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Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
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1

Model Predictive Control Wind Turbines  

E-Print Network [OSTI]

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

2

Model Predictive Control for Energy Efficient Buildings  

E-Print Network [OSTI]

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

Ma, Yudong

2012-01-01T23:59:59.000Z

3

Model predictive torque control of a Switched Reluctance Motor  

Science Journals Connector (OSTI)

The strongly nonlinear magnetic characteristic of Switched Reluctance Motors (SRMs) makes their torque control a challenging task. In contrast to standard current-based control schemes, we use Model Predictive Control (MPC) and directly manipulate the ...

Helfried Peyrl; Georgios Papafotiou; Manfred Morari

2009-02-01T23:59:59.000Z

4

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

E-Print Network [OSTI]

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

Zhang, Fumin

5

Model Predictive Control of a Kaibel Distillation Column  

E-Print Network [OSTI]

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

Skogestad, Sigurd

6

Economic and Distributed Model Predictive Control of Nonlinear Systems  

E-Print Network [OSTI]

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

Heidarinejad, Mohsen

2012-01-01T23:59:59.000Z

7

Reduced-order residential home modeling for model predictive control  

Science Journals Connector (OSTI)

Abstract Building simulation software packages such as EnergyPlus are useful energy modeling tools. These software packages, however, are often not amenable to model-based control due to model complexity or difficulties connecting control algorithms with the software. We present a method for automatically generating input/output data from an EnergyPlus residential home model using the OpenStudio software suite. These input/output data are used to create a simple reduced-order model that can be evaluated in fractions of a second. The reduced-order model is implemented in a model predictive controller to minimize the home's electricity costs during summer months in Austin, Texas, USA. The controller optimally precools the home in the morning and turns down or off the air conditioning system in the afternoon. For this example, electricity prices were taken from actual market prices in the Austin area. The optimal precooling strategy given by the model predictive controller reduces peak energy consumption from the air conditioning unit by an average of 70% and reduces operating costs by 60%. Precooling, however, consumes more total energy versus not precooling. Reducing peak energy consumption by 1 kWh results, on average, in an increase of 0.63 kWh in overall energy consumption.

Wesley J. Cole; Kody M. Powell; Elaine T. Hale; Thomas F. Edgar

2014-01-01T23:59:59.000Z

8

Nonlinear Model Predictive Control of Municipal Solid Waste Combustion Plants  

E-Print Network [OSTI]

. Also, the energy that results from waste combustion is often used to produce heat and/or electricityNonlinear Model Predictive Control of Municipal Solid Waste Combustion Plants M. Leskens , R.h.Bosgra@tudelft.nl, p.m.j.vandenhof@tudelft.nl Keywords : nonlinear model predictive control, municipal solid waste

Van den Hof, Paul

9

Interactive software for model predictive control with simultaneous identification  

E-Print Network [OSTI]

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

Echeverria Del Rio, Pablo

2000-01-01T23:59:59.000Z

10

Model Predictive Control for Energy Efficient Buildings  

E-Print Network [OSTI]

control logics in S1 works as follow: condensed water supply temperature (control variables to be optimized by MPC include the chilled water supply temperaturesupply temperatures, and high mass flow rates. This control

Ma, Yudong

2012-01-01T23:59:59.000Z

11

Model Predictive Control for Energy Efficient Buildings  

E-Print Network [OSTI]

automation system “Automated Logic Web Control. ” In theto the campus through the Automated Logics Web Control (ALC)using WebCTRL developed by Automated Logic Corporation. The

Ma, Yudong

2012-01-01T23:59:59.000Z

12

Model Predictive Control for Energy Efficient Buildings  

E-Print Network [OSTI]

feedback control. Green buildings are expected to maintainHigh-performance green buildings are expected to maintain

Ma, Yudong

2012-01-01T23:59:59.000Z

13

Adaptive model predictive process control using neural networks  

DOE Patents [OSTI]

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.

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

1997-01-01T23:59:59.000Z

14

Adaptive model predictive process control using neural networks  

DOE Patents [OSTI]

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.

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

1997-08-19T23:59:59.000Z

15

Model Predictive Control of Integrated Gasification Combined Cycle Power Plants  

SciTech Connect (OSTI)

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.

B. Wayne Bequette; Priyadarshi Mahapatra

2010-08-31T23:59:59.000Z

16

Model Predictive Control for the Operation of Building Cooling Systems  

E-Print Network [OSTI]

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

Ma, Yudong

2010-01-01T23:59:59.000Z

17

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

E-Print Network [OSTI]

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

18

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

E-Print Network [OSTI]

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

Huang, Yinlun

19

Selecting Building Predictive Control Based on Model Uncertainty  

E-Print Network [OSTI]

S. Pr´?vara et al. “Building Modeling as a Crucial Part forThe details of building thermal modeling and estimation ofModeling and Optimal Control Algorithm Design for HVAC Systems in Energy Efficient Buildings”.

