; Laughery, K.R.; Persenky, J.J.

    1995-09-01

    The United States Nuclear Regulatory Commission (NRC) requires a technical basis for regulatory actions. In the area of human factors, one possible technical basis is human performance modeling technology including task network modeling. This study assessed the feasibility and validity of task network modeling to predict the performance of control room crews. Task network models were built that matched the experimental conditions of a study on computerized procedures that was conducted at North Carolina State University. The data from the {open_quotes}paper procedures{close_quotes} conditions were used to calibrate the task network models. Then, the models were manipulated to reflect expected changes when computerized procedures were used. These models` predictions were then compared to the experimental data from the {open_quotes}computerized conditions{close_quotes} of the North Carolina State University study. Analyses indicated that the models predicted some subsets of the data well, but not all. Implications for the use of task network modeling are discussed.

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

    SciTech Connect (OSTI)

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

    2014-09-01

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

  19. Stimulation Prediction Models | Open Energy Information

    Open Energy Info (EERE)

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

  20. Predictable SCR co-benefits for mercury control

    SciTech Connect (OSTI)

    Pritchard, S.

    2009-01-15

    A test program, performed in cooperation with Dominion Power and the Babcock and Wilcox Co., was executed at Dominion Power's Mount Storm power plant in Grant County, W. Va. The program was focused on both the selective catalytic reduction (SCR) catalyst capability to oxide mercury as well as the scrubber's capability to capture and retain the oxidized mercury. This article focuses on the SCR catalyst performance aspects. The Mount Storm site consists of three units totaling approximately 1,660 MW. All units are equipped with SCR systems for NOx control. A full-scale test to evaluate the effect of the SCR was performed on Unit 2, a 550 MWT-fired boiler firing a medium sulfur bituminous coal. This test program demonstrated that the presence of an SCR catalyst can significantly affect the mercury speciation profile. Observation showed that in the absence of an SCR catalyst, the extent of oxidation of element a mercury at the inlet of the flue gas desulfurization system was about 64%. The presence of a Cornertech SCR catalyst improved this oxidation to levels greater than 95% almost all of which was captured by the downstream wet FGD system. Cornertech's proprietary SCR Hg oxidation model was used to accurately predict the field results. 1 ref., 2 figs., 1 tab.

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

  3. Predictive modeling of reactive wetting and metal joining.

    SciTech Connect (OSTI)

    van Swol, Frank B.

    2013-09-01

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

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

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

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

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

    SciTech Connect (OSTI)

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

    2010-01-01

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

  6. Degradation Mechanisms and Lifetime Prediction for Lithium-Ion Batteries -- A Control Perspective: Preprint

    SciTech Connect (OSTI)

    Smith, Kandler; Shi, Ying; Santhanagopalan, Shriram

    2015-07-29

    Predictive models of Li-ion battery lifetime must consider a multiplicity of electrochemical, thermal, and mechanical degradation modes experienced by batteries in application environments. To complicate matters, Li-ion batteries can experience different degradation trajectories that depend 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. We present a generalized battery life prognostic model framework for battery systems design and control. The model framework consists of trial functions that are statistically regressed to Li-ion cell life datasets wherein the cells have been aged under different levels of stress. Degradation mechanisms and rate laws dependent on temperature, storage, and cycling condition are regressed to the data, with multiple model hypotheses evaluated and the best model down-selected based on statistics. The resulting life prognostic model, implemented in state variable form, is extensible to arbitrary real-world scenarios. The model is applicable in real-time control algorithms to maximize battery life and performance. We discuss efforts to reduce lifetime prediction error and accommodate its inevitable impact in controller design.

  7. CFD Modeling for Mercury Control Technology

    SciTech Connect (OSTI)

    Madsen, J.I.

    2006-12-01

    Compliance with the Clean Air Mercury Rule will require implementation of dedicated mercury control solutions at a significant portion of the U.S. coal-fired utility fleet. Activated Carbon Injection (ACI) upstream of a particulate control device (ESP or baghouse) remains one of the most promising near-term mercury control technologies. The DOE/NETL field testing program has advanced the understanding of mercury control by ACI, but a persistent need remains to develop predictive models that may improve the understanding and practical implementation of this technology. This presentation describes the development of an advanced model of in-flight mercury capture based on Computational Fluid Dynamics (CFD). The model makes detailed predictions of the induct spatial distribution and residence time of sorbent, as well as predictions of mercury capture efficiency for particular sorbent flow rates and injection grid configurations. Hence, CFD enables cost efficient optimization of sorbent injection systems for mercury control to a degree that would otherwise be impractical both for new and existing plants. In this way, modeling tools may directly address the main cost component of operating an ACI system the sorbent expense. A typical 300 MW system is expected to require between $1 and $2 million of sorbent per year, and so even modest reductions (say 10-20%) in necessary sorbent feed injection rates will quickly make any optimization effort very worthwhile. There are few existing models of mercury capture, and these typically make gross assumptions of plug gas flow, zero velocity slip between particle and gas phase, and uniform sorbent dispersion. All of these assumptions are overcome with the current model, which is based on first principles and includes mass transfer processes occurring at multiple scales, ranging from the large-scale transport in the duct to transport within the porous structure of a sorbent particle. In principle any single one of these processes

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

    SciTech Connect (OSTI)

    Tippett, Michael K.

    2014-04-09

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

  9. LHC diphoton Higgs signal predicted by little Higgs models

    SciTech Connect (OSTI)

    Wang Lei; Yang Jinmin

    2011-10-01

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

  10. New model predicts once-mysterious chemical reactions

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

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

  11. A predictive ocean oil spill model

    SciTech Connect (OSTI)

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

    1996-07-01

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

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

    SciTech Connect (OSTI)

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

    2007-07-01

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

  13. SimTable helps firefighters model and predict fire direction

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

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

  14. In silico modeling to predict drug-induced phospholipidosis

    SciTech Connect (OSTI)

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

    2013-06-01

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

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

    SciTech Connect (OSTI)

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

    1996-04-01

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

  16. Statistical thermodynamics model and empirical correlations for predicting

    Office of Scientific and Technical Information (OSTI)

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

  17. PV Module Intraconnect Thermomechanical Durability Damage Prediction Model

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

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

  20. Predictive models of circulating fluidized bed combustors

    SciTech Connect (OSTI)

    Gidaspow, D.

    1992-07-01

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

  1. Predictive powertrain control using powertrain history and GPS data

    DOE Patents [OSTI]

    Weslati, Feisel; Krupadanam, Ashish A

    2015-03-03

    A method and powertrain apparatus that predicts a route of travel for a vehicle and uses historical powertrain loads and speeds for the predicted route of travel to optimize at least one powertrain operation for the vehicle.

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

    National Nuclear Security Administration (NNSA)

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

  3. Mathematical modeling to predict residential solid waste generation

    SciTech Connect (OSTI)

    Ojeda Benitez, Sara; Vega, Carolina Armijo de

    2008-07-01

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

  4. Lepton Flavor Violation in Predictive SUSY-GUT Models

    SciTech Connect (OSTI)

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

    2008-02-01

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

  5. Predictive RANS simulations via Bayesian Model-Scenario Averaging

    SciTech Connect (OSTI)

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

    2014-10-15

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

  6. Product component genealogy modeling and field-failure prediction

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

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

    2016-04-13

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

  7. The origins of computer weather prediction and climate modeling

    SciTech Connect (OSTI)

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

    2008-03-20

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

  8. Numerical prediction of energy consumption in buildings with controlled interior temperature

    SciTech Connect (OSTI)

    Jarošová, P.; Št’astník, S.

    2015-03-10

    New European directives bring strong requirement to the energy consumption of building objects, supporting the renewable energy sources. Whereas in the case of family and similar houses this can lead up to absurd consequences, for building objects with controlled interior temperature the optimization of energy demand is really needed. The paper demonstrates the system approach to the modelling of thermal insulation and accumulation abilities of such objetcs, incorporating the significant influence of additional physical processes, as surface heat radiation and moisture-driven deterioration of insulation layers. An illustrative example shows the numerical prediction of energy consumption of a freezing plant in one Central European climatic year.

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

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

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

    2015-08-01

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

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

    SciTech Connect (OSTI)

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

    2015-08-01

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

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

    SciTech Connect (OSTI)

    Granier, C.; Brasseur, G. )

    1992-11-20

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

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

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

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

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

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

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

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

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

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

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

    SciTech Connect (OSTI)

    Ying, Khor Chia; Hin, Pooi Ah

    2014-06-19

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

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

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

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

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

    SciTech Connect (OSTI)

    Dowding, Kevin J.; Rutherford, Brian Milne

    2003-07-01

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

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

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

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

    2015-05-26

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

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

    SciTech Connect (OSTI)

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

    2015-05-26

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

  20. Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory

    SciTech Connect (OSTI)

    Gregor P. Henze; Moncef Krarti

    2005-09-30

    Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid. Time-of-use electricity rates encourage shifting of electrical loads to off-peak periods at night and weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the building's massive structure or the use of active thermal energy storage systems such as ice storage. While these two thermal batteries have been engaged separately in the past, this project investigated the merits of harnessing both storage media concurrently in the context of predictive optimal control. To pursue the analysis, modeling, and simulation research of Phase 1, two separate simulation environments were developed. Based on the new dynamic building simulation program EnergyPlus, a utility rate module, two thermal energy storage models were added. Also, a sequential optimization approach to the cost minimization problem using direct search, gradient-based, and dynamic programming methods was incorporated. The objective function was the total utility bill including the cost of reheat and a time-of-use electricity rate either with or without demand charges. An alternative simulation environment based on TRNSYS and Matlab was developed to allow for comparison and cross-validation with EnergyPlus. The initial evaluation of the theoretical potential of the combined optimal control assumed perfect weather prediction and match between the building model and the actual building counterpart. The analysis showed that the combined utilization leads to cost savings that is significantly greater than either storage but less than the sum of the individual savings. The findings reveal that the cooling-related on-peak electrical demand of commercial buildings can be considerably reduced. A subsequent analysis of the impact of forecasting uncertainty in the required short-term weather forecasts determined that it takes only very simple

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

    SciTech Connect (OSTI)

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

    2013-09-01

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

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

    SciTech Connect (OSTI)

    Yeboah-Amankwah, D.; Agyeman, K.

    1990-01-01

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

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

    SciTech Connect (OSTI)

    DelSole, Timothy

    2015-08-31

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

  4. Advanced Sensors, Control, Platforms, and Modeling

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

    Advanced Sensors, Control, Platforms, and Modeling 1 for Manufacturing (Smart Manufacturing): 2 Technology Assessment 3 Contents 4 1. Introduction to the Technology/System ............................................................................................... 2 5 1.1 Overview ....................................................................................................................................... 2 6 1.2 Challenges and opportunities

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

    SciTech Connect (OSTI)

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

    1993-06-01

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    SciTech Connect (OSTI)

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

    2002-05-01

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

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

    SciTech Connect (OSTI)

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

    1990-11-01

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

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

    SciTech Connect (OSTI)

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

    1983-04-01

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

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

    SciTech Connect (OSTI)

    Hoffman, E.; Skidmore, E.

    2009-11-24

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

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

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

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

    2015-08-05

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

  14. Estimating vehicle roadside encroachment frequency using accident prediction models

    SciTech Connect (OSTI)

    Miaou, S.-P.

    1996-07-01

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

  15. Model based control of a coke battery

    SciTech Connect (OSTI)

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

    1997-12-31

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

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

    SciTech Connect (OSTI)

    Almassalkhi, MR; Hiskens, IA

    2015-01-01

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

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

    SciTech Connect (OSTI)

    Kumaran, K.; Babu, V.

    2009-04-15

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

  18. Modeling of Lean Exhaust Emissions Control Systems | Department...

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

    Lean Exhaust Emissions Control Systems Modeling of Lean Exhaust Emissions Control Systems 2002 DEER Conference Presentation: National Renewable Energy Laboratory ...

  19. Stability of Ensemble Models Predicts Productivity of Enzymatic Systems

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

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

    2016-03-10

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

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

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

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

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

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

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

  2. Aggregated Modeling and Control of Air Conditioning Loads for...

    Office of Scientific and Technical Information (OSTI)

    Journal Article: Aggregated Modeling and Control of Air Conditioning Loads for Demand Response Citation Details In-Document Search Title: Aggregated Modeling and Control of Air...

  3. Advanced LD Engine Systems and Emissions Control Modeling and...

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

    LD Engine Systems and Emissions Control Modeling and Analysis Advanced LD Engine Systems and Emissions Control Modeling and Analysis 2012 DOE Hydrogen and Fuel Cells Program and ...

  4. Advanced PHEV Engine Systems and Emissions Control Modeling and...

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

    PHEV Engine Systems and Emissions Control Modeling and Analysis Advanced PHEV Engine Systems and Emissions Control Modeling and Analysis 2011 DOE Hydrogen and Fuel Cells Program, ...

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

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

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

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

    SciTech Connect (OSTI)

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

    2015-08-05

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

  7. Model Identification for Optimal Diesel Emissions Control

    SciTech Connect (OSTI)

    Stevens, Andrew J.; Sun, Yannan; Song, Xiaobo; Parker, Gordon

    2013-06-20

    In this paper we develop a model based con- troller for diesel emission reduction using system identification methods. Specifically, our method minimizes the downstream readings from a production NOx sensor while injecting a minimal amount of urea upstream. Based on the linear quadratic estimator we derive the closed form solution to a cost function that accounts for the case some of the system inputs are not controllable. Our cost function can also be tuned to trade-off between input usage and output optimization. Our approach performs better than a production controller in simulation. Our NOx conversion efficiency was 92.7% while the production controller achieved 92.4%. For NH3 conversion, our efficiency was 98.7% compared to 88.5% for the production controller.

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

    SciTech Connect (OSTI)

    Valerio, Luis G.; Cross, Kevin P.

    2012-05-01

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

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

    SciTech Connect (OSTI)

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

    2014-06-15

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

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

    SciTech Connect (OSTI)

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

    2003-10-01

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

  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

    2013-07-21

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

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

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

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

  13. Global nuclear material flow/control model

    SciTech Connect (OSTI)

    Dreicer, J.S.; Rutherford, D.S.; Fasel, P.K.; Riese, J.M.

    1997-10-01

    This is the final report of a two-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The nuclear danger can be reduced by a system for global management, protection, control, and accounting as part of an international regime for nuclear materials. The development of an international fissile material management and control regime requires conceptual research supported by an analytical and modeling tool which treats the nuclear fuel cycle as a complete system. The prototype model developed visually represents the fundamental data, information, and capabilities related to the nuclear fuel cycle in a framework supportive of national or an international perspective. This includes an assessment of the global distribution of military and civilian fissile material inventories, a representation of the proliferation pertinent physical processes, facility specific geographic identification, and the capability to estimate resource requirements for the management and control of nuclear material. The model establishes the foundation for evaluating the global production, disposition, and safeguards and security requirements for fissile nuclear material and supports the development of other pertinent algorithmic capabilities necessary to undertake further global nuclear material related studies.

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

    Broader source: Energy.gov [DOE]

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

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

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

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

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

  18. A novel mathematical model for controllable near-field electrospinning

    SciTech Connect (OSTI)

    Ru, Changhai E-mail: luojun@shu.edu.cn; Robotics and Microsystems Center, Soochow University, Suzhou 215021 ; Chen, Jie; Shao, Zhushuai; Pang, Ming; Luo, Jun E-mail: luojun@shu.edu.cn

    2014-01-15

    Near-field electrospinning (NFES) had better controllability than conventional electrospinning. However, due to the lack of guidance of theoretical model, precise deposition of micro/nano fibers could only accomplished by experience. To analyze the behavior of charged jet in NFES using mathematical model, the momentum balance equation was simplified and a new expression between jet cross-sectional radius and axial position was derived. Using this new expression and mass conservation equation, expressions for jet cross-sectional radius and velocity were derived in terms of axial position and initial jet acceleration in the form of exponential functions. Based on Slender-body theory and Giesekus model, a quadratic equation for initial jet acceleration was acquired. With the proposed model, it was able to accurately predict the diameter and velocity of polymer fibers in NFES, and mathematical analysis rather than experimental methods could be applied to study the effects of the process parameters in NFES. Moreover, the movement velocity of the collector stage can be regulated by mathematical model rather than experience. Therefore, the model proposed in this paper had important guiding significance to precise deposition of polymer fibers.

  19. Modeling Combustion Control for High Power Diesel Mode Switching...

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

    Combustion Control for High Power Diesel Mode Switching Modeling Combustion Control for High Power Diesel Mode Switching Poster presentation given at the 16th Directions in ...

  20. SimTable helps firefighters model and predict fire direction

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

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

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

    SciTech Connect (OSTI)

    Watney, W.L.

    1992-01-01

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

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

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

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

  3. Validation of model based active control of combustion instability

    SciTech Connect (OSTI)

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

    1998-07-01

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

  4. Modelling of edge localised modes and edge localised mode control [Modelling of ELMs and ELM control

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

    Huijsmans, G. T. A.; Chang, C. S.; Ferraro, N.; Sugiyama, L.; Waelbroeck, F.; Xu, X. Q.; Loarte, A.; Futatani, S.

    2015-02-07

    Edge Localised Modes (ELMs) in ITER Q = 10 H-mode plasmas are likely to lead to large transient heat loads to the divertor. In order to avoid an ELM induced reduction of the divertor lifetime, the large ELM energy losses need to be controlled. In ITER, ELM control is foreseen using magnetic field perturbations created by in-vessel coils and the injection of small D2 pellets. ITER plasmas are characterised by low collisionality at a high density (high fraction of the Greenwald density limit). These parameters cannot simultaneously be achieved in current experiments. Thus, the extrapolation of the ELM properties andmore » the requirements for ELM control in ITER relies on the development of validated physics models and numerical simulations. Here, we describe the modelling of ELMs and ELM control methods in ITER. The aim of this paper is not a complete review on the subject of ELM and ELM control modelling but rather to describe the current status and discuss open issues.« less

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

    SciTech Connect (OSTI)

    Almassalkhi, MR; Hiskens, IA

    2015-01-01

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

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

    SciTech Connect (OSTI)

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

    2013-12-18

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

  7. Predictive Modeling of Terrestrial Radiation Exposure from Geologic Materials

    SciTech Connect (OSTI)

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

    2015-01-01

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

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

    SciTech Connect (OSTI)

    Gan, G.

    1998-02-06

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

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

    SciTech Connect (OSTI)

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

    1993-01-01

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

  10. Modelling hepatitis C therapy—predicting effects of treatment

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

    Perelson, Alan S.; Guedj, Jeremie

    2015-06-30

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

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

    SciTech Connect (OSTI)

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

    1996-04-01

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

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

    SciTech Connect (OSTI)

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

    1983-01-01

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

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

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

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

  14. Model based control of dynamic atomic force microscope

    SciTech Connect (OSTI)

    Lee, Chibum; Salapaka, Srinivasa M.

    2015-04-15

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

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

    SciTech Connect (OSTI)

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

    2013-10-15

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

  16. Improving models to predict phenological responses to global change

    SciTech Connect (OSTI)

    Richardson, Andrew D.

    2015-11-25

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

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

    SciTech Connect (OSTI)

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

    2009-07-15

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

  18. Final Scientific Technical Report: INTEGRATED PREDICTIVE DEMAND RESPONSE CONTROLLER FOR COMMERCIAL BUILDINGS

    SciTech Connect (OSTI)

    Wenzel, Mike

    2013-10-14

    This project provides algorithms to perform demand response using the thermal mass of a building. Using the thermal mass of the building is an attractive method for performing demand response because there is no need for capital expenditure. The algorithms rely on the thermal capacitance inherent in the building?s construction materials. A near-optimal ?day ahead? predictive approach is developed that is meant to keep the building?s electrical demand constant during the high cost periods. This type of approach is appropriate for both time-of-use and critical peak pricing utility rate structures. The approach uses the past days data in order to determine the best temperature setpoints for the building during the high price periods on the next day. A second ?model predictive approach? (MPC) uses a thermal model of the building to determine the best temperature for the next sample period. The approach uses constant feedback from the building and is capable of appropriately handling real time pricing. Both approaches are capable of using weather forecasts to improve performance.

  19. Simplified predictive models for CO2 sequestration performance assessment

    SciTech Connect (OSTI)

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

    2015-09-30

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

  20. Experimental Studies for DPF and SCR Model, Control System, and...

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

    Using Diesel and Biodiesel Fuels Experimental Studies for DPF and SCR Model, Control System, and OBD Development for Engines Using Diesel and Biodiesel Fuels Advanced Engine...

  1. Experimental Studies for DPF and SCR Model, Control System, and...

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

    Using Diesel and Biodiesel Fuels Experimental Studies for DPF and SCR Model, Control System, and OBD Development for Engines Using Diesel and Biodiesel Fuels Measuring PM ...

  2. Experimental Studies for DPF and SCR Model, Control System, and...

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

    Using Diesel and Biodiesel Fuels Experimental Studies for DPF and SCR Model, Control System, and OBD Development for Engines Using Diesel and Biodiesel Fuels Combination and ...

  3. A simple Analytical Model to Study and Control Azimuthal Instabilities...

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

    A simple Analytical Model to Study and Control Azimuthal Instabilities in Annular Combustion Chambers Authors: Parmentier, J-F., Salas, P., Wolf, P., Staffelbach, G., Nicoud, F., ...

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

    SciTech Connect (OSTI)

    Langton, C.; Kosson, D.

    2009-11-30

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

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

    SciTech Connect (OSTI)

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

    2015-08-19

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

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

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

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

    2015-08-19

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

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

    SciTech Connect (OSTI)

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

    2008-09-01

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

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

    SciTech Connect (OSTI)

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

    2014-06-24

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

  9. Control room habitability system review models

    SciTech Connect (OSTI)

    Gilpin, H. )

    1990-12-01

    This report provides a method of calculating control room operator doses from postulated reactor accidents and chemical spills as part of the resolution of TMI Action Plan III.D.3.4. The computer codes contained in this report use source concentrations calculated by either TACT5, FPFP, or EXTRAN, and transport them via user-defined flow rates to the control room envelope. The codes compute doses to six organs from up to 150 radionuclides (or 1 toxic chemical) for time steps as short as one second. Supporting codes written in Clipper assist in data entry and manipulation, and graphically display the results of the FORTRAN calculations. 7 refs., 22 figs.

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

    Office of Scientific and Technical Information (OSTI)

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

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

    SciTech Connect (OSTI)

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

    2011-12-05

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

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

    SciTech Connect (OSTI)

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

    1996-04-01

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

  13. Integrated Sensing and Controls for Coal Gasification - Development of Model-Based Controls for GE's Gasifier and Syngas Cooler

    SciTech Connect (OSTI)

    Aditya Kumar

    2010-12-30

    This report summarizes the achievements and final results of this program. The objective of this program is to develop a comprehensive systems approach to integrated design of sensing and control systems for an Integrated Gasification Combined Cycle (IGCC) plant, using advanced model-based techniques. In particular, this program is focused on the model-based sensing and control system design for the core gasification section of an IGCC plant. The overall approach consists of (i) developing a first-principles physics-based dynamic model of the gasification section, (ii) performing model-reduction where needed to derive low-order models suitable for controls analysis and design, (iii) developing a sensing system solution combining online sensors with model-based estimation for important process variables not measured directly, and (iv) optimizing the steady-state and transient operation of the plant for normal operation as well as for startup using model predictive controls (MPC). Initially, available process unit models were implemented in a common platform using Matlab/Simulink{reg_sign}, and appropriate model reduction and model updates were performed to obtain the overall gasification section dynamic model. Also, a set of sensor packages were developed through extensive lab testing and implemented in the Tampa Electric Company IGCC plant at Polk power station in 2009, to measure temperature and strain in the radiant syngas cooler (RSC). Plant operation data was also used to validate the overall gasification section model. The overall dynamic model was then used to develop a sensing solution including a set of online sensors coupled with model-based estimation using nonlinear extended Kalman filter (EKF). Its performance in terms of estimating key unmeasured variables like gasifier temperature, carbon conversion, etc., was studied through extensive simulations in the presence sensing errors (noise and bias) and modeling errors (e.g. unknown gasifier kinetics, RSC

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

    SciTech Connect (OSTI)

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

    2015-09-02

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

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

    SciTech Connect (OSTI)

    Jaroslav Solc

    2009-06-01

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

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

    SciTech Connect (OSTI)

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

    2005-09-01

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

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

    SciTech Connect (OSTI)

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

    2014-06-19

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

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

    SciTech Connect (OSTI)

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

    2015-04-15

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

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

    SciTech Connect (OSTI)

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

    2013-12-15

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

  20. Model-free adaptive control of advanced power plants

    SciTech Connect (OSTI)

    Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang

    2015-08-18

    A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.

  1. Reference Model for Control and Automation Systems in Electrical...

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

    Reference Model for Control and Automation Systems in Electrical Power (October 2005) (473.71 KB) More Documents & Publications DOE National SCADA Test Bed Program Multi-Year Plan ...

  2. Model Specification for Networked Outdoor Lighting Control Systems

    Broader source: Energy.gov [DOE]

    The DOE Municipal Solid-State Street Lighting Consortium's Model Specification for Networked Outdoor Lighting Control Systems is a tool designed to help cities, utilities, and other local agencies...

  3. Correlation of a hypoxia based tumor control model with observed local control rates in nasopharyngeal carcinoma treated with chemoradiotherapy

    SciTech Connect (OSTI)

    Avanzo, Michele; Stancanello, Joseph; Franchin, Giovanni; Sartor, Giovanna; Jena, Rajesh; Drigo, Annalisa; Dassie, Andrea; Gigante, Marco; Capra, Elvira

    2010-04-15

    Purpose: To extend the application of current radiation therapy (RT) based tumor control probability (TCP) models of nasopharyngeal carcinoma (NPC) to include the effects of hypoxia and chemoradiotherapy (CRT). Methods: A TCP model is described based on the linear-quadratic model modified to account for repopulation, chemotherapy, heterogeneity of dose to the tumor, and hypoxia. Sensitivity analysis was performed to determine which parameters exert the greatest influence on the uncertainty of modeled TCP. On the basis of the sensitivity analysis, the values of specific radiobiological parameters were set to nominal values reported in the literature for NPC or head and neck tumors. The remaining radiobiological parameters were determined by fitting TCP to clinical local control data from published randomized studies using both RT and CRT. Validation of the model was performed by comparison of estimated TCP and average overall local control rate (LCR) for 45 patients treated at the institution with conventional linear-accelerator-based or helical tomotherapy based intensity-modulated RT and neoadjuvant chemotherapy. Results: Sensitivity analysis demonstrates that the model is most sensitive to the radiosensitivity term {alpha} and the dose per fraction. The estimated values of {alpha} and OER from data fitting were 0.396 Gy{sup -1} and 1.417. The model estimate of TCP (average 90.9%, range 26.9%-99.2%) showed good correlation with the LCR (86.7%). Conclusions: The model implemented in this work provides clinicians with a useful tool to predict the success rate of treatment, optimize treatment plans, and compare the effects of multimodality therapy.

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

    SciTech Connect (OSTI)

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

    2009-03-01

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

  5. Modeling Combustion Control for High Power Diesel Mode Switching |

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

    Department of Energy Combustion Control for High Power Diesel Mode Switching Modeling Combustion Control for High Power Diesel Mode Switching Poster presentation given at the 16th Directions in Engine-Efficiency and Emissions Research (DEER) Conference in Detroit, MI, September 27-30, 2010. p-20_banerjee.pdf (160.26 KB) More Documents & Publications Diesel Injection Shear-Stress Advanced Nozzle (DISSAN) In-Cylinder Mechanisms of PCI Heat-Release Rate Control by Fuel Reactivity

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

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

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

    2015-09-02

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

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

    SciTech Connect (OSTI)

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

    2008-09-01

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

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

    SciTech Connect (OSTI)

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

    1994-09-01

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

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

    Office of Science (SC) Website

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

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

    SciTech Connect (OSTI)

    Blumberg, D.G.; Greeley, R.

    1996-12-01

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

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

    SciTech Connect (OSTI)

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

    1983-04-01

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

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

    SciTech Connect (OSTI)

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

    1996-12-01

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

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

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

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

    2016-01-27

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

  14. Application of a fuzzy neural network model in predicting polycyclic aromatic hydrocarbon-mediated perturbations of the Cyp1b1 transcriptional regulatory network in mouse skin

    SciTech Connect (OSTI)

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

    2013-03-01

    Polycyclic aromatic hydrocarbons (PAHs) are present in the environment as complex mixtures with components that have diverse carcinogenic potencies and mostly unknown interactive effects. Non-additive PAH interactions have been observed in regulation of cytochrome P450 (CYP) gene expression in the CYP1 family. To better understand and predict biological effects of complex mixtures, such as environmental PAHs, an 11 gene input-1 gene output fuzzy neural network (FNN) was developed for predicting PAH-mediated perturbations of dermal Cyp1b1 transcription in mice. Input values were generalized using fuzzy logic into low, medium, and high fuzzy subsets, and sorted using k-means clustering to create Mamdani logic functions for predicting Cyp1b1 mRNA expression. Model testing was performed with data from microarray analysis of skin samples from FVB/N mice treated with toluene (vehicle control), dibenzo[def,p]chrysene (DBC), benzo[a]pyrene (BaP), or 1 of 3 combinations of diesel particulate extract (DPE), coal tar extract (CTE) and cigarette smoke condensate (CSC) using leave-one-out cross-validation. Predictions were within 1 log{sub 2} fold change unit of microarray data, with the exception of the DBC treatment group, where the unexpected down-regulation of Cyp1b1 expression was predicted but did not reach statistical significance on the microarrays. Adding CTE to DPE was predicted to increase Cyp1b1 expression, whereas adding CSC to CTE and DPE was predicted to have no effect, in agreement with microarray results. The aryl hydrocarbon receptor repressor (Ahrr) was determined to be the most significant input variable for model predictions using back-propagation and normalization of FNN weights. - Highlights: ? Tested a model to predict PAH mixture-mediated changes in Cyp1b1 expression ? Quantitative predictions in agreement with microarrays for Cyp1b1 induction ? Unexpected difference in expression between DBC and other treatments predicted ? Model predictions for

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

    SciTech Connect (OSTI)

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

    2010-07-01

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

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

    SciTech Connect (OSTI)

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

    2013-01-01

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

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

    SciTech Connect (OSTI)

    G. R. Odette; G. E. Lucas

    2005-11-15

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

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

    SciTech Connect (OSTI)

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

    2013-06-01

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

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

    SciTech Connect (OSTI)

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

    2014-04-23

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

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

    SciTech Connect (OSTI)

    Watney, W.L.

    1994-12-01

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

  1. Optimal control of CPR procedure using hemodynamic circulation model

    DOE Patents [OSTI]

    Lenhart, Suzanne M.; Protopopescu, Vladimir A.; Jung, Eunok

    2007-12-25

    A method for determining a chest pressure profile for cardiopulmonary resuscitation (CPR) includes the steps of representing a hemodynamic circulation model based on a plurality of difference equations for a patient, applying an optimal control (OC) algorithm to the circulation model, and determining a chest pressure profile. The chest pressure profile defines a timing pattern of externally applied pressure to a chest of the patient to maximize blood flow through the patient. A CPR device includes a chest compressor, a controller communicably connected to the chest compressor, and a computer communicably connected to the controller. The computer determines the chest pressure profile by applying an OC algorithm to a hemodynamic circulation model based on the plurality of difference equations.

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

    SciTech Connect (OSTI)

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

    2015-12-31

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

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

    SciTech Connect (OSTI)

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

    2011-01-20

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

  4. Predicting reservoir facies distribution using high resolution forward stratigraphic modeling (upper Permian Zechstein 2 carbonate, North Germany)

    SciTech Connect (OSTI)

    Leyrer, K.; Strohmenger, C.; Rockenbauch, K.

    1995-08-01

    To improve the prediction of facies within the Upper Permian Zechstein 2 Carbonate (Ca2), high resolution forward stratigraphic modeling was performed. The results show differences in the sedimentary history of various parts of the Southern Permian Basin, permitting a better prediction of reservoir facies distribution. The Zechstein 2 Carbonate contains North Germany`s largest hydrocarbon accumulation. The reservoir overlies the anhydrites of the first Zechstein cycle (Werra Anhydrite, or A1) and is sealed by the anhydrites of the second Zechstein cycle (Basal Anhydrite, or A2). The Ca2 can be subdivided into platform, upper slope, middle slope, lower slope, and basina1 facies with a total of 26 subfacies types. It comprises the transgressive and highstand systems tract, of the third Zechstein sequence (ZS3) and the lowstand systems tract of the fourth Zechstein sequence (ZS4). Furthermore the Ca2 can be subdivided into seven parasequences indicating high-order fluctuations. Although the Ca2 in both Northwest and Northeast Germany share this geological framework, many differences concerning reservoir distribution exist between the two areas. A general stratigraphic, simulation program (PHIL{sup TM} 1.5) was used for two-dimensional modeling of the Ca2 throughout North Germany. Using well data along with published data and modifying the sedimentation-governing factors, it was possible to simulate the current sequence stratigraphic and facies model. Sedimentation during Ca2-time can be characterized as a highly complex system; thus, only slight variations of the input data result in vastly different facies and stratigraphic patterns. This sensitivity offers the possibility to test depositional models and to estimate the relative influences of the sediment-controlling parameters during Ca2-time in different paleotopographic settings.

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

    SciTech Connect (OSTI)

    Fok, Alex

    2013-10-30

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

  6. Validation of the thermal transport model used for ITER startup scenario predictions with DIII-D experimental data

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

    Casper, T. A.; Meyer, W. H.; Jackson, G. L.; Luce, T. C.; Hyatt, A. W.; Humphreys, D. A.; Turco, F.

    2010-12-08

    We are exploring characteristics of ITER startup scenarios in similarity experiments conducted on the DIII-D Tokamak. In these experiments, we have validated scenarios for the ITER current ramp up to full current and developed methods to control the plasma parameters to achieve stability. Predictive simulations of ITER startup using 2D free-boundary equilibrium and 1D transport codes rely on accurate estimates of the electron and ion temperature profiles that determine the electrical conductivity and pressure profiles during the current rise. Here we present results of validation studies that apply the transport model used by the ITER team to DIII-D discharge evolutionmore » and comparisons with data from our similarity experiments.« less

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

    SciTech Connect (OSTI)

    Strobel, Calvin J.

    1993-01-28

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

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

    SciTech Connect (OSTI)

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

    2009-03-03

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

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

    SciTech Connect (OSTI)

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

    2014-05-01

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

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

    SciTech Connect (OSTI)

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

    2012-10-01

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

  11. Neural Networks for Modeling and Control of Particle Accelerators

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

    Edelen, A. L.; Biedron, S. G.; Chase, B. E.; Edstrom, D.; Milton, S. V.; Stabile, P.

    2016-04-01

    Myriad nonlinear and complex physical phenomena are host to particle accelerators. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems,more » as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Moreover, many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. For the purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We also describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.« less

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

    SciTech Connect (OSTI)

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

    2013-09-01

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

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

    SciTech Connect (OSTI)

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

    2014-12-31

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

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

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

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

    2014-12-31

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

  15. Modelling of edge localised modes and edge localised mode control

    SciTech Connect (OSTI)

    Huijsmans, G. T. A.; Loarte, A.; Chang, C. S.; Ferraro, N.; Sugiyama, L.; Waelbroeck, F.; Xu, X. Q.; Futatani, S.

    2015-02-15

    Edge Localised Modes (ELMs) in ITER Q = 10 H-mode plasmas are likely to lead to large transient heat loads to the divertor. To avoid an ELM induced reduction of the divertor lifetime, the large ELM energy losses need to be controlled. In ITER, ELM control is foreseen using magnetic field perturbations created by in-vessel coils and the injection of small D2 pellets. ITER plasmas are characterised by low collisionality at a high density (high fraction of the Greenwald density limit). These parameters cannot simultaneously be achieved in current experiments. Therefore, the extrapolation of the ELM properties and the requirements for ELM control in ITER relies on the development of validated physics models and numerical simulations. In this paper, we describe the modelling of ELMs and ELM control methods in ITER. The aim of this paper is not a complete review on the subject of ELM and ELM control modelling but rather to describe the current status and discuss open issues.

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

    SciTech Connect (OSTI)

    Tribbia, Joseph

    2015-11-25

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

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

    SciTech Connect (OSTI)

    Drover, Damion, Ryan

    2011-12-01

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

  18. Electric Water Heater Modeling and Control Strategies for Demand Response

    SciTech Connect (OSTI)

    Diao, Ruisheng; Lu, Shuai; Elizondo, Marcelo A.; Mayhorn, Ebony T.; Zhang, Yu; Samaan, Nader A.

    2012-07-22

    Abstract Demand response (DR) has a great potential to provide balancing services at normal operating conditions and emergency support when a power system is subject to disturbances. Effective control strategies can significantly relieve the balancing burden of conventional generators and reduce investment on generation and transmission expansion. This paper is aimed at modeling electric water heaters (EWH) in households and tests their response to control strategies to implement DR. The open-loop response of EWH to a centralized signal is studied by adjusting temperature settings to provide regulation services; and two types of decentralized controllers are tested to provide frequency support following generator trips. EWH models are included in a simulation platform in DIgSILENT to perform electromechanical simulation, which contains 147 households in a distribution feeder. Simulation results show the dependence of EWH response on water heater usage . These results provide insight suggestions on the need of control strategies to achieve better performance for demand response implementation. Index Terms Centralized control, decentralized control, demand response, electrical water heater, smart grid

  19. Feasibility of High-Power Diode Laser Array Surrogate to Support Development of Predictive Laser Lethality Model

    SciTech Connect (OSTI)

    Lowdermilk, W H; Rubenchik, A M; Springer, H K

    2011-01-13

    Predictive modeling and simulation of high power laser-target interactions is sufficiently undeveloped that full-scale, field testing is required to assess lethality of military directed-energy (DE) systems. The cost and complexity of such testing programs severely limit the ability to vary and optimize parameters of the interaction. Thus development of advanced simulation tools, validated by experiments under well-controlled and diagnosed laboratory conditions that are able to provide detailed physics insight into the laser-target interaction and reduce requirements for full-scale testing will accelerate development of DE weapon systems. The ultimate goal is a comprehensive end-to-end simulation capability, from targeting and firing the laser system through laser-target interaction and dispersal of target debris; a 'Stockpile Science' - like capability for DE weapon systems. To support development of advanced modeling and simulation tools requires laboratory experiments to generate laser-target interaction data. Until now, to make relevant measurements required construction and operation of very high power and complex lasers, which are themselves costly and often unique devices, operating in dedicated facilities that don't permit experiments on targets containing energetic materials. High power diode laser arrays, pioneered by LLNL, provide a way to circumvent this limitation, as such arrays capable of delivering irradiances characteristic of De weapon requires are self-contained, compact, light weight and thus easily transportable to facilities, such as the High Explosives Applications Facility (HEAF) at Lawrence Livermore National Laboratory (LLNL) where testing with energetic materials can be performed. The purpose of this study was to establish the feasibility of using such arrays to support future development of advanced laser lethality and vulnerability simulation codes through providing data for materials characterization and laser-material interaction

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

    SciTech Connect (OSTI)

    Singh, Kunwar P. Gupta, Shikha

    2014-03-15

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

  1. Control-Oriented Modeling for HCCI Combustion and Multi-Cylinder...

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

    Control-Oriented Modeling for HCCI Combustion and Multi-Cylinder HCCI Experimental Activities Control-Oriented Modeling for HCCI Combustion and Multi-Cylinder HCCI Experimental ...

  2. Physical control oriented model of large scale refrigerators to synthesize advanced control schemes. Design, validation, and first control results

    SciTech Connect (OSTI)

    Bonne, François; Bonnay, Patrick

    2014-01-29

    In this paper, a physical method to obtain control-oriented dynamical models of large scale cryogenic refrigerators is proposed, in order to synthesize model-based advanced control schemes. These schemes aim to replace classical user experience designed approaches usually based on many independent PI controllers. This is particularly useful in the case where cryoplants are submitted to large pulsed thermal loads, expected to take place in the cryogenic cooling systems of future fusion reactors such as the International Thermonuclear Experimental Reactor (ITER) or the Japan Torus-60 Super Advanced Fusion Experiment (JT-60SA). Advanced control schemes lead to a better perturbation immunity and rejection, to offer a safer utilization of cryoplants. The paper gives details on how basic components used in the field of large scale helium refrigeration (especially those present on the 400W @1.8K helium test facility at CEA-Grenoble) are modeled and assembled to obtain the complete dynamic description of controllable subsystems of the refrigerator (controllable subsystems are namely the Joule-Thompson Cycle, the Brayton Cycle, the Liquid Nitrogen Precooling Unit and the Warm Compression Station). The complete 400W @1.8K (in the 400W @4.4K configuration) helium test facility model is then validated against experimental data and the optimal control of both the Joule-Thompson valve and the turbine valve is proposed, to stabilize the plant under highly variable thermals loads. This work is partially supported through the European Fusion Development Agreement (EFDA) Goal Oriented Training Program, task agreement WP10-GOT-GIRO.

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

    SciTech Connect (OSTI)

    Yunovich, M.; Thompson, N.G.

    1998-12-31

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

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

    SciTech Connect (OSTI)

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

    2013-01-01

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

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

    SciTech Connect (OSTI)

    Lall, Pradeep; Wei, Junchao; Sakalaukus, Peter

    2014-06-22

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

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

    SciTech Connect (OSTI)

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

    1981-07-01

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

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

    Energy Science and Technology Software Center (OSTI)

    1989-11-01

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

  8. Control of high level radioactive waste-glass melters. Part 5, Modelling of complex redox effects

    SciTech Connect (OSTI)

    Bickford, D.F.; Choi, A.S.

    1991-12-31

    Slurry Fed Melters (SFM) are being developed in the United States, Europe and Japan for the conversion of high-level radioactive waste to borosilicate glass for permanent disposal. The high transition metal, noble metal, nitrate, organic, and sulfate contents of these wastes lead to unique melter redox control requirements. Pilot waste-glass melter operations have indicated the possibility of nickel sulfide or noble-metal fission-product accumulation on melter floors, which can lead to distortion of electric heating patterns, and decrease melter life. Sulfide formation is prevented by control of the redox chemistry of the melter feed. The redox state of waste-glass melters is determined by balance between the reducing potential of organic compounds in the feed, and the oxidizing potential of gases above the melt, and nitrates and polyvalent elements in the waste. Semiquantitative models predicting limitations of organic content have been developed based on crucible testing. Computerized thermodynamic computations are being developed to predict the sequence and products of redox reactions and is assessing process variations. Continuous melter test results have been compared to improved computer staged-thermodynamic-models of redox behavior. Feed chemistry control to prevent sulfide and moderate noble metal accumulations are discussed. 17 refs., 3 figs.

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

    SciTech Connect (OSTI)

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

    2015-07-15

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

  10. Aggregate Model for Heterogeneous Thermostatically Controlled Loads with Demand Response

    SciTech Connect (OSTI)

    Zhang, Wei; Kalsi, Karanjit; Fuller, Jason C.; Elizondo, Marcelo A.; Chassin, David P.

    2012-07-22

    Due to the potentially large number of Distributed Energy Resources (DERs) demand response, distributed generation, distributed storage - that are expected to be deployed, it is impractical to use detailed models of these resources when integrated with the transmission system. Being able to accurately estimate the fast transients caused by demand response is especially important to analyze the stability of the system under different demand response strategies. On the other hand, a less complex model is more amenable to design feedback control strategies for the population of devices to provide ancillary services. The main contribution of this paper is to develop aggregated models for a heterogeneous population of Thermostatic Controlled Loads (TCLs) to accurately capture their collective behavior under demand response and other time varying effects of the system. The aggregated model efficiently includes statistical information of the population and accounts for a second order effect necessary to accurately capture the collective dynamic behavior. The developed aggregated models are validated against simulations of thousands of detailed building models using GridLAB-D (an open source distribution simulation software) under both steady state and severe dynamic conditions caused due to temperature set point changes.

  11. Tectonic control of the sedimentary record: Constraints from quantitative basin modeling

    SciTech Connect (OSTI)

    Cloetingh, S.A.P.L.; Van Balen, R.T.; Zoetemeijer, B.P. )

    1993-09-01

    The incorporation of finite strength of the lithosphere during rifting in models for extensional basin formation in conjunction with temporal changes in tectonic stress levels leads to the prediction of rapid vertical motions in these basins with a rate and magnitude comparable to second- and third-order changes in relative sea level. We present results of modeling simulations, incorporating the interplay of flank uplift and erosion for rifted basins in the northern Atlantic/North Sea area. The incorporation of the mechanical properties of the lithosphere in forward stratigraphic modeling appears also to be of key importance for an accurate prediction of the record of vertical motions in foreland fold and thrust belts. Models invoking the mechanical coupling between plate flexure and near-surface brittle tectonics are capable of producing onlap/offlap patterns in syntectonic basins sometimes strikingly similar to the basin-fill signatures attributed to third-order glacio-eustatic signals. The full incorporation of structural geological constraints in forward modeling of basin stratigraphy proves to be a powerful instrument in linking different temporal and spatial scales in the sedimentary record. This approach also leads to a quantification of the tectonic control of the sedimentary record in frequency bands hitherto primarily attributed to external forcing functions.

  12. Wind Plant Power Optimization through Yaw Control using a Parametric Model for Wake Effects -- A CFD Simulation Study

    SciTech Connect (OSTI)

    Gebraad, P. M. O.; Teeuwisse, F. W.; van Wingerden, J. W.; Fleming, Paul A.; Ruben, S. D.; Marden, J. R.; Pao, L. Y.

    2016-01-01

    This article presents a wind plant control strategy that optimizes the yaw settings of wind turbines for improved energy production of the whole wind plant by taking into account wake effects. The optimization controller is based on a novel internal parametric model for wake effects, called the FLOw Redirection and Induction in Steady-state (FLORIS) model. The FLORIS model predicts the steady-state wake locations and the effective flow velocities at each turbine, and the resulting turbine electrical energy production levels, as a function of the axial induction and the yaw angle of the different rotors. The FLORIS model has a limited number of parameters that are estimated based on turbine electrical power production data. In high-fidelity computational fluid dynamics simulations of a small wind plant, we demonstrate that the optimization control based on the FLORIS model increases the energy production of the wind plant, with a reduction of loads on the turbines as an additional effect.

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

    SciTech Connect (OSTI)

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

    1980-10-01

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

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

    SciTech Connect (OSTI)

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

    2015-03-16

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

  15. Dynamic Modeling in Solid-Oxide Fuel Cells Controller Design

    SciTech Connect (OSTI)

    Lu, Ning; Li, Qinghe; Sun, Xin; Khaleel, Mohammad A.

    2007-06-28

    In this paper, a dynamic model of the solid-oxide fuel cell (SOFC) power unit is developed for the purpose of designing a controller to regulate fuel flow rate, fuel temperature, air flow rate, and air temperature to maintain the SOFC stack temperature, fuel utilization rate, and voltage within operation limits. A lumped model is used to consider the thermal dynamics and the electro-chemial dynamics inside an SOFC power unit. The fluid dynamics at the fuel and air inlets are considered by using the in-flow ramp-rates.

  16. Model and control of heat release in engines

    SciTech Connect (OSTI)

    Oppenheim, A.K.; Packard, A.K.; Hedrick, J.K.; Kuhl, A.L.; Johnson, W.P.

    1996-09-01

    The concept of the paper stems from the premise that the process of heat release in engines involves in essence the evolution and deposition of exothermic energy generated by combustion--events that can be governed promptly by a feedback, adaptive micro-electronic control system. The key to its realization is the principle of DISC (Direct Injection Stratified Charge) engine, implemented by a multi-jet system. The background and the salient features of such a system, referred to as a CCE (Controlled Combustion Engine), have been described in a companion paper (SAE 951961). Presented here are fundamental aspects of the model of the exothermic process and the intrinsic properties of its control system.

  17. Reference Model for Control and Automation Systems in Electrical Power

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

    Reference Model for Control and Automation Systems in Electrical Power Version 1.2 October 12, 2005 Prepared by: Sandia National Laboratories' Center for SCADA Security Jason Stamp, Technical Lead Michael Berg, Co-Technical Lead Michael Baca, Project Lead This work was conducted for the DOE Office of Electricity Delivery and Energy Reliability under Contract M64SCADSNL Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department

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

    SciTech Connect (OSTI)

    Malini, B.H.

    1997-12-31

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

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

    SciTech Connect (OSTI)

    Granderson, Jessica; Price, Phillip N.

    2014-03-01

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

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

    SciTech Connect (OSTI)

    Duffy, Stephen

    2013-09-09

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

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

    SciTech Connect (OSTI)

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

    2008-01-01

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

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

    SciTech Connect (OSTI)

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

    1999-07-01

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

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

    SciTech Connect (OSTI)

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

    2011-11-15

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

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

    SciTech Connect (OSTI)

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

    2014-02-01

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

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

    SciTech Connect (OSTI)

    Garud, Y.S.

    1985-01-01

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

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

    SciTech Connect (OSTI)

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

    2014-06-01

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

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

    SciTech Connect (OSTI)

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

    1995-09-01

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

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

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

    Cholis, Ilias; Hooper, Dan; Linden, Tim

    2016-02-23

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

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

    SciTech Connect (OSTI)

    Maguire, J.; Burch, J.

    2013-08-01

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

  10. Optimal SCR Control Using Data-Driven Models

    SciTech Connect (OSTI)

    Stevens, Andrew J.; Sun, Yannan; Lian, Jianming; Devarakonda, Maruthi N.; Parker, Gordon

    2013-04-16

    We present an optimal control solution for the urea injection for a heavy-duty diesel (HDD) selective catalytic reduction (SCR). The approach taken here is useful beyond SCR and could be applied to any system where a control strategy is desired and input-output data is available. For example, the strategy could also be used for the diesel oxidation catalyst (DOC) system. In this paper, we identify and validate a one-step ahead Kalman state-space estimator for downstream NOx using the bench reactor data of an SCR core sample. The test data was acquired using a 2010 Cummins 6.7L ISB production engine with a 2010 Cummins production aftertreatment system. We used a surrogate HDD federal test procedure (FTP), developed at Michigan Technological University (MTU), which simulates the representative transients of the standard FTP cycle, but has less engine speed/load points. The identified state-space model is then used to develop a tunable cost function that simultaneously minimizes NOx emissions and urea usage. The cost function is quadratic and univariate, thus the minimum can be computed analytically. We show the performance of the closed-loop controller in using a reduced-order discrete SCR simulator developed at MTU. Our experiments with the surrogate HDD-FTP data show that the strategy developed in this paper can be used to identify performance bounds for urea dose controllers.

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

    SciTech Connect (OSTI)

    Laskowski, Gregory Michael

    2005-12-01

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

  12. Model-reference adaptive control applied to load-following of a space-nuclear power system

    SciTech Connect (OSTI)

    Metzger, J.D.; El-Genk, M.S.; Parlos, A.G.; New Mexico Univ., Albuquerque, NM . Inst. for Space Nuclear Power Studies; Texas A and M Univ., College Station, TX . Dept. of Nuclear Engineering)

    1989-01-01

    Nuclear power systems are presently being investigated as an alternative for both commercial and military space power systems because of their projected longevity of 7 to 10 years, their mass advantage over other space power sources at powers above approximately 25 kW{sub e}, and their ability to operate without direct illumination from the sun. These space-nuclear power systems are being designed to supply from tens of kilowatts to multimegawatts of power for continuous operation of seven years and more. Space-nuclear power systems designs that meet these requirements will not be available for refueling or maintenance during their lifetime. To ensure that the space-nuclear power system will operate safely and will respond in a predictable and desired manner, the design of the system's controller must account for changes in the system parameters over its lifetime. This paper applies model-reference adaptive control to an increase in the power demand by the load. A model-reference adaptive controller will force the actual space-nuclear power system to follow the predictable and desired response of a reference model, despite changes in the actual system's operating parameters. Included in this paper are the model-reference adaptive control algorithm, the description of the computer simulation of a space-nuclear power system and the reference model, and results that demonstrate the application of model-reference adaptive control to a change in the load power demand. The results demonstrate that model-reference adaptive control can ensure the transient response of the system despite differences between the design of the system and the as-built system as well as for variations in the systems parameters. 5 refs., 3 figs.

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

    SciTech Connect (OSTI)

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

    2014-09-14

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

  14. Integrated Air Pollution Control System (IAPCS), Executable Model (Version 4. 0) (for microcomputers). Model-Simulation

    SciTech Connect (OSTI)

    Not Available

    1990-10-29

    The Integrated Air Pollution Control System (IAPCS) Cost Model is an IBM PC cost model that can be used to estimate the cost of installing SO2, NOx, and particulate matter control systems at coal-fired utility electric generating facilities. The model integrates various combinations of the following technologies: physical coal cleaning, coal switching, overfire air/low NOx burners, natural gas reburning, LIMB, ADVACATE, electrostatic precipitator, fabric filter, gas conditioning, wet lime or limestone FGD, lime spray drying/duct spray drying, dry sorbent injection, pressurized fluidized bed combustion, integrated gasification combined cycle, and pulverized coal burning boiler. The model generates capital, annualized, and unitized pollutant removal costs in either constant or current dollars for any year.

  15. Statistical circuit simulation with measurement-based active device models: Implications for process control and IC manufacturability

    SciTech Connect (OSTI)

    Root, D.E.; McGinty, D.; Hughes, B.

    1995-12-31

    This paper presents a new approach to statistical active circuit design which unifies device parametric-based process control and non-parametric circuit simulation. Predictions of circuit sensitivity to process variation and yield-loss of circuits fabricated in two different GaAs IC processes are described. The simulations make use of measurement-based active device models which are not formulated in terms of conventional parametric statistical variables. The technique is implemented in commercially available simulation software (HP MDS).

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

    SciTech Connect (OSTI)

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

    2014-05-15

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

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

    SciTech Connect (OSTI)

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

    2010-09-01

    , 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

  18. Modeling, Analysis, and Control of Demand Response Resources

    SciTech Connect (OSTI)

    Mathieu, Johanna L.

    2012-05-01

    While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can plan an active role in power systems via Demand Response (DR), defined by the Department of Energy (DOE) as “a tariff or program established to motivate changes in electric use by end-use customers in response to changes in the price of electricity over time, or to give incentive payments designed to induce lower electricity use at times of high market prices or when grid reliability is jeopardized” [29]. DR can provide a variety of benefits including reducing peak electric loads when the power system is stressed and fast timescale energy balancing. Therefore, DR can improve grid reliability and reduce wholesale energy prices and their volatility. This dissertation focuses on analyzing both recent and emerging DR paradigms. Recent DR programs have focused on peak load reduction in commercial buildings and industrial facilities (C&I facilities). We present methods for using 15-minute-interval electric load data, commonly available from C&I facilities, to help building managers understand building energy consumption and ‘ask the right questions’ to discover opportunities for DR. Additionally, we present a regression-based model of whole building electric load, i.e., a baseline model, which allows us to quantify DR performance. We use this baseline model to understand the performance of 38 C&I facilities participating in an automated dynamic pricing DR program in California. In this program, facilities are expected to exhibit the same response each DR event. We find that baseline model error makes it difficult to precisely quantify changes in electricity consumption and understand if C&I facilities exhibit event-to-event variability in their response to DR signals. Therefore, we present a method to compute baseline model error and a metric to determine how much observed DR variability results from baseline model error rather than real

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

    SciTech Connect (OSTI)

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

    1998-10-01

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

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

    SciTech Connect (OSTI)

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

    1998-01-01

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

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

    SciTech Connect (OSTI)

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

    1999-03-01

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

  2. Hydrodynamic modeling for corrosion control in the oil and gas industry

    SciTech Connect (OSTI)

    Palacios, C.A.; Morales, J.L.

    1995-10-01

    This article describes a methodology used to select and establish corrosion control programs. These include corrosion rate predictions using well known correlations for flowing systems, materials selection, optimization of inhibitors and corrosion monitoring techniques. The methodology characterizes internal corrosion phenomenon integrating the hydrodynamic conditions of the flow (flow velocities, flow pattern, liquid holdups, and where the condensation is taking place within a pipeline) with those that predict corrosion rates. It can be applied in the whole oil/gas production system, including subsurface and surface equipment. The methodology uses single and two phase flow modeling techniques to: (1) optimize the entire production system to obtain the most efficient objective flow rate, taking into consideration the corrosive/erosive nature of the produced fluids and (2) characterize the corrosion nature of oil and gas transmission lines. As an example of its use, a characterization of corrosion nature of a gas transmission line is described. The hydrodynamic simulation was performed using commercially available simulators, and the corrosion rates were determined using published correlations. Results using this methodology allowed for corrosion control strategies, protection and monitoring criteria, and inhibition optimization.

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

    SciTech Connect (OSTI)

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

    1996-08-09

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

  4. Modeling Species Inhibition of NO Oxidation in Urea-SCR Catalysts for Diesel Engine NOx Control

    SciTech Connect (OSTI)

    Devarakonda, Maruthi N.; Tonkyn, Russell G.; Tran, Diana N.; Lee, Jong H.; Herling, Darrell R.

    2011-04-20

    Urea-selective catalytic reduction (SCR) catalysts are regarded as the leading NOx aftertreatment technology to meet the 2010 NOx emission standards for on-highway vehicles running on heavy-duty diesel engines. However, issues such as low NOx conversion at low temperature conditions still exist due to various factors, including incomplete urea thermolysis, inhibition of SCR reactions by hydrocarbons and H2O. We have observed a noticeable reduction in the standard SCR reaction efficiency at low temperature with increasing water content. We observed a similar effect when hydrocarbons are present in the stream. This effect is absent under fast SCR conditions where NO ~ NO2 in the feed gas. As a first step in understanding the effects of such inhibition on SCR reaction steps, kinetic models that predict the inhibition behavior of H2O and hydrocarbons on NO oxidation are presented in the paper. A one-dimensional SCR model was developed based on conservation of species equations and was coded as a C-language S-function and implemented in Matlab/Simulink environment. NO oxidation and NO2 dissociation kinetics were defined as a function of the respective adsorbate’s storage in the Fe-zeolite SCR catalyst. The corresponding kinetic models were then validated on temperature ramp tests that showed good match with the test data. Such inhibition models will improve the accuracy of model based control design for integrated DPF-SCR aftertreatment systems.

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

    SciTech Connect (OSTI)

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

    1995-09-01

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

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

    SciTech Connect (OSTI)

    Palmer, D.L.

    1986-09-01

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

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

    SciTech Connect (OSTI)

    Greitzer, Frank L.; Frincke, Deborah A.

    2010-09-01

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

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

    SciTech Connect (OSTI)

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

    2015-12-11

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

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

    SciTech Connect (OSTI)

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

    2006-10-01

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

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

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

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

    2015-12-11

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

  11. Integrated Air Pollution Control System (IAPCS), Executable Model and Source Model (version 4. 0) (for microcomputers). Model-Simulation

    SciTech Connect (OSTI)

    Not Available

    1990-10-29

    The Integrated Air Pollution Control System (IAPCS) Cost Model is an IBM PC cost model that can be used to estimate the cost of installing SO2, NOx, and particulate matter control systems at coal-fired utility electric generating facilities. The model integrates various combinations of the following technologies: physical coal cleaning, coal switching, overfire air/low NOx burners, natural gas reburning, LIMB, ADVACATE, electrostatic precipitator, fabric filter, gas conditioning, wet lime or limestone FGD, lime spray drying/duct spray drying, dry sorbent injection, pressurized fluidized bed combustion, integrated gasification combined cycle, and pulverized coal burning boiler. The model generates capital, annualized, and unitized pollutant removal costs in either constant or current dollars for any year.

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

    Broader source: Energy.gov [DOE]

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

  13. Embedded Sensors and Controls to Improve Component Performance and Reliability - System Dynamics Modeling and Control System Design

    SciTech Connect (OSTI)

    Melin, Alexander M.; Kisner, Roger A.; Fugate, David L.

    2013-10-01

    This report documents the current status of the modeling, control design, and embedded control research for the magnetic bearing canned rotor pump being used as a demonstration platform for deeply integrating instrumentation and controls (I{\\&}C) into nuclear power plant components. This pump is a highly inter-connected thermo/electro/mechanical system that requires an active control system to operate. Magnetic bearings are inherently unstable system and without active, moment by moment control, the rotor would contact fixed surfaces in the pump causing physical damage. This report details the modeling of the pump rotordynamics, fluid forces, electromagnetic properties of the protective cans, active magnetic bearings, power electronics, and interactions between different dynamical models. The system stability of the unforced and controlled rotor are investigated analytically. Additionally, controllers are designed using proportional derivative (PD) control, proportional integral derivative (PID) control, voltage control, and linear quadratic regulator (LQR) control. Finally, a design optimization problem that joins the electrical, mechanical, magnetic, and control system design into one problem to balance the opposing needs of various design criteria using the embedded system approach is presented.

  14. Controls on terrestrial carbon feedbacks by productivity vs. turnover in the CMIP5 Earth System Models

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

    Koven, C. D.; Chambers, J. Q.; Georgiou, K.; Knox, R.; Negron-Juarez, R.; Riley, W. J.; Arora, V. K.; Brovkin, V.; Friedlingstein, P.; Jones, C. D.

    2015-04-16

    To better understand sources of uncertainty in projections of terrestrial carbon cycle feedbacks, we present an approach to separate the controls on modeled carbon changes. We separate carbon changes into 4 categories using a linearized, equilibrium approach: those arising from changed inputs (productivity-driven changes), and outputs (turnover-driven changes), and apply the analysis separately to the live and dead carbon pools. Using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations for 5 models, we find that changes to the live pools are primarily explained by productivity-driven changes, with only one model showing large compensating changes to live carbon turnover times. Formore » dead carbon pools, the situation is more complex as all models predict a large reduction in turnover times in response to increases in productivity. This responses arises from the common representation of a broad spectrum of decomposition turnover times via a multi-pool approach, in which flux-weighted turnover times are faster than mass-weighted turnover times. This leads to a shift in the distribution of carbon among dead pools in response to changes in inputs, and therefore a transient but long-lived reduction in turnover times in response to increases in productivity. Since this behavior, a reduction in inferred turnover times resulting from an increase in inputs, is superficially similar to priming processes, but occurring without the mechanisms responsible for priming, we call the phenomenon "false priming", and show that it masks much of the intrinsic changes to dead carbon turnover times as a result of changing climate. These patterns hold across the fully-coupled, biogeochemically-coupled, and radiatively-coupled 1% yr−1 increasing CO2 experiments. We disaggregate inter-model uncertainty in the globally-integrated equilibrium carbon responses to initial turnover times, inital productivity, fractional changes in turnover, and fractional changes in

  15. Controls on terrestrial carbon feedbacks by productivity versus turnover in the CMIP5 Earth System Models

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

    Koven, C. D.; Chambers, J. Q.; Georgiou, K.; Knox, R.; Negron-Juarez, R.; Riley, W. J.; Arora, V. K.; Brovkin, V.; Friedlingstein, P.; Jones, C. D.

    2015-09-07

    To better understand sources of uncertainty in projections of terrestrial carbon cycle feedbacks, we present an approach to separate the controls on modeled carbon changes. We separate carbon changes into four categories using a linearized, equilibrium approach: those arising from changed inputs (productivity-driven changes), and outputs (turnover-driven changes), of both the live and dead carbon pools. Using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations for five models, we find that changes to the live pools are primarily explained by productivity-driven changes, with only one model showing large compensating changes to live carbon turnover times. For dead carbon pools, themore » situation is more complex as all models predict a large reduction in turnover times in response to increases in productivity. This response arises from the common representation of a broad spectrum of decomposition turnover times via a multi-pool approach, in which flux-weighted turnover times are faster than mass-weighted turnover times. This leads to a shift in the distribution of carbon among dead pools in response to changes in inputs, and therefore a transient but long-lived reduction in turnover times. Since this behavior, a reduction in inferred turnover times resulting from an increase in inputs, is superficially similar to priming processes, but occurring without the mechanisms responsible for priming, we call the phenomenon "false priming", and show that it masks much of the intrinsic changes to dead carbon turnover times as a result of changing climate. These patterns hold across the fully coupled, biogeochemically coupled, and radiatively coupled 1 % yr−1 increasing CO2 experiments. We disaggregate inter-model uncertainty in the globally integrated equilibrium carbon responses to initial turnover times, initial productivity, fractional changes in turnover, and fractional changes in productivity. For both the live and dead carbon pools, inter-model

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

    SciTech Connect (OSTI)

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

    2010-05-05

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

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

    SciTech Connect (OSTI)

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

    1996-12-01

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

  18. Dynamic model of Italy`s Progetto Energia cogeneration plants aims to better predict plant performance, cut start-up costs

    SciTech Connect (OSTI)

    1996-12-31

    Over the next four years, the Progetto Energia project will be building several cogeneration plants to help satisfy the increasing demands of Italy`s industrial users and the country`s demand for electrical power. Located at six different sites within Italy, these combined-cycle cogeneration plants will supply a total of 500 MW of electricity and 100 tons/hr of process steam to Italian industries and residences. To ensure project success, a dynamic model of the 50-MW base unit was developed. The goal established for the model was to predict the dynamic behavior of the complex thermodynamic system in order to assess equipment performance and control system effectiveness for normal operation and, more importantly, abrupt load changes. In addition to fulfilling its goals, the dynamic study guided modifications to controller logic that significantly improved steam drum pressure control and bypassed steam desuperheating performance simulations of normal and abrupt transient events allowed engineers to define optimum controller gain coefficients. The dynamic study will undoubtedly reduce the associated plant start-up costs and contribute to a smooth commercial plant acceptance. As a result of the work, the control system has already been through its check-out and performance evaluation, usually performed during the plant start-up phase. Field engineers will directly benefit from this effort to identify and resolve control system {open_quotes}bugs{close_quotes} before the equipment reaches the field. High thermal efficiency, rapid dispatch and high plant availability were key reasons why the natural gas combined-cycle plant was chosen. Other favorable attributes of the combined-cycle plant contributing to the decision were: Minimal environmental impact; a simple and effective process and control philosophy to result in safe and easy plant operation; a choice of technologies and equipment proven in a large number of applications.

  19. Diffusion-controlled reactions modeling in Geant4-DNA

    SciTech Connect (OSTI)

    Karamitros, M.; Luan, S.; Bernal, M.A.; Allison, J.; Baldacchino, G.; Davidkova, M.; Francis, Z.; Friedland, W.; Ivantchenko, V.; Ivantchenko, A.; Mantero, A.; Nieminem, P.; Santin, G.; Tran, H.N.; Stepan, V.; Incerti, S.

    2014-10-01

    Context Under irradiation, a biological system undergoes a cascade of chemical reactions that can lead to an alteration of its normal operation. There are different types of radiation and many competing reactions. As a result the kinetics of chemical species is extremely complex. The simulation becomes then a powerful tool which, by describing the basic principles of chemical reactions, can reveal the dynamics of the macroscopic system. To understand the dynamics of biological systems under radiation, since the 80s there have been on-going efforts carried out by several research groups to establish a mechanistic model that consists in describing all the physical, chemical and biological phenomena following the irradiation of single cells. This approach is generally divided into a succession of stages that follow each other in time: (1) the physical stage, where the ionizing particles interact directly with the biological material; (2) the physico-chemical stage, where the targeted molecules release their energy by dissociating, creating new chemical species; (3) the chemical stage, where the new chemical species interact with each other or with the biomolecules; (4) the biological stage, where the repairing mechanisms of the cell come into play. This article focuses on the modeling of the chemical stage. Method This article presents a general method of speeding-up chemical reaction simulations in fluids based on the Smoluchowski equation and Monte-Carlo methods, where all molecules are explicitly simulated and the solvent is treated as a continuum. The model describes diffusion-controlled reactions. This method has been implemented in Geant4-DNA. The keys to the new algorithm include: (1) the combination of a method to compute time steps dynamically with a Brownian bridge process to account for chemical reactions, which avoids costly fixed time step simulations; (2) a kd tree data structure for quickly locating, for a given molecule, its closest reactants. The

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

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

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

    2015-10-06

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

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

    SciTech Connect (OSTI)

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

    2013-08-01

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

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

    Office of Scientific and Technical Information (OSTI)

    that has proven successful in ow control design problems) is applied to obtain a low ... The controller is applied on the non-reduced, nonlinear MHW equations to stabilize the ...