Maasoumy, Mehdi

2014-01-01T23:59:59.000Z

20

Explicit-Ready Nonlinear Model Predictive Control for Turbocharged Spark-Ignited Engines  

E-Print Network [OSTI]

Explicit-Ready Nonlinear Model Predictive Control for Turbocharged Spark- Ignited Engines J. El with saturated actuators. In this context, the need for model-based control laws is greater than ever with saturated actuators. In this paper, we evaluate the benefits of a nonlinear model predictive control (NMPC

Paris-Sud XI, Université de

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

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

E-Print Network [OSTI]

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

Alaniz, Abran, 1980-

2004-01-01T23:59:59.000Z

22

Interval Methods for Sensitivity-Based Model-Predictive Control of  

E-Print Network [OSTI]

Interval Methods for Sensitivity-Based Model-Predictive Control of Solid Oxide Fuel Cell Systems and experiment for the thermal subprocess of a high-temperature solid oxide fuel cell system. Keywords: Interval analysis, model-predictive control, sensitivity analysis, tracking control, solid oxide fuel cells AMS

Kearfott, R. Baker

23

Model predictive controller design for the dynamic positioning system of a semi-submersible platform  

Science Journals Connector (OSTI)

This paper researches how to apply the advanced control technology of model predictive control (MPC) to the design of the dynamic positioning system (DPS) of a semi-submersible platform. First, a linear low-frequ...

Hongli Chen; Lei Wan; Fang Wang…

2012-09-01T23:59:59.000Z

24

PREDICTIVE MODELS  

SciTech Connect (OSTI)

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

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

1988-10-01T23:59:59.000Z

25

Model Predictive Control for Starvation Prevention in a Hybrid Fuel Cell System1  

E-Print Network [OSTI]

voltage, a control system is necessary for maintaining optimal temperature, membrane humidity and pressure: Schematic of the fuel cell stack and air supply control sys- tem. The fuel cell stack consists of 350 cellsModel Predictive Control for Starvation Prevention in a Hybrid Fuel Cell System1 Ardalan Vahidi 2

Stefanopoulou, Anna

26

Decentralized model predictive control of a multiple evaporator HVAC system  

E-Print Network [OSTI]

Vapor compression cooling systems are the primary method used for refrigeration and air conditioning, and as such are a major component of household and commercial building energy consumption. Application of advanced control techniques...

Elliott, Matthew Stuart

2009-05-15T23:59:59.000Z

27

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

E-Print Network [OSTI]

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

Avci, Mesut

2013-01-01T23:59:59.000Z

28

Putting Nonlinear Model Predictive Control Bjarne A. Foss1  

E-Print Network [OSTI]

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

Foss, Bjarne A.

29

Efficiency-Optimized Model Predictive Torque Control for IPMSM  

E-Print Network [OSTI]

, Joachim B¨ocker 3 Power Electronics and Electrical Drives, Paderborn University, D-33095 Paderborn of the efficiency of an electrical drive train can be shown. Thus, the DT-MPC provides maximum torque per current as well as efficiency [1]. To fully exploid the performance of an electric drive, adequate control

Paderborn, Universität

30

PREDICTIVE MODELS  

SciTech Connect (OSTI)

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

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

1986-12-01T23:59:59.000Z

31

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

E-Print Network [OSTI]

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

Johansson, Karl Henrik

32

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

E-Print Network [OSTI]

................................................................... 20 3.2 ARX model structure ................................................................................. 21 3.3 One-step-ahead prediction of accumulation signal in 3% CLR network using ARX model designed by Bhattacharya[9...] ........................... 27 3.4 One-step-ahead estimation of accumulation signal in 3% CLR network using the proposed ARX model. ......................................... 28 4.1 Schematic of MPC strategy...

Duong, Thien Chi

2011-02-22T23:59:59.000Z

33

Development and Testing of Model Predictive Control for a Campus Chilled  

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

Development and Testing of Model Predictive Control for a Campus Chilled Development and Testing of Model Predictive Control for a Campus Chilled Water Plant with Thermal Storage Title Development and Testing of Model Predictive Control for a Campus Chilled Water Plant with Thermal Storage Publication Type Conference Proceedings Year of Publication 2010 Authors Coffey, Brian, Philip Haves, Michael Wetter, Brandon Hencey, Francesco Borrelli, Yudong Ma, and Sorin Bengea Conference Name 2010 ACEEE Summer Study on Energy Efficiency in Buildings Date Published 2010 Publisher Omnipress Conference Location Asilomar, California, USA ISBN 0-918249-60-0 Abstract A Model Predictive Control (MPC) implementation was developed for a university campus chilled water plant. The 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. A detailed model of the chilled water plant and simplified models of the campus buildings 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 dynamic model of the chilled water storage tank was also developed and calibrated. A semi-empirical model was 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 MPC 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 paper describes the development and testing of the MPC implementation and discusses lessons learned and next steps in further research

34

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

SciTech Connect (OSTI)

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.

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

2013-04-09T23:59:59.000Z

35

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

SciTech Connect (OSTI)

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.

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

2014-02-01T23:59:59.000Z

36

Feedforward artificial neural network to improve model predictive control in biological processes  

Science Journals Connector (OSTI)

Artificial neural networks (ANNs) offer the versatility of being able to model the dynamics of a biosystem without requiring a phenomenological model. In addition, model predictive control (MPC) is a member of advanced discrete-time process control algorithms. The recent developments in the biotechnology due to MPC utilising the capability of ANN make the practical application of non-linear process control strategies a reality. This paper reviews the recent enhancement and applications of MPC in various biochemical processes using feedforward artificial neural networks which is also known as neural predictive control. The capability of neural predictive control to handle the common problems associated with biochemical processes, namely optimisation of objective function, optimisation of dynamic behaviour of the system, control of ill-defined non-linear systems, improving the computational efficiency of the strategy, disturbance rejection ability and evaluating the control effectiveness are discussed. The review clearly indicates that enormous work has been carried out involving dynamic behaviour of the bioreactor system which is analysed and optimised revealing that feedforward neural network has evolved as a good bioreactor neuro-controller.

Senthil Kumar Arumugasamy; Zainal Ahmad

2011-01-01T23:59:59.000Z

37

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

E-Print Network [OSTI]

Scenario-Based Fault-Tolerant Model Predictive Control for Diesel-Electric Marine Power Plant where diesel gener- ator sets (a diesel engine connected to a generator) produce electrical power, which Email: torstein.bo@itk.ntnu.no, tor.arne.johansen@itk.ntnu.no Abstract--Diesel-electric propulsion

Johansen, Tor Arne

38

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

E-Print Network [OSTI]

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

Grossmann, Ignacio E.

39

OPERATOR INTERACTION WITH MODEL-BASED PREDICTIVE CONTROLLERS IN PETROCHEMICAL REFINING  

E-Print Network [OSTI]

. These differences in level may explain why we observed refinery operators asking questions of the automation not. This could also explain why we did not observe refinery operators having difficultyOPERATOR INTERACTION WITH MODEL-BASED PREDICTIVE CONTROLLERS IN PETROCHEMICAL REFINING Greg A

Virginia, University of

40

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

E-Print Network [OSTI]

Energy Savings Through Application of Model Predictive Control to an Air Separation Facility Thomas C. Hanson PauiF. Scharf Manager Senior Engineering Associate Process Development Process Control Technology Praxair, Inc., Tonawanda, New York...TM based operator interface was developed by Praxair to make the system usable in our operations. 174 ESL-IE-96-04-24 Proceedings from the Eighteenth Industrial Energy Technology Conference, Houston, TX, April 17-18, 1996 Benefits overview MPC has...

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

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Artificial Neural Network Estimator Design for the Inferential Model Predictive Control of an Industrial Distillation Column  

Science Journals Connector (OSTI)

The ANN architecture is a multilayer perceptron (MLP), which is a typical feed-forward (layered) neural network.2 A collection of neurons connected to each other forms the artificial neural network. ... It is shown that the how artificial neural networks can model the column, and demonstrated that the network model is as good or better than a simplified first principles model when used for model predictive control. ... A dynamic, nonlinear, multi-input multi-output application using the recurrent dynamic neuron network (RDNN) model is presented for a two-by-two distn. ...

Alm?la Bahar; Canan Özgen; Kemal Leblebicio?lu; U?ur Hal?c?

2004-08-12T23:59:59.000Z

42

A novel exergy-event based model predictive control strategy for energy saving  

Science Journals Connector (OSTI)

Abstract Industrial processes are among the biggest energy consumers and also the highest energy-wasting fields and many applied methods have been proposed to save energy more in these processes. The main purpose of event-based control is to reduce the computing load and communication efforts only after an event occurs which could save energy. Energy consumption and control performance are major challenges in event-based control. Exergy is the basic criterion to analyze a process in terms of the energy associated with control performance. MPC a widely used in industry, is utilized to solve an optimal control problem based on control performance aiming to save more energy. Moreover, MPC enables the controller to cope explicitly with MIMO plants and constraints such as state constraints and actuator constraints. The exergy-event based strategy under the general model predictive control (MPC) framework from viewpoint of energy saving is investigated in this paper. It will be shown that the proposed architecture is guaranteed to reduce the energy and exergy losses, the computational burden and communication effort of the whole system.

Mohsen Hadian; M.H. Asheri; Karim Salahshoor

2014-01-01T23:59:59.000Z

43

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

E-Print Network [OSTI]

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

Joshi, Praveen Sudhakar

2012-06-07T23:59:59.000Z

44

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

E-Print Network [OSTI]

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

Hespanha, João Pedro

45

Short-term production optimization of offshore oil and gas production using nonlinear model predictive control  

Science Journals Connector (OSTI)

The topic of this paper is the application of nonlinear model predictive control (NMPC) for optimizing control of an offshore oil and gas production facility. Of particular interest is the use of NMPC for direct short-term production optimization, where two methods for (one-layer) production optimization in NMPC are investigated. The first method is the unreachable setpoints method where an unreachable setpoint is used in order to maximize oil production. The ideas from this method are combined with the exact penalty function for soft constraints in a second method, named infeasible soft-constraints. Both methods can be implemented within standard NMPC software tools. The case-study first looks into the use of NMPC for ‘conventional’ pressure control, where disturbance rejection of time-varying disturbances (caused, e.g., by the ‘slugging’ phenomenon) is an issue. Then the above two methods for production optimization are employed, where both methods find the economically optimal operating point. Two different types of reservoir models are studied, using rate-independent and rate-dependent gas/oil ratios. These models lead to different types of optimums. The relative merits of the two methods for production optimization, and advantages of the two one-layer approaches compared to a two-layer structure, are discussed.