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

    SciTech Connect (OSTI)

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

    2006-01-01

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

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

    SciTech Connect (OSTI)

    McClelland, M A; Maienschein, J L; Nichols, A L; Wardell, J F; Atwood, A I; Curran, P O

    2002-03-19

    ALE3D simulations are presented for the thermal explosion of PBXN-109 (RDX, AI, HTPB, DOA) in support of an effort by the U. S. Navy and Department of Energy (DOE) to validate computational models. The U.S. Navy is performing benchmark tests for the slow cookoff of PBXN-109 in a sealed tube. Candidate models are being tested using the ALE3D code, which can simulate the coupled thermal, mechanical, and chemical behavior during heating, ignition, and explosion. The strength behavior of the solid constituents is represented by a Steinberg-Guinan model while polynomial and gamma-law expressions are used for the Equation Of State (EOS) for the solid and gas species, respectively. A void model is employed to represent the air in gaps. ALE3D model 'parameters are specified using measurements of thermal and mechanical properties including thermal expansion, heat capacity, shear modulus, and bulk modulus. A standard three-step chemical kinetics model is used during the thermal ramp, and a pressure-dependent burn front model is employed during the rapid expansion. Parameters for the three-step kinetics model are specified using measurements of the One-Dimensional-Time-to-Explosion (ODTX), while measurements for burn rate of pristine and thermally damaged material are employed to determine parameters in the burn front model. Results are given for calculations in which heating, ignition, and explosion are modeled in a single simulation. We compare model results to measurements for the cookoff temperature and tube wall strain.

  5. Validation of a Fast-Fluid-Dynamics Model for Predicting Distribution of Particles with Low Stokes Number

    SciTech Connect (OSTI)

    Zuo, Wangda; Chen, Qingyan

    2011-06-01

    To design a healthy indoor environment, it is important to study airborne particle distribution indoors. As an intermediate model between multizone models and computational fluid dynamics (CFD), a fast fluid dynamics (FFD) model can be used to provide temporal and spatial information of particle dispersion in real time. This study evaluated the accuracy of the FFD for predicting transportation of particles with low Stokes number in a duct and in a room with mixed convection. The evaluation was to compare the numerical results calculated by the FFD with the corresponding experimental data and the results obtained by the CFD. The comparison showed that the FFD could capture major pattern of particle dispersion, which is missed in models with well-mixed assumptions. Although the FFD was less accurate than the CFD partially due to its simplification in numeric schemes, it was 53 times faster than the CFD.

  6. Progress toward bridging from atomistic to continuum modeling to predict nuclear waste glass dissolution.

    SciTech Connect (OSTI)

    Zapol, Peter; Bourg, Ian; Criscenti, Louise Jacqueline; Steefel, Carl I.; Schultz, Peter Andrew

    2011-10-01

    This report summarizes research performed for the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Subcontinuum and Upscaling Task. The work conducted focused on developing a roadmap to include molecular scale, mechanistic information in continuum-scale models of nuclear waste glass dissolution. This information is derived from molecular-scale modeling efforts that are validated through comparison with experimental data. In addition to developing a master plan to incorporate a subcontinuum mechanistic understanding of glass dissolution into continuum models, methods were developed to generate constitutive dissolution rate expressions from quantum calculations, force field models were selected to generate multicomponent glass structures and gel layers, classical molecular modeling was used to study diffusion through nanopores analogous to those in the interfacial gel layer, and a micro-continuum model (K{mu}C) was developed to study coupled diffusion and reaction at the glass-gel-solution interface.

  7. Impact of Higher Fidelity Models on Active Aerodynamic Load Control...

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

    simulation of active aerodynamic load control technology is provided here. Turbine component fatigue damage calculations require time-series load histories at the turbine...

  8. Divergent predictions of carbon storage between two global land models: attribution of the causes through traceability analysis

    SciTech Connect (OSTI)

    Rafique, Rashid; Xia, Jianyang; Hararuk, Oleksandra; Asrar, Ghassem R.; Wang, Yingping; Luo, Yiqi

    2015-08-27

    Representations of the terrestrial carbon cycle in land models are becoming increasingly complex. It is crucial to develop approaches for critical assessment of the complex model properties in order to understand key factors contributing to models’ performance. In this study, we applied a traceability analysis, which decomposes carbon cycle models into traceable components, to two global land models (CABLE and CLM-CASA’) to diagnose the causes of their differences in simulating ecosystem carbon storage capacity. Driven with similar forcing data, the CLM-CASA’ model predicted ~31% larger carbon storage capacity than the CABLE model. Since ecosystem carbon storage capacity is a product of net primary productivity (NPP) and ecosystem residence time (τE), the predicted difference in the storage capacity between the two models results from differences in either NPP or τE or both. Our analysis showed that CLM-CASA’ simulated 37% higher NPP than CABLE due to higher rates of carboxylation (Vcmax) in CLM-CASA’. On the other hand, τE , which was a function the baseline carbon residence time (τ´E) and environmental effect on carbon residence time, was on average 11 years longer in CABLE than CLM-CASA’. The difference in τE was mainly found to be caused by longer τ´E in CABLE than CLM-CASA’. This difference in τE was mainly caused by longer τ´E of woody biomass (23 vs. 14 years in CLM-CASA’) and higher proportion of NPP allocated to woody biomass (23% vs. 16%). Differences in environmental effects on carbon residence times had smaller influences on differences in ecosystem carbon storage capacities compared to differences in NPP and τ´E. Overall; the traceability analysis is an effective method for identifying sources of variations between the two models.

  9. A Model For Stress-Controlled Pipe Growth | Open Energy Information

    Open Energy Info (EERE)

    Stress-Controlled Pipe Growth Jump to: navigation, search OpenEI Reference LibraryAdd to library Journal Article: A Model For Stress-Controlled Pipe Growth Abstract The rock...

  10. Wind Plant Power Optimization through Yaw Control using a Parametric Model for Wake Effects -- A CFD Simulation Study

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

    Gebraad, P. M. O.; Teeuwisse, F. W.; van Wingerden, J. W.; Fleming, Paul A.; Ruben, S. D.; Marden, J. R.; Pao, L. Y.

    2016-01-01

    This article presents a wind plant control strategy that optimizes the yaw settings of wind turbines for improved energy production of the whole wind plant by taking into account wake effects. The optimization controller is based on a novel internal parametric model for wake effects, called the FLOw Redirection and Induction in Steady-state (FLORIS) model. The FLORIS model predicts the steady-state wake locations and the effective flow velocities at each turbine, and the resulting turbine electrical energy production levels, as a function of the axial induction and the yaw angle of the different rotors. The FLORIS model has a limitedmore » number of parameters that are estimated based on turbine electrical power production data. In high-fidelity computational fluid dynamics simulations of a small wind plant, we demonstrate that the optimization control based on the FLORIS model increases the energy production of the wind plant, with a reduction of loads on the turbines as an additional effect.« less

  11. Campus Energy Model for Control and Performance Validation

    Energy Science and Technology Software Center (OSTI)

    2014-09-19

    The core of the modeling platform is an extensible block library for the MATLAB/Simulink software suite. The platform enables true co-simulation (interaction at each simulation time step) with NREL's state-of-the-art modeling tools and other energy modeling software.

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

    Office of Scientific and Technical Information (OSTI)

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

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

    Office of Scientific and Technical Information (OSTI)

    Resource Relation: Conference: Community Earth System Model Workshop ; 2012-06-18 - ... Sponsoring Org: DOELANL Country of Publication: United States Language: English Subject: ...

  14. Control-Oriented Modeling for HCCI Combustion and Multi-Cylinder HCCI

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

    Experimental Activities | Department of Energy Control-Oriented Modeling for HCCI Combustion and Multi-Cylinder HCCI Experimental Activities Control-Oriented Modeling for HCCI Combustion and Multi-Cylinder HCCI Experimental Activities 2005 Diesel Engine Emissions Reduction (DEER) Conference Presentations and Posters 2005_deer_guezennec.pdf (1.36 MB) More Documents & Publications Detailed Modeling of HCCI and PCCI combustion and Multi-cylinder HCCI Engine Control Flex Fuel Optimized SI

  15. Demonstrating and Validating a Next Generation Model-Based Controller for

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

    Fuel Efficient, Low Emissions Diesel Engines | Department of Energy and Validating a Next Generation Model-Based Controller for Fuel Efficient, Low Emissions Diesel Engines Demonstrating and Validating a Next Generation Model-Based Controller for Fuel Efficient, Low Emissions Diesel Engines Fully model-based, practically-mapless engine control concept is viable deer09_allain.pdf (625.73 KB) More Documents & Publications Increased Engine Efficiency via Advancements in Engine Combustion

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

    SciTech Connect (OSTI)

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

    2015-10-06

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

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

    SciTech Connect (OSTI)

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

    2015-06-01

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

  18. Demonstrating Fuel Consumption and Emissions Reductions with Next Generation Model-Based Diesel Engine Control

    Broader source: Energy.gov [DOE]

    Presents a next generation model-based engine controller that incorporates real-time fuel efficiency optimization and tested under fully transient engine and vehicle operating conditions.

  19. Integrated Sensing & Controls for Coal Gasification - Development of Model-Based Controls for GE's Gasifier & Syngas Cooler. Topical Rerport for Phase III

    SciTech Connect (OSTI)

    Kumar, Aditya

    2011-02-17

    This Topical Report for the final Phase III of the program summarizes the results from the Task 3 of the program. In this task, the separately designed extended Kalman Filter (EKF) and model predictive controls (MPC) with ideal sensing, developed in Phase II, were integrated to achieve the overall sensing and control system for the gasification section of an IGCC plant. The EKF and MPC algorithms were updated and re-tuned to achieve closed-loop system stability as well as good steady-state and transient control response. In particular, the performance of the integrated EKF and MPC solution was tested extensively through multiple simulation studies to achieve improved steady-state as well as transient performance, with coal as well as coal-petcoke blended fuel, in the presence of unknown modeling errors as well as sensor errors (noise and bias). The simulation studies demonstrated significant improvements in steady state and transient operation performance, similar to that achieved by MPC with ideal sensors in Phase II of the program.

  20. FRAMEWORK AND APPLICATION FOR MODELING CONTROL ROOM CREW PERFORMANCE AT NUCLEAR POWER PLANTS

    SciTech Connect (OSTI)

    Ronald L Boring; David I Gertman; Tuan Q Tran; Brian F Gore

    2008-09-01

    This paper summarizes an emerging project regarding the utilization of high-fidelity MIDAS simulations for visualizing and modeling control room crew performance at nuclear power plants. The key envisioned uses for MIDAS-based control room simulations are: (i) the estimation of human error associated with advanced control room equipment and configurations, (ii) the investigative determination of contributory cognitive factors for risk significant scenarios involving control room operating crews, and (iii) the certification of reduced staffing levels in advanced control rooms. It is proposed that MIDAS serves as a key component for the effective modeling of cognition, elements of situation awareness, and risk associated with human performance in next generation control rooms.

  1. A comparison WEC control strategies for a linear WEC model

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

    OR. A number of metrics, ranging from power-flow char- acteristics to kinematics are ... In this WEC optimal control problem, the space-time domain is discretized. At each time ...

  2. A grillage model for predicting wrinkles in annular graphene under circular shearing

    SciTech Connect (OSTI)

    Zhang, Z.; Duan, W. H.; Wang, C. M.

    2013-01-07

    This paper is concerned with a Timoshenko grillage model for modeling the wrinkling phenomenon in annular graphene under circular shearing applied at its inner edge. By calibrating the grillage model results against the molecular mechanics (MM) results, the grillage model comprising beams of elliptical cross-section orientated along the carbon-carbon bond has section dimensions of 0.06 nm for the major axis length and 0.036 nm for the minor axis length. Moreover, the beams are connected to one another at 0.00212 nm from the geometric centric. This eccentric connection of beams allows the proposed grillage model to cater for the cross-couplings among bonds that produce the out-of-plane wrinkling pattern. The out-of-plane to in-plane bending stiffnesses' ratio is 0.36, and the cross bending stiffness provided by the ellipse eccentricity is 0.025 times that of the in-plane bending stiffness. Besides furnishing identical wave numbers as well as amplitudes and wavelengths that are in good agreement with MM results, the grillage model can capture wrinkling patterns with a boundary layer, whereas plate and membrane models could not mimic the boundary layer.

  3. Depositional sequence analysis and sedimentologic modeling for improved prediction of Pennsylvanian reservoirs (Annex 1). Annual report, February 1, 1991--January 31, 1992

    SciTech Connect (OSTI)

    Watney, W.L.

    1992-08-01

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

  4. Sensors and Controls Sub-Program Logic Model

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

    technologies, control systems & transactive communication platforms are regularly innovated & widely used to enhance building performance, increase energy savings, facilitate use of distributed renewables, & improve demand response, while lowering overall costs to building owners & occupants. The Sensors and Controls Sub-Program develops cost-effective building energy management solutions to optimize energy performance, increase energy savings and reduce costs, as well as

  5. Commercial absorption chiller models for evaluation of control strategies

    SciTech Connect (OSTI)

    Koeppel, E.A.; Klein, S.A.; Mitchell, J.W.

    1995-08-01

    A steady-state computer simulation model of a direct fired double-effect water-lithium bromide absorption chiller in the parallel-flow configuration was developed from first principles. Unknown model parameters such as heat transfer coefficients were determined by matching the model`s calculated state points and coefficient of performance (COP) against nominal full-load operating data and COPs obtained from a manufacturer`s catalog. The model compares favorably with the manufacturer`s performance ratings for varying water circuit (chilled and cooling) temperatures at full load conditions and for chiller part-load performance. The model was used (1) to investigate the effect of varying the water circuit flow rates with the chiller load and (2) to optimize chiller part-load performance with respect to the distribution and flow of the weak solution.

  6. Reflected kinetics model for nuclear space reactor kinetics and control scoping calculations

    SciTech Connect (OSTI)

    Washington, K.E.

    1986-05-01

    The objective of this research is to develop a model that offers an alternative to the point kinetics (PK) modelling approach in the analysis of space reactor kinetics and control studies. Modelling effort will focus on the explicit treatment of control drums as reactivity input devices so that the transition to automatic control can be smoothly done. The proposed model is developed for the specific integration of automatic control and the solution of the servo mechanism problem. The integration of the kinetics model with an automatic controller will provide a useful tool for performing space reactor scoping studies for different designs and configurations. Such a tool should prove to be invaluable in the design phase of a space nuclear system from the point of view of kinetics and control limitations.

  7. Recovery Act. Development and Validation of an Advanced Stimulation Prediction Model for Enhanced Geothermal Systems

    SciTech Connect (OSTI)

    Gutierrez, Marte

    2013-12-31

    This research project aims to develop and validate an advanced computer model that can be used in the planning and design of stimulation techniques to create engineered reservoirs for Enhanced Geothermal Systems. The specific objectives of the proposal are to; Develop a true three-dimensional hydro-thermal fracturing simulator that is particularly suited for EGS reservoir creation; Perform laboratory scale model tests of hydraulic fracturing and proppant flow/transport using a polyaxial loading device, and use the laboratory results to test and validate the 3D simulator; Perform discrete element/particulate modeling of proppant transport in hydraulic fractures, and use the results to improve understand of proppant flow and transport; Test and validate the 3D hydro-thermal fracturing simulator against case histories of EGS energy production; and Develop a plan to commercialize the 3D fracturing and proppant flow/transport simulator. The project is expected to yield several specific results and benefits. Major technical products from the proposal include; A true-3D hydro-thermal fracturing computer code that is particularly suited to EGS; Documented results of scale model tests on hydro-thermal fracturing and fracture propping in an analogue crystalline rock; Documented procedures and results of discrete element/particulate modeling of flow and transport of proppants for EGS applications; and Database of monitoring data, with focus of Acoustic Emissions (AE) from lab scale modeling and field case histories of EGS reservoir creation.

  8. Tritium monitoring in groundwater and evaluation of model predictions for the Hanford Site 200 Area Effluent Treatment Facility

    SciTech Connect (OSTI)

    Barnett, D.B.; Bergeron, M.P.; Cole, C.R.; Freshley, M.D.; Wurstner, S.K.

    1997-08-01

    The Effluent Treatment Facility (ETF) disposal site, also known as the State-Approved Land Disposal Site (SALDS), receives treated effluent containing tritium, which is allowed to infiltrate through the soil column to the water table. Tritium was first detected in groundwater monitoring wells around the facility in July 1996. The SALDS groundwater monitoring plan requires revision of a predictive groundwater model and reevaluation of the monitoring well network one year from the first detection of tritium in groundwater. This document is written primarily to satisfy these requirements and to report on analytical results for tritium in the SALDS groundwater monitoring network through April 1997. The document also recommends an approach to continued groundwater monitoring for tritium at the SALDS. Comparison of numerical groundwater models applied over the last several years indicate that earlier predictions, which show tritium from the SALDS approaching the Columbia River, were too simplified or overly robust in source assumptions. The most recent modeling indicates that concentrations of tritium above 500 pCi/L will extend, at most, no further than {approximately}1.5 km from the facility, using the most reasonable projections of ETF operation. This extent encompasses only the wells in the current SALDS tritium-tracking network.

  9. Methods and apparatus for measurement of a dimensional characteristic and methods of predictive modeling related thereto

    DOE Patents [OSTI]

    Robertson, Eric P; Christiansen, Richard L.

    2007-05-29

    A method of optically determining a change in magnitude of at least one dimensional characteristic of a sample in response to a selected chamber environment. A magnitude of at least one dimension of the at least one sample may be optically determined subsequent to altering the at least one environmental condition within the chamber. A maximum change in dimension of the at least one sample may be predicted. A dimensional measurement apparatus for indicating a change in at least one dimension of at least one sample. The dimensional measurement apparatus may include a housing with a chamber configured for accommodating pressure changes and an optical perception device for measuring a dimension of at least one sample disposed in the chamber. Methods of simulating injection of a gas into a subterranean formation, injecting gas into a subterranean formation, and producing methane from a coal bed are also disclosed.

  10. Methods for measurement of a dimensional characteristic and methods of predictive modeling related thereto

    DOE Patents [OSTI]

    Robertson, Eric P; Christiansen, Richard L.

    2007-10-23

    A method of optically determining a change in magnitude of at least one dimensional characteristic of a sample in response to a selected chamber environment. A magnitude of at least one dimension of the at least one sample may be optically determined subsequent to altering the at least one environmental condition within the chamber. A maximum change in dimension of the at least one sample may be predicted. A dimensional measurement apparatus for indicating a change in at least one dimension of at least one sample. The dimensional measurement apparatus may include a housing with a chamber configured for accommodating pressure changes and an optical perception device for measuring a dimension of at least one sample disposed in the chamber. Methods of simulating injection of a gas into a subterranean formation, injecting gas into a subterranean formation, and producing methane from a coal bed are also disclosed.

  11. A new model for predicting the fouling deposit weight of coal

    SciTech Connect (OSTI)

    Yeakel, J.D. ); Finkelman, R.B. )

    1988-06-01

    One of the major problems associated with coal combustion is the buildup of sintered ash deposits in the convective passes of boilers. These deposits, referred to as fouling deposits, can drastically reduce heat transfer, cause erosion by channelizing gas flow, and contribute to the corrosion of exposed metal surfaces. Downtime for cleaning fouled commercial boilers can be a multi-million-dollar expense. Utility boilers generally are designed to burn coal that falls within a specific fouling behavior range. Therefore, to minimize the deleterious effects of boiler fouling and to maximize boiler efficiency, it is necessary to anticipate or assess the fouling characteristics of a coal prior to combustion. This paper introduces a new method for predicting fouling deposit weights by using commonly available coal quality data. The authors have developed a modified concept of the coal quality characteristics that influence fouling. This concept evolved from a review of the literature and from the statistical analysis of results from 44 combustion tests.

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

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

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

    2014-12-31

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

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

    SciTech Connect (OSTI)

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

    2014-12-31

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

  14. Comparison of Uncertainty of Two Precipitation Prediction Models at Los Alamos National Lab Technical Area 54

    SciTech Connect (OSTI)

    Shield, Stephen Allan; Dai, Zhenxue

    2015-08-18

    Meteorological inputs are an important part of subsurface flow and transport modeling. The choice of source for meteorological data used as inputs has significant impacts on the results of subsurface flow and transport studies. One method to obtain the meteorological data required for flow and transport studies is the use of weather generating models. This paper compares the difference in performance of two weather generating models at Technical Area 54 of Los Alamos National Lab. Technical Area 54 is contains several waste pits for low-level radioactive waste and is the site for subsurface flow and transport studies. This makes the comparison of the performance of the two weather generators at this site particularly valuable.

  15. Development and Validation of an Advanced Stimulation Prediction Model for Enhanced Geothermal Systems (EGS)

    Broader source: Energy.gov [DOE]

    Project objectives: Develop a true 3D hydro-thermal fracturing and proppant flow/transport simulator that is particularly suited for EGS reservoir creation. Perform laboratory scale model tests of hydraulic fracturing and proppant flow/transport using a polyaxial loading device, and use the laboratory results to test and validate the 3D simulator.

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

    SciTech Connect (OSTI)

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

    2010-09-01

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

  17. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

    SciTech Connect (OSTI)

    Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Tropsha, Alexander

    2015-04-15

    Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. • Putative

  18. Critical Infrastructure Modeling: An Approach to Characterizing Interdependencies of Complex Networks & Control Systems

    SciTech Connect (OSTI)

    Stuart Walsh; Shane Cherry; Lyle Roybal

    2009-05-01

    Critical infrastructure control systems face many challenges entering the 21st century, including natural disasters, cyber attacks, and terrorist attacks. Revolutionary change is required to solve many existing issues, including gaining greater situational awareness and resiliency through embedding modeling and advanced control algorithms in smart sensors and control devices instead of in a central controller. To support design, testing, and component analysis, a flexible simulation and modeling capability is needed. Researchers at Idaho National Laboratory are developing and evaluating such a capability through their CIPRsim modeling and simulation framework.

  19. REDUCING UNCERTAINTIES IN MODEL PREDICTIONS VIA HISTORY MATCHING OF CO2 MIGRATION AND REACTIVE TRANSPORT MODELING OF CO2 FATE AT THE SLEIPNER PROJECT

    SciTech Connect (OSTI)

    Zhu, Chen

    2015-03-31

    An important question for the Carbon Capture, Storage, and Utility program is “can we adequately predict the CO2 plume migration?” For tracking CO2 plume development, the Sleipner project in the Norwegian North Sea provides more time-lapse seismic monitoring data than any other sites, but significant uncertainties still exist for some of the reservoir parameters. In Part I, we assessed model uncertainties by applying two multi-phase compositional simulators to the Sleipner Benchmark model for the uppermost layer (Layer 9) of the Utsira Sand and calibrated our model against the time-lapsed seismic monitoring data for the site from 1999 to 2010. Approximate match with the observed plume was achieved by introducing lateral permeability anisotropy, adding CH4 into the CO2 stream, and adjusting the reservoir temperatures. Model-predicted gas saturation, CO2 accumulation thickness, and CO2 solubility in brine—none were used as calibration metrics—were all comparable with the interpretations of the seismic data in the literature. In Part II & III, we evaluated the uncertainties of predicted long-term CO2 fate up to 10,000 years, due to uncertain reaction kinetics. Under four scenarios of the kinetic rate laws, the temporal and spatial evolution of CO2 partitioning into the four trapping mechanisms (hydrodynamic/structural, solubility, residual/capillary, and mineral) was simulated with ToughReact, taking into account the CO2-brine-rock reactions and the multi-phase reactive flow and mass transport. Modeling results show that different rate laws for mineral dissolution and precipitation reactions resulted in different predicted amounts of trapped CO2 by carbonate minerals, with scenarios of the conventional linear rate law for feldspar dissolution having twice as much mineral trapping (21% of the injected CO2) as scenarios with a Burch-type or Alekseyev et al.–type rate law for feldspar dissolution (11%). So far, most reactive transport modeling (RTM) studies for

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

    SciTech Connect (OSTI)

    Mishra, Srikanta; Schuetter, Jared

    2014-11-01

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

  1. A Reference Model for Distribution Grid Control in the 21st Century

    SciTech Connect (OSTI)

    Taft, Jeffrey D.; De Martini, Paul; Kristov, Lorenzo

    2015-07-01

    Intensive changes in the structure of the grid due to the penetration of new technologies, coupled with changing societal needs are outpacing the capabilities of traditional grid control systems. The gap is widening at an accelerating rate with the biggest impacts occurring at the distribution level due to the widespread adoption of diverse distribution-connected energy resources (DER) . This paper outlines the emerging distribution grid control environment, defines the new distribution control problem, and provides a distribution control reference model. The reference model offers a schematic representation of the problem domain to inform development of system architecture and control solutions for the high-DER electric system.

  2. Improved atmosphere-ocean coupled modeling in the tropics for climate prediction

    SciTech Connect (OSTI)

    Zhang, Minghua

    2015-01-01

    We investigated the initial development of the double ITCZ in the Community Climate System Model (CCSM Version 3) in the central Pacific. Starting from a resting initial condition of the ocean in January, the model developed a warm bias of sea-surface temperature (SST) in the central Pacific from 5oS to 10oS in the first three months. We found this initial bias to be caused by excessive surface shortwave radiation that is also present in the standalone atmospheric model. The initial bias is further amplified by biases in both surface latent heat flux and horizontal heat transport in the upper ocean. These biases are caused by the responses of surface winds to SST bias and the thermocline structure to surface wind curls. We also showed that the warming biases in surface solar radiation and latent heat fluxes are seasonally offset by cooling biases from reduced solar radiation after the austral summer due to cloud responses and in the austral fall due to enhanced evaporation when the maximum SST is closest to the equator. The warming biases from the dynamic heat transport by ocean currents however stay throughout all seasons once they are developed, which are eventually balanced by enhanced energy exchange and penetration of solar radiation below the mixed layer. Our results also showed that the equatorial cold tongue develops after the warm biases in the south central Pacific, and the overestimation of surface shortwave radiation recurs in the austral summer in each year.

  3. Comparison of high pressure transient PVT measurements and model predictions. Part I.

    SciTech Connect (OSTI)

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

    2010-07-01

    A series of experiments consisting of vessel-to-vessel transfers of pressurized gas using Transient PVT methodology have been conducted to provide a data set for optimizing heat transfer correlations in high pressure flow systems. In rapid expansions such as these, the heat transfer conditions are neither adiabatic nor isothermal. Compressible flow tools exist, such as NETFLOW that can accurately calculate the pressure and other dynamical mechanical properties of such a system as a function of time. However to properly evaluate the mass that has transferred as a function of time these computational tools rely on heat transfer correlations that must be confirmed experimentally. In this work new data sets using helium gas are used to evaluate the accuracy of these correlations for receiver vessel sizes ranging from 0.090 L to 13 L and initial supply pressures ranging from 2 MPa to 40 MPa. The comparisons show that the correlations developed in the 1980s from sparse data sets perform well for the supply vessels but are not accurate for the receivers, particularly at early time during the transfers. This report focuses on the experiments used to obtain high quality data sets that can be used to validate computational models. Part II of this report discusses how these data were used to gain insight into the physics of gas transfer and to improve vessel heat transfer correlations. Network flow modeling and CFD modeling is also discussed.

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

    SciTech Connect (OSTI)

    Sakalaukus, Peter Joseph

    2015-08-01

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

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

    SciTech Connect (OSTI)

    Harrison, T.D.

    1981-05-01

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

  6. Computational Tools for Predictive Modeling of Properties in Complex Actinide Systems

    SciTech Connect (OSTI)

    Autschbach, Jochen; Govind, Niranjan; Atta Fynn, Raymond; Bylaska, Eric J.; Weare, John H.; de Jong, Wibe A.

    2015-03-30

    In this chapter we focus on methodological and computational aspects that are key to accurately modeling the spectroscopic and thermodynamic properties of molecular systems containing actinides within the density functional theory (DFT) framework. Our focus is on properties that require either an accurate relativistic all-electron description or an accurate description of the dynamical behavior of actinide species in an environment at finite temperature, or both. The implementation of the methods and the calculations discussed in this chapter were done with the NWChem software suite (Valiev et al. 2010). In the first two sections we discuss two methods that account for relativistic effects, the ZORA and the X2C Hamiltonian. Section 1.2.1 discusses the implementation of the approximate relativistic ZORA Hamiltonian and its extension to magnetic properties. Section 1.3 focuses on the exact X2C Hamiltonian and the application of this methodology to obtain accurate molecular properties. In Section 1.4 we examine the role of a dynamical environment at finite temperature as well as the presence of other ions on the thermodynamics of hydrolysis and exchange reaction mechanisms. Finally, Section 1.5 discusses the modeling of XAS (EXAFS, XANES) properties in realistic environments accounting for both the dynamics of the system and (for XANES) the relativistic effects.

  7. Predictive models of circulating fluidized bed combustors. 12th technical progress report

    SciTech Connect (OSTI)

    Gidaspow, D.

    1992-07-01

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

  8. Evaluation Of The Integrated Solubility Model, A Graded Approach For Predicting Phase Distribution In Hanford Tank Waste

    SciTech Connect (OSTI)

    Pierson, Kayla L.; Belsher, Jeremy D.; Seniow, Kendra R.

    2012-10-19

    The mission of the DOE River Protection Project (RPP) is to store, retrieve, treat and dispose of Hanford's tank waste. Waste is retrieved from the underground tanks and delivered to the Waste Treatment and Immobilization Plant (WTP). Waste is processed through a pretreatment facility where it is separated into low activity waste (LAW), which is primarily liquid, and high level waste (HLW), which is primarily solid. The LAW and HLW are sent to two different vitrification facilities and glass canisters are then disposed of onsite (for LAW) or shipped off-site (for HLW). The RPP mission is modeled by the Hanford Tank Waste Operations Simulator (HTWOS), a dynamic flowsheet simulator and mass balance model that is used for mission analysis and strategic planning. The integrated solubility model (ISM) was developed to improve the chemistry basis in HTWOS and better predict the outcome of the RPP mission. The ISM uses a graded approach to focus on the components that have the greatest impact to the mission while building the infrastructure for continued future improvement and expansion. Components in the ISM are grouped depending upon their relative solubility and impact to the RPP mission. The solubility of each group of components is characterized by sub-models of varying levels of complexity, ranging from simplified correlations to a set of Pitzer equations used for the minimization of Gibbs Energy.

  9. Strong field coherent control of molecular torsions—Analytical models

    SciTech Connect (OSTI)

    Ashwell, Benjamin A.; Ramakrishna, S.; Seideman, Tamar

    2015-08-14

    We introduce analytical models of torsional alignment by moderately intense laser pulses that are applicable to the limiting cases of the torsional barrier heights. Using these models, we explore in detail the role that the laser intensity and pulse duration play in coherent torsional dynamics, addressing both experimental and theoretical concerns. Our results suggest strategies for minimizing the risk of off-resonant ionization, noting the qualitative differences between the case of torsional alignment subject to a field-free torsional barrier and that of torsional alignment of a barrier-less system (equivalent to a 2D rigid rotor). We also investigate several interesting torsional phenomena, including the onset of impulsive alignment of torsions, field-driven oscillations in quantum number space, and the disappearance of an alignment upper bound observed for a rigid rotor in the impulsive torsional alignment limit.

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

    SciTech Connect (OSTI)

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

    2013-03-19

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

  11. Modeling and Control of Aggregated Air Conditioning Loads Under Realistic Conditions

    SciTech Connect (OSTI)

    Chang, Chin-Yao; Zhang, Wei; Lian, Jianming; Kalsi, Karanjit

    2013-02-24

    Demand-side control is playing an increasingly important role in smart grid control strategies. Modeling the dynamical behavior of a large population of appliances is especially important to evaluate the effectiveness of various load control strategies. In this paper, a high accuracy aggregated model is first developed for a population of HVAC units. The model efficiently includes statistical information of the population, systematically deals with heterogeneity, and accounts for a second-order effect necessary to accurately capture the transient dynamics in the collective response. Furthermore, the model takes into account the lockout effect of the compressor in order to represent the dynamics of the system under control more accurately. Then, a novel closed loop load control strategy is designed to track a desired demand curve and to ensure a stable and smooth response.

  12. An integrated model supporting histological and biometric responses as predictive biomarkers of fish health status

    SciTech Connect (OSTI)

    Torres Junior, Audalio Rebelo; Sousa, Débora Batista Pinheiro; Neta, Raimunda Nonata Fortes Carvalho

    2014-10-06

    In this work, an experimental system of histological (branchial lesions) biomarkers and biometric data in catfish (Sciades herzbergii) was modeled. The fish were sampled along known pollution areas (S1) and from environmental protect areas (S2) in São Marcos' Bay, Brazil. Gills were fixed in 10% formalin and usual histological techniques were used in the first gill arch right. The lesions were observed by light microscopy. There were no histopathological changes in animals captured at reference site (S1). However, in the catfish collected in the potentially contaminated area (S2) was observed several branchial lesions, such as lifting of the lamellar epithelium, fusion of some secondary lamellae, hypertrophy of epithelial cells and lamellar aneurysm. The analysis using the biometric data showed significant differences, being highest in fish analyzed in the reference area. This approach revealed spatial differences related with biometric patterns and morphological modifications of catfish.

  13. Nuclear Shell Model Analyses and Predictions of Double-Beta Decay Observables

    SciTech Connect (OSTI)

    Horoi, Mihai [Department of Physics, Central Michigan University, Mount Pleasant, Michigan, 48859 (United States)

    2010-11-24

    Recent results from neutrino oscillation experiments have convincingly demonstrated that neutrinos have mass and they can mix. The neutrinoless double beta decay is the most sensitive process to determine the absolute scale of the neutrino masses, and the only one that can distinguish whether neutrino is a Dirac or a Majorana particle. A key ingredient for extracting the absolute neutrino masses from neutrinoless double beta decay experiments is a precise knowledge of the nuclear matrix elements (NME) for this process. Newly developed shell model approaches for computing the NME and half-lifes for the two-neutrino and neutrinoless double beta decay modes using modern effective interactions are presented. The implications of the new results on the experimental limits of the effective neutrino mass are discussed by comparing the decays of {sup 48}Ca and {sup 76}Ge.

  14. Life Prediction and Classification of Failure Modes in Solid State Luminaires Using Bayesian Probabilistic Models

    SciTech Connect (OSTI)

    Lall, Pradeep; Wei, Junchao; Sakalaukus, Peter

    2014-05-27

    A new method has been developed for assessment of the onset of degradation in solid state luminaires to classify failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identify luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. It is expected that, the new test technique will allow the development of failure distributions without testing till L70 life for the manifestation of failure.

  15. Bayesian Models for Life Prediction and Fault-Mode Classification in Solid State Lamps

    SciTech Connect (OSTI)

    Lall, Pradeep; Wei, Junchao; Sakalaukus, Peter

    2015-04-19

    A new method has been developed for assessment of the onset of degradation in solid state luminaires to classifY failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identifY luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. It is expected that, the new test technique will allow the development of failure distributions without testing till L 70 life for the manifestation of failure.

  16. Predictive modeling of CO{sub 2} sequestration in deep saline sandstone reservoirs: Impacts of geochemical kinetics

    SciTech Connect (OSTI)

    Balashov, Victor N.; Guthrie, George D.; Hakala, J. Alexandra; Lopano, Christina L. J.; Rimstidt, Donald; Brantley, Susan L.

    2013-03-01

    One idea for mitigating the increase in fossil-fuel generated CO{sub 2} in the atmosphere is to inject CO{sub 2} into subsurface saline sandstone reservoirs. To decide whether to try such sequestration at a globally significant scale will require the ability to predict the fate of injected CO{sub 2}. Thus, models are needed to predict the rates and extents of subsurface rock-water-gas interactions. Several reactive transport models for CO{sub 2} sequestration created in the last decade predicted sequestration in sandstone reservoirs of ~17 to ~90 kg CO{sub 2} m{sup -3|. To build confidence in such models, a baseline problem including rock + water chemistry is proposed as the basis for future modeling so that both the models and the parameterizations can be compared systematically. In addition, a reactive diffusion model is used to investigate the fate of injected supercritical CO{sub 2} fluid in the proposed baseline reservoir + brine system. In the baseline problem, injected CO{sub 2} is redistributed from the supercritical (SC) free phase by dissolution into pore brine and by formation of carbonates in the sandstone. The numerical transport model incorporates a full kinetic description of mineral-water reactions under the assumption that transport is by diffusion only. Sensitivity tests were also run to understand which mineral kinetics reactions are important for CO{sub 2} trapping. The diffusion transport model shows that for the first ~20 years after CO{sub 2} diffusion initiates, CO{sub 2} is mostly consumed by dissolution into the brine to form CO{sub 2,aq} (solubility trapping). From 20-200 years, both solubility and mineral trapping are important as calcite precipitation is driven by dissolution of oligoclase. From 200 to 1000 years, mineral trapping is the most important sequestration mechanism, as smectite dissolves and calcite precipitates. Beyond 2000 years, most trapping is due to formation of aqueous HCO{sub 3}{sup -}. Ninety-seven percent of the

  17. Predicting tropospheric ozone and hydroxyl radical in a global, three-dimensional, chemistry, transport, and deposition model

    SciTech Connect (OSTI)

    Atherton, C.S.

    1995-01-05

    Two of the most important chemically reactive tropospheric gases are ozone (O{sub 3}) and the hydroxyl radical (OH). Although ozone in the stratosphere is a necessary protector against the sun`s radiation, tropospheric ozone is actually a pollutant which damages materials and vegetation, acts as a respiratory irritant, and is a greenhouse gas. One of the two main sources of ozone in the troposphere is photochemical production. The photochemistry is initiated when hydrocarbons and carbon monoxide (CO) react with nitrogen oxides (NO{sub x} = NO + NO{sub 2}) in the presence of sunlight. Reaction with the hydroxyl radical, OH, is the main sink for many tropospheric gases. The hydroxyl radical is highly reactive and has a lifetime on the order of seconds. Its formation is initiated by the photolysis of tropospheric ozone. Tropospheric chemistry involves a complex, non-linear set of chemical reactions between atmospheric species that vary substantially in time and space. To model these and other species on a global scale requires the use of a global, three-dimensional chemistry, transport, and deposition (CTD) model. In this work, I developed two such three dimensional CTD models. The first model incorporated the chemistry necessary to model tropospheric ozone production from the reactions of nitrogen oxides with carbon monoxide (CO) and methane (CH{sub 4}). The second also included longer-lived alkane species and the biogenic hydrocarbon isoprene, which is emitted by growing plants and trees. The models` ability to predict a number of key variables (including the concentration of O{sub 3}, OH, and other species) were evaluated. Then, several scenarios were simulated to understand the change in the chemistry of the troposphere since preindustrial times and the role of anthropogenic NO{sub x} on present day conditions.

  18. Energy-efficient housing alternatives: a predictive model of factors affecting household perceptions

    SciTech Connect (OSTI)

    Schreckengost, R.L.

    1985-01-01

    The major purpose of this investigation was to assess the impact of household socio-economic factors, dwelling characteristics, energy conservation behavior, and energy attitudes on the perceptions of energy-efficient housing alternatives. Perceptions of passive solar, active solar, earth sheltered, and retrofitted housing were examined. Data used were from the Southern Regional Research Project, S-141, Housing for Low and Moderate Income Families. Responses from 1804 households living in seven southern states were analyzed. A conceptual model was proposed to test the hypothesized relationships which were examined by path analysis. Perceptions of energy efficient housing alternatives were found to be a function of selected household and dwelling characteristics, energy attitude, household economic factors, and household conservation behavior. Age and education of the respondent, family size, housing-income ratio, utility income ratio, energy attitude, and size of the dwelling unit were found to have direct and indirect effects on perceptions of energy-efficient housing alternatives. Energy conservation behavior made a significant direct impact with behavioral energy conservation changes having the most profound influence. Conservation behavior was influenced by selected household and dwelling characteristics, energy attitude, and household economic factors.

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

    SciTech Connect (OSTI)

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

    2011-03-31

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

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

    SciTech Connect (OSTI)

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

    1996-10-25

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

  1. Dynamic Modeling and Control Studies of a Two-Stage Bubbling Fluidized Bed Adsorber-Reactor for Solid-Sorbent CO{sub 2} Capture

    SciTech Connect (OSTI)

    Modekurti, Srinivasarao; Bhattacharyya, Debangsu; Zitney, Stephen E.

    2013-07-31

    A one-dimensional, non-isothermal, pressure-driven dynamic model has been developed for a two-stage bubbling fluidized bed (BFB) adsorber-reactor for solid-sorbent carbon dioxide (CO{sub 2}) capture using Aspen Custom Modeler® (ACM). The BFB model for the flow of gas through a continuous phase of downward moving solids considers three regions: emulsion, bubble, and cloud-wake. Both the upper and lower reactor stages are of overflow-type configuration, i.e., the solids leave from the top of each stage. In addition, dynamic models have been developed for the downcomer that transfers solids between the stages and the exit hopper that removes solids from the bottom of the bed. The models of all auxiliary equipment such as valves and gas distributor have been integrated with the main model of the two-stage adsorber reactor. Using the developed dynamic model, the transient responses of various process variables such as CO{sub 2} capture rate and flue gas outlet temperatures have been studied by simulating typical disturbances such as change in the temperature, flowrate, and composition of the incoming flue gas from pulverized coal-fired power plants. In control studies, the performance of a proportional-integral-derivative (PID) controller, feedback-augmented feedforward controller, and linear model predictive controller (LMPC) are evaluated for maintaining the overall CO{sub 2} capture rate at a desired level in the face of typical disturbances.

  2. Evaluating temperature and fuel stratification for heat-release rate control in a reactivity-controlled compression-ignition engine using optical diagnostics and chemical kinetics modeling

    SciTech Connect (OSTI)

    Musculus, Mark P. B.; Kokjohn, Sage L.; Reitz, Rolf D.

    2015-04-23

    We investigated the combustion process in a dual-fuel, reactivity-controlled compression-ignition (RCCI) engine using a combination of optical diagnostics and chemical kinetics modeling to explain the role of equivalence ratio, temperature, and fuel reactivity stratification for heat-release rate control. An optically accessible engine is operated in the RCCI combustion mode using gasoline primary reference fuels (PRF). A well-mixed charge of iso-octane (PRF = 100) is created by injecting fuel into the engine cylinder during the intake stroke using a gasoline-type direct injector. Later in the cycle, n-heptane (PRF = 0) is delivered through a centrally mounted diesel-type common-rail injector. This injection strategy generates stratification in equivalence ratio, fuel blend, and temperature. The first part of this study uses a high-speed camera to image the injection events and record high-temperature combustion chemiluminescence. Moreover, the chemiluminescence imaging showed that, at the operating condition studied in the present work, mixtures in the squish region ignite first, and the reaction zone proceeds inward toward the center of the combustion chamber. The second part of this study investigates the charge preparation of the RCCI strategy using planar laser-induced fluorescence (PLIF) of a fuel tracer under non-reacting conditions to quantify fuel concentration distributions prior to ignition. The fuel-tracer PLIF data show that the combustion event proceeds down gradients in the n-heptane distribution. The third part of the study uses chemical kinetics modeling over a range of mixtures spanning the distributions observed from the fuel-tracer fluorescence imaging to isolate the roles of temperature, equivalence ratio, and PRF number stratification. The simulations predict that PRF number stratification is the dominant factor controlling the ignition location and growth rate of the reaction zone. Equivalence ratio has a smaller, but still significant

  3. Development of the integrated environmental control model. Quarterly progress report, April 1995--June 1995

    SciTech Connect (OSTI)

    Kalagnanam, J.R.; Rubin, E.S.

    1995-06-01

    The purpose of this contract is to develop and refine the Integrated Environmental Control Model (IECM). In its current configuration, the IECM provides a capability to model various conventional and advanced processes for controlling air pollutant emissions from coal-fired power plants before, during, or after combustion. The principal purpose of the model is to calculate the performance, emissions, and cost of power plant configurations employing alternative environmental control methods. The model consists of various control technology modules, which may be integrated into a complete utility plant in any desired combination. In contrast to conventional deterministic models, the IECM offers the unique capability to assign probabilistic values to all model input parameters, and to obtain probabilistic outputs in the form of cumulative distribution functions indicating the likelihood of different costs and performance results. The work in this contract is divided into two phases. Phase I deals with further developing the existing version of the IECM and training PETC personnel on the effective use of the model. Phase H deals with creating new technology modules, linking the IECM with PETC databases, and training PETC personnel on the effective use of the updated model. The present report summarizes recent progress on the Phase I effort during the period April 1, 1995 through June 30, 1995. This report presents additional revisions to the new cost models of flue gas desulfurization (FGD) technology initially reported in our fourth quarterly report. For convenience, the complete description of the revised FGD models are presented here.

  4. Municipal Consortium Releases Updated Model Specification for Networked Outdoor Lighting Control Systems

    Broader source: Energy.gov [DOE]

    The U.S. Department of Energy's Municipal Solid-State Street Lighting Consortium (MSSLC) has released an update to its Model Specification for Adaptive Control and Remote Monitoring of LED Roadway...

  5. Nonlinear process model based control of a propylene sidestream draw column

    SciTech Connect (OSTI)

    Riggs, J.B. )

    1990-11-01

    While sidestream draw columns offer the incentives of reduced capital and operating expenses, they also pose more challenging control problems than ordinary distillation columns. This paper describes the application of nonlinear process model based control (PMBC) for composition control of all product streams for a simulation of a distillation column with a liquid sidestream draw. A tray-to-tray simulator of an industrial propylene/propane column that considers 5-min composition analyzer dead time was used to test the nonlinear PMBC controller for setpoint changes, a feed flow rate change, and feed composition changes. The nonlinear PMBC controller used an approximate model based upon the Smoker equation directly to make control decisions. The nonlinear PMBC controller exhibits excellent control performance for all test cases with a maximum relative deviation of the impurity from setpoint of about 10% for the two product streams. The nonlinear PMBC controller provides significantly improved control performance over a conventional single loop control scheme that is currently in industrial use.

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

    SciTech Connect (OSTI)

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

    1995-02-22

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

  7. A review of existing models and methods to estimate employment effects of pollution control policies

    SciTech Connect (OSTI)

    Darwin, R.F.; Nesse, R.J.

    1988-02-01

    The purpose of this paper is to provide information about existing models and methods used to estimate coal mining employment impacts of pollution control policies. The EPA is currently assessing the consequences of various alternative policies to reduce air pollution. One important potential consequence of these policies is that coal mining employment may decline or shift from low-sulfur to high-sulfur coal producing regions. The EPA requires models that can estimate the magnitude and cost of these employment changes at the local level. This paper contains descriptions and evaluations of three models and methods currently used to estimate the size and cost of coal mining employment changes. The first model reviewed is the Coal and Electric Utilities Model (CEUM), a well established, general purpose model that has been used by the EPA and other groups to simulate air pollution control policies. The second model reviewed is the Advanced Utility Simulation Model (AUSM), which was developed for the EPA specifically to analyze the impacts of air pollution control policies. Finally, the methodology used by Arthur D. Little, Inc. to estimate the costs of alternative air pollution control policies for the Consolidated Coal Company is discussed. These descriptions and evaluations are based on information obtained from published reports and from draft documentation of the models provided by the EPA. 12 refs., 1 fig.

  8. Hydrogen and Nitrogen Control in Ladle and Casting Operations

    SciTech Connect (OSTI)

    2002-01-01

    Development of Models will Help Predict and Control Hydrogen and Nitrogen Levels in Electric Arc Furnace and Basic Oxygen Furnace Steelmaking

  9. Modeling the effects of control systems of wind turbine fatigue life

    SciTech Connect (OSTI)

    Pierce, K.G.; Laino, D.J.

    1996-12-31

    In this study we look at the effect on fatigue life of two types of control systems. First, we investigate the Micon 65, an upwind, three bladed turbine with a simple yaw control system. Results indicate that increased fatigue damage to the blade root can be attributed to continuous operation at significant yaw error allowed by the control system. Next, we model a two-bladed teetered rotor turbine using three different control systems to adjust flap deflections. The first two limit peak power output, the third limits peak power and cyclic power output over the entire range of operation. Results for simulations conducted both with and without active control are compared to determine how active control affects fatigue life. Improvement in fatigue lifetimes were seen for all control schemes, with increasing fatigue lifetime corresponding to increased flap deflection activity. 13 refs., 6 figs., 2 tabs.

  10. Steady state and dynamic modeling of a packed bed reactor for the partial oxidation of methanol to formaldehyde: experimental results compared with model predictions

    SciTech Connect (OSTI)

    Schwedock, M.J.; Windes, L.C.; Ray, W.H.

    1985-01-01

    Heterogeneous and pseudohomogeneous models are compared to experimental data from a packed bed reactor for the partical oxidation of methanol to formaldehyde over an iron oxide-molybdenum oxide catalyst. Heat transfer parameters which were successful in matching data from experiments without reaction were not successful in matching temperature data from experiments with reaction. This made it necessary to decrease the fluid radial heat transfer to obtain good fit. A good fit was obtained for steady state composition profiles by optimizing selected frequency factors and the activation energy for methanol. A redox rate expression for the oxidation of formaldehyde to carbon monoxide was proposed since a simple first-order rate expression did not fit the data. The pseudohomogeneous model gave results similar to the heterogeneous model for both steady state and dynamic experiments and has been recommended for future experimental state estimation and control studies. 21 refs., 31 figs., 6 tabs.

  11. Predictivity of dog co-culture model, primary human hepatocytes and HepG2 cells for the detection of hepatotoxic drugs in humans

    SciTech Connect (OSTI)

    Atienzar, Franck A.; Novik, Eric I.; Gerets, Helga H.; Parekh, Amit; Delatour, Claude; Cardenas, Alvaro; MacDonald, James; Yarmush, Martin L.; Dhalluin, Stphane

    2014-02-15

    Drug Induced Liver Injury (DILI) is a major cause of attrition during early and late stage drug development. Consequently, there is a need to develop better in vitro primary hepatocyte models from different species for predicting hepatotoxicity in both animals and humans early in drug development. Dog is often chosen as the non-rodent species for toxicology studies. Unfortunately, dog in vitro models allowing long term cultures are not available. The objective of the present manuscript is to describe the development of a co-culture dog model for predicting hepatotoxic drugs in humans and to compare the predictivity of the canine model along with primary human hepatocytes and HepG2 cells. After rigorous optimization, the dog co-culture model displayed metabolic capacities that were maintained up to 2 weeks which indicates that such model could be also used for long term metabolism studies. Most of the human hepatotoxic drugs were detected with a sensitivity of approximately 80% (n = 40) for the three cellular models. Nevertheless, the specificity was low approximately 40% for the HepG2 cells and hepatocytes compared to 72.7% for the canine model (n = 11). Furthermore, the dog co-culture model showed a higher superiority for the classification of 5 pairs of close structural analogs with different DILI concerns in comparison to both human cellular models. Finally, the reproducibility of the canine system was also satisfactory with a coefficient of correlation of 75.2% (n = 14). Overall, the present manuscript indicates that the dog co-culture model may represent a relevant tool to perform chronic hepatotoxicity and metabolism studies. - Highlights: Importance of species differences in drug development. Relevance of dog co-culture model for metabolism and toxicology studies. Hepatotoxicity: higher predictivity of dog co-culture vs HepG2 and human hepatocytes.

  12. Model-free adaptive control of supercritical circulating fluidized-bed boilers

    DOE Patents [OSTI]

    Cheng, George Shu-Xing; Mulkey, Steven L

    2014-12-16

    A novel 3-Input-3-Output (3.times.3) Fuel-Air Ratio Model-Free Adaptive (MFA) controller is introduced, which can effectively control key process variables including Bed Temperature, Excess O2, and Furnace Negative Pressure of combustion processes of advanced boilers. A novel 7-input-7-output (7.times.7) MFA control system is also described for controlling a combined 3-Input-3-Output (3.times.3) process of Boiler-Turbine-Generator (BTG) units and a 5.times.5 CFB combustion process of advanced boilers. Those boilers include Circulating Fluidized-Bed (CFB) Boilers and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.

  13. Modeling of integrated environmental control systems for coal-fired power plants

    SciTech Connect (OSTI)

    Rubin, E.S.

    1989-10-01

    The general goal of this research project is to enhance, and transfer to DOE, a new computer simulation model for analyzing the performance and cost of environmental control systems for coal-fired power plants. Systems utilizing pre-combustion, combustion, or post-combustion control methods, individually or in combination, may be considered. A unique capability of this model is the probabilistic representation of uncertainty in model input parameters. This stochastic simulation capability allows the performance and cost of environmental control systems to be quantified probabilistically, accounting for the interactions among all uncertain process and economic parameters. This method facilitates more rigorous comparisons between conventional and advanced clean coal technologies promising improved cost and/or effectiveness for SO{sub 2} and NO{sub x} removal. Detailed modeling of several pre-combustion and post-combustion processes of interest to DOE/PETC have been selected for analysis as part of this project.

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

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

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

    2016-06-23

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

  15. Experimentally validated long-term energy production prediction model for solar dish/Stirling electric generating systems

    SciTech Connect (OSTI)

    Stine, W.B.

    1995-12-31

    Dish/Stirling solar electric systems are currently being tested for performance and longevity in order to bring them to the electric power generation market. Studies both in Germany and the United States indicate that a significant market exists for these systems if they perform in actual installations according to tested conditions, and if, when produced in large numbers their cost will drop to goals currently being projected. In the 1980`s, considerable experience was gained operating eight dish/Stirling systems of three different designs. One of these recorded the world`s record for converting solar energy into electricity of 29.4%. The approach to system performance prediction taken in this presentation results from lessons learned in testing these early systems, and those currently being tested. Recently the IEA through the SolarPACES working group, has embarked on a program to develop uniform guidelines for measuring and presenting performance data. These guidelines are to help potential buyers who want to evaluate a specific system relative to other dish/Stirling systems, or relative to other technologies such as photovoltaic, parabolic trough or central receiver systems. In this paper, a procedure is described that permits modeling of long-term energy production using only a few experimentally determined parameters. The benefit of using this technique is that relatively simple tests performed over a period of a few months can provide performance parameters that can be used in a computer model requiring only the input of insolation and ambient temperature data to determine long-term energy production information. A portion of this analytical procedure has been tested on the three 9-kW(e) systems in operation in Almeria, Spain. Further evaluation of these concepts is planned on a 7.5-kW(e) system currently undergoing testing at Cal Poly University in Pomona, California and later on the 25 kW(e) USJVP systems currently under development.

  16. Aggregated Modeling of Thermostatic Loads in Demand Response: A Systems and Control Perspective

    SciTech Connect (OSTI)

    Kalsi, Karanjit; Chassin, Forrest S.; Chassin, David P.

    2011-12-12

    Demand response is playing an increasingly important role in smart grid research and technologies being examined in recently undertaken demonstration projects. The behavior of load as it is affected by various load control strategies is important to understanding the degree to which different classes of end-use load can contribute to demand response programs at various times. This paper focuses on developing aggregated models for a homogeneous population of thermostatically controlled loads. The different types of loads considered in this paper include, but are not limited to, water heaters and HVAC units. The effects of demand response and user over-ride on the load population dynamics are investigated. The controllability of the developed lumped models is validated which forms the basis for designing different control strategies.

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

    SciTech Connect (OSTI)

    Bonnard, R.; McKone, T.E.

    2009-03-01

    The predictions of two source-to-dose models are systematically evaluated with observed data collected in a village polluted by a currently operating secondary lead smelter. Both models were built up from several sub-models linked together and run using Monte-Carlo simulation, to calculate the distribution children's blood lead levels attributable to the emissions from the facility. The first model system is composed of the CalTOX model linked to a recoded version of the IEUBK model. This system provides the distribution of the media-specific lead concentrations (air, soil, fruit, vegetables and blood) in the whole area investigated. The second model consists of a statistical model to estimate the lead deposition on the ground, a modified version of the model HHRAP and the same recoded version of the IEUBK model. This system provides an estimate of the concentration of exposure of specific individuals living in the study area. The predictions of the first model system were improved in terms of accuracy and precision by performing a sensitivity analysis and using field data to correct the default value provided for the leaf wet density. However, in this case study, the first model system tends to overestimate the exposure due to exposed vegetables. The second model was tested for nine children with contrasting exposure conditions. It managed to capture the blood levels for eight of them. In the last case, the exposure of the child by pathways not considered in the model may explain the failure of the model. The interest of this integrated model is to provide outputs with lower variance than the first model system, but at the moment further tests are necessary to conclude about its accuracy.

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

    SciTech Connect (OSTI)

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

    1980-05-01

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

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

    SciTech Connect (OSTI)

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

    2015-06-30

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

  20. Development and Validation of Aggregated Models for Thermostatic Controlled Loads with Demand Response

    SciTech Connect (OSTI)

    Kalsi, Karanjit; Elizondo, Marcelo A.; Fuller, Jason C.; Lu, Shuai; Chassin, David P.

    2012-01-04

    Demand response is playing an increasingly important role in smart grid research and technologies being examined in recently undertaken demonstration projects. The behavior of load as it is affected by various load control strategies is important to understanding the degree to which different classes of end-use load can contribute to demand response programs at various times. This paper focuses on developing aggregated control models for a population of thermostatically controlled loads. The effects of demand response on the load population dynamics are investigated.

  1. Modeling CANDU-6 liquid zone controllers for effects of thorium-based fuels

    SciTech Connect (OSTI)

    St-Aubin, E.; Marleau, G.

    2012-07-01

    We use the DRAGON code to model the CANDU-6 liquid zone controllers and evaluate the effects of thorium-based fuels on their incremental cross sections and reactivity worth. We optimize both the numerical quadrature and spatial discretization for 2D cell models in order to provide accurate fuel properties for 3D liquid zone controller supercell models. We propose a low computer cost parameterized pseudo-exact 3D cluster geometries modeling approach that avoids tracking issues on small external surfaces. This methodology provides consistent incremental cross sections and reactivity worths when the thickness of the buffer region is reduced. When compared with an approximate annular geometry representation of the fuel and coolant region, we observe that the cluster description of fuel bundles in the supercell models does not increase considerably the precision of the results while increasing substantially the CPU time. In addition, this comparison shows that it is imperative to finely describe the liquid zone controller geometry since it has a strong impact of the incremental cross sections. This paper also shows that liquid zone controller reactivity worth is greatly decreased in presence of thorium-based fuels compared to the reference natural uranium fuel, since the fission and the fast to thermal scattering incremental cross sections are higher for the new fuels. (authors)

  2. Aggregated Modeling and Control of Air Conditioning Loads for Demand Response

    SciTech Connect (OSTI)

    Zhang, Wei; Lian, Jianming; Chang, Chin-Yao; Kalsi, Karanjit

    2013-06-21

    Demand response is playing an increasingly important role in the efficient and reliable operation of the electric grid. Modeling the dynamic behavior of a large population of responsive loads is especially important to evaluate the effectiveness of various demand response strategies. In this paper, a highly-accurate aggregated model is developed for a population of air conditioning loads. The model effectively includes statistical information of the population, systematically deals with load heterogeneity, and accounts for second-order dynamics necessary to accurately capture the transient dynamics in the collective response. Based on the model, a novel aggregated control strategy is designed for the load population under realistic conditions. The proposed controller is fully responsive and achieves the control objective without sacrificing end-use performance. The proposed aggregated modeling and control strategies are validated through realistic simulations using GridLAB-D. Extensive simulation results indicate that the proposed approach can effectively manage a large number of air conditioning systems to provide various demand response services, such as frequency regulation and peak load reduction.

  3. Accuracy and Validation of Measured and Modeled Data for Distributed PV Interconnection and Control

    SciTech Connect (OSTI)

    Stewart, Emma; Kiliccote, Sila; Arnold, Daniel; von Meier, Alexandra; Arghandeh, R.

    2015-07-27

    The distribution grid is changing to become an active resource with complex modeling needs. The new active distribution grid will, within the next ten years, contain a complex mix of load, generation, storage and automated resources all operating with different objectives on different time scales from each other and requiring detailed analysis. Electrical analysis tools that are used to perform capacity and stability studies have been used for transmission system planning for many years. In these tools, the distribution grid was considered a load and its details and physical components were not modeled. The increase in measured data sources can be utilized for better modeling, but also control of distributed energy resources (DER). The utilization of these sources and advanced modeling tools will require data management, and knowledgeable users. Each of these measurement and modeling devices have accuracy constraints, which will ultimately define their future ability to be planned and controlled. This paper discusses the importance of measured data accuracy for inverter control, interconnection and planning tools and proposes ranges of control accuracy needed to satisfy all concerns based on the present grid infrastructure.

  4. Modeling of integrated environmental control systems for coal-fired power plants. Final report

    SciTech Connect (OSTI)

    Rubin, E.S.; Salmento, J.S.; Frey, H.C.; Abu-Baker, A.; Berkenpas, M.

    1991-05-01

    The Integrated Environmental Control Model (IECM) was designed to permit the systematic evaluation of environmental control options for pulverized coal-fired (PC) power plants. Of special interest was the ability to compare the performance and cost of advanced pollution control systems to ``conventional`` technologies for the control of particulate, SO{sub 2} and NO{sub x}. Of importance also was the ability to consider pre-combustion, combustion and post-combustion control methods employed alone or in combination to meet tough air pollution emission standards. Finally, the ability to conduct probabilistic analyses is a unique capability of the IECM. Key results are characterized as distribution functions rather than as single deterministic values. (VC)

  5. Modeling of integrated environmental control systems for coal-fired power plants

    SciTech Connect (OSTI)

    Rubin, E.S.; Salmento, J.S.; Frey, H.C.; Abu-Baker, A.; Berkenpas, M.

    1991-05-01

    The Integrated Environmental Control Model (IECM) was designed to permit the systematic evaluation of environmental control options for pulverized coal-fired (PC) power plants. Of special interest was the ability to compare the performance and cost of advanced pollution control systems to conventional'' technologies for the control of particulate, SO{sub 2} and NO{sub x}. Of importance also was the ability to consider pre-combustion, combustion and post-combustion control methods employed alone or in combination to meet tough air pollution emission standards. Finally, the ability to conduct probabilistic analyses is a unique capability of the IECM. Key results are characterized as distribution functions rather than as single deterministic values. (VC)

  6. Prediction of Thermal Conductivity for Irradiated SiC/SiC Composites by Informing Continuum Models with Molecular Dynamics Data

    SciTech Connect (OSTI)

    Nguyen, Ba Nghiep; Gao, Fei; Henager, Charles H.; Kurtz, Richard J.

    2014-05-01

    This article proposes a new method to estimate the thermal conductivity of SiC/SiC composites subjected to neutron irradiation. The modeling method bridges different scales from the atomic scale to the scale of a 2D SiC/SiC composite. First, it studies the irradiation-induced point defects in perfect crystalline SiC using molecular dynamics (MD) simulations to compute the defect thermal resistance as a function of vacancy concentration and irradiation dose. The concept of defect thermal resistance is explored explicitly in the MD data using vacancy concentrations and thermal conductivity decrements due to phonon scattering. Point defect-induced swelling for chemical vapor deposited (CVD) SiC as a function of irradiation dose is approximated by scaling the corresponding MD results for perfect crystal ?-SiC to experimental data for CVD-SiC at various temperatures. The computed thermal defect resistance, thermal conductivity as a function of grain size, and definition of defect thermal resistance are used to compute the thermal conductivities of CVD-SiC, isothermal chemical vapor infiltrated (ICVI) SiC and nearly-stoichiometric SiC fibers. The computed fiber and ICVI-SiC matrix thermal conductivities are then used as input for an Eshelby-Mori-Tanaka approach to compute the thermal conductivities of 2D SiC/SiC composites subjected to neutron irradiation within the same irradiation doses. Predicted thermal conductivities for an irradiated Tyranno-SA/ICVI-SiC composite are found to be comparable to available experimental data for a similar composite ICVI-processed with these fibers.

  7. Modeling of integrated environmental control systems for coal-fired power plants

    SciTech Connect (OSTI)

    Rubin, E.S.

    1988-10-01

    This is the fourth quarterly report of DOE Contract No. DE-AC22-87PC79864, entitled Modeling of Integrated Environmental Control Systems for Coal-Fired Power Plants.'' This report summarizes accomplishments during the period July 1, 1988 to September 30, 1988. Our efforts during the last quarter focused primarily on the completion, testing and documentation of the NO{sub x}SO process model. The sections below present the details of these developments.

  8. Evaluating temperature and fuel stratification for heat-release rate control in a reactivity-controlled compression-ignition engine using optical diagnostics and chemical kinetics modeling

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

    Musculus, Mark P. B.; Kokjohn, Sage L.; Reitz, Rolf D.

    2015-04-23

    We investigated the combustion process in a dual-fuel, reactivity-controlled compression-ignition (RCCI) engine using a combination of optical diagnostics and chemical kinetics modeling to explain the role of equivalence ratio, temperature, and fuel reactivity stratification for heat-release rate control. An optically accessible engine is operated in the RCCI combustion mode using gasoline primary reference fuels (PRF). A well-mixed charge of iso-octane (PRF = 100) is created by injecting fuel into the engine cylinder during the intake stroke using a gasoline-type direct injector. Later in the cycle, n-heptane (PRF = 0) is delivered through a centrally mounted diesel-type common-rail injector. This injectionmore » strategy generates stratification in equivalence ratio, fuel blend, and temperature. The first part of this study uses a high-speed camera to image the injection events and record high-temperature combustion chemiluminescence. Moreover, the chemiluminescence imaging showed that, at the operating condition studied in the present work, mixtures in the squish region ignite first, and the reaction zone proceeds inward toward the center of the combustion chamber. The second part of this study investigates the charge preparation of the RCCI strategy using planar laser-induced fluorescence (PLIF) of a fuel tracer under non-reacting conditions to quantify fuel concentration distributions prior to ignition. The fuel-tracer PLIF data show that the combustion event proceeds down gradients in the n-heptane distribution. The third part of the study uses chemical kinetics modeling over a range of mixtures spanning the distributions observed from the fuel-tracer fluorescence imaging to isolate the roles of temperature, equivalence ratio, and PRF number stratification. The simulations predict that PRF number stratification is the dominant factor controlling the ignition location and growth rate of the reaction zone. Equivalence ratio has a smaller, but still

  9. Circuit model of the ITER-like antenna for JET and simulation of its control algorithms

    SciTech Connect (OSTI)

    Durodié, Frédéric Křivská, Alena; Helou, Walid; Collaboration: EUROfusion Consortium

    2015-12-10

    The ITER-like Antenna (ILA) for JET [1] is a 2 toroidal by 2 poloidal array of Resonant Double Loops (RDL) featuring in-vessel matching capacitors feeding RF current straps in conjugate-T manner, a low impedance quarter-wave impedance transformer, a service stub allowing hydraulic actuator and water cooling services to reach the aforementioned capacitors and a 2nd stage phase-shifter-stub matching circuit allowing to correct/choose the conjugate-T working impedance. Toroidally adjacent RDLs are fed from a 3dB hybrid splitter. It has been operated at 33, 42 and 47MHz on plasma (2008-2009) while it presently estimated frequency range is from 29 to 49MHz. At the time of the design (2001-2004) as well as the experiments the circuit models of the ILA were quite basic. The ILA front face and strap array Topica model was relatively crude and failed to correctly represent the poloidal central septum, Faraday Screen attachment as well as the segmented antenna central septum limiter. The ILA matching capacitors, T-junction, Vacuum Transmission Line (VTL) and Service Stubs were represented by lumped circuit elements and simple transmission line models. The assessment of the ILA results carried out to decide on the repair of the ILA identified that achieving routine full array operation requires a better understanding of the RF circuit, a feedback control algorithm for the 2nd stage matching as well as tighter calibrations of RF measurements. The paper presents the progress in modelling of the ILA comprising a more detailed Topica model of the front face for various plasma Scrape Off Layer profiles, a comprehensive HFSS model of the matching capacitors including internal bellows and electrode cylinders, 3D-EM models of the VTL including vacuum ceramic window, Service stub, a transmission line model of the 2nd stage matching circuit and main transmission lines including the 3dB hybrid splitters. A time evolving simulation using the improved circuit model allowed to design and

  10. Control method and system for hydraulic machines employing a dynamic joint motion model

    DOE Patents [OSTI]

    Danko, George

    2011-11-22

    A control method and system for controlling a hydraulically actuated mechanical arm to perform a task, the mechanical arm optionally being a hydraulically actuated excavator arm. The method can include determining a dynamic model of the motion of the hydraulic arm for each hydraulic arm link by relating the input signal vector for each respective link to the output signal vector for the same link. Also the method can include determining an error signal for each link as the weighted sum of the differences between a measured position and a reference position and between the time derivatives of the measured position and the time derivatives of the reference position for each respective link. The weights used in the determination of the error signal can be determined from the constant coefficients of the dynamic model. The error signal can be applied in a closed negative feedback control loop to diminish or eliminate the error signal for each respective link.

  11. A synthetic ecology perspective: How well does behavior of model organisms in the laboratory predict microbial activities in natural habitats?