Anders Willersrud; Lars Imsland; Svein Olav Hauger; Pål Kittilsen

2013-01-01T23:59:59.000Z

46

Real-Time Control of Full Actuated Biped Robot Based on Nonlinear Model Predictive Control  

Science Journals Connector (OSTI)

A trajectory free walking control scheme was proposed for actuated biped robot with the NMPC method in order to carry out real-time gait programming. The basic feature in the proposed strategy is to use iterative on-line optimization approach to compute ... Keywords: NMPC, biped robot, real-time gait programming

Zhibin Zhu; Yan Wang; Xinglin Chen

2008-10-01T23:59:59.000Z

47

Embedded Model Predictive Control for an Electric Submersible Pump on a Programmable Logic Controller*  

E-Print Network [OSTI]

]. Though MPC is very common in the onshore petroleum industry, it is not common offshore, where safety, offshore equipment tend to be of a considerable smaller scale, leading to much faster dynamics. Better control performance may be possible to achieve by letting fast MPC optimize the plant directly, bypassing

Johansen, Tor Arne

48

Handling model uncertainty in model predictive control for energy efficient buildings  

E-Print Network [OSTI]

to apply to other building modeling practices. 2. Wemodel 3.1. Mathematical modeling Building models proposed inMore details of building thermal modeling and estimation of

Maasoumy, Mehdi; Razmara, M; Shahbakhti, M; Sangiovanni-Vincentelli, Alberto

2014-01-01T23:59:59.000Z

49

Artificial Neural Networks Modelling of PID and Model Predictive Controlled Waste Water Treatment Plant Based on the Benchmark Simulation Model No.1  

Science Journals Connector (OSTI)

The paper presents techniques for the design and training of Artificial Neural Networks (ANN) models for the dynamic simulation of the controlled Benchmark Simulation Model no. 1 (BSM1) Waste Water Treatment Plant (WWTP). The developed ANN model of the WWTP and its associated control system is used for the assessment of the plant behaviour in integrated urban waste water system simulations. Both embedded PID (Proportional-Integral-Derivative) control and Model Predictive Control (MPC) structures for the WWTP are investigated. The control of the Dissolved Oxygen (DO) mass concentration in the aerated reactors and nitrate (NO) mass concentration in the anoxic compartments are presented. The ANN based simulators reveal good accuracy for predicting important process variables and an important reduction of the simulation time, compared to the first principle WWTP simulator.

Vasile-Mircea Cristea; Cristian Pop; Paul Serban Agachi

2009-01-01T23:59:59.000Z

50

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

E-Print Network [OSTI]

inputs. The idea of modeling building thermal behavior usingThe detail of building thermal modeling is pre- sented in [Modeling and optimal control algorithm design for hvac systems in energy efficient buildings,’’

Maasoumy, Mehdi; Sangiovanni-Vincentelli, Alberto

2012-01-01T23:59:59.000Z

51

Handling model uncertainty in model predictive control for energy efficient buildings  

E-Print Network [OSTI]

trol for the operation of building cooling systems, IEEEK. Wirth, Energy ef?cient building climate control usingSagerschnig, E. Z ? á?ceková, Building [8] J. Prí vara, S.

Maasoumy, Mehdi; Razmara, M; Shahbakhti, M; Sangiovanni-Vincentelli, Alberto

2014-01-01T23:59:59.000Z

52

Model predictive control of power plant superheater comparison of multi model and nonlinear approaches  

E-Print Network [OSTI]

, the responses to large load demand changes (between 50 and 100% of boiler rated power) typical of today variables and control loops is high and many sources of nonlinearity and interactions are present. This increases the plant efficiency because efficiency is proportional to the superheated steam temperature

Johansen, Tor Arne

53

Supervisory hybrid model predictive control for voltage stability of power networks  

E-Print Network [OSTI]

on the predicted behavior of a model featuring hybrid dynamics of the loads and the generation system. I (via solar energy or wind energy installations) will start to feed electricity into the network [2 continuous dynamics and discrete events, i.e., power systems exhibit hybrid behavior. Components

Paris-Sud XI, Université de

54

Embedded Model Predictive Control on a PLC Using a Primal-Dual First-Order Method for a Subsea Separation Process  

E-Print Network [OSTI]

Embedded Model Predictive Control on a PLC Using a Primal-Dual First-Order Method for a Subsea. Eikrem3 Abstract-- The results of a PLC implementation of embedded Model Predictive Control (MPC to underline its potential. The embedded MPC was implemented on the ABB AC500 PLC, and its performance

Johansen, Tor Arne

55

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

E-Print Network [OSTI]

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

Haves, Phillip

2010-01-01T23:59:59.000Z

56

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

E-Print Network [OSTI]

Figure 2.33: Supply Air Temperature control error, 15?water supply temperature, which is a control  variable, so the feedback  control.   The  supply  air  temperature  is 

Haves, Phillip

2010-01-01T23:59:59.000Z

57

Robust nonlinear model predictive control for nuclear power plants in load following operations with bounded xenon oscillations  

Science Journals Connector (OSTI)

One of the important operations in nuclear power plants is load-following in which imbalance of axial power distribution induces xenon oscillations. These oscillations must be maintained within acceptable limits otherwise the nuclear power plant could become unstable. Therefore, bounded xenon oscillation considered to be a constraint for the load-following operation. In this paper, a robust nonlinear model predictive control for the load-following operation problem is proposed that ensures xenon oscillations are kept bounded within acceptable limits. The proposed controller uses constant axial offset (AO) strategy to maintain xenon oscillations to be bounded. The constant AO is a robust state constraint for load-following problem. The controller imposes restricted state constraints on the predicted trajectory during optimization which guarantees robust satisfaction of state constraints without restoring to a min–max optimization problem. Simulation results show that the proposed controller for the load-following operation is so effective so that the xenon oscillations kept bounded in the given region.

H. Eliasi; M.B. Menhaj; H. Davilu

2011-01-01T23:59:59.000Z

58

ASSESSMENT OF ECONOMIC PERFORMANCE OF MODEL PREDICTIVE  

E-Print Network [OSTI]

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

Huang, Biao

59

Model Predictive Control from Signal Temporal Logic Specifications: A Case Study   

E-Print Network [OSTI]

regulation services to the power grid. We then show how thestudy using a simpli?ed power grid model with un- certainarea. More details on the power grid model can be found in [

Raman, Vasumathi; Maasoumy, Mehdi; Donzé, Alexandre

2014-01-01T23:59:59.000Z

60

Real-Time Implementation of an Online Model Predictive Control for IPMSM Using Parallel  

E-Print Network [OSTI]

on FPGA Michael Leuer, Joachim B¨ocker Power Electronics and Electrical Drives Paderborn University D [1]. To fully exploid the performance of an electric drive, adequate control is essential, as they are common in the electric drive technology, have to be faced. However, there are new MPC approaches which

Paderborn, Universität

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Model prediction-based approach to fault-tolerant control with applications  

Science Journals Connector (OSTI)

......manipulated inputs for the first reactor, and using the heat input...manipulated inputs for the second reactor. Operation at the unstable...Self-repairing flight control system reliability and maintainability program...tolerance techniques in the analysis and evaluation of computing......

Magdi S. Mahmoud; Haris M. Khalid

2014-06-01T23:59:59.000Z

62

Interval-Based Model-Predictive Control for Uncertain Dynamic Systems with Actuator Constraints  

E-Print Network [OSTI]

and for the control of the thermal behavior of high-temperature fuel cell stacks. This application scenario uncertainty due to limited measurement facilities in the interior of the fuel cell stack can be expressed performance by the minimization of suitable cost functions in real time. These criteria typically take

Appelrath, Hans-Jürgen

63

Model Predictive Control of Regulation Services from Commercial Buildings to the Smart Grid  

E-Print Network [OSTI]

regulation service to the power grid using at-scalesimplified model of the power grid with uncertain demand andsuch resources into the power grid in a large scale as

Maasoumy, Mehdi

2014-01-01T23:59:59.000Z

64

Application of Multivariable Model Predictive Advanced Control for a 2×310T/H CFB Boiler Unit  

Science Journals Connector (OSTI)

When a CFB boiler is in automatic control, there are ... non-linear combustion model, based on the CFB combustion characteristics of bed fuel inventory, heating values, bed lime inventory and consumption. CFB adv...

Zhao Weijie; Dai Zongllao; Gou Rong…

2010-01-01T23:59:59.000Z

65

Fuzzy predictive control of district heating network  

Science Journals Connector (OSTI)

This paper presents a concept for controlling the supply temperature in district heating networks (DHNs) using model predictive control. Due to the inherent non-linearity in the response characteristics caused by varying flow rates the use of fuzzy dynamic matrix control (DMC) is proposed. The fuzzy partitions of the local finite impulse response (FIR) models are constructed by an axis-orthogonal, incremental partitioning scheme. Furthermore, a novel approach for determining future fuzzy trajectory based on heat load forecasts is implemented. It is demonstrated that the fuzzy DMC performs well for the case study considered. In addition, different set point strategies are applied and the results are evaluated with respect to operational costs. In this context it is shown that the trade-off between pumping and heat loss cost plays an important role in minimising overall costs.

S. Grosswindhager; M. Kozek; Andreas Voigt; Lukas Haffner

2013-01-01T23:59:59.000Z

66

Validation of a zero-dimensional model for prediction of \\{NOx\\} and engine performance for electronically controlled marine two-stroke diesel engines  

Science Journals Connector (OSTI)

The aim of this paper is to derive a methodology suitable for energy system analysis for predicting the performance and \\{NOx\\} emissions of marine low speed diesel engines. The paper describes a zero-dimensional model, evaluating the engine performance by means of an energy balance and a two zone combustion model using ideal gas law equations over a complete crank cycle. The combustion process is divided into intervals, and the product composition and flame temperature are calculated in each interval. The \\{NOx\\} emissions are predicted using the extended Zeldovich mechanism. The model is validated using experimental data from two MAN B&W engines; one case being data subject to engine parameter changes corresponding to simulating an electronically controlled engine; the second case providing data covering almost all model input and output parameters. The first case of validation suggests that the model can predict specific fuel oil consumption and \\{NOx\\} emissions within the 95% confidence intervals given by the experimental measurements. The second validation confirms the capability of the model to match measured engine output parameters based on measured engine input parameters with a maximum 5% deviation.