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

    Yu, Zheng; Krause, Sascha M. B.; Beck, David A. C.; Chistoserdova, Ludmila

    2016-06-15

    In this perspective article, we question how well model organisms, the ones that are easy to cultivate in the laboratory and that show robust growth and biomass accumulation, reflect the dynamics and interactions of microbial communities observed in nature. Today's -omics toolbox allows assessing the genomic potential of microbes in natural environments in a high-throughput fashion and at a strain-level resolution. However, understanding of the details of microbial activities and of the mechanistic bases of community function still requires experimental validation in simplified and fully controlled systems such as synthetic communities. We have studied methane utilization in Lake Washington sedimentmore » for a few decades and have identified a number of species genetically equipped for this activity. We have also identified cooccurring satellite species that appear to form functional communities together with the methanotrophs. Here, we compare experimental findings from manipulation of natural communities involved in metabolism of methane in this niche with findings from manipulation of synthetic communities assembled in the laboratory of species originating from the same study site, from very simple (two-species) to rather complex (50-species) synthetic communities. We observe some common trends in community dynamics between the two types of communities, toward representation of specific functional guilds. However, we also identify strong discrepancies between the dominant methane oxidizers in synthetic communities compared to natural communities, under similar incubation conditions. Furthermore, these findings highlight the challenges that exist in using the synthetic community approach to modeling dynamics and species interactions in natural communities.« less

  12. Validation of mathematical models for the prediction of organs-at-risk dosimetric metrics in high-dose-rate gynecologic interstitial brachytherapy

    SciTech Connect (OSTI)

    Damato, Antonio L.; Viswanathan, Akila N.; Cormack, Robert A.

    2013-10-15

    Purpose: Given the complicated nature of an interstitial gynecologic brachytherapy treatment plan, the use of a quantitative tool to evaluate the quality of the achieved metrics compared to clinical practice would be advantageous. For this purpose, predictive mathematical models to predict the D{sub 2cc} of rectum and bladder in interstitial gynecologic brachytherapy are discussed and validated.Methods: Previous plans were used to establish the relationship between D2cc and the overlapping volume of the organ at risk with the targeted area (C0) or a 1-cm expansion of the target area (C1). Three mathematical models were evaluated: D{sub 2cc}=α*C{sub 1}+β (LIN); D{sub 2cc}=α– exp(–β*C{sub 0}) (EXP); and a mixed approach (MIX), where both C{sub 0} and C{sub 1} were inputs of the model. The parameters of the models were optimized on a training set of patient data, and the predictive error of each model (predicted D{sub 2cc}− real D{sub 2cc}) was calculated on a validation set of patient data. The data of 20 patients were used to perform a K-fold cross validation analysis, with K = 2, 4, 6, 8, 10, and 20.Results: MIX was associated with the smallest mean prediction error <6.4% for an 18-patient training set; LIN had an error <8.5%; EXP had an error <8.3%. Best case scenario analysis shows that an error ≤5% can be achieved for a ten-patient training set with MIX, an error ≤7.4% for LIN, and an error ≤6.9% for EXP. The error decreases with the increase in training set size, with the most marked decrease observed for MIX.Conclusions: The MIX model can predict the D{sub 2cc} of the organs at risk with an error lower than 5% with a training set of ten patients or greater. The model can be used in the development of quality assurance tools to identify treatment plans with suboptimal sparing of the organs at risk. It can also be used to improve preplanning and in the development of real-time intraoperative planning tools.

  13. Automation, Control and Modeling of Compound Semiconductor Thin-Film Growth

    SciTech Connect (OSTI)

    Breiland, W.G.; Coltrin, M.E.; Drummond, T.J.; Horn, K.M.; Hou, H.Q.; Klem, J.F.; Tsao, J.Y.

    1999-02-01

    This report documents the results of a laboratory-directed research and development (LDRD) project on control and agile manufacturing in the critical metalorganic chemical vapor deposition (MOCVD) and molecular beam epitaxy (MBE) materials growth processes essential to high-speed microelectronics and optoelectronic components. This effort is founded on a modular and configurable process automation system that serves as a backbone allowing integration of process-specific models and sensors. We have developed and integrated MOCVD- and MBE-specific models in this system, and demonstrated the effectiveness of sensor-based feedback control in improving the accuracy and reproducibility of semiconductor heterostructures. In addition, within this framework we have constructed ''virtual reactor'' models for growth processes, with the goal of greatly shortening the epitaxial growth process development cycle.

  14. On-line Chemistry within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model

    SciTech Connect (OSTI)

    Grell, Georg; Fast, Jerome D.; Gustafson, William I.; Peckham, Steven E.; McKeen, Stuart A.; Salzmann, Marc; Freitas, Saulo

    2010-01-01

    This is a conference proceeding that is now being put together as a book. This is chapter 2 of the book: "INTEGRATED SYSTEMS OF MESO-METEOROLOGICAL AND CHEMICAL TRANSPORT MODELS" published by Springer. The chapter title is "On-line Chemistry within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model." The original conference was the COST-728/NetFAM workshop on Integrated systems of meso-meteorological and chemical transport models, Danish Meteorological Institute, Copenhagen, May 21-23, 2007.

  15. Modeling for control of rotating stall in high-speed multistage axial compressors

    SciTech Connect (OSTI)

    Feulner, M.R.; Hendricks, G.J.; Paduano, J.D.

    1996-01-01

    Using a two-dimensional compressible flow representation of axial compressor dynamics, a control-theoretic input-output model is derived, which is of general utility in rotating stall/surge active control studies. The derivation presented here begins with a review of the fluid dynamic model, which is a two-dimensional stage stacking technique that accounts for blade row pressure rise, loss, and deviation as well as blade row and interblade row compressible flow. This model is extended to include the effects of the upstream and downstream geometry and boundary conditions, and then manipulated into a transfer function form that dynamically relates actuator motion to sensor measurements. Key relationships in this input-output form are then approximated using rational polynomials. Further manipulation yields an approximate model in standard form for studying active control of rotating stall and surge. As an example of high current relevance, the transfer function from an array of jet actuators to an array of static pressure sensors is derived. Numerical examples are also presented, including a demonstration of the importance of proper choice of sensor and actuator locations, as well as a comparison between sensor types. Under a variety of conditions, it was found that sensor locations near the front of the compressor or in the downstream gap are consistently the best choices, based on a quadratic optimization criterion and a specific three-stage compressor model. The modeling and evaluation procedures presented here are a first step toward a rigorous approach to the design of active control systems for high-speed axial compressors.

  16. A neural network model for predicting the silicon content of the hot metal at No. 2 blast furnace of SSAB Luleaa

    SciTech Connect (OSTI)

    Zuo Guangqing; Ma Jitang; Bo, B.

    1996-12-31

    To predict the silicon content of hot metal at No. 2 blast furnace, SSAB, Luleaa Works, a three-layer Back-Propagation network model has been established. The network consists of twenty-eight inputs, six middle nodes and one output and uses a generalized delta rule for training. Different network structures and different training strategies have been tested. A well-functioning network with dynamic updating has been designed. The off-line test and the on-line application results showed that more than 80% of the predictions can match the actual silicon content in hot metal in a normal operation, if the allowable prediction error was set to {+-}0.05% Si, while the actual fluctuation of the silicon content was larger than {+-}0.10% Si.

  17. COLLABORATIVE RESEARCH: TOWARDS ADVANCED UNDERSTANDING AND PREDICTIVE CAPABILITY OF CLIMATE CHANGE IN THE ARCTIC USING A HIGH-RESOLUTION REGIONAL ARCTIC CLIMATE SYSTEM MODEL

    SciTech Connect (OSTI)

    Gutowski, William J.

    2013-02-07

    The motivation for this project was to advance the science of climate change and prediction in the Arctic region. Its primary goals were to (i) develop a state-of-the-art Regional Arctic Climate system Model (RACM) including high-resolution atmosphere, land, ocean, sea ice and land hydrology components and (ii) to perform extended numerical experiments using high performance computers to minimize uncertainties and fundamentally improve current predictions of climate change in the northern polar regions. These goals were realized first through evaluation studies of climate system components via one-way coupling experiments. Simulations were then used to examine the effects of advancements in climate component systems on their representation of main physics, time-mean fields and to understand variability signals at scales over many years. As such this research directly addressed some of the major science objectives of the BER Climate Change Research Division (CCRD) regarding the advancement of long-term climate prediction.

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

    SciTech Connect (OSTI)

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

    1985-08-01

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

  19. Application of the Software as a Service Model to the Control of Complex Building Systems

    SciTech Connect (OSTI)

    Stadler, Michael; Donadee, Jonathan; Marnay, Chris; Mendes, Goncalo; Appen, Jan von; Megel, Oliver; Bhattacharya, Prajesh; DeForest, Nicholas; Lai, Judy

    2011-03-17

    In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building. The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analysed.

  20. Application of the Software as a Service Model to the Control of Complex Building Systems

    SciTech Connect (OSTI)

    Stadler, Michael; Donadee, Jon; Marnay, Chris; Lai, Judy; Mendes, Goncalo; Appen, Jan von; Mégel, Oliver; Bhattacharya, Prajesh; DeForest, Nicholas; Lai, Judy

    2011-03-18

    In an effort to create broad access to its optimization software, Lawrence Berkeley National Laboratory (LBNL), in collaboration with the University of California at Davis (UC Davis) and OSISoft, has recently developed a Software as a Service (SaaS) Model for reducing energy costs, cutting peak power demand, and reducing carbon emissions for multipurpose buildings. UC Davis currently collects and stores energy usage data from buildings on its campus. Researchers at LBNL sought to demonstrate that a SaaS application architecture could be built on top of this data system to optimize the scheduling of electricity and heat delivery in the building. The SaaS interface, known as WebOpt, consists of two major parts: a) the investment& planning and b) the operations module, which builds on the investment& planning module. The operational scheduling and load shifting optimization models within the operations module use data from load prediction and electrical grid emissions models to create an optimal operating schedule for the next week, reducing peak electricity consumption while maintaining quality of energy services. LBNL's application also provides facility managers with suggested energy infrastructure investments for achieving their energy cost and emission goals based on historical data collected with OSISoft's system. This paper describes these models as well as the SaaS architecture employed by LBNL researchers to provide asset scheduling services to UC Davis. The peak demand, emissions, and cost implications of the asset operation schedule and investments suggested by this optimization model are analyzed.

  1. Modeling Local Control After Hypofractionated Stereotactic Body Radiation Therapy for Stage I Non-Small Cell Lung Cancer: A Report From the Elekta Collaborative Lung Research Group

    SciTech Connect (OSTI)

    Ohri, Nitin; Werner-Wasik, Maria; Grills, Inga S.; Belderbos, Jose; Hope, Andrew; Yan Di; Kestin, Larry L.; Guckenberger, Matthias; Sonke, Jan-Jakob; Bissonnette, Jean-Pierre; Xiao, Ying

    2012-11-01

    Purpose: Hypofractionated stereotactic body radiation therapy (SBRT) has emerged as an effective treatment option for early-stage non-small cell lung cancer (NSCLC). Using data collected by the Elekta Lung Research Group, we generated a tumor control probability (TCP) model that predicts 2-year local control after SBRT as a function of biologically effective dose (BED) and tumor size. Methods and Materials: We formulated our TCP model as follows: TCP = e{sup [BED10-c Asterisk-Operator L-TCD50]/k} Division-Sign (1 + e{sup [BED10-c Asterisk-Operator L-TCD50]/k}), where BED10 is the biologically effective SBRT dose, c is a constant, L is the maximal tumor diameter, and TCD50 and k are parameters that define the shape of the TCP curve. Least-squares optimization with a bootstrap resampling approach was used to identify the values of c, TCD50, and k that provided the best fit with observed actuarial 2-year local control rates. Results: Data from 504 NSCLC tumors treated with a variety of SBRT schedules were available. The mean follow-up time was 18.4 months, and 26 local recurrences were observed. The optimal values for c, TCD50, and k were 10 Gy/cm, 0 Gy, and 31 Gy, respectively. Thus, size-adjusted BED (sBED) may be defined as BED minus 10 times the tumor diameter (in centimeters). Our TCP model indicates that sBED values of 44 Gy, 69 Gy, and 93 Gy provide 80%, 90%, and 95% chances of tumor control at 2 years, respectively. When patients were grouped by sBED, the model accurately characterized the relationship between sBED and actuarial 2-year local control (r=0.847, P=.008). Conclusion: We have developed a TCP model that predicts 2-year local control rate after hypofractionated SBRT for early-stage NSCLC as a function of biologically effective dose and tumor diameter. Further testing of this model with additional datasets is warranted.

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

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

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

    2015-01-16

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

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

    SciTech Connect (OSTI)

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

    2015-01-16

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

  4. Redox control of electric melters with complex feed compositions. Part I: analytical methods and models

    SciTech Connect (OSTI)

    Bickford, D F; Diemer, Jr, R B

    1985-01-01

    The redox state of glass from electric melters with complex feed compositions is determined by balance between gases above the melt, and transition metals and organic compounds in the feed. Part I discusses experimental and computational methods of relating flowrates and other melter operating conditions to the redox state of glass, and composition of the melter offgas. Computerized thermodynamic computational methods are useful in predicting the sequence and products of redox reactions and in assessing individual process variations. Melter redox state can be predicted by combining monitoring of melter operating conditions, redox measurement of fused melter feed samples, and periodic redox measurement of product. Mossbauer spectroscopy, and other methods which measure Fe(II)/Fe(III) in glass, can be used to measure melter redox state. Part II develops preliminary operating limits for the vitrification of High-Level Radioactive Waste. Limits on reducing potential to preclude the accumulation of combustible gases, accumulation of sulfides and selenides, and degradation of melter components are the most critical. Problems associated with excessively oxidizing conditions, such as glass foaming and potential ruthenium volatility, are controlled when sufficient formic acid is added to adjust melter feed rheology.

  5. A simple Analytical Model to Study and Control Azimuthal Instabilities in

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

    Annular Combustion Chambers | Argonne Leadership Computing Facility A simple Analytical Model to Study and Control Azimuthal Instabilities in Annular Combustion Chambers Authors: Parmentier, J-F., Salas, P., Wolf, P., Staffelbach, G., Nicoud, F., Poinsot, T. This study describes a simple analytical method to compute the azimuthal modes appearing in annular combustion chambers and help analyzing experimental, acoustic and large eddy simulation (LES) data obtained in these combustion chambers.

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

    SciTech Connect (OSTI)

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

    2014-06-15

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

  7. Macromodel for assessing residential concentrations of combustion-generated pollutants: Model development and preliminary predictions for CO, NO/sub 2/, and respirable suspended particles

    SciTech Connect (OSTI)

    Traynor, G.W.; Aceti, J.C.; Apte, M.G.; Smith, B.V.; Green, L.L.; Smith-Reiser, A.; Novak, K.M.; Moses, D.O.

    1989-01-01

    A simulation model (also called a ''macromodel'') has been developed to predict residential air pollutant concentration distributions for specified populations. The model inputs include the market penetration of pollution sources, pollution source characteristics (e.g., emission rates, source usage rates), building characteristics (e.g., house volume, air exchange rates), and meteorological parameters (e.g., outside temperature). Four geographically distinct regions of the US have been modeled using Monte Carlo and deterministic simulation techniques. Single-source simulations were also conducted. The highest predicted CO and NO/sub 2/ residential concentrations were associated with the winter-time use of unvented gas and kerosene space heaters. The highest predicted respirable suspended particulate concentrations were associated with indoor cigarette smoking and the winter-time use of non-airtight wood stoves, radiant kerosene heaters, convective unvented gas space heaters, and oil forced-air furnaces. Future field studies in this area should (1) fill information gaps identified in this report, and (2) collect information on the macromodel input parameters to properly interpret the results. It is almost more important to measure the parameters that affect indoor concentration than it is to measure the concentrations themselves.

  8. Controlling

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

    Controlling chaos in low- and high-dimensional systems with periodic parametric perturbations K. A. Mirus and J. C. Sprott Department of Physics, University of Wisconsin, Madison, Wisconsin 53706 ͑Received 29 June 1998͒ The effect of applying a periodic perturbation to an accessible parameter of various chaotic systems is examined. Numerical results indicate that perturbation frequencies near the natural frequencies of the unstable periodic orbits of the chaotic systems can result in limit

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

    SciTech Connect (OSTI)

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

    2013-01-01

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

  10. Prediction and analysis of infra and low-frequency noise of upwind horizontal axis wind turbine using statistical wind speed model

    SciTech Connect (OSTI)

    Lee, Gwang-Se; Cheong, Cheolung

    2014-12-15

    Despite increasing concern about low-frequency noise of modern large horizontal-axis wind turbines (HAWTs), few studies have focused on its origin or its prediction methods. In this paper, infra- and low-frequency (the ILF) wind turbine noise are closely examined and an efficient method is developed for its prediction. Although most previous studies have assumed that the ILF noise consists primarily of blade passing frequency (BPF) noise components, these tonal noise components are seldom identified in the measured noise spectrum, except for the case of downwind wind turbines. In reality, since modern HAWTs are very large, during rotation, a single blade of the turbine experiences inflow with variation in wind speed in time as well as in space, breaking periodic perturbations of the BPF. Consequently, this transforms acoustic contributions at the BPF harmonics into broadband noise components. In this study, the ILF noise of wind turbines is predicted by combining Lowson’s acoustic analogy with the stochastic wind model, which is employed to reproduce realistic wind speed conditions. In order to predict the effects of these wind conditions on pressure variation on the blade surface, unsteadiness in the incident wind speed is incorporated into the XFOIL code by varying incident flow velocities on each blade section, which depend on the azimuthal locations of the rotating blade. The calculated surface pressure distribution is subsequently used to predict acoustic pressure at an observing location by using Lowson’s analogy. These predictions are compared with measured data, which ensures that the present method can reproduce the broadband characteristics of the measured low-frequency noise spectrum. Further investigations are carried out to characterize the IFL noise in terms of pressure loading on blade surface, narrow-band noise spectrum and noise maps around the turbine.

  11. Modeling, system identification, and control for slosh-free motion of an open container of liquid

    SciTech Connect (OSTI)

    Feddema, J.; Baty, R.; Dykhuizen, R.; Dohrmann, C.; Parker, G.; Robinett, R.; Romero, V.; Schmitt, D.

    1996-04-01

    This report discusses work performed under a Cooperative Research And Development Agreement (CRADA) with Corning, Inc., to analyze and test various techniques for controlling the motion of a high speed robotic arm carrying an open container of viscous liquid, in this case, molten glass. A computer model was generated to estimate the modes of oscillation of the liquid based on the shape of the container and the viscosity of the liquid. This fluid model was experimentally verified and tuned based on experimental data from a capacitive sensor on the side of the container. A model of the robot dynamics was also developed and verified through experimental tests on a Fanuc S-800 robot arm. These two models were used to estimate the overall modes of oscillation of an open container of liquid being carried by a robot arm. Using the estimated modes, inverse dynamic control techniques were used to determine a motion profile which would eliminate waves on the liquid`s surface. Experimental tests showed that residual surface waves in an open container of water at the end of motion were reduced by over 95% and that in-motion surface waves were reduced by over 75%.

  12. Continuum Modeling and Control of Large Nonuniform Wireless Networks via Nonlinear Partial Differential Equations

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

    Zhang, Yang; Chong, Edwin K. P.; Hannig, Jan; Estep, Donald

    2013-01-01

    We inmore » troduce a continuum modeling method to approximate a class of large wireless networks by nonlinear partial differential equations (PDEs). This method is based on the convergence of a sequence of underlying Markov chains of the network indexed by N , the number of nodes in the network. As N goes to infinity, the sequence converges to a continuum limit, which is the solution of a certain nonlinear PDE. We first describe PDE models for networks with uniformly located nodes and then generalize to networks with nonuniformly located, and possibly mobile, nodes. Based on the PDE models, we develop a method to control the transmissions in nonuniform networks so that the continuum limit is invariant under perturbations in node locations. This enables the networks to maintain stable global characteristics in the presence of varying node locations.« less

  13. Analysis of axial-induction-based wind plant control using an engineering and a high-order wind plant model

    SciTech Connect (OSTI)

    Annoni, Jennifer; Gebraad, Pieter M. O.; Scholbrock, Andrew K.; Fleming, Paul A.; Wingerden, Jan-Willem van

    2015-08-14

    Wind turbines are typically operated to maximize their performance without considering the impact of wake effects on nearby turbines. Wind plant control concepts aim to increase overall wind plant performance by coordinating the operation of the turbines. This paper focuses on axial-induction-based wind plant control techniques, in which the generator torque or blade pitch degrees of freedom of the wind turbines are adjusted. The paper addresses discrepancies between a high-order wind plant model and an engineering wind plant model. Changes in the engineering model are proposed to better capture the effects of axial-induction-based control shown in the high-order model.

  14. Predictive Geosciences

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

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

  15. Modeling Species Inhibition of NO oxidation in Urea-SCR Catalysts for Diesel Engine NOx Control

    SciTech Connect (OSTI)

    Devarakonda, Maruthi N.; Tonkyn, Russell G.; Tran, Diana N.; Lee, Jong H.; Herling, Darrell R.

    2010-09-15

    Urea-selective catalytic reduction (SCR) catalysts are regarded as the leading NOx aftertreatment technology to meet the 2010 NOx emission standards for on-highway vehicles running on heavy-duty diesel engines. However, issues such as low NOx conversion at low temperature conditions still exist due to various factors, including incomplete urea thermolysis, inhibition of SCR reactions by hydrocarbons and H2O. We have observed a noticeable reduction in the standard SCR reaction efficiency at low temperature with increasing water content. We observed a similar effect when hydrocarbons are present in the stream. This effect is absent under fast SCR conditions where NO ~ NO2 in the feed gas. As a first step in understanding the effects of such inhibition on SCR reaction steps, kinetic models that predict the inhibition behavior of H2O and hydrocarbons on NO oxidation are presented in the paper. A one-dimensional SCR model was developed based on conservation of species equations and was coded as a C-language S-function and implemented in Matlab/Simulink environment. NO oxidation and NO2 dissociation kinetics were defined as a function of the respective adsorbate’s storage in the SCR catalyst. The corresponding kinetic models were then validated on temperature ramp tests that showed good match with the test data.

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

    SciTech Connect (OSTI)

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

    1998-03-01

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

  17. Development of Chemical Model to Predict the Interactions between Supercritical CO2and Fluid, and Rocks in EGS Reservoirs

    Broader source: Energy.gov [DOE]

    This project will develop a chemical model, based on existing models and databases, that is capable of simulating chemical reactions between supercritical (SC) CO2 and Enhanced Geothermal System (EGS) reservoir rocks of various compositions in aqueous, non-aqueous and 2-phase environments.

  18. A Mathematical Tumor Model with Immune Resistance and Drug Therapy: An Optimal Control Approach

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

    De Pillis, L. G.; Radunskaya, A.

    2001-01-01

    We present a competition model of cancer tumor growth that includes both the immune system response and drug therapy. This is a four-population model that includes tumor cells, host cells, immune cells, and drug interaction. We analyze the stability of the drug-free equilibria with respect to the immune response in order to look for target basins of attraction. One of our goals was to simulate qualitatively the asynchronous tumor-drug interaction known as “Jeffs phenomenon.” The model we develop is successful in generating this asynchronous response behavior. Our other goal was to identify treatment protocols that could improve standard pulsed chemotherapymore » regimens. Using optimal control theory with constraints and numerical simulations, we obtain new therapy protocols that we then compare with traditional pulsed periodic treatment. The optimal control generated therapies produce larger oscillations in the tumor population over time. However, by the end of the treatment period, total tumor size is smaller than that achieved through traditional pulsed therapy, and the normal cell population suffers nearly no oscillations.« less

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

    SciTech Connect (OSTI)

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

    2014-06-15

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

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

    SciTech Connect (OSTI)

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

    1994-06-01

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

  1. Nuclear matrix elements for 0??{sup ?}?{sup ?} decays: Comparative analysis of the QRPA, shell model and IBM predictions

    SciTech Connect (OSTI)

    Civitarese, Osvaldo; Suhonen, Jouni

    2013-12-30

    In this work we report on general properties of the nuclear matrix elements involved in the neutrinoless double ?{sup ?} decays (0??{sup ?}?{sup ?} decays) of several nuclei. A summary of the values of the NMEs calculated along the years by the Jyvskyl-La Plata collaboration is presented. These NMEs, calculated in the framework of the quasiparticle random phase approximation (QRPA), are compared with those of the other available calculations, like the Shell Model (ISM) and the interacting boson model (IBA-2)

  2. Predictive Technology Development and Crash Energy Management...

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

    Predictive Technology Development and Crash Energy Management Predictive Technology ... Merit Review 2015: Validation of Material Models for Crash Simulation of Automotive Carbon ...

  3. Models of human operators: Their need and usefulness for improvement of advanced control systems and control rooms

    SciTech Connect (OSTI)

    Knee, H.E.; Schryver, J.C.

    1991-01-01

    Models of human behavior and cognition (HB C) are necessary for understanding the total response of complex systems. Many such model have come available over the past thirty years for various applications. Many potential model users remain skeptical about their practically, acceptability, and usefulness. Such hesitancy stems in part from disbelief in the ability to model complex cognitive processes, and a belief that relevant human behavior can be adequately accounted for through the use of common-sense heuristics. This paper will highlight several models of HB C and identify existing and potential applications in attempt to dispel such notions. 26 refs.

  4. In-situ model analysis of STARS missile flight data and comparison to per-flight predictions from test-reconciled models

    SciTech Connect (OSTI)

    James, G.H.; Carne, T.G.; Marek, E.L.

    1994-08-01

    The Natural Excitation Technique (NExT) was used to analyze STARS launch data during first and second stage flight using telemetered acceleration data. A continuous track of modal frequencies and modal damping was acquired for the first and second elastic modes of the system during first stage flight and for the first mode during second stage flight. Generally, the first mode was predicted to be lower than seen in actual flight. The second mode predictions were very close to those seen in flight. Damping values were found to be within the range estimated by ground testing or slightly less. The results from this modal analysis of launch data allowed a final quantification of the inherent bias errors which resulted from the STARS ground-based modal tests as well as pointing out structures which were in need of further test/analysis correlation.

  5. Modeling, Simulation Design and Control of Hybrid-Electric Vehicle Drives

    SciTech Connect (OSTI)

    Giorgio Rizzoni

    2005-09-30

    Ohio State University (OSU) is uniquely poised to establish such a center, with interdisciplinary emphasis on modeling, simulation, design and control of hybrid-electric drives for a number of reasons, some of which are: (1) The OSU Center for Automotive Research (CAR) already provides an infrastructure for interdisciplinary automotive research and graduate education; the facilities available at OSU-CAR in the area of vehicle and powertrain research are among the best in the country. CAR facilities include 31,000 sq. feet of space, multiple chassis and engine dynamometers, an anechoic chamber, and a high bay area. (2) OSU has in excess of 10 graduate level courses related to automotive systems. A graduate level sequence has already been initiated with GM. In addition, an Automotive Systems Engineering (ASE) program cosponsored by the mechanical and electrical engineering programs, had been formulated earlier at OSU, independent of the GATE program proposal. The main objective of the ASE is to provide multidisciplinary graduate education and training in the field of automotive systems to Masters level students. This graduate program can be easily adapted to fulfill the spirit of the GATE Center of Excellence. (3) A program in Mechatronic Systems Engineering has been in place at OSU since 1994; this program has a strong emphasis on automotive system integration issues, and has emphasized hybrid-electric vehicles as one of its application areas. (4) OSU researchers affiliated with CAR have been directly involved in the development and study of: HEV modeling and simulation; electric drives; transmission design and control; combustion engines; and energy storage systems. These activities have been conducted in collaboration with government and automotive industry sponsors; further, the same researchers have been actively involved in continuing education programs in these areas with the automotive industry. The proposed effort will include: (1) The development of a

  6. Predicting long-term carbon sequestration in response to CO2 enrichment: How and why do current ecosystem models differ?

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

    Walker, Anthony P.; Zaehle, Sönke; Medlyn, Belinda E.; De Kauwe, Martin G.; Asao, Shinichi; Hickler, Thomas; Parton, William; Ricciuto, Daniel M.; Wang, Ying -Ping; Wårlind, David; et al

    2015-04-27

    Large uncertainty exists in model projections of the land carbon (C) sink response to increasing atmospheric CO2. Free-Air CO2 Enrichment (FACE) experiments lasting a decade or more have investigated ecosystem responses to a step change in atmospheric CO2 concentration. To interpret FACE results in the context of gradual increases in atmospheric CO2 over decades to centuries, we used a suite of seven models to simulate the Duke and Oak Ridge FACE experiments extended for 300 years of CO2 enrichment. We also determine key modeling assumptions that drive divergent projections of terrestrial C uptake and evaluate whether these assumptions can bemore » constrained by experimental evidence. All models simulated increased terrestrial C pools resulting from CO2 enrichment, though there was substantial variability in quasi-equilibrium C sequestration and rates of change. In two of two models that assume that plant nitrogen (N) uptake is solely a function of soil N supply, the net primary production response to elevated CO2 became progressively N limited. In four of five models that assume that N uptake is a function of both soil N supply and plant N demand, elevated CO2 led to reduced ecosystem N losses and thus progressively relaxed nitrogen limitation. Many allocation assumptions resulted in increased wood allocation relative to leaves and roots which reduced the vegetation turnover rate and increased C sequestration. Additionally, self-thinning assumptions had a substantial impact on C sequestration in two models. As a result, accurate representation of N process dynamics (in particular N uptake), allocation, and forest self-thinning is key to minimizing uncertainty in projections of future C sequestration in response to elevated atmospheric CO2.« less

  7. Characteristic operator functions for quantum input-plant-output models and coherent control

    SciTech Connect (OSTI)

    Gough, John E.

    2015-01-15

    We introduce the characteristic operator as the generalization of the usual concept of a transfer function of linear input-plant-output systems to arbitrary quantum nonlinear Markovian input-output models. This is intended as a tool in the characterization of quantum feedback control systems that fits in with the general theory of networks. The definition exploits the linearity of noise differentials in both the plant Heisenberg equations of motion and the differential form of the input-output relations. Mathematically, the characteristic operator is a matrix of dimension equal to the number of outputs times the number of inputs (which must coincide), but with entries that are operators of the plant system. In this sense, the characteristic operator retains details of the effective plant dynamical structure and is an essentially quantum object. We illustrate the relevance to model reduction and simplification definition by showing that the convergence of the characteristic operator in adiabatic elimination limit models requires the same conditions and assumptions appearing in the work on limit quantum stochastic differential theorems of Bouten and Silberfarb [Commun. Math. Phys. 283, 491-505 (2008)]. This approach also shows in a natural way that the limit coefficients of the quantum stochastic differential equations in adiabatic elimination problems arise algebraically as Schur complements and amounts to a model reduction where the fast degrees of freedom are decoupled from the slow ones and eliminated.

  8. Normalized Elution Time Prediction Utility

    Energy Science and Technology Software Center (OSTI)

    2011-02-17

    This program is used to compute the predicted normalized elution time (NET) for a list of peptide sequences. It includes the Kangas/Petritis neural network trained model, the Krokhin hydrophobicity model, and the Mant hydrophobicity model. In addition, it can compute the predicted strong cation exchange (SCX) fraction (on a 0 to 1 scale) in which a given peptide will appear.

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

    SciTech Connect (OSTI)

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

    2015-09-01

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

  10. The potential use of Chernobyl fallout data to test and evaluate the predictions of environmental radiological assessment models

    SciTech Connect (OSTI)

    Richmond, C.R.; Hoffman, F.O.; Blaylock, B.G.; Eckerman, K.F.; Lesslie, P.A.; Miller, C.W.; Ng, Y.C.; Till, J.E.

    1988-06-01

    The objectives of the Model Validation Committee were to collaborate with US and foreign scientists to collect, manage, and evaluate data for identifying critical research issues and data needs to support an integrated assessment of the Chernobyl nuclear accident; test environmental transport, human dosimetric, and health effects models against measured data to determine their efficacy in guiding decisions on protective actions and in estimating exposures to populations and individuals following a nuclear accident; and apply Chernobyl data to quantifications of key processes governing the environmental transport, fate and effects of radionuclides and other trace substances. 55 refs.

  11. SU-E-QI-13: Predictable Models for Radio-Sensitizing Agent Kinetics: Application to Stereotactic Synchrotron Radiation Therapy

    SciTech Connect (OSTI)

    Obeid, L; Schmitt, M; Esteve, F; Adam, J

    2014-06-15

    Purpose: Iodine-enhanced radiotherapy is an innovative treatment combining the selective accumulation of an iodinated contrast agent in brain tumors with irradiations using monochromatic medium energy x-rays. The radiation dose enhancement depends on the time course of iodine in the tumors. A prolonged CT scanning (∼30 min) is required to follow-up iodine kinetics for recruited patients. This protocol could lead to substantial radiation dose to the patient. A novel method is proposed to reduce the acquisition time. Methods: 12 patients received an intravenous bolus of iodinated contrast agent, followed by a steady-state infusion to ensure stable intra-tumoral amounts of iodine during the treatment. Absolute iodine concentrations (IC) were derived from 40 multi-slice dynamic conventional CT images of the brain. The impulse response function (IRF) to the bolus was estimated using the adiabatic approximation of the Johnson and Wilson's model. The arterial input function (AIF) of the steady-state infusion was fitted with several models: Gamma, Gamma with recirculation and hybrid. Estimated IC were calculated by convolving the IRF with the modeled AIF and were compared to the measured data. Results: The gamma variate function was not relevant to model the AIF due to high differences with the measured AIF. The hybrid and the gamma with recirculation models provided differences below 8% during the whole acquisition time. The absolute difference between the measured and the estimated IC was lower than 0.5 mg/ml, which corresponds to 5% of dose enhancement error. Conclusion: The proposed method allows a good estimation of the iodine time course with reduced scanning delays (3 instead of 30 min) and dose to the patient. The results suggest that the dose errors may stay within the radiotherapy standards.

  12. Magnetic BiMn-α phase synthesis prediction: First-principles calculation, thermodynamic modeling and nonequilibrium chemical partitioning

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

    Zhou, S. H.; Liu, C.; Yao, Y. X.; Du, Y.; Zhang, L. J.; Wang, C. -Z.; Ho, K. -M.; Kramer, M. J.

    2016-04-29

    BiMn-α is promising permanent magnet. Due to its peritectic formation feature, there is a synthetic challenge to produce single BiMn-α phase. The objective of this study is to assess driving force for crystalline phase pathways under far-from-equilibrium conditions. First-principles calculations with Hubbard U correction are performed to provide a robust description of the thermodynamic behavior. The energetics associated with various degrees of the chemical partitioning are quantified to predict temperature, magnetic field, and time dependence of the phase selection. By assessing the phase transformation under the influence of the chemical partitioning, temperatures, and cooling rate from our calculations, we suggestmore » that it is possible to synthesize the magnetic BiMn-α compound in a congruent manner by rapid solidification. The external magnetic field enhances the stability of the BiMn-α phase. In conclusion, the compositions of the initial compounds from these highly driven liquids can be far from equilibrium.« less

  13. Strategy and gaps for modeling, simulation, and control of hybrid systems

    SciTech Connect (OSTI)

    Rabiti, Cristian; Garcia, Humberto E.; Hovsapian, Rob; Kinoshita, Robert; Mesina, George L.; Bragg-Sitton, Shannon M.; Boardman, Richard D.