Fabio Scappin; Sigurður H. Stefansson; Fredrik Haglind; Anders Andreasen; Ulrik Larsen

2012-01-01T23:59:59.000Z

67

PREDICTIVE MODELS. Enhanced Oil Recovery Model  

SciTech Connect (OSTI)

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

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

1992-02-26T23:59:59.000Z

68

Distributed Predictive Control and Estimation for Systems with Information  

E-Print Network [OSTI]

constraints and a stationary LQG (Linear Quadratic Gaussian) control law is presented based on the model control and estimation law is demonstrated through a numerical simulation of smart grid. KeywordsDistributed Predictive Control and Estimation for Systems with Information Structures Exemplified

69

Integrated Predictive Demand Response Controller Research Project |  

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

Predictive Demand Response Predictive Demand Response Controller Research Project Integrated Predictive Demand Response Controller Research Project The U.S. Department of Energy (DOE) is currently conducting research into integrated predictive demand response (IPDR) controllers. The project team will attempt to design an IPDR controller so that it can be used in new or existing buildings or in collections of buildings. In the case of collections of buildings, they may be colocated on a single campus or remotely located as long as they are served by a single utility or independent service operator. Project Description This project seeks to perform the necessary applied research, development, and testing to provide a communications interface using industry standard open protocols and emerging National Institute of Standards and Technology

70

Journal Article: Simplified Protein Models: Predicting Folding...  

Office of Scientific and Technical Information (OSTI)

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

71

Model Predictive Control of a Nonlinear Large-Scale Process Network Used in the Production of Vinyl Acetate  

E-Print Network [OSTI]

both dynamic economic optimization and process control isand R. Amrit. Optimizing process economic performance usingOptimizing chemical processes from an economic perspective

Tu, TungSheng

2013-01-01T23:59:59.000Z

72

Stimulation Prediction Models | Open Energy Information  

Open Energy Info (EERE)

Stimulation Prediction Models Stimulation Prediction Models Jump to: navigation, search Geothermal ARRA Funded Projects for Stimulation Prediction Models Loading map... {"format":"googlemaps3","type":"ROADMAP","types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"limit":200,"offset":0,"link":"all","sort":[""],"order":[],"headers":"show","mainlabel":"","intro":"","outro":"","searchlabel":"\u2026 further results","default":"","geoservice":"google","zoom":false,"width":"600px","height":"350px","centre":false,"layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","icon":"","visitedicon":"","forceshow":true,"showtitle":true,"hidenamespace":false,"template":false,"title":"","label":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"locations":[{"text":"

73

PREDICTIVE MODELS. Enhanced Oil Recovery Model  

SciTech Connect (OSTI)

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

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

1992-02-26T23:59:59.000Z

74

Application of linear multiple model predictive control (MMPC) framework towards dynamic maximazation of oxygen yield in an elevated-pressure air separation unit  

SciTech Connect (OSTI)

In a typical air separation unit (ASU) utilizing either a simple gaseous oxygen (GOX) cycle or a pumped liquid oxygen (PLOX) cycle, the flowrate of liquid nitrogen (LN2) stream connecting high-pressure and low-pressure ASU columns plays an important role in the total oxygen yield. It has been observed that this yield reaches a maximum at a certain optimal flowrate of LN2 stream. At nominal full-load operation, the flowrate of LN2 stream is maintained near this optimum value, whereas at part-load conditions this flowrate is typically modified in proportion with the load-change (oxygen demand) through a ratio/feed-forward controller. Due to nonlinearity in the entire ASU process, the ratio-modified LN2 flowrate does not guarantee an optimal oxygen yield at part-load conditions. This is further exacerbated when process disturbances in form of “cold-box” heat-leaks enter the system. To address this problem of dynamically maximizing the oxygen yield while the ASU undergoes a load-change and/or a process disturbance, a multiple model predictive control (MMPC) algorithm is proposed. This approach has been used in previous studies to handle large ramp-rates of oxygen demand posed by the gasifier in an IGCC plant. In this study, the proposed algorithm uses linear step-response “blackbox” models surrounding the operating points corresponding to maximum oxygen yield points at different loads. It has been shown that at any operating point of the ASU, the MMPC algorithm, through model-weight calculation based on plant measurements, naturally and continuously selects the dominant model(s) corresponding to the current plant state, while making control-move decisions that approach the maximum oxygen yield point. This dynamically facilitates less energy consumption in form of compressed feed-air compared to a simple ratio control during load-swings. In addition, since a linear optimization problem is solved at each time step, the approach involves much less computational cost compared to a firstprinciple based nonlinear MPC. Introduction

Mahapatra, P.; Zitney, S.; Bequette, B. Wayne

2012-01-01T23:59:59.000Z

75

Hierarchical predictive control of integrated wastewater treatment systems  

Science Journals Connector (OSTI)

The paper proposes an approach to designing the control structure and algorithms for optimising control of integrated wastewater treatment plant-sewer systems (IWWTS) under a full range of disturbance inputs. The optimised control of IWWTS allows for significant cost savings, fulfilling the effluent discharge limits over a long period and maintaining the system in sustainable operation. Due to the specific features of a wastewater system a hierarchical control structure is applied. The functional decomposition leads to three control layers: supervisory, optimising and follow-up. A temporal decomposition that is applied in order to efficiently accommodate the system's multiple time scales leads to further decomposition of the optimising control layer into three control sublayers: slow, medium, and fast. An extended Kalman Filter is used to carry out an estimation of needed but not measured plant states in real time. The robustly feasible model predictive controller produces manipulated variable trajectories based on a dedicated grey box (GB) model of the biological processes and drawing its physical reality from the well known \\{ASM2d\\} model. The GB model parameters are dependant on the plant operating point and therefore are continuously estimated. As it is impossible to efficiently control the plant under all influent conditions that may occur by using one universal control strategy, different control strategies are designed. Recently developed mechanisms for soft switching between the MPC control strategies are applied in order to smooth the state and control transient processes during the switching. The methodologies and algorithms proposed in the paper are validated by simulation based on real data records from a wastewater system located in Kartuzy, northern Poland. The control system was implemented at the case-study site to generate in real time the control actions that were assessed by the plant operators and verified by simulation based on a calibrated plant model.

M.A. Brdys; M. Grochowski; T. Gminski; K. Konarczak; M. Drewa

2008-01-01T23:59:59.000Z

76

Productivity prediction model based on Bayesian analysis and productivity console  

E-Print Network [OSTI]

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

Yun, Seok Jun

2005-08-29T23:59:59.000Z

77

A Generalized Predictive Force Controller for electropneumatic cylinders  

E-Print Network [OSTI]

and the number of control parameters is very reduced: the weighting coefficient and the prediction horizon and the valve are not taken into account. No studies of predictive force control of pneumatic actuators have

Paris-Sud XI, Université de

78

Predictive Power Control of Doubly-Fed Induction Generator for Wave Energy Converters  

E-Print Network [OSTI]

the Doubly- fed induction generator (DFIG). This paper deals then with a model-based predictive power control of a DFIG-based Wave Energy Converter (WEC). In the proposed control approach, the predicted output power was calculated using a DFIG linearized state-space model. The DFIG-based WEC power tracking performances further

Paris-Sud XI, Université de

79

Model accurately predicts directional borehole trajectory  

SciTech Connect (OSTI)

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

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

1994-08-29T23:59:59.000Z

80

Including Ocean Model Uncertainties in Climate Predictions  

E-Print Network [OSTI]

Including Ocean Model Uncertainties in Climate Predictions Chris Brierley, Alan Thorpe, Mat Collins's to perform the integrations Currently uses a `slab' ocean #12;An Ocean Model Required to accurately model transient behaviour Will have its own uncertainties Requires even more computing power Create new models

Jones, Peter JS

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

Predictive Models of Forest Dynamics  

Science Journals Connector (OSTI)

...currently highly uncertain (Fig. 1), making vegetation dynamics one of the largest sources of uncertainty in Earth system models. Reducing this uncertainty requires work on several fronts. For example, physiological parameters need to be...

Drew Purves; Stephen Pacala

2008-06-13T23:59:59.000Z

82

Landslide Prediction Based on Neural Network Modelling  

Science Journals Connector (OSTI)

The opportunities of artificial neural networks model application to landslide forecasting are considered, namely prediction of landslide types and parameters of landslide damage area. The data collected by ob...

Yuri Aleshin; Isakbek Torgoev

2013-01-01T23:59:59.000Z

83

Enhancing feedback process scheduling via a predictive control approach  

E-Print Network [OSTI]

Enhancing feedback process scheduling via a predictive control approach Alessandro Vittorio the application possibilities at an affordable additional cost. Keywords: feedback scheduling; control that preemptive process schedulers in multitasking operating systems can be viewed, and above all designed

Como, Giacomo

84

Predictive wavefront control for Adaptive Optics with arbitrary control loop delays  

SciTech Connect (OSTI)

We present a modification of the closed-loop state space model for AO control which allows delays that are a non-integer multiple of the system frame rate. We derive the new forms of the Predictive Fourier Control Kalman filters for arbitrary delays and show that they are linear combinations of the whole-frame delay terms. This structure of the controller is independent of the delay. System stability margins and residual error variance both transition gracefully between integer-frame delays.

Poyneer, L A; Veran, J

2007-10-30T23:59:59.000Z

85

Fuzzy predictive control for nitrogen removal in biological wastewater treatment  

E-Print Network [OSTI]

Fuzzy predictive control for nitrogen removal in biological wastewater treatment S. Marsili wastewater is too low, full denitrification is difficult to obtain and an additional source of organic carbon predictive control; wastewater treatment plant Introduction The problem of improving the nitrogen removal

86

Design and Certification of Industrial Predictive Controllers  

E-Print Network [OSTI]

.g. a car moving over a terrain with changing slopes. Many others can be viewed as a composition of interacting subsystems like harvester machines, wind mills etc. Further in this thesis, practical solutions for controlling such nonlinear and distributed...

Dutta, Abhishek

2014-09-24T23:59:59.000Z

87

Development of an Ocean Model Adjoint for Decadal Prediction | Argonne  

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

Development of an Ocean Model Adjoint for Decadal Prediction Development of an Ocean Model Adjoint for Decadal Prediction Development of an Ocean Model Adjoint for Decadal Prediction This project will develop an adjoint of the Parallel Ocean Program (POP; version 2.0.1) using automatic differentiation (AD) techniques. We have already had success with AD on sea ice models and will use this knowledge with POP. It is now unequivocal that the Earth's climate system is warming. The most recent IPCC assessment concludes that the increased temperatures in the latter 20th century are very likely due to anthropogenic greenhouse gases, and continued greenhouse emissions will likely result in even larger increases during the 21st century. Even if controls could be put on greenhouse emissions immediately, there is still some climate change that

88

The evolutionary development of roughness prediction models  

Science Journals Connector (OSTI)