    2015-04-01

    The purpose of this report is to establish a strategy for modeling and simulation of candidate hybrid energy systems. Modeling and simulation is necessary to design, evaluate, and optimize the system technical and economic performance. Accordingly, this report first establishes the simulation requirements to analysis candidate hybrid systems. Simulation fidelity levels are established based on the temporal scale, real and synthetic data availability or needs, solution accuracy, and output parameters needed to evaluate case-specific figures of merit. Accordingly, the associated computational and co-simulation resources needed are established; including physical models when needed, code assembly and integrated solutions platforms, mathematical solvers, and data processing. This report first attempts to describe the figures of merit, systems requirements, and constraints that are necessary and sufficient to characterize the grid and hybrid systems behavior and market interactions. Loss of Load Probability (LOLP) and effective cost of Effective Cost of Energy (ECE), as opposed to the standard Levelized Cost of Electricty (LCOE), are introduced as technical and economical indices for integrated energy system evaluations. Financial assessment methods are subsequently introduced for evaluation of non-traditional, hybrid energy systems. Algorithms for coupled and iterative evaluation of the technical and economic performance are subsequently discussed. This report further defines modeling objectives, computational tools, solution approaches, and real-time data collection and processing (in some cases using real test units) that will be required to model, co-simulate, and optimize; (a) an energy system components (e.g., power generation unit, chemical process, electricity management unit), (b) system domains (e.g., thermal, electrical or chemical energy generation, conversion, and transport), and (c) systems control modules. Co-simulation of complex, tightly coupled

  14. Phase formation sequences in the silicon-phosphorous system : determined by in-situ synchrotron andj conventional x-ray diffraction measurements and predicted by a theoretical model.

    SciTech Connect (OSTI)

    Carlsson, J. R. A.; Clevenger, L.; Madsen, L. D.; Hultman, L.; Li, X.-H.; Jordan-Sweet, J.; Lavoie, C.; Roy, R. A.; Cabral, C., Jr.; Morales, G.; Ludwig, K. L.; Stephenson, G. B.; Hentzell, H. T. G.; Materials Science Division; Linkoeping Univ.; IBM T. J. Watson Research Center; Boston Univ.

    1997-01-01

    The phase formation sequences of Si-P alloy thin films with P concentrations between 20 and 44 at. % have been studied. The samples were annealed at progressively higher temperatures and the newly formed phases were identified both after each annealing step by ex-situ conventional X-ray diffraction (XRD) and continuously by in-situ synchrotron XRD. It was found that Si was the only phase to form in a sample with 20 at.% P since the evaporation of P at the crystallization temperature prevented phosphides from forming. For a sample with 30at.% P, the Si{sub 12}P{sub 5} phase formed prior to the SiP phase. For samples with 35 and 44at.%P, the formation of SiP preceded the formation of the Si{sub 12}P{sub 5} phase. The experimentally determined phase formation sequences were successfully predicted by a proposed model. According to the model, the first and second crystalline phases to form are those with the lowest and next-lowest crystallization temperatures of the competing compounds predicted by the Gibbs free-energy diagram.

  15. Chapter 6: Innovating Clean Energy Technologies in Advanced Manufacturing | Advanced Sensors, Controls, Platforms and Modeling for Manufacturing Technology Assessment

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

    Advanced Sensors, Controls, Platforms and Modeling for Manufacturing Chapter 6: Technology Assessments NOTE: This technology assessment is available as an appendix to the 2015 Quadrennial Technology Review (QTR). Advanced Sensors, Controls, Platforms and Modeling for Manufacturing is one of fourteen manufacturing-focused technology assessments prepared in support of Chapter 6: Innovating Clean Energy Technologies in Advanced Manufacturing. For context within the 2015 QTR, key connections between

  16. Controllable atomistic graphene oxide model and its application in hydrogen sulfide removal

    SciTech Connect (OSTI)

    Huang, Liangliang; Gubbins, Keith E., E-mail: keg@ncsu.edu [Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695 (United States); Seredych, Mykola; Bandosz, Teresa J. [Department of Chemistry, The City College of New York and the Graduate School of the City University of New York, New York 10031 (United States)] [Department of Chemistry, The City College of New York and the Graduate School of the City University of New York, New York 10031 (United States); Duin, Adri C. T. van [Department of Mechanical and Nuclear Engineering, Pennsylvania State University, University Park, Pennsylvania 16801 (United States)] [Department of Mechanical and Nuclear Engineering, Pennsylvania State University, University Park, Pennsylvania 16801 (United States); Lu, Xiaohua [State Key Laboratory of Materials-Oriented Chemical Engineering, Nanjing University of Technology, Nanjing 210009 (China)] [State Key Laboratory of Materials-Oriented Chemical Engineering, Nanjing University of Technology, Nanjing 210009 (China)

    2013-11-21

    The determination of an atomistic graphene oxide (GO) model has been challenging due to the structural dependence on different synthesis methods. In this work we combine temperature-programmed molecular dynamics simulation techniques and the ReaxFF reactive force field to generate realistic atomistic GO structures. By grafting a mixture of epoxy and hydroxyl groups to the basal graphene surface and fine-tuning their initial concentrations, we produce in a controllable manner the GO structures with different functional groups and defects. The models agree with structural experimental data and with other ab initio quantum calculations. Using the generated atomistic models, we perform reactive adsorption calculations for H{sub 2}S and H{sub 2}O/H{sub 2}S mixtures on GO materials and compare the results with experiment. We find that H{sub 2}S molecules dissociate on the carbonyl functional groups, and H{sub 2}O, CO{sub 2}, and CO molecules are released as reaction products from the GO surface. The calculation reveals that for the H{sub 2}O/H{sub 2}S mixtures, H{sub 2}O molecules are preferentially adsorbed to the carbonyl sites and block the potential active sites for H{sub 2}S decomposition. The calculation agrees well with the experiments. The methodology and the procedure applied in this work open a new door to the theoretical studies of GO and can be extended to the research on other amorphous materials.

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

    SciTech Connect (OSTI)

    Harrison, T.D.

    1981-04-01

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

  18. Controlling intake of uranium in the workplace: Applications of biokinetic modeling and occupational monitoring data

    SciTech Connect (OSTI)

    Leggett, Richard Wayne; Eckerman, Keith F; McGinn, Wilson; Meck, Dr. Robert A.

    2012-01-01

    This report provides methods for interpreting and applying occupational uranium monitoring data. The methods are based on current international radiation protection guidance, current information on the chemical toxicity of uranium, and best available biokinetic models for uranium. Emphasis is on air monitoring data and three types of bioassay data: the concentration of uranium in urine; the concentration of uranium in feces; and the externally measured content of uranium in the chest. Primary Reference guidance levels for prevention of chemical effects and limitation of radiation effects are selected based on a review of current scientific data and regulatory principles for setting standards. Generic investigation levels and immediate action levels are then defined in terms of these primary guidance levels. The generic investigation and immediate actions levels are stated in terms of radiation dose and concentration of uranium in the kidneys. These are not directly measurable quantities, but models can be used to relate the generic levels to the concentration of uranium in air, urine, or feces, or the total uranium activity in the chest. Default investigation and immediate action levels for uranium in air, urine, feces, and chest are recommended for situations in which there is little information on the form of uranium taken into the body. Methods are prescribed also for deriving case-specific investigation and immediate action levels for uranium in air, urine, feces, and chest when there is sufficient information on the form of uranium to narrow the range of predictions of accumulation of uranium in the main target organs for uranium: kidneys for chemical effects and lungs for radiological effects. In addition, methods for using the information herein for alternative guidance levels, different from the ones selected for this report, are described.

  19. Implementation of a TMP Advanced Quality Control System at a Newsprint Manufacturing Plant

    SciTech Connect (OSTI)

    Sebastien Kidd

    2006-02-14

    This project provided for the implementation of an advanced, model predictive multi-variant controller that works with the mill that has existing distributed control system. The method provides real time and online predictive models and modifies control actions to maximize quality and minimize energy costs. Using software sensors, the system can predict difficult-to-measure quality and process variables and make necessary process control decisions to accurately control pulp quality while minimizing electrical usage. This method of control has allowed Augusta Newsprint Company to optimize the operation of its Thermo Mechanical Pulp mill for lower energy consumption and lower pulp quality variance.

  20. Optimal control for competitive-cooperative systems: Modeling flexible coalitions in tomorrow`s competitive world

    SciTech Connect (OSTI)

    Lenhart, S. |; Protopopescu, V.

    1994-09-01

    The last years have witnessed a dramatic shift of the world`s military, political, and economic paradigm from a bi-polar competitive gridlock to a more fluid, multi-player environment. This change has necessarily been followed by a re-evaluation of the strategic thinking and by a reassessment of mutual positions, options, and decisions. The essential attributes of the new situation are modeled by a system of nonlinear evolution equations with competitive/cooperative interactions. The mathematical setting is quite general to accommodate models related to military confrontation, arms control, economic competition, political negotiations, etc. Irrespective of the specific details, all these situations share a common denominator, namely the presence of various players with different and often changing interests and goals. The interests, ranging from conflicting to consensual, are defined in a context of interactions between the players that vary from competitive to cooperative. Players with converging interests tend to build up cooperative coalitions while coalitions with diverging interests usually compete among themselves, but this is not an absolute requirement (namely, one may have groups with converging interests and competitive interactions, and vice-versa). Appurtenance to a coalition may change in time according to the shift in one`s perceptions, interests, or obligations. During the time evolution, the players try to modify their strategies as to best achieve their respective goals. An objective functional quantifying the rate of success (payoff) vs. effort (cost) measures the degree of goal attainment for all players involved, thus selecting an optimal strategy based on optimal controls. While the technical details may vary from problem to problem, the general approach described here establishes a standard framework for a host of concrete situations that may arise from tomorrow`s {open_quotes}next competition{close_quotes}.

  1. Chemical structures of low-pressure premixed methylcyclohexane flames as benchmarks for the development of a predictive combustion chemistry model

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

    Skeen, Scott A.; Yang, Bin; Jasper, Ahren W.; Pitz, William J.; Hansen, Nils

    2011-11-14

    The chemical compositions of three low-pressure premixed flames of methylcyclohexane (MCH) are investigated with the emphasis on the chemistry of MCH decomposition and the formation of aromatic species, including benzene and toluene. The flames are stabilized on a flat-flame (McKenna type) burner at equivalence ratios of φ = 1.0, 1.75, and 1.9 and at low pressures between 15 Torr (= 20 mbar) and 30 Torr (= 40 mbar). The complex chemistry of MCH consumption is illustrated in the experimental identification of several C7H12, C7H10, C6H12, and C6H10 isomers sampled from the flames as a function of distance from the burner.more » Three initiation steps for MCH consumption are discussed: ring-opening to heptenes and methyl-hexenes (isomerization), methyl radical loss yielding the cyclohexyl radical (dissociation), and H abstraction from MCH. Mole fraction profiles as a function of distance from the burner for the C7 species supplemented by theoretical calculations are presented, indicating that flame structures resulting in steeper temperature gradients and/or greater peak temperatures can lead to a relative increase in MCH consumption through the dissociation and isomerization channels. Trends observed among the stable C6 species as well as 1,3-pentadiene and isoprene also support this conclusion. Relatively large amounts of toluene and benzene are observed in the experiments, illustrating the importance of sequential H-abstraction steps from MCH to toluene and from cyclohexyl to benzene. Furthermore, modeled results using the detailed chemical model of Pitz et al. (Proc. Combust. Inst.2007, 31, 267–275) are also provided to illustrate the use of these data as a benchmark for the improvement or future development of a MCH mechanism.« less

  2. Atomistic simulation of laser-pulse surface modification: Predictions of models with various length and time scales

    SciTech Connect (OSTI)

    Starikov, Sergey V. Pisarev, Vasily V.

    2015-04-07

    In this work, the femtosecond laser pulse modification of surface is studied for aluminium (Al) and gold (Au) by use of two-temperature atomistic simulation. The results are obtained for various atomistic models with different scales: from pseudo-one-dimensional to full-scale three-dimensional simulation. The surface modification after laser irradiation can be caused by ablation and melting. For low energy laser pulses, the nanoscale ripples may be induced on a surface by melting without laser ablation. In this case, nanoscale changes of the surface are due to a splash of molten metal under temperature gradient. Laser ablation occurs at a higher pulse energy when a crater is formed on the surface. There are essential differences between Al ablation and Au ablation. In the first step of shock-wave induced ablation, swelling and void formation occur for both metals. However, the simulation of ablation in gold shows an additional athermal type of ablation that is associated with electron pressure relaxation. This type of ablation takes place at the surface layer, at a depth of several nanometers, and does not induce swelling.

  3. Spectral softening in the X-RAY afterglow of GRB 130925A as predicted by the dust scattering model

    SciTech Connect (OSTI)

    Zhao, Yi-Nan; Shao, Lang, E-mail: lshao@hebtu.edu.cn [Department of Space Science and Astronomy, Hebei Normal University, Shijiazhuang 050024 (China)

    2014-07-01

    Gamma-ray bursts (GRBs) usually occur in a dense star-forming region with a massive circumburst medium. The small-angle scattering of intense prompt X-ray emission off the surrounding dust grains will have observable consequences and sometimes can dominate the X-ray afterglow. In most of the previous studies, only the Rayleigh-Gans (RG) approximation is employed for describing the scattering process, which works accurately for the typical size of grains (with radius of a ? 0.1 ?m) in the diffuse interstellar medium. When the size of the grains may significantly increase, as in a more dense region where GRBs would occur, the RG approximation may not be valid enough for modeling detailed observational data. In order to study the temporal and spectral properties of the scattered X-ray emission more accurately with potentially larger dust grains, we provide a practical approach using the series expansions of anomalous diffraction (AD) approximation based on the complicated Mie theory. We apply our calculations to understand the puzzling X-ray afterglow of recently observed GRB 130925A that showed a significant spectral softening. We find that the X-ray scattering scenarios with either AD or RG approximation adopted could well reproduce both the temporal and spectral profile simultaneously. Given the plateau present in the early X-ray light curve, a typical distribution of smaller grains as in the interstellar medium would be suggested for GRB 130925A.

  4. Development and Integration of Genome-Enabled Techniques to Track and Predict the Cycling of Carbon in Model Microbial Communities

    SciTech Connect (OSTI)

    Banfield, Jillian

    2014-11-26

    The primary objective of this project was to establish widely applicable, high-throughput omics methods for tracking carbon flow in microbial communities at a strain-resolved molecular level. We developed and applied these methods to study a well-established microbial community model system with a long history of omics innovation: chemoautotrophic biofilms grown in an acid mine drainage (AMD) environment. The methods are now being transitioned (in a new project) to study soil. Using metagenomics, stable-isotope proteomics, stable-isotope metabolomics, transcriptomics, and microscopy, we tracked carbon flow during initial biofilm growth involving CO2 fixation, through the maturing biofilm community consisting of multiple trophic levels, and during an anaerobic degradative phase after biofilms sink. This work included explicit consideration of the often overlooked roles of archaea and microbial eukaryotes (fungi) in carbon turnover. We also analyzed where the eosystem begins to fail in response to thermal perturbation, and how perturbation propagates through a carbon cycle. We investigated the form of strain variation in microbial communities, the importance of strain variants, and the rate and form of strain evolution. Overall, the project generated an array of new, integrated omics approaches and provided unprecedented insight into the functioning of a natural ecosystem. This project supported graduate training for five Ph.D. students and three post doctoral fellows and contributed directly to at least 26 publications (two in Science).

  5. Hydrodynamic Effects on Modeling and Control of a High Temperature Active Magnetic Bearing Pump with a Canned Rotor

    SciTech Connect (OSTI)

    Melin, Alexander M; Kisner, Roger A; Fugate, David L; Holcomb, David Eugene

    2015-01-01

    Embedding instrumentation and control Embedding instrumentation and control (I\\&C) at the component level in nuclear power plants can improve component performance, lifetime, and resilience by optimizing operation, reducing the constraints on physical design, and providing on-board prognostics and diagnostics. However, the extreme environments that many nuclear power plant components operate in makes embedding instrumentation and control at the component level difficult. Successfully utilizing embedded I\\&C requires developing a deep understanding of the system's dynamics and using that knowledge to overcome material and physical limitations imposed by the environment. In this paper, we will develop a coupled dynamic model of a high temperature (700 $^\\circ$C) canned rotor pump that incorporates rotordynamics, hydrodynamics, and active magnetic bearing dynamics. Then we will compare two control design methods, one that uses a simplified decoupled model of the system and another that utilizes the full coupled system model. It will be seen that utilizing all the available knowledge of the system dynamics in the controller design yield an order of magnitude improvement in the magnitude of the magnetic bearing response to disturbances at the same level of control effort, a large reduction in the settling time of the system, and a smoother control action.

  6. Ecological Impacts of the Cerro Grande Fire: Predicting Elk Movement and Distribution Patterns in Response to Vegetative Recovery through Simulation Modeling October 2005

    SciTech Connect (OSTI)

    S.P. Rupp

    2005-10-01

    SAVANNA included a land cover map, long-term weather data, soil maps, and a digital elevation model. Parameterization and calibration were conducted using field plots. Model predictions of herbaceous biomass production and weather were consistent with available data and spatial interpolations of snow were considered reasonable for this study. Dynamic outputs generated by SAVANNA were integrated with static variables, movement rules, and parameters developed for the individual-based model through the application of a habitat suitability index. Model validation indicated reasonable model fit when compared to an independent test set. The finished model was applied to 2 realistic management scenarios for the Jemez Mountains and management implications were discussed. Ongoing validation of the individual-based model presented in this dissertation provides an adaptive management tool that integrates interdisciplinary experience and scientific information, which allows users to make predictions about the impact of alternative management policies.

  7. Predicting Stimulation Response Relationships For Engineered...

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

    Predicting Stimulation Response Relationships For Engineered Geothermal Reservoirs Project objectives: Using existing LLNL computer programs, develop realistic models of EGS ...

  8. TH-E-BRF-03: A Multivariate Interaction Model for Assessment of Hippocampal Vascular Dose-Response and Early Prediction of Radiation-Induced Neurocognitive Dysfunction

    SciTech Connect (OSTI)

    Farjam, R; Pramanik, P; Srinivasan, A; Chapman, C; Tsien, C; Lawrence, T; Cao, Y

    2014-06-15

    Purpose: Vascular injury could be a cause of hippocampal dysfunction leading to late neurocognitive decline in patients receiving brain radiotherapy (RT). Hence, our aim was to develop a multivariate interaction model for characterization of hippocampal vascular dose-response and early prediction of radiation-induced late neurocognitive impairments. Methods: 27 patients (17 males and 10 females, age 31–80 years) were enrolled in an IRB-approved prospective longitudinal study. All patients were diagnosed with a low-grade glioma or benign tumor and treated by 3-D conformal or intensity-modulated RT with a median dose of 54 Gy (50.4–59.4 Gy in 1.8− Gy fractions). Six DCE-MRI scans were performed from pre-RT to 18 months post-RT. DCE data were fitted to the modified Toft model to obtain the transfer constant of gadolinium influx from the intravascular space into the extravascular extracellular space, Ktrans, and the fraction of blood plasma volume, Vp. The hippocampus vascular property alterations after starting RT were characterized by changes in the hippocampal mean values of, μh(Ktrans)τ and μh(Vp)τ. The dose-response, Δμh(Ktrans/Vp)pre->τ, was modeled using a multivariate linear regression considering integrations of doses with age, sex, hippocampal laterality and presence of tumor/edema near a hippocampus. Finally, the early vascular dose-response in hippocampus was correlated with neurocognitive decline 6 and 18 months post-RT. Results: The μh(Ktrans) increased significantly from pre-RT to 1 month post-RT (p<0.0004). The multivariate model showed that the dose effect on Δμh(Ktrans)pre->1M post-RT was interacted with sex (p<0.0007) and age (p<0.00004), with the dose-response more pronounced in older females. Also, the vascular dose-response in the left hippocampus of females was significantly correlated with memory function decline at 6 (r = − 0.95, p<0.0006) and 18 (r = −0.88, p<0.02) months post-RT. Conclusion: The hippocampal vascular

  9. Risk and Vulnerability Assessment Using Cybernomic Computational Models: Tailored for Industrial Control Systems

    SciTech Connect (OSTI)

    Abercrombie, Robert K; Sheldon, Federick T.; Schlicher, Bob G

    2015-01-01

    There are many influencing economic factors to weigh from the defender-practitioner stakeholder point-of-view that involve cost combined with development/deployment models. Some examples include the cost of countermeasures themselves, the cost of training and the cost of maintenance. Meanwhile, we must better anticipate the total cost from a compromise. The return on investment in countermeasures is essentially impact costs (i.e., the costs from violating availability, integrity and confidentiality / privacy requirements). The natural question arises about choosing the main risks that must be mitigated/controlled and monitored in deciding where to focus security investments. To answer this question, we have investigated the cost/benefits to the attacker/defender to better estimate risk exposure. In doing so, it s important to develop a sound basis for estimating the factors that derive risk exposure, such as likelihood that a threat will emerge and whether it will be thwarted. This impact assessment framework can provide key information for ranking cybersecurity threats and managing risk.

  10. Predictive Technology Development and Crash Energy Management

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

    ... projects titled: * Multiscale Modeling for Crash Prediction of Composite Structures * Modeling of The Manufacturing Process Induced Effects on Matrix Properties of Textile ...

  11. Absorption of ethanol, acetone, benzene and 1,2-dichloroethane through human skin in vitro: a test of diffusion model predictions

    SciTech Connect (OSTI)

    Gajjar, Rachna M.; Kasting, Gerald B.

    2014-11-15

    The overall goal of this research was to further develop and improve an existing skin diffusion model by experimentally confirming the predicted absorption rates of topically-applied volatile organic compounds (VOCs) based on their physicochemical properties, the skin surface temperature, and the wind velocity. In vitro human skin permeation of two hydrophilic solvents (acetone and ethanol) and two lipophilic solvents (benzene and 1,2-dichloroethane) was studied in Franz cells placed in a fume hood. Four doses of each {sup 14}C-radiolabed compound were tested — 5, 10, 20, and 40 μL cm{sup −2}, corresponding to specific doses ranging in mass from 5.0 to 63 mg cm{sup −2}. The maximum percentage of radiolabel absorbed into the receptor solutions for all test conditions was 0.3%. Although the absolute absorption of each solvent increased with dose, percentage absorption decreased. This decrease was consistent with the concept of a stratum corneum deposition region, which traps small amounts of solvent in the upper skin layers, decreasing the evaporation rate. The diffusion model satisfactorily described the cumulative absorption of ethanol; however, values for the other VOCs were underpredicted in a manner related to their ability to disrupt or solubilize skin lipids. In order to more closely describe the permeation data, significant increases in the stratum corneum/water partition coefficients, K{sub sc}, and modest changes to the diffusion coefficients, D{sub sc}, were required. The analysis provided strong evidence for both skin swelling and barrier disruption by VOCs, even by the minute amounts absorbed under these in vitro test conditions. - Highlights: • Human skin absorption of small doses of VOCs was measured in vitro in a fume hood. • The VOCs tested were ethanol, acetone, benzene and 1,2-dichloroethane. • Fraction of dose absorbed for all compounds at all doses tested was less than 0.3%. • The more aggressive VOCs absorbed at higher levels than

  12. Numerical research of the optimal control problem in the semi-Markov inventory model

    SciTech Connect (OSTI)

    Gorshenin, Andrey K.

    2015-03-10

    This paper is devoted to the numerical simulation of stochastic system for inventory management products using controlled semi-Markov process. The results of a special software for the systems research and finding the optimal control are presented.

  13. CBERD: Building Energy Simulation and Modeling | Department of Energy

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

    Energy Simulation and Modeling CBERD: Building Energy Simulation and Modeling Figure 1: Screenshot of the alpha version of CBERD eDOT (early design optimization tool), an online tool that enables multi-parameter optimization. Source: LBNL. Figure 1: Screenshot of the alpha version of CBERD eDOT (early design optimization tool), an online tool that enables multi-parameter optimization. Source: LBNL. Figure 2: CBERD Model Predictive Control: Model identification and closed loop predictive control

  14. Dream controller

    SciTech Connect (OSTI)

    Cheng, George Shu-Xing; Mulkey, Steven L; Wang, Qiang; Chow, Andrew J

    2013-11-26

    A method and apparatus for intelligently controlling continuous process variables. A Dream Controller comprises an Intelligent Engine mechanism and a number of Model-Free Adaptive (MFA) controllers, each of which is suitable to control a process with specific behaviors. The Intelligent Engine can automatically select the appropriate MFA controller and its parameters so that the Dream Controller can be easily used by people with limited control experience and those who do not have the time to commission, tune, and maintain automatic controllers.

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

    SciTech Connect (OSTI)

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

    2010-09-06

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

  16. Heat Transfer Salts for Nuclear Reactor Systems - Chemistry Control, Corrosion Mitigation, and Modeling

    SciTech Connect (OSTI)

    Anderson, Mark; Sridharan, Kumar; Morgan, Dane; Peterson, Per; Calderoni, Pattrick; Scheele, Randall; Casekka, Andrew; McNamara, Bruce

    2015-01-22

    The concept of a molten salt reactor has existed for nearly sixty years. Previously all work was done during a large collaborative effort at Oak Ridge National Laboratory, culminating in a research reactor which operated for 15,000 hours without major error. This technical success has garnished interest in modern, high temperature, reactor schemes. Research using molten fluoride salts for nuclear applications requires a steady supply of high grade molten salts. There is no bulk supplier of research grade fluoride salts in the world, so a facility which could provide all the salt needed for testing at the University of Wisconsin had to be produced. Two salt purification devices were made for this purpose, a large scale purifier, and a small scale purifier, each designed to clean the salts from impurities and reduce their corrosion potential. As of now, the small scale has performed with flibe salt, hydrogen, and hydrogen fluoride, yielding clean salt. This salt is currently being used in corrosion testing facilities at the Massachusetts Institute of Technology and the University of Wisconsin. Working with the beryllium based salts requires extensive safety measures and health monitoring to prevent the development of acute or chronic beryllium disease, two pulmonary diseases created by an allergic reaction to beryllium in the lungs. Extensive health monitoring, engineering controls, and environment monitoring had to be set up with the University of Wisconsin department of Environment, Health and Safety. The hydrogen fluoride required for purification was also an extreme health hazard requiring thoughtful planning and execution. These dangers have made research a slow and tedious process. Simple processes, such as chemical handling and clean-up, can take large amounts of ingenuity and time. Other work has complemented the experimental research at Wisconsin to advance high temperature reactor goals. Modeling work has been performed in house to re

  17. Predictive two-dimensional scrape-off layer plasma transport modeling of phase-I operations of tokamak SST-1 using SOLPS5

    SciTech Connect (OSTI)

    Himabindu, M.; Tyagi, Anil; Sharma, Devendra; Deshpande, Shishir P. [Institute for Plasma Research, Bhat, Gandhinagar 382428 (India)] [Institute for Plasma Research, Bhat, Gandhinagar 382428 (India); Bonnin, Xavier [Laboratoire des Sciences des Procds et des Matriaux, CNRS, Universit Paris13, Sorbonne Paris Cit, Villetaneuse 93430 (France)] [Laboratoire des Sciences des Procds et des Matriaux, CNRS, Universit Paris13, Sorbonne Paris Cit, Villetaneuse 93430 (France)

    2014-02-15

    Computational analysis of coupled plasma and neutral transport in the Scrape-Off Layer (SOL) region of the Steady-State Superconducting Tokamak (SST-1) is done using SOLPS for Phase-I of double-null divertor plasma operations. An optimum set of plasma parameters is explored computationally for the first phase operations with the central objective of achieving an effective control over particle and power exhaust. While the transport of plasma species is treated using a fluid model in the B2.5 code, a full kinetic description is provided by the EIRENE code for the neutral particle transport in a realistic geometry. Cases with and without external gas puffing are analyzed for finding regimes where an effective control of plasma operations can be exercised by controlling the SOL plasma conditions over a range of heating powers. In the desired parameter range, a reasonable neutral penetration across the SOL is observed, capable of causing a variation of up to 15% of the total input power, in the power deposited on the divertors. Our computational characterization of the SOL plasma with input power 1 MW and lower hybrid current drive, for the separatrix density up to 10{sup 19}?m{sup ?3}, indicates that there will be access to high recycling operations producing reduction in the temperature and the peak heat flux at the divertor targets. This indicates that a control of the core plasma density and temperature would be achievable. A power balance analysis done using the kinetic neutral transport code EIRENE indicates about 60%-75% of the total power diverted to the targets, providing quantitative estimates for the relative power loading of the targets and the rest of the plasma facing components.

  18. Application Of A New Semi-Empirical Model For Forming Limit Prediction Of Sheet Material Including Superposed Loads Of Bending And Shearing

    SciTech Connect (OSTI)

    Held, Christian; Liewald, Mathias; Schleich, Ralf; Sindel, Manfred

    2010-06-15

    The use of lightweight materials offers substantial strength and weight advantages in car body design. Unfortunately such kinds of sheet material are more susceptible to wrinkling, spring back and fracture during press shop operations. For characterization of capability of sheet material dedicated to deep drawing processes in the automotive industry, mainly Forming Limit Diagrams (FLD) are used. However, new investigations at the Institute for Metal Forming Technology have shown that High Strength Steel Sheet Material and Aluminum Alloys show increased formability in case of bending loads are superposed to stretching loads. Likewise, by superposing shearing on in plane uniaxial or biaxial tension formability changes because of materials crystallographic texture. Such mixed stress and strain conditions including bending and shearing effects can occur in deep-drawing processes of complex car body parts as well as subsequent forming operations like flanging. But changes in formability cannot be described by using the conventional FLC. Hence, for purpose of improvement of failure prediction in numerical simulation codes significant failure criteria for these strain conditions are missing. Considering such aspects in defining suitable failure criteria which is easy to implement into FEA a new semi-empirical model has been developed considering the effect of bending and shearing in sheet metals formability. This failure criterion consists of the combination of the so called cFLC (combined Forming Limit Curve), which considers superposed bending load conditions and the SFLC (Shear Forming Limit Curve), which again includes the effect of shearing on sheet metal's formability.

  19. Transaction-based building controls framework, Volume 2: Platform descriptive model and requirements

    SciTech Connect (OSTI)

    Akyol, Bora A.; Haack, Jereme N.; Carpenter, Brandon J.; Katipamula, Srinivas; Lutes, Robert G.; Hernandez, George

    2015-07-31

    Transaction-based Building Controls (TBC) offer a control systems platform that provides an agent execution environment that meets the growing requirements for security, resource utilization, and reliability. This report outlines the requirements for a platform to meet these needs and describes an illustrative/exemplary implementation.

  20. Predictive Capability Maturity Model for computational modeling...

    Office of Scientific and Technical Information (OSTI)

    Sponsoring Org: USDOE Country of Publication: United States Language: English Subject: 97 MATHEMATICAL METHODS AND COMPUTING; 99 GENERAL AND MISCELLANEOUSMATHEMATICS, COMPUTING, ...

  1. Model based multivariable controller for large scale compression stations. Design and experimental validation on the LHC 18KW cryorefrigerator

    SciTech Connect (OSTI)

    Bonne, François; Bonnay, Patrick; Bradu, Benjamin

    2014-01-29

    In this paper, a multivariable model-based non-linear controller for Warm Compression Stations (WCS) is proposed. The strategy is to replace all the PID loops controlling the WCS with an optimally designed model-based multivariable loop. This new strategy leads to high stability and fast disturbance rejection such as those induced by a turbine or a compressor stop, a key-aspect in the case of large scale cryogenic refrigeration. The proposed control scheme can be used to have precise control of every pressure in normal operation or to stabilize and control the cryoplant under high variation of thermal loads (such as a pulsed heat load expected to take place in future fusion reactors such as those expected in the cryogenic cooling systems of the International Thermonuclear Experimental Reactor ITER or the Japan Torus-60 Super Advanced fusion experiment JT-60SA). The paper details how to set the WCS model up to synthesize the Linear Quadratic Optimal feedback gain and how to use it. After preliminary tuning at CEA-Grenoble on the 400W@1.8K helium test facility, the controller has been implemented on a Schneider PLC and fully tested first on the CERN's real-time simulator. Then, it was experimentally validated on a real CERN cryoplant. The efficiency of the solution is experimentally assessed using a reasonable operating scenario of start and stop of compressors and cryogenic turbines. This work is partially supported through the European Fusion Development Agreement (EFDA) Goal Oriented Training Program, task agreement WP10-GOT-GIRO.

  2. Predicting Hurricanes with Supercomputers

    SciTech Connect (OSTI)

    2010-01-01

    Hurricane Emily, formed in the Atlantic Ocean on July 10, 2005, was the strongest hurricane ever to form before August. By checking computer models against the actual path of the storm, researchers can improve hurricane prediction. In 2010, NOAA researchers were awarded 25 million processor-hours on Argonne's BlueGene/P supercomputer for the project. Read more at http://go.usa.gov/OLh

  3. API Requirements for Dynamic Graph Prediction

    SciTech Connect (OSTI)

    Gallagher, B; Eliassi-Rad, T

    2006-10-13

    Given a large-scale time-evolving multi-modal and multi-relational complex network (a.k.a., a large-scale dynamic semantic graph), we want to implement algorithms that discover patterns of activities on the graph and learn predictive models of those discovered patterns. This document outlines the application programming interface (API) requirements for fast prototyping of feature extraction, learning, and prediction algorithms on large dynamic semantic graphs. Since our algorithms must operate on large-scale dynamic semantic graphs, we have chosen to use the graph API developed in the CASC Complex Networks Project. This API is supported on the back end by a semantic graph database (developed by Scott Kohn and his team). The advantages of using this API are (i) we have full-control of its development and (ii) the current API meets almost all of the requirements outlined in this document.

  4. Local Sensitivity of Predicted CO2 Injectivity and Plume Extent to Model Inputs for the FutureGen 2.0 site

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

    Zhang, Z. Fred; White, Signe K.; Bonneville, Alain; Gilmore, Tyler J.

    2014-12-31

    Numerical simulations have been used for estimating CO2 injectivity, CO2 plume extent, pressure distribution, and Area of Review (AoR), and for the design of CO2 injection operations and monitoring network for the FutureGen project. The simulation results are affected by uncertainties associated with numerous input parameters, the conceptual model, initial and boundary conditions, and factors related to injection operations. Furthermore, the uncertainties in the simulation results also vary in space and time. The key need is to identify those uncertainties that critically impact the simulation results and quantify their impacts. We introduce an approach to determine the local sensitivity coefficientmore » (LSC), defined as the response of the output in percent, to rank the importance of model inputs on outputs. The uncertainty of an input with higher sensitivity has larger impacts on the output. The LSC is scalable by the error of an input parameter. The composite sensitivity of an output to a subset of inputs can be calculated by summing the individual LSC values. We propose a local sensitivity coefficient method and applied it to the FutureGen 2.0 Site in Morgan County, Illinois, USA, to investigate the sensitivity of input parameters and initial conditions. The conceptual model for the site consists of 31 layers, each of which has a unique set of input parameters. The sensitivity of 11 parameters for each layer and 7 inputs as initial conditions is then investigated. For CO2 injectivity and plume size, about half of the uncertainty is due to only 4 or 5 of the 348 inputs and 3/4 of the uncertainty is due to about 15 of the inputs. The initial conditions and the properties of the injection layer and its neighbour layers contribute to most of the sensitivity. Overall, the simulation outputs are very sensitive to only a small fraction of the inputs. However, the parameters that are important for controlling CO2 injectivity are not the same as those controlling

  5. Local Sensitivity of Predicted CO2 Injectivity and Plume Extent to Model Inputs for the FutureGen 2.0 site

    SciTech Connect (OSTI)

    Zhang, Z. Fred; White, Signe K.; Bonneville, Alain; Gilmore, Tyler J.

    2014-12-31

    Numerical simulations have been used for estimating CO2 injectivity, CO2 plume extent, pressure distribution, and Area of Review (AoR), and for the design of CO2 injection operations and monitoring network for the FutureGen project. The simulation results are affected by uncertainties associated with numerous input parameters, the conceptual model, initial and boundary conditions, and factors related to injection operations. Furthermore, the uncertainties in the simulation results also vary in space and time. The key need is to identify those uncertainties that critically impact the simulation results and quantify their impacts. We introduce an approach to determine the local sensitivity coefficient (LSC), defined as the response of the output in percent, to rank the importance of model inputs on outputs. The uncertainty of an input with higher sensitivity has larger impacts on the output. The LSC is scalable by the error of an input parameter. The composite sensitivity of an output to a subset of inputs can be calculated by summing the individual LSC values. We propose a local sensitivity coefficient method and applied it to the FutureGen 2.0 Site in Morgan County, Illinois, USA, to investigate the sensitivity of input parameters and initial conditions. The conceptual model for the site consists of 31 layers, each of which has a unique set of input parameters. The sensitivity of 11 parameters for each layer and 7 inputs as initial conditions is then investigated. For CO2 injectivity and plume size, about half of the uncertainty is due to only 4 or 5 of the 348 inputs and 3/4 of the uncertainty is due to about 15 of the inputs. The initial conditions and the properties of the injection layer and its neighbour layers contribute to most of the sensitivity. Overall, the simulation outputs are very sensitive to only a small fraction of the inputs. However, the parameters that are important for controlling CO2 injectivity are not the same as those controlling the plume

  6. Multi-scale Atmospheric Modeling of Green House Gas Dispersion in Complex Terrain. Controlled Release Study

    SciTech Connect (OSTI)

    Costigan, Keeley Rochelle; Sauer, Jeremy A.; Dubey, Manvendra Krishna

    2015-07-10

    This report discusses the ghgas IC project which when applied, allows for an evaluation of LANL's HIGRAD model which can be used to create atmospheric simulations.

  7. Method and device for predicting wavelength dependent radiation influences in thermal systems

    DOE Patents [OSTI]

    Kee, Robert J.; Ting, Aili

    1996-01-01

    A method and apparatus for predicting the spectral (wavelength-dependent) radiation transport in thermal systems including interaction by the radiation with partially transmitting medium. The predicted model of the thermal system is used to design and control the thermal system. The predictions are well suited to be implemented in design and control of rapid thermal processing (RTP) reactors. The method involves generating a spectral thermal radiation transport model of an RTP reactor. The method also involves specifying a desired wafer time dependent temperature profile. The method further involves calculating an inverse of the generated model using the desired wafer time dependent temperature to determine heating element parameters required to produce the desired profile. The method also involves controlling the heating elements of the RTP reactor in accordance with the heating element parameters to heat the wafer in accordance with the desired profile.

  8. Making, Measuring, and Modeling Materials

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

    Making, Measuring, and Modeling Materials Making, Measuring, and Modeling Materials M4 facility aims to accelerate the transition from observation to control of materials providing unique synthesis and characterization tools to advance the frontiers of materials design and discovery. CONTACT Mark Bourke (505) 667-9667 Email Predicting and Controlling Materials' Performance MaRIE's Making, Measuring, and Modeling Materials (M4) Facility aims to accelerate the transition from observation to

  9. Evaluation of a hybrid kinetics/mixing-controlled combustion model for turbulent premixed and diffusion combustion using KIVA-2

    SciTech Connect (OSTI)

    Nguyen, H.L.; Wey, Mingjyh.

    1990-01-01

    Two dimensional calculations were made of spark ignited premixed-charge combustion and direct injection stratified-charge combustion in gasoline fueled piston engines. Results are obtained using kinetic-controlled combustion submodel governed by a four-step global chemical reaction or a hybrid laminar kinetics/mixing-controlled combustion submodel that accounts for laminar kinetics and turbulent mixing effects. The numerical solutions are obtained by using KIVA-2 computer code which uses a kinetic-controlled combustion submodel governed by a four-step global chemical reaction (i.e., it assumes that the mixing time is smaller than the chemistry). A hybrid laminar/mixing-controlled combustion submodel was implemented into KIVA-2. In this model, chemical species approach their thermodynamics equilibrium with a rate that is a combination of the turbulent-mixing time and the chemical-kinetics time. The combination is formed in such a way that the longer of the two times has more influence on the conversion rate and the energy release. An additional element of the model is that the laminar-flame kinetics strongly influence the early flame development following ignition.

  10. Springback Prediction on Slit-Ring Test

    SciTech Connect (OSTI)

    Chen Xiaoming; Shi, Ming F.; Ren Feng; Xia, Z. Cedric

    2005-08-05

    Advanced high strength steels (AHSS) are increasingly being used in the automotive industry to reduce vehicle weight while improving vehicle crash performance. One of the concerns in manufacturing is springback control after stamping. Although computer simulation technologies have been successfully applied to predict stamping formability, they still face major challenges in springback prediction, particularly for AHSS. Springback analysis is very complicated and involves large deformation problems in the forming stage and mechanical multiplying effect during the elastic recovery after releasing a part from the die. Therefore, the predictions are very sensitive to the simulation parameters used. It is very critical in springback simulation to choose an appropriate material model, element formulation and contact algorithm. In this study, a springback benchmark test, the slit ring cup, is used in the springback simulation with commercially available finite element analysis (FEA) software, LS-DYNA. The sensitivity of seven simulation variables on springback predictions was investigated, and a set of parameters with stable simulation results was identified. Final simulations using the selected set of parameters were conducted on six different materials including two AHSS steels, two conventional high strength steels, one mild steel and an aluminum alloy. The simulation results are compared with experimental measurements for all six materials and a favorable result is achieved. Simulation errors as compared against test results falls within 10%.

  11. Metabolome of human gut microbiome is predictive of host dysbiosis...

    Office of Scientific and Technical Information (OSTI)

    Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of ...

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

    SciTech Connect (OSTI)

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

    1988-04-01

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

  13. Aqueous precipitation: Population balance modeling and control in multi-cation systems

    SciTech Connect (OSTI)

    Voigt, J.A.

    1996-03-01

    Efficient separation of metal species from aqueous streams by precipitation techniques requires a fundamental understanding of the processes that occur during precipitation. These processes include particle nucleation, particle growth by solute deposition, agglomerate formation, and agglomerate breakup. Population balance method has been used to develop a kinetic model that accounts for these competing kinetic processes. The usefulness of the model is illustrated through its application to precipitation of yttrium hydroxynitrate, YHN. Kinetic parameters calculated from the model equations and system-specific solution chemistry are used to describe several aspects of the effect of pH on YHN precipitation. Implications for simultaneous precipitation of more than one cation type are discussed with examples. Effects of solution chemistry, precipitator design, and solvent choice are considered.

  14. Predicting Individual Fuel Economy

    SciTech Connect (OSTI)

    Lin, Zhenhong; Greene, David L

    2011-01-01

    To make informed decisions about travel and vehicle purchase, consumers need unbiased and accurate information of the fuel economy they will actually obtain. In the past, the EPA fuel economy estimates based on its 1984 rules have been widely criticized for overestimating on-road fuel economy. In 2008, EPA adopted a new estimation rule. This study compares the usefulness of the EPA's 1984 and 2008 estimates based on their prediction bias and accuracy and attempts to improve the prediction of on-road fuel economies based on consumer and vehicle attributes. We examine the usefulness of the EPA fuel economy estimates using a large sample of self-reported on-road fuel economy data and develop an Individualized Model for more accurately predicting an individual driver's on-road fuel economy based on easily determined vehicle and driver attributes. Accuracy rather than bias appears to have limited the usefulness of the EPA 1984 estimates in predicting on-road MPG. The EPA 2008 estimates appear to be equally inaccurate and substantially more biased relative to the self-reported data. Furthermore, the 2008 estimates exhibit an underestimation bias that increases with increasing fuel economy, suggesting that the new numbers will tend to underestimate the real-world benefits of fuel economy and emissions standards. By including several simple driver and vehicle attributes, the Individualized Model reduces the unexplained variance by over 55% and the standard error by 33% based on an independent test sample. The additional explanatory variables can be easily provided by the individuals.

  15. Substrate and environmental controls on microbial assimilation of soil organic carbon: a framework for Earth System Models

    SciTech Connect (OSTI)

    Xu, Xiaofeng; Schimel, Joshua; Thornton, Peter E; Song, Xia; Yuan, Fengming; Goswami, Santonu

    2014-01-01

    Microbial assimilation of soil organic carbon is one of the fundamental processes of global carbon cycling and it determines the magnitude of microbial biomass in soils. Mechanistic understanding of microbial assimilation of soil organic carbon and its controls is important for to improve Earth system models ability to simulate carbon-climate feedbacks. Although microbial assimilation of soil organic carbon is broadly considered to be an important parameter, it really comprises two separate physiological processes: one-time assimilation efficiency and time-dependent microbial maintenance energy. Representing of these two mechanisms is crucial to more accurately simulate carbon cycling in soils. In this study, a simple modeling framework was developed to evaluate the substrate and environmental controls on microbial assimilation of soil organic carbon using a new term: microbial annual active period (the length of microbes remaining active in one year). Substrate quality has a positive effect on microbial assimilation of soil organic carbon: higher substrate quality (lower C:N ratio) leads to higher ratio of microbial carbon to soil organic carbon and vice versa. Increases in microbial annual active period from zero stimulate microbial assimilation of soil organic carbon; however, when microbial annual active period is longer than an optimal threshold, increasing this period decreases microbial biomass. The simulated ratios of soil microbial biomass to soil organic carbon are reasonably consistent with a recently compiled global dataset at the biome-level. The modeling framework of microbial assimilation of soil organic carbon and its controls developed in this study offers an applicable ways to incorporate microbial contributions to the carbon cycling into Earth system models for simulating carbon-climate feedbacks and to explain global patterns of microbial biomass.

  16. DREAM tool increases space weather predictions

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

    DREAM tool increases space weather predictions Model addresses radiation hazards of the space environment on space systems. April 13, 2012 Scientists studying Earth's radiation ...

  17. Fracture Toughness Prediction for MWCNT Reinforced Ceramics

    SciTech Connect (OSTI)

    Henager, Charles H.; Nguyen, Ba Nghiep

    2013-09-01

    This report describes the development of a micromechanics model to predict fracture toughness of multiwall carbon nanotube (MWCNT) reinforced ceramic composites to guide future experimental work for this project. The modeling work described in this report includes (i) prediction of elastic properties, (ii) development of a mechanistic damage model accounting for matrix cracking to predict the composite nonlinear stress/strain response to tensile loading to failure, and (iii) application of this damage model in a modified boundary layer (MBL) analysis using ABAQUS to predict fracture toughness and crack resistance behavior (R-curves) for ceramic materials containing MWCNTs at various volume fractions.

  18. Comparison of Hydrodynamic Load Predictions Between Engineering Models and Computational Fluid Dynamics for the OC4-DeepCwind Semi-Submersible: Preprint

    SciTech Connect (OSTI)

    Benitz, M. A.; Schmidt, D. P.; Lackner, M. A.; Stewart, G. M.; Jonkman, J.; Robertson, A.

    2014-09-01

    Hydrodynamic loads on the platforms of floating offshore wind turbines are often predicted with computer-aided engineering tools that employ Morison's equation and/or potential-flow theory. This work compares results from one such tool, FAST, NREL's wind turbine computer-aided engineering tool, and the computational fluid dynamics package, OpenFOAM, for the OC4-DeepCwind semi-submersible analyzed in the International Energy Agency Wind Task 30 project. Load predictions from HydroDyn, the offshore hydrodynamics module of FAST, are compared with high-fidelity results from OpenFOAM. HydroDyn uses a combination of Morison's equations and potential flow to predict the hydrodynamic forces on the structure. The implications of the assumptions in HydroDyn are evaluated based on this code-to-code comparison.

  19. Experimental Studies for CPF and SCR Model, Control System, and OBD Development for Engines Using Diesel and Biodiesel Fuels

    SciTech Connect (OSTI)

    Johnson, John; Naber, Jeffrey; Parker, Gordon; Yang, Song-Lin; Stevens, Andrews; Pihl, Josh

    2013-04-30

    The research carried out on this project developed experimentally validated Diesel Oxidation Catalyst (DOC), Diesel Particulate Filter (DPF), and Selective Catalytic Reduction (SCR) high‐fidelity models that served as the basis for the reduced order models used for internal state estimation. The high‐fidelity and reduced order/estimator codes were evaluated by the industrial partners with feedback to MTU that improved the codes. Ammonia, particulate matter (PM) mass retained, PM concentration, and NOX sensors were evaluated and used in conjunction with the estimator codes. The data collected from PM experiments were used to develop the PM kinetics using the high‐fidelity DPF code for both NO2 assisted oxidation and thermal oxidation for Ultra Low Sulfur Fuel (ULSF), and B10 and B20 biodiesel fuels. Nine SAE papers were presented and this technology transfer process should provide the basis for industry to improve the OBD and control of urea injection and fuel injection for active regeneration of the PM in the DPF using the computational techniques developed. This knowledge will provide industry the ability to reduce the emissions and fuel consumption from vehicles in the field. Four MS and three PhD Mechanical Engineering students were supported on this project and their thesis research provided them with expertise in experimental, modeling, and controls in aftertreatment systems.

  20. Centralized and Decentralized Control for Demand Response

    SciTech Connect (OSTI)

    Lu, Shuai; Samaan, Nader A.; Diao, Ruisheng; Elizondo, Marcelo A.; Jin, Chunlian; Mayhorn, Ebony T.; Zhang, Yu; Kirkham, Harold

    2011-04-29

    Demand response has been recognized as an essential element of the smart grid. Frequency response, regulation and contingency reserve functions performed traditionally by generation resources are now starting to involve demand side resources. Additional benefits from demand response include peak reduction and load shifting, which will defer new infrastructure investment and improve generator operation efficiency. Technical approaches designed to realize these functionalities can be categorized into centralized control and decentralized control, depending on where the response decision is made. This paper discusses these two control philosophies and compares their relative advantages and disadvantages in terms of delay time, predictability, complexity, and reliability. A distribution system model with detailed household loads and controls is built to demonstrate the characteristics of the two approaches. The conclusion is that the promptness and reliability of decentralized control should be combined with the predictability and simplicity of centralized control to achieve the best performance of the smart grid.

  1. Studies of Ocean Predictability at Decade to Century Time Scales Using a Global Ocean General Circulation Model in a Parallel Computing Environment

    SciTech Connect (OSTI)

    Barnett, T.P.

    1998-11-30

    The objectives of this report are to determine the structure of oceanic natural variability at time scales of decades to centuries, characterize the physical mechanisms responsible for the variability; determine the relative importance of heat, fresh water, and moment fluxes on the variability; determine the predictability of the variability on these times scales. (B204)

  2. Collaborative Research: Towards Advanced Understanding and Predictive Capability of Climate Change in the Arctic Using a High-Resolution Regional Arctic Climate Model

    SciTech Connect (OSTI)

    Cassano, John

    2013-06-30

    The primary research task completed for this project was the development of the Regional Arctic Climate Model (RACM). This involved coupling existing atmosphere, ocean, sea ice, and land models using the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM) coupler (CPL7). RACM is based on the Weather Research and Forecasting (WRF) atmospheric model, the Parallel Ocean Program (POP) ocean model, the CICE sea ice model, and the Variable Infiltration Capacity (VIC) land model. A secondary research task for this project was testing and evaluation of WRF for climate-scale simulations on the large pan-Arctic model domain used in RACM. This involved identification of a preferred set of model physical parameterizations for use in our coupled RACM simulations and documenting any atmospheric biases present in RACM.

  3. Benchmark of Atucha-2 PHWR RELAP5-3D control rod model by Monte Carlo MCNP5 core calculation

    SciTech Connect (OSTI)

    Pecchia, M.; D'Auria, F.; Mazzantini, O.

    2012-07-01

    Atucha-2 is a Siemens-designed PHWR reactor under construction in the Republic of Argentina. Its geometrical complexity and peculiarities require the adoption of advanced Monte Carlo codes for performing realistic neutronic simulations. Therefore core models of Atucha-2 PHWR were developed using MCNP5. In this work a methodology was set up to collect the flux in the hexagonal mesh by which the Atucha-2 core is represented. The scope of this activity is to evaluate the effect of obliquely inserted control rod on neutron flux in order to validate the RELAP5-3D{sup C}/NESTLE three dimensional neutron kinetic coupled thermal-hydraulic model, applied by GRNSPG/UNIPI for performing selected transients of Chapter 15 FSAR of Atucha-2. (authors)

  4. MODELING COMPETITIVE ADSORPTION IN UREA-SCR CATALYSTS FOR EFFECTIVE LOW TEMPERATURE NOX CONTROL

    SciTech Connect (OSTI)

    Devarakonda, Maruthi N.; Tonkyn, Russell G.; Tran, Diana N.; Lee, Jong H.; Herling, Darrell R.

    2010-09-17

    Although the SCR technology exhibits higher NOx reduction efficiency over a wider range of temperatures among the lean NOx reduction technologies, further improvement in low-temperature performance is required to meet the future emission standards and to lower the system cost. In order to improve the catalyst technologies and optimize the system performance, it is critical to understand the reaction mechanisms and catalyst behaviors with respect to operating conditions. For example, it is well known that the ammonia coverage on catalyst surface is critical for NOx reduction efficiency. However, the level of ammonia storage is influenced by competitive adsorption by other species, such as H2O and NO2. Moreover, hydrocarbon species that slip through the upstream DOC during the cold-start period can also inhibit the SCR performance, especially at low temperatures. Therefore, a one-dimensional detailed kinetic model that can account for the effects of such competitive adsorption has been developed based on steady state surface isotherm tests on a commercial Fe-zeolite catalyst. The model is developed as a C language S-function and implemented in Matlab/Simulink environment. Rate kinetics of adsorption and desorption of each of the adsorbents are determined from individual adsorption tests and validated for a set of test conditions that had all the adsorbents in the feed gas.

  5. Cervical Gross Tumor Volume Dose Predicts Local Control Using Magnetic Resonance Imaging/Diffusion-Weighted Imaging—Guided High-Dose-Rate and Positron Emission Tomography/Computed Tomography—Guided Intensity Modulated Radiation Therapy

    SciTech Connect (OSTI)

    Dyk, Pawel; Jiang, Naomi; Sun, Baozhou; DeWees, Todd A.; Fowler, Kathryn J.; Narra, Vamsi; Garcia-Ramirez, Jose L.; Schwarz, Julie K.; Grigsby, Perry W.

    2014-11-15

    Purpose: Magnetic resonance imaging/diffusion weighted-imaging (MRI/DWI)-guided high-dose-rate (HDR) brachytherapy and {sup 18}F-fluorodeoxyglucose (FDG) — positron emission tomography/computed tomography (PET/CT)-guided intensity modulated radiation therapy (IMRT) for the definitive treatment of cervical cancer is a novel treatment technique. The purpose of this study was to report our analysis of dose-volume parameters predicting gross tumor volume (GTV) control. Methods and Materials: We analyzed the records of 134 patients with International Federation of Gynecology and Obstetrics stages IB1-IVB cervical cancer treated with combined MRI-guided HDR and IMRT from July 2009 to July 2011. IMRT was targeted to the metabolic tumor volume and lymph nodes by use of FDG-PET/CT simulation. The GTV for each HDR fraction was delineated by use of T2-weighted or apparent diffusion coefficient maps from diffusion-weighted sequences. The D100, D90, and Dmean delivered to the GTV from HDR and IMRT were summed to EQD2. Results: One hundred twenty-five patients received all irradiation treatment as planned, and 9 did not complete treatment. All 134 patients are included in this analysis. Treatment failure in the cervix occurred in 24 patients (18.0%). Patients with cervix failures had a lower D100, D90, and Dmean than those who did not experience failure in the cervix. The respective doses to the GTV were 41, 58, and 136 Gy for failures compared with 67, 99, and 236 Gy for those who did not experience failure (P<.001). Probit analysis estimated the minimum D100, D90, and Dmean doses required for ≥90% local control to be 69, 98, and 260 Gy (P<.001). Conclusions: Total dose delivered to the GTV from combined MRI-guided HDR and PET/CT-guided IMRT is highly correlated with local tumor control. The findings can be directly applied in the clinic for dose adaptation to maximize local control.

  6. Development of a Low-Lift Chiller Controller and Simplified Precooling Control Algorithm - Final Report

    SciTech Connect (OSTI)

    Gayeski, N.; Armstrong, Peter; Alvira, M.; Gagne, J.; Katipamula, Srinivas

    2011-11-30

    KGS Buildings LLC (KGS) and Pacific Northwest National Laboratory (PNNL) have developed a simplified control algorithm and prototype low-lift chiller controller suitable for model-predictive control in a demonstration project of low-lift cooling. Low-lift cooling is a highly efficient cooling strategy conceived to enable low or net-zero energy buildings. A low-lift cooling system consists of a high efficiency low-lift chiller, radiant cooling, thermal storage, and model-predictive control to pre-cool thermal storage overnight on an optimal cooling rate trajectory. We call the properly integrated and controlled combination of these elements a low-lift cooling system (LLCS). This document is the final report for that project.

  7. DOE/DHS INDUSTRIAL CONTROL SYSTEM CYBER SECURITY PROGRAMS: A MODEL FOR USE IN NUCLEAR FACILITY SAFEGUARDS AND SECURITY

    SciTech Connect (OSTI)

    Robert S. Anderson; Mark Schanfein; Trond Bjornard; Paul Moskowitz

    2011-07-01

    Many critical infrastructure sectors have been investigating cyber security issues for several years especially with the help of two primary government programs. The U.S. Department of Energy (DOE) National SCADA Test Bed and the U.S. Department of Homeland Security (DHS) Control Systems Security Program have both implemented activities aimed at securing the industrial control systems that operate the North American electric grid along with several other critical infrastructure sectors (ICS). These programs have spent the last seven years working with industry including asset owners, educational institutions, standards and regulating bodies, and control system vendors. The programs common mission is to provide outreach, identification of cyber vulnerabilities to ICS and mitigation strategies to enhance security postures. The success of these programs indicates that a similar approach can be successfully translated into other sectors including nuclear operations, safeguards, and security. The industry regulating bodies have included cyber security requirements and in some cases, have incorporated sets of standards with penalties for non-compliance such as the North American Electric Reliability Corporation Critical Infrastructure Protection standards. These DOE and DHS programs that address security improvements by both suppliers and end users provide an excellent model for nuclear facility personnel concerned with safeguards and security cyber vulnerabilities and countermeasures. It is not a stretch to imagine complete surreptitious collapse of protection against the removal of nuclear material or even initiation of a criticality event as witnessed at Three Mile Island or Chernobyl in a nuclear ICS inadequately protected against the cyber threat.

  8. Demonstration of Data Center Energy Use Prediction Software

    SciTech Connect (OSTI)

    Coles, Henry; Greenberg, Steve; Tschudi, William

    2013-09-30

    This report documents a demonstration of a software modeling tool from Romonet that was used to predict energy use and forecast energy use improvements in an operating data center. The demonstration was conducted in a conventional data center with a 15,500 square foot raised floor and an IT equipment load of 332 kilowatts. It was cooled using traditional computer room air handlers and a compressor-based chilled water system. The data center also utilized an uninterruptible power supply system for power conditioning and backup. Electrical energy monitoring was available at a number of locations within the data center. The software modeling tool predicted the energy use of the data center?s cooling and electrical power distribution systems, as well as electrical energy use and heat removal for the site. The actual energy used by the computer equipment was recorded from power distribution devices located at each computer equipment row. The model simulated the total energy use in the data center and supporting infrastructure and predicted energy use at energy-consuming points throughout the power distribution system. The initial predicted power levels were compared to actual meter readings and were found to be within approximately 10 percent at a particular measurement point, resulting in a site overall variance of 4.7 percent. Some variances were investigated, and more accurate information was entered into the model. In this case the overall variance was reduced to approximately 1.2 percent. The model was then used to predict energy use for various modification opportunities to the data center in successive iterations. These included increasing the IT equipment load, adding computer room air handler fan speed controls, and adding a water-side economizer. The demonstration showed that the software can be used to simulate data center energy use and create a model that is useful for investigating energy efficiency design changes.

  9. Risk Level Based Management System: a control banding model for occupational health and safety risk management in a highly regulated environment

    SciTech Connect (OSTI)

    Zalk, D; Kamerzell, R; Paik, S; Kapp, J; Harrington, D; Swuste, P

    2009-05-27

    The Risk Level Based Management System (RLBMS) is an occupational risk management (ORM) model that focuses occupational safety, hygeiene, and health (OSHH) resources on the highest risk procedures at work. This article demonstrates the model's simplicity through an implementation within a heavily regulated research institution. The model utilizes control banding strategies with a stratification of four risk levels (RLs) for many commonly performed maintenance and support activities, characterizing risk consistently for comparable tasks. RLBMS creates an auditable tracking of activities, maximizes OSHH professional field time, and standardizes documentation and control commensurate to a given task's RL. Validation of RLs and their exposure control effectiveness is collected in a traditional quantitative collection regime for regulatory auditing. However, qualitative risk assessment methods are also used within this validation process. Participatory approaches are used throughout the RLBMS process. Workers are involved in all phases of building, maintaining, and improving this model. This work participation also improves the implementation of established controls.

  10. Development of an Advanced Simulator to Model Mobility Control and Geomechanics during CO{sub 2} Floods

    SciTech Connect (OSTI)

    Delshad, Mojdeh; Wheeler, Mary; Sepehrnoori, Kamy; Pope, Gary

    2013-12-31

    The simulator is an isothermal, three-dimensional, four-phase, compositional, equation-of– state (EOS) simulator. We have named the simulator UTDOE-CO2 capable of simulating various recovery processes (i.e., primary, secondary waterflooding, and miscible and immiscible gas flooding). We include both the Peng-Robinson EOS and the Redlich-Kwong EOS models. A Gibbs stability test is also included in the model to perform a phase identification test to consistently label each phase for subsequent property calculations such as relative permeability, viscosity, density, interfacial tension, and capillary pressure. Our time step strategy is based on an IMPEC-type method (implicit pressure and explicit concentration). The gridblock pressure is solved first using the explicit dating of saturation-dependent terms. Subsequently, the material balance equations are solved explicitly for the total concentration of each component. The physical dispersion term is also included in the governing equations. The simulator includes (1) several foam model(s) for gas mobility control, (2) compositional relative permeability models with the hysteresis option, (3) corner point grid and several efficient solvers, (4) geomechanics module to compute stress field as the result of CO{sub 2} injection/production, (5) the format of commercial visualization software, S3graf from Science-soft Ltd., was implemented for user friendly visualization of the simulation results. All tasks are completed and the simulator was fully tested and delivered to the DOE office including a user’s guide and several input files and the executable for Windows Pcs. We have published several SPE papers, presented several posters, and one MS thesis is completed (V. Pudugramam, 2013) resulting from this DOE funded project.

  11. Workshop on Current Issues in Predictive Approaches to Intelligence and Security Analytics: Fostering the Creation of Decision Advantage through Model Integration and Evaluation

    SciTech Connect (OSTI)

    Sanfilippo, Antonio P.

    2010-05-23

    The increasing asymmetric nature of threats to the security, health and sustainable growth of our society requires that anticipatory reasoning become an everyday activity. Currently, the use of anticipatory reasoning is hindered by the lack of systematic methods for combining knowledge- and evidence-based models, integrating modeling algorithms, and assessing model validity, accuracy and utility. The workshop addresses these gaps with the intent of fostering the creation of a community of interest on model integration and evaluation that may serve as an aggregation point for existing efforts and a launch pad for new approaches.

  12. Initial Value Predictability of Intrinsic Oceanic Modes and Implications for Decadal Prediction over North America

    SciTech Connect (OSTI)

    Branstator, Grant

    2014-12-09

    The overall aim of our project was to quantify and characterize predictability of the climate as it pertains to decadal time scale predictions. By predictability we mean the degree to which a climate forecast can be distinguished from the climate that exists at initial forecast time, taking into consideration the growth of uncertainty that occurs as a result of the climate system being chaotic. In our project we were especially interested in predictability that arises from initializing forecasts from some specific state though we also contrast this predictability with predictability arising from forecasting the reaction of the system to external forcing – for example changes in greenhouse gas concentration. Also, we put special emphasis on the predictability of prominent intrinsic patterns of the system because they often dominate system behavior. Highlights from this work include: • Development of novel methods for estimating the predictability of climate forecast models. • Quantification of the initial value predictability limits of ocean heat content and the overturning circulation in the Atlantic as they are represented in various state of the artclimate models. These limits varied substantially from model to model but on average were about a decade with North Atlantic heat content tending to be more predictable than North Pacific heat content. • Comparison of predictability resulting from knowledge of the current state of the climate system with predictability resulting from estimates of how the climate system will react to changes in greenhouse gas concentrations. It turned out that knowledge of the initial state produces a larger impact on forecasts for the first 5 to 10 years of projections. • Estimation of tbe predictability of dominant patterns of ocean variability including well-known patterns of variability in the North Pacific and North Atlantic. For the most part these patterns were predictable for 5 to 10 years. • Determination of

  13. Collaborative Research: Towards Advanced Understanding and Predictive Capability of Climate Change in the Arctic using a High-Resolution Regional Arctic Climate System Model

    SciTech Connect (OSTI)

    Lettenmaier, Dennis P

    2013-04-08

    Primary activities are reported in these areas: climate system component studies via one-way coupling experiments; development of the Regional Arctic Climate System Model (RACM); and physical feedback studies focusing on changes in Arctic sea ice using the fully coupled model.

  14. Prediction of Corrosion of Advanced Materials and Fabricated Components

    SciTech Connect (OSTI)

    A. Anderko; G. Engelhardt; M.M. Lencka; M.A. Jakab; G. Tormoen; N. Sridhar

    2007-09-29

    The goal of this project is to provide materials engineers, chemical engineers and plant operators with a software tool that will enable them to predict localized corrosion of process equipment including fabricated components as well as base alloys. For design and revamp purposes, the software predicts the occurrence of localized corrosion as a function of environment chemistry and assists the user in selecting the optimum alloy for a given environment. For the operation of existing plants, the software enables the users to predict the remaining life of equipment and help in scheduling maintenance activities. This project combined fundamental understanding of mechanisms of corrosion with focused experimental results to predict the corrosion of advanced, base or fabricated, alloys in real-world environments encountered in the chemical industry. At the heart of this approach is the development of models that predict the fundamental parameters that control the occurrence of localized corrosion as a function of environmental conditions and alloy composition. The fundamental parameters that dictate the occurrence of localized corrosion are the corrosion and repassivation potentials. The program team, OLI Systems and Southwest Research Institute, has developed theoretical models for these parameters. These theoretical models have been applied to predict the occurrence of localized corrosion of base materials and heat-treated components in a variety of environments containing aggressive and non-aggressive species. As a result of this project, a comprehensive model has been established and extensively verified for predicting the occurrence of localized corrosion as a function of environment chemistry and temperature by calculating the corrosion and repassivation potentials.To support and calibrate the model, an experimental database has been developed to elucidate (1) the effects of various inhibiting species as well as aggressive species on localized corrosion of nickel

  15. Methane modeling: predicting the inflow of methane gas into coal mines. Quarterly technical progress report, April 1, 1982-June 30, 1982

    SciTech Connect (OSTI)

    Boyer, C.M. II; Hoysan, P.M.; Pavone, A.M.; Richmond, O.; Schwerer, F.C.; Smelser, R.E.

    1982-01-01

    Work on Phase I of the Contract program is essentially complete and was reported in the Phase I Technical Report which has been reviewed and accepted by the Contract Technical Project Officer. Phase I work included a survey of relevant technical literature and development, demonstration and documentation of a computer model, MINE1D, for flow of methane and water in coal strata for geometries corresponding to an advancing mine face and to a mine pillar. The Phase I models are one-dimensional in the space variable but describe time-dependent (nonsteady) phenomena and include gas sorption phenomena. Some revisions have been made to input/output sections of MINE1D and the documentation has been expanded. These modifications will be reported in the next Quarterly Technical Report. Preliminary test scenarios have been formulated and reviewed with the Contract Technical Project Officer for measurement of emissions during room-and-pillar and longwall mining operations. These preliminary scenarios are described in this report. A mathematical model has been developed to describe the increased stresses on the coal seam near mine openings. The model is based on an approximate elastic/plastic treatment of the coal seam and an elastic treatment of surrounding strata. In this model, elastic compaction of the coal seam decreases porosity and permeability, whereas plastic deformation increases the porosity of the natural fracture network and thereby increases the permeability. The model takes into account the effect of changes in pore fluid pressure (in the natural fracture network of the coal seam) on the deformation of the coal seam. This model is described in this report, and will be programmed for inclusion in revised versions of MINE1D and for use in the two-dimensional computer models now under development. 8 figures.

  16. New process modeling [sic], design, and control strategies for energy efficiency, high product quality, and improved productivity in the process industries. Final project report

    SciTech Connect (OSTI)

    Ray, W. Harmon

    2002-06-05

    This project was concerned with the development of process design and control strategies for improving energy efficiency, product quality, and productivity in the process industries. In particular, (i) the resilient design and control of chemical reactors, and (ii) the operation of complex processing systems, was investigated. Specific topics studied included new process modeling procedures, nonlinear controller designs, and control strategies for multiunit integrated processes. Both fundamental and immediately applicable results were obtained. The new design and operation results from this project were incorporated into computer-aided design software and disseminated to industry. The principles and design procedures have found their way into industrial practice.

  17. Quantifying Uncertainty in Computer Predictions | netl.doe.gov

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

    multiphase computational fluid dynamics (CFD) models that underpin the simulation of ... Multiphase CFD models, for example, have the ability to predict the performance of ...

  18. Final Technical Report: Increasing Prediction Accuracy.

    SciTech Connect (OSTI)

    King, Bruce Hardison; Hansen, Clifford; Stein, Joshua

    2015-12-01

    PV performance models are used to quantify the value of PV plants in a given location. They combine the performance characteristics of the system, the measured or predicted irradiance and weather at a site, and the system configuration and design into a prediction of the amount of energy that will be produced by a PV system. These predictions must be as accurate as possible in order for finance charges to be minimized. Higher accuracy equals lower project risk. The Increasing Prediction Accuracy project at Sandia focuses on quantifying and reducing uncertainties in PV system performance models.

  19. Modeling of integrated environmental control systems for coal-fired power plants. Technical progress report, [June 1, 1989--September 30, 1989

    SciTech Connect (OSTI)

    Rubin, E.S.

    1989-10-01

    The general goal of this research project is to enhance, and transfer to DOE, a new computer simulation model for analyzing the performance and cost of environmental control systems for coal-fired power plants. Systems utilizing pre-combustion, combustion, or post-combustion control methods, individually or in combination, may be considered. A unique capability of this model is the probabilistic representation of uncertainty in model input parameters. This stochastic simulation capability allows the performance and cost of environmental control systems to be quantified probabilistically, accounting for the interactions among all uncertain process and economic parameters. This method facilitates more rigorous comparisons between conventional and advanced clean coal technologies promising improved cost and/or effectiveness for SO{sub 2} and NO{sub x} removal. Detailed modeling of several pre-combustion and post-combustion processes of interest to DOE/PETC have been selected for analysis as part of this project.

  20. Predicting long-term carbon sequestration in response to CO2 enrichment: How and why do current ecosystem models differ?

    SciTech Connect (OSTI)

    Walker, Anthony P.; Zaehle, Sönke; Medlyn, Belinda E.; De Kauwe, Martin G.; Asao, Shinichi; Hickler, Thomas; Parton, William; Ricciuto, Daniel M.; Wang, Ying -Ping; Wårlind, David; Norby, Richard J.

    2015-04-27

    Large uncertainty exists in model projections of the land carbon (C) sink response to increasing atmospheric CO2. Free-Air CO2 Enrichment (FACE) experiments lasting a decade or more have investigated ecosystem responses to a step change in atmospheric CO2 concentration. To interpret FACE results in the context of gradual increases in atmospheric CO2 over decades to centuries, we used a suite of seven models to simulate the Duke and Oak Ridge FACE experiments extended for 300 years of CO2 enrichment. We also determine key modeling assumptions that drive divergent projections of terrestrial C uptake and evaluate whether these assumptions can be constrained by experimental evidence. All models simulated increased terrestrial C pools resulting from CO2 enrichment, though there was substantial variability in quasi-equilibrium C sequestration and rates of change. In two of two models that assume that plant nitrogen (N) uptake is solely a function of soil N supply, the net primary production response to elevated CO2 became progressively N limited. In four of five models that assume that N uptake is a function of both soil N supply and plant N demand, elevated CO2 led to reduced ecosystem N losses and thus progressively relaxed nitrogen limitation. Many allocation assumptions resulted in increased wood allocation relative to leaves and roots which reduced the vegetation turnover rate and increased C sequestration. Additionally, self-thinning assumptions had a substantial impact on C sequestration in two models. As a result, accurate representation of N process dynamics (in particular N uptake), allocation, and forest self-thinning is key to minimizing uncertainty in projections of future C sequestration in response to elevated atmospheric CO2.

  1. WRF-Chem model predictions of the regional impacts of N2O5 heterogeneous processes on night-time chemistry over north-western Europe

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

    Lowe, Douglas; Archer-Nicholls, Scott; Morgan, Will; Allan, James D.; Utembe, Steve; Ouyang, Bin; Aruffo, Eleonora; Le Breton, Michael; Zaveri, Rahul A.; di Carlo, Piero; et al

    2015-02-09

    Chemical modelling studies have been conducted over north-western Europe in summer conditions, showing that night-time dinitrogen pentoxide (N2O5) heterogeneous reactive uptake is important regionally in modulating particulate nitrate and has a~modest influence on oxidative chemistry. Results from Weather Research and Forecasting model with Chemistry (WRF-Chem) model simulations, run with a detailed volatile organic compound (VOC) gas-phase chemistry scheme and the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) sectional aerosol scheme, were compared with a series of airborne gas and particulate measurements made over the UK in July 2010. Modelled mixing ratios of key gas-phase species were reasonably accurate (correlationsmore » with measurements of 0.7–0.9 for NO2 and O3). However modelled loadings of particulate species were less accurate (correlation with measurements for particulate sulfate and ammonium were between 0.0 and 0.6). Sulfate mass loadings were particularly low (modelled means of 0.5–0.7 μg kg−1air, compared with measurements of 1.0–1.5 μg kg−1air). Two flights from the campaign were used as test cases – one with low relative humidity (RH) (60–70%), the other with high RH (80–90%). N2O5 heterogeneous chemistry was found to not be important in the low-RH test case; but in the high-RH test case it had a strong effect and significantly improved the agreement between modelled and measured NO3 and N2O5. When the model failed to capture atmospheric RH correctly, the modelled NO3 and N2O5 mixing ratios for these flights differed significantly from the measurements. This demonstrates that, for regional modelling which involves heterogeneous processes, it is essential to capture the ambient temperature and water vapour profiles. The night-time NO3 oxidation of VOCs across the whole region was found to be 100–300 times slower than the daytime OH oxidation of these compounds. The difference in contribution was less for

  2. Predictive model for the determination of the economic feasibility of construction and demolition waste recycling in the Air Force. Master's thesis

    SciTech Connect (OSTI)

    Dixon, B.L.

    1993-09-01

    This study created a model to be used at a CONUS Air Force base to determine the economic feasibility of Construction and Demolition (CD) waste recycling. Three areas investigated to develop this model: the methods to determine amounts and types of CD waste generated at a specific location, the markets for recycled CD wastes, and the recycling methods currently available. From this data, gathered through records searches and interviews, a procedure was developed to perform cost/benefit analyses on the available recycling options. A model was then created based on these calculations which can arm a manager with information to either support or reject a recycling program by indicating cost savings or losses from recycling CD waste. Also, the model aids managers in determining the approximate quantities of recyclable materials being generated, which could be valuable in reaching base recycling goals. To demonstrate the model, the feasibility of recycling CD waste at Hill AFB, Utah in 1994 was evaluated. In addition to determining recycling feasibility, a method was presented to perform sensitivity analyses on the base-specific input variables. This procedure can help determine when it will become feasible to create a CD waste recycling program.

  3. Control of the Accumulation of Non-Process Elements in Pulp Mills with Bleach Filtrate Reuse: A Chemical Equilibrium Approach to Predicting the Partitioning of Metals in Pulp Mill and Bleach Plant Streams

    SciTech Connect (OSTI)

    Frederick, W.J. Jr.; Rudie, A.W.; Schmidl, G.W.; Sinquefield, S.A.; Rorrer, G.L.; Laver, M.L.; Yantasee, W.; Ming, D.

    2000-08-01

    The overall goal of this project was to develop fundamental, experimentally based methods for predicting the solubility or organic and inorganic matter and their interactions in recycled effluent from kraft pulp mills and bleach plants. This included: characterizing the capacity of wood pulp and dissolved organic matter to bind metal ions, developing a thermodynamic database of properties needed to describe the solubility of inorganic matter in pulp mill streams, incorporation of the database into equilibrium calculation software for predicting the solubility of the metals of interest, and evaluating its capability to predict the distribution of the metals between pulp fibers, inorganic precipitates, and solution.

  4. PREDICTION OF 4\

    Office of Scientific and Technical Information (OSTI)

    PREDICTION OF 4nu1 RESONANCE OF A HIGH INTENSITY LINAC* Citation Details In-Document Search Title: PREDICTION OF 4nu1 RESONANCE OF A HIGH INTENSITY LINAC* The 4nu1 resonance ...

  5. Total dissolved gas prediction and optimization in RiverWare

    SciTech Connect (OSTI)

    Stewart, Kevin M.; Witt, Adam M.; Hadjerioua, Boualem

    2015-09-01

    Management and operation of dams within the Columbia River Basin (CRB) provides the region with irrigation, hydropower production, flood control, navigation, and fish passage. These various system-wide demands can require unique dam operations that may result in both voluntary and involuntary spill, thereby increasing tailrace levels of total dissolved gas (TDG) which can be fatal to fish. Appropriately managing TDG levels within the context of the systematic demands requires a predictive framework robust enough to capture the operationally related effects on TDG levels. Development of the TDG predictive methodology herein attempts to capture the different modes of hydro operation, thereby making it a viable tool to be used in conjunction with a real-time scheduling model such as RiverWare. The end result of the effort will allow hydro operators to minimize system-wide TDG while meeting hydropower operational targets and constraints. The physical parameters such as spill and hydropower flow proportions, accompanied by the characteristics of the dam such as plant head levels and tailrace depths, are used to develop the empirically-based prediction model. In the broader study, two different models are developed a simplified and comprehensive model. The latter model incorporates more specific bubble physics parameters for the prediction of tailrace TDG levels. The former model is presented herein and utilizes an empirically based approach to predict downstream TDG levels based on local saturation depth, spillway and powerhouse flow proportions, and entrainment effects. Representative data collected from each of the hydro projects is used to calibrate and validate model performance and the accuracy of predicted TDG uptake. ORNL, in conjunction with IIHR - Hydroscience & Engineering, The University of Iowa, carried out model adjustments to adequately capture TDG levels with respect to each plant while maintaining a generalized model configuration. Validation results

  6. Derivation of a crack opening deflection relationship for fibre reinforced concrete panels using a stochastic model: Application for predicting the flexural behaviour of round panels using stress crack opening diagrams

    SciTech Connect (OSTI)

    Nour, Ali; Massicotte, Bruno; De Montaignac, Renaud; Charron, Jean-Philippe

    2011-09-15

    This study is aimed at proposing a simple analytical model to investigate the post-cracking behaviour of FRC panels, using an arbitrary tension softening, stress crack opening diagram, as the input. A new relationship that links the crack opening to the panel deflection is proposed. Due to the stochastic nature of material properties, the random fibre distribution, and other uncertainties that are involved in concrete mix, this relationship is developed from the analysis of beams having the same thickness using the Monte Carlo simulation (MCS) technique. The softening diagrams obtained from direct tensile tests are used as the input for the calculation, in a deterministic way, of the mean load displacement response of round panels. A good agreement is found between the model predictions and the experimental results.

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

    SciTech Connect (OSTI)

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

    2015-06-15

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

  8. Final Report: Development of a Chemical Model to Predict the Interactions between Supercritical CO2, Fluid and Rock in EGS Reservoirs

    SciTech Connect (OSTI)

    McPherson, Brian J.; Pan, Feng

    2014-09-24

    This report summarizes development of a coupled-process reservoir model for simulating enhanced geothermal systems (EGS) that utilize supercritical carbon dioxide as a working fluid. Specifically, the project team developed an advanced chemical kinetic model for evaluating important processes in EGS reservoirs, such as mineral precipitation and dissolution at elevated temperature and pressure, and for evaluating potential impacts on EGS surface facilities by related chemical processes. We assembled a new database for better-calibrated simulation of water/brine/ rock/CO2 interactions in EGS reservoirs. This database utilizes existing kinetic and other chemical data, and we updated those data to reflect corrections for elevated temperature and pressure conditions of EGS reservoirs.

  9. Building A Simulation Model For The Prediction Of Temperature Distribution In Pulsed Laser Spot Welding Of Dissimilar Low Carbon Steel 1020 To Aluminum Alloy 6061

    SciTech Connect (OSTI)

    Yousef, Adel K. M.; Taha, Ziad A.; Shehab, Abeer A.

    2011-01-17

    This paper describes the development of a computer model used to analyze the heat flow during pulsed Nd: YAG laser spot welding of dissimilar metal; low carbon steel (1020) to aluminum alloy (6061). The model is built using ANSYS FLUENT 3.6 software where almost all the environments simulated to be similar to the experimental environments. A simulation analysis was implemented based on conduction heat transfer out of the key hole where no melting occurs. The effect of laser power and pulse duration was studied.Three peak powers 1, 1.66 and 2.5 kW were varied during pulsed laser spot welding (keeping the energy constant), also the effect of two pulse durations 4 and 8 ms (with constant peak power), on the transient temperature distribution and weld pool dimension were predicated using the present simulation. It was found that the present simulation model can give an indication for choosing the suitable laser parameters (i.e. pulse durations, peak power and interaction time required) during pulsed laser spot welding of dissimilar metals.

  10. An Evaluation of Mesoscale Model Predictions of Down-Valley and Canyon Flows and Their Consequences Using Doppler Lidar Measurements During VTMX 2000

    SciTech Connect (OSTI)

    Fast, Jerome D.; Darby, Lisa S.

    2004-04-01

    A mesoscale model, a Lagrangian particle dispersion model, and extensive Doppler lidar wind measurements during the VTMX 2000 field campaign were used to examine converging flows over the Salt Lake Valley and their effect on vertical mixing of tracers at night and during the morning transition period. The simulated wind components were transformed into radial velocities to make a direct comparison with about 1.3 million Doppler lidar data points and critically evaluate, using correlation coefficients, the spatial variations in the simulated wind fields aloft. The mesoscale model captured reasonably well the general features of the observed circulations including the daytime up-valley flow, the nighttime slope, canyon, and down-valley flows, and the convergence of the flows over the valley. When there were errors in the simulated wind fields, they were usually associated with the timing, structure, or strength of specific flows. Simulated outflows from canyons along the Wasatch Mountains propagated over the valley and converged with the down-valley flow, but the advance and retreat of these simulated flows was often out of phase with the lidar measurements. While the flow reversal during the evening transition period produced rising motions over much of the valley atmosphere in the absence of significant ambient winds, average vertical velocities became close to zero as the down-valley flow developed. Still, vertical velocities between 5 and 15 cm s-1 occurred where down-slope, canyon and down-valley flows converged and vertical velocities greater than 50 cm s-1 were produced by hydraulic jumps at the base of the canyons. The presence of strong ambient winds resulted in smaller average rising motions during the evening transition period and larger average vertical velocities after that. A fraction of the tracer released at the surface was transported up to the height of the surrounding mountains; however, higher concentrations were produced aloft for evenings

  11. Integrated controls design optimization

    SciTech Connect (OSTI)

    Lou, Xinsheng; Neuschaefer, Carl H.

    2015-09-01

    A control system (207) for optimizing a chemical looping process of a power plant includes an optimizer (420), an income algorithm (230) and a cost algorithm (225) and a chemical looping process models. The process models are used to predict the process outputs from process input variables. Some of the process in puts and output variables are related to the income of the plant; and some others are related to the cost of the plant operations. The income algorithm (230) provides an income input to the optimizer (420) based on a plurality of input parameters (215) of the power plant. The cost algorithm (225) provides a cost input to the optimizer (420) based on a plurality of output parameters (220) of the power plant. The optimizer (420) determines an optimized operating parameter solution based on at least one of the income input and the cost input, and supplies the optimized operating parameter solution to the power plant.

  12. WINDOW-WALL INTERFACE CORRECTION FACTORS: THERMAL MODELING OF INTEGRATED FENESTRATION AND OPAQUE ENVELOPE SYSTEMS FOR IMPROVED PREDICTION OF ENERGY USE

    SciTech Connect (OSTI)

    Bhandari, Mahabir S; Ravi, Dr. Srinivasan

    2012-01-01

    The boundary conditions for thermal modeling of fenestration systems assume an adiabatic condition between the fenestration system installed and the opaque envelope system. This theoretical adiabatic boundary condition may not be appropriate owing to heat transfer at the interfaces, particularly for aluminum- framed windows affixed to metal- framed walls. In such scenarios, the heat transfer at the interface may increase the discrepancy between real world thermal indices and laboratory measured or calculated indices based on NFRC Rating System.This paper discusses the development of window-wall Interface Correction Factors (ICF) to improve energy impacts of building envelope systems

  13. Finite element model to predict the flow of underground contaminants due to leakage of chemical and/or radio active material from a buried containment. Final technical report

    SciTech Connect (OSTI)

    Anand, S.C.; Pandit, A.

    1983-06-01

    In the investigation, a Galerkin finite element model in two dimensions is developed to study the phenomena of mass transfer in porous media. In particular, the problems of the saltwater encroachment in coastal aquifers and the transport of hazardous wastes in groundwater environment are studied for a wide range of aquifer parameters. The coupled governing partial differential equations are nondimensionalized and solved for a two-dimensional, saturated aquifer in the vertical plane for both steady state and transient conditions using an iterative solution procedure. The flow transport is represented either in terms of the stream function or the freshwater hydraulic head.

  14. Methane modeling: predicting the inflow of methane gas into coal mines. Quarterly technical progress report, October 1, 1982-December 31, 1982

    SciTech Connect (OSTI)

    Boyer, C.M. II; Hoysan, P.M.; Pavone, A.M.; Schwerer, F.C.

    1982-01-01

    Maintenance and laboratory calibrations were obtained for automatic recording methanometers for use during in-mine tests. Speecifications and quotations have been obtained for battery operated versions of the automatic recording methanometers for monitoring in the tailgate region of the longwall operation. Due to mine closings, meetings with mine operators to discuss in-mine testing and to observe the mining section to be monitored have been delayed until February 1983. Assuming a resumption of coal production, actual in-mine tests are tentatively scheduled for March, 1983. Development and testing of software modules for a general two-dimensional model has continued with good progress. The major work emphasis is on the efficient computer execution of the numerical algorithms. Preliminary simulation test runs of an isolated, unstimulated well in an isotropic, homogeneous coalbed have been made. Work has been initiated on incorporating an infinite conductivity fracture in the simulation. Graphical representation of the data generated from the two-dimensional model will be produced and verified. A request was initiated for a no-cost, six-minths extension; this request has subsequently been approved. There is no change in the contract objectives or technical approach, and the project is on target with respect to expenditures.

  15. Modeling of integrated environmental control systems for coal-fired power plants. Quarterly progress report, [July 1, 1988--September 30, 1988

    SciTech Connect (OSTI)

    Rubin, E.S.

    1988-10-01

    This is the fourth quarterly report of DOE Contract No. DE-AC22-87PC79864, entitled ``Modeling of Integrated Environmental Control Systems for Coal-Fired Power Plants.`` This report summarizes accomplishments during the period July 1, 1988 to September 30, 1988. Our efforts during the last quarter focused primarily on the completion, testing and documentation of the NO{sub x}SO process model. The sections below present the details of these developments.

  16. Predicting Hurricanes with Supercomputers | Argonne National Laboratory

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

    Predicting Hurricanes with Supercomputers Share Description Hurricane Emily, formed in the Atlantic Ocean on July 10, 2005, was the strongest hurricane ever to form before August. By checking computer models against the actual path of the storm, researchers can improve hurricane prediction. In 2010, NOAA researchers were awarded 25 million processor-hours on Argonne's BlueGene/P supercomputer for the project. Duration 0:28 Topic Programs Mathematics, computing, & computer science Modeling,

  17. PISCEES for prediction

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

    PISCEES for prediction PISCEES for prediction The Greenland and Antarctic ice sheets will make a dominant contribution to twenty-first century sea-level rise if current climate trends continue, studied in a five-year project called Predicting Ice Sheet and Climate Evolution at Extreme Scales (PISCEES) February 19, 2016 Human-gorilla divergence may have occurred two million years earlier than thought (Photo : Flickr: Rod Waddington) Antarctica "The data we get from climate scientists are

  18. Precise determination of the mass of the Higgs boson and tests of compatibility of its couplings with the standard model predictions using proton collisions at 7 and 8 TeV

    SciTech Connect (OSTI)

    Khachatryan, Vardan

    2015-05-14

    Properties of the Higgs boson with mass near 125 GeV are measured in proton-proton collisions with the CMS experiment at the LHC. Comprehensive sets of production and decay measurements are combined. The decay channels include ??, ZZ, WW, ??, bb, and ?? pairs. The data samples were collected in 2011 and 2012 and correspond to integrated luminosities of up to 5.1 fb? at 7 TeV and up to 19.7 fb? at 8 TeV. From the high-resolution ?? and ZZ channels, the mass of the Higgs boson is determined to be 125.02\\,+0.26-0.27(stat)+0.14-0.15(syst) GeV. For this mass value, the event yields obtained in the different analyses tagging specific decay channels and production mechanisms are consistent with those expected for the standard model Higgs boson. The combined best-fit signal relative to the standard model expectation is 1.00 0.09 (stat), +0.08 -0.07 (theo) 0.07 (syst) at the measured mass. The couplings of the Higgs boson are probed for deviations in magnitude from the standard model predictions in multiple ways, including searches for invisible and undetected decays. No significant deviations are found.

  19. Precise determination of the mass of the Higgs boson and tests of compatibility of its couplings with the standard model predictions using proton collisions at 7 and 8 TeV

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

    Khachatryan, Vardan

    2015-05-14

    Properties of the Higgs boson with mass near 125 GeV are measured in proton-proton collisions with the CMS experiment at the LHC. Comprehensive sets of production and decay measurements are combined. The decay channels include ??, ZZ, WW, ??, bb, and ?? pairs. The data samples were collected in 2011 and 2012 and correspond to integrated luminosities of up to 5.1 fb? at 7 TeV and up to 19.7 fb? at 8 TeV. From the high-resolution ?? and ZZ channels, the mass of the Higgs boson is determined to be 125.02\\,+0.26-0.27(stat)+0.14-0.15(syst) GeV. For this mass value, the event yields obtainedmorein the different analyses tagging specific decay channels and production mechanisms are consistent with those expected for the standard model Higgs boson. The combined best-fit signal relative to the standard model expectation is 1.00 0.09 (stat), +0.08 -0.07 (theo) 0.07 (syst) at the measured mass. The couplings of the Higgs boson are probed for deviations in magnitude from the standard model predictions in multiple ways, including searches for invisible and undetected decays. No significant deviations are found.less

  20. Precise determination of the mass of the Higgs boson and tests of compatibility of its couplings with the standard model predictions using proton collisions at 7 and 8 $$\\,\\text {TeV}$$

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

    Khachatryan, Vardan

    2015-05-14

    Properties of the Higgs boson with mass near 125GeV are measured in proton-proton collisions with the CMS experiment at the LHC. Comprehensive sets of production and decay measurements are combined. The decay channels include γγ, ZZ, WW, ττ, bb, and μμ pairs. The data samples were collected in 2011 and 2012 and correspond to integrated luminosities of up to 5.1fb-1 at 7TeV and up to 19.7fb-1 at 8TeV. From the high-resolution γγ and ZZ channels, the mass of the Higgs boson is determined to be 125.02+0.26–0.27 (stat) +0.14–0.15 (syst) GeV. For this mass value, the event yields obtained in themore » different analyses tagging specific decay channels and production mechanisms are consistent with those expected for the standard model Higgs boson. The combined best-fit signal relative to the standard model expectation is 1.00 ± 0.09(stat)+0.08–0.07 (theo) ± 0.07(syst) at the measured mass. The couplings of the Higgs boson are probed for deviations in magnitude from the standard model predictions in multiple ways, including searches for invisible and undetected decays. As a result, no significant deviations are found.« less

  1. Modeling and Control System Design for an Integrated Solar Generation and Energy Storage System with a Ride-Through Capability: Preprint

    SciTech Connect (OSTI)

    Wang, X.; Yue, M.; Muljadi, E.

    2012-09-01

    This paper presents a generic approach for PV panel modeling. Data for this modeling can be easily obtained from manufacturer datasheet, which provides a convenient way for the researchers and engineers to investigate the PV integration issues. A two-stage power conversion system (PCS) is adopted in this paper for the PV generation system and a Battery Energy Storage System (BESS) can be connected to the dc-link through a bi-directional dc/dc converter. In this way, the BESS can provide some ancillary services which may be required in the high penetration PV generation scenario. In this paper, the fault ride-through (FRT) capability is specifically focused. The integrated BESS and PV generation system together with the associated control systems is modeled in PSCAD and Matlab platforms and the effectiveness of the controller is validated by the simulation results.

  2. Application of computational neural networks in predicting atmospheric pollutant concentrations due to fossil-fired electric power generation

    SciTech Connect (OSTI)

    El-Hawary, F.

    1995-12-31

    The ability to accurately predict the behavior of a dynamic system is of essential importance in monitoring and control of complex processes. In this regard recent advances in neural-net based system identification represent a significant step toward development and design of a new generation of control tools for increased system performance and reliability. The enabling functionality is the one of accurate representation of a model of a nonlinear and nonstationary dynamic system. This functionality provides valuable new opportunities including: (1) The ability to predict future system behavior on the basis of actual system observations, (2) On-line evaluation and display of system performance and design of early warning systems, and (3) Controller optimization for improved system performance. In this presentation, we discuss the issues involved in definition and design of learning control systems and their impact on power system control. Several numerical examples are provided for illustrative purpose.

  3. Engineering Model for Ash Formation

    Energy Science and Technology Software Center (OSTI)

    1994-12-02

    Ash deposition is controlled by the impaction and sticking of individual ash particles to heat transfer surfaces. Prediction of deposition therefore requires that the important factors in this process be predictable from coal and operational parameters. Coal combustion, boiler heat transfer, ash formation, ash particle aerodynamic, and ash particle sticking models are all essential steps in this process. The model described herein addresses the prediction of ash particle size and composition distributions based upon combustionmore » conditions and coal parameters. Key features of the model include a mineral redistribution routine to invert CCSEM mineralogical data, and a mineral interaction routine that simulates the conversion of mineral matter into ash during coal burning and yields ash particle size and composition distributions.« less

  4. Prediction of Combustion Stability and Flashback in Turbines with High-Hydrogen Fuel

    SciTech Connect (OSTI)

    Lieuwen, Tim; Santavicca, Dom; Yang, Vigor

    2012-03-31

    During the duration of this sponsorship, we broadened our understanding of combustion instabilities through both analytical and experimental work. Predictive models were developed for flame response to transverse acoustic instabilities and for quantifying how a turbulent flame responds to velocity and fuel/air ratio forcing. Analysis was performed on the key instability mechanisms controlling heat release response for flames over a wide range of instability frequencies. Importantly, work was done closely with industrial partners to transition existing models into internal instability prediction codes. Experimentally, the forced response of hydrogen-enriched natural gas/air premixed and partially premixed flames were measured. The response of a lean premixed flame was investigated, subjected to velocity, equivalence ratio, and both forcing mechanisms simultaneously. In addition, important physical mechanisms controlling the response of partially premixed flames to inlet velocity and equivalence ratio oscillations were analyzed. This final technical report summarizes our findings and major publications stemming from this program.

  5. Fuzzy-Logic Subsumption Controller for Home Energy Management Systems

    SciTech Connect (OSTI)

    Ainsworth, Nathan; Johnson, Brian; Lundstrom, Blake

    2015-10-06

    Home Energy Management Systems (HEMS) are controllers that manage and coordinate the generation, storage, and loads in a home. These controllers are increasingly necessary to ensure that increasing penetrations of distributed energy resources are used effectively and do not disrupt the operation of the grid. In this paper, we propose a novel approach to HEMS design based on behavioral control methods, which do not require accurate models or predictions and are very responsive to changing conditions. We develop a proof-of-concept behavioral HEMS controller and show by simulation on an example home energy system that it capable of making context-dependent tradeoffs between goals under challenging conditions.

  6. Validation of the Hot Strip Mill Model

    SciTech Connect (OSTI)

    Richard Shulkosky; David Rosberg; Jerrud Chapman

    2005-03-30

    The Hot Strip Mill Model (HSMM) is an off-line, PC based software originally developed by the University of British Columbia (UBC) and the National Institute of Standards and Technology (NIST) under the AISI/DOE Advanced Process Control Program. The HSMM was developed to predict the temperatures, deformations, microstructure evolution and mechanical properties of steel strip or plate rolled in a hot mill. INTEG process group inc. undertook the current task of enhancing and validating the technology. With the support of 5 North American steel producers, INTEG process group tested and validated the model using actual operating data from the steel plants and enhanced the model to improve prediction results.

  7. LLNL-TR-411072 A Predictive Model

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

    ... This capability reduces the risk to NIF optics and diagnostics from damage due to target ... VI. Acknowledgements Laser spall experiments were conducted at the Jupiter Laser Facility ...

  8. To develop a dynamic model of a collector loop for purpose of improved control of solar heating and cooling. Final technical report. [TRNSYS code

    SciTech Connect (OSTI)

    Herczfeld, P R; Fischl, R

    1980-01-01

    The program objectives were to (1) assess the feasibility of using the TRNSYS computer code for solar heating and cooling control studies and modify it wherever possible, and (2) develop a new dynamic model of the solar collector which reflects the performance of the collector under transient conditions. Also, the sensitivity of the performance of this model to the various system parameters such as collector time constants, flow rates, turn-on and turn-off temperature set points, solar insolation, etc., was studied. Results are presented and discussed. (WHK)

  9. A simple correlation to predict the hydrate quadruple point temperature for LPG mixtures

    SciTech Connect (OSTI)

    Yousif, M.H.

    1997-12-31

    A simple correlation to predict the hydrate upper quadruple point temperature, T{sub Q2B} for liquefied petroleum gas (LPG) mixtures was developed. It was developed for use as a part of a modeling and control system for a LPG pipeline in Russia. For performance reasons, a simple hydrate prediction correlation was required that could be incorporated into the real-time and predictive pipeline simulation models. The operating company required both real time and predictive simulation tools be developed to assist in preventing hydrate blockages while minimizing the use of methanol. In this particular pipeline, LPG fluid moves through the pipeline as a single phase liquid above its bubble point pressure. Because of the very low flow rates, the trace amount of water present in the LPG drops out and creates water pools at low points in the pipeline. The pipeline pressure and seasonal temperatures are conducive for hydrate formation in these pools. Methanol and monoethylene glycol (MEG) are injected in the pipeline to help prevent hydrate formation. The newly developed correlation predicts the hydrate quadruple point temperature using only the composition and the molecular weight of the LPG mixture while retaining an accuracy comparable to the statistical thermodynamic models throughout the range of normal operating conditions.

  10. Thermodynamic Guidelines for the Prediction of Hydrogen Storage...

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

    Thermodynamic guidelines for the prediction of hydrogen storage reactions and their application to destabilized hydride mixtures Hydrogen Storage & Nanoscale Modeling Group Ford ...

  11. Accurate Predictions of Fuel Effects on Combustion and Emissions...

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

    With Detailed Fuel Chemistry Accurate Predictions of Fuel Effects on Combustion and Emissions in Engines Using CFD Simulations With Detailed Fuel Chemistry Accurate fuel models ...

  12. Predicting Stimulation Response Relationships For Engineered Geothermal

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

    Reservoirs | Department of Energy Predicting Stimulation Response Relationships For Engineered Geothermal Reservoirs Predicting Stimulation Response Relationships For Engineered Geothermal Reservoirs Project objectives: Using existing LLNL computer programs, develop realistic models of EGS stimulation-response scenarios involving hydraulic and explosive propagation of tensile/shear fracture systems in hard rock formations where a pre-existing fracture network may be present along with

  13. Predicting the reliability of electronic circuits.

    SciTech Connect (OSTI)

    Loescher, Douglas H.

    2004-06-01

    Procedures to predict the reliability of electrical circuits are discussed. Three cases are introduced and discussed. In Case 1, an analyst predicts the probability of any failure in the intended relations between circuit inputs and circuit outputs. In Case 2, an analyst predicts the probability that specified unintended outputs would occur. In Case 3, an analyst considers coupling between circuits. Logic models are given for the three cases, and sources of failure probabilities of components are mentioned. Methods of analysis are given, software tools are mentioned, and recommendations for presentation and review of results are discussed.

  14. Bursting frequency prediction in turbulent boundary layers

    SciTech Connect (OSTI)

    LIOU,WILLIAM W.; FANG,YICHUNG

    2000-02-01

    The frequencies of the bursting events associated with the streamwise coherent structures of spatially developing incompressible turbulent boundary layers were predicted using global numerical solution of the Orr-Sommerfeld and the vertical vorticity equations of hydrodynamic stability problems. The structures were modeled as wavelike disturbances associated with the turbulent mean flow. The global method developed here involves the use of second and fourth order accurate finite difference formula for the differential equations as well as the boundary conditions. An automated prediction tool, BURFIT, was developed. The predicted resonance frequencies were found to agree very well with previous results using a local shooting technique and measured data.

  15. Modeling

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

    Modeling & Analysis, News, News & Events, Photovoltaic, Renewable Energy, Research & Capabilities, Solar, Solar Newsletter, SunShot, Systems Analysis Sandia Develops Stochastic ...

  16. Modeling

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

    Monte Carlo modeling it was found that for noisy signals with a significant background component, accuracy is improved by fitting the total emission data which includes the...

  17. Modeling

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

    Solar Sandia Labs Releases New Version of PVLib Toolbox Sandia has released version 1.3 of PVLib, its widely used Matlab toolbox for modeling photovoltaic (PV) power ...

  18. Modeling

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

    ... Sandia Will Host PV Bankability Workshop at Solar Power International (SPI) 2013 Computational Modeling & Simulation, Distribution Grid Integration, Energy, Facilities, Grid ...

  19. Modeling

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

    Science and Actuarial Practice" Read More Permalink New Project Is the ACME of Computer Science to Address Climate Change Analysis, Climate, Global Climate & Energy, Modeling, ...

  20. Modeling

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

    Though adequate for modeling mean transport, this approach does not address ... Microphysics such as diffusive transport and chemical kinetics are represented by ...