The vigorous expansion of wind energy power generation over the last decade has also entailed innovative improvements to surface roughness prediction models applied to high-torque milling operations. Artificial neural networks are the most widely used ... Keywords: Dimensionality reduction, Genetic algorithm, High-torque milling, Surface roughness

Maciej Grzenda; Andres Bustillo

2013-05-01T23:59:59.000Z

89

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

E-Print Network [OSTI]

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

Paris-Sud XI, Université de

90

Quantitative Quality Management through Defect Prediction and Statistical Process Control  

E-Print Network [OSTI]

Quantitative Quality Management through Defect Prediction and Statistical Process Control Pankaj: To produce high quality software, the final software should have as few defects as possible. The task of quality management in a software project is to plan suitable quality control activities, and properly

Jalote, Pankaj

91

BEHAVIOR PREDICTION FOR DECISION AND CONTROL IN COGNITIVE AUTONOMOUS SYSTEMS  

E-Print Network [OSTI]

BEHAVIOR PREDICTION FOR DECISION AND CONTROL IN COGNITIVE AUTONOMOUS SYSTEMS ASOK RAY*, SHASHI for decision and control in cognitive autonomous systems. The objective is to coordinate human­machine collaboration such that human operators can assess and enable autonomous systems to utilize their experi- ential

Ray, Asok

92

Coordinating Regulation and Demand Response in Electric Power Grids: Direct and Price-Based Tracking Using Multirate Economic Model Predictive Control  

Science Journals Connector (OSTI)

?Based on “Coordinating regulation and demand response in electric power grids using multirate model...

Haitham Hindi; Daniel Greene…

2012-01-01T23:59:59.000Z

93

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

E-Print Network [OSTI]

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

Causa, Javier

2008-01-01T23:59:59.000Z

94

Hybrid Modeling and Control of a Hydroelectric Power Plant  

E-Print Network [OSTI]

Hybrid Modeling and Control of a Hydroelectric Power Plant Giancarlo Ferrari-Trecate, Domenico,mignone,castagnoli,morari}@aut.ee.ethz.ch Abstract In this work we present the model of a hydroelectric power plant in the framework of Mixed Logic with a model predictive control scheme. 1 Introduction The outflow control for hydroelectric power plants

Ferrari-Trecate, Giancarlo

95

Predictive control of a real-world Diesel engine using an extended online active set strategy  

Science Journals Connector (OSTI)

In order to meet tight emission limits Diesel engines are nowadays equipped with additional hardware components like an exhaust gas recirculation valve and a variable geometry turbocharger. Conventional engine control units use two SISO control loops to regulate the exhaust gas recirculation valve and the variable geometry turbocharger, although their effects are highly coupled. Moreover, these actuators are subject to physical constraints which seems to make an advanced control approach like model predictive control (MPC) the method of choice. In order to deal with MPC sampling times in the order of milliseconds, we employed an extension of the recently developed online active set strategy for controlling a real-world Diesel engine in a closed-loop manner. The results show that predictive engine control based on online optimisation can be accomplished in real-time – even on cheap controller hardware – and leads to increased controller performance.

Hans Joachim Ferreau; Peter Ortner; Peter Langthaler; Luigi del Re; Moritz Diehl

2007-01-01T23:59:59.000Z

96

Bulk Power System Dynamics and Control VI, August 22-27, 2004, Cortina d'Ampezzo, Italy Voltage Stability Enhancement via Model Predictive  

E-Print Network [OSTI]

Bulk Power System Dynamics and Control VI, August 22-27, 2004, Cortina d'Ampezzo, Italy Voltage of the North American power system in August 2003 could have been avoided by tripping a relatively small amount be more palatable. Recent advances in communications and computer systems facilitate such non-disruptive

Hiskens, Ian A.

97

Development and Validation of an Advanced Stimulation Prediction Model for  

Open Energy Info (EERE)

Validation of an Advanced Stimulation Prediction Model for Validation of an Advanced Stimulation Prediction Model for Enhanced Geothermal Systems Geothermal Project Jump to: navigation, search Last modified on July 22, 2011. Project Title Development and Validation of an Advanced Stimulation Prediction Model for Enhanced Geothermal Systems Project Type / Topic 1 Recovery Act: Enhanced Geothermal Systems Component Research and Development/Analysis Project Type / Topic 2 Stimulation Prediction Models Project Description The proposal is in response to DOE FOA DE-PS36-08GO99018/DE-FOA-0000075, specifically: the Topic Area: Stimulation Prediction Models - "To develop and validate models to predict a reservoir's response to stimulation and/or to quantitatively compare existing stimulation prediction models," and the Target Specification: "Development of stimulation prediction models capable of accurately predicting the location, spacing, orientation, and flow properties of created fractures."

98

Predicting Operator Capacity for Supervisory Control of Multiple UAVs  

E-Print Network [OSTI]

Predicting Operator Capacity for Supervisory Control of Multiple UAVs M.L. Cummings, C. E. Nehme, J, uninhabited (also known as unmanned) ae- rial vehicles (UAVs) have become indispensable assets to militarized forces. UAVs require human guidance to varying degrees and often through several operators. However

Cummings, Mary "Missy"

99

On the Predictive Uncertainty of a Distributed Hydrologic Model  

E-Print Network [OSTI]

We use models to simulate the real world mainly for prediction purposes. However, since any model is a simplification of reality, there remains a great deal of uncertainty even after the calibration of model parameters. The model’s identifiability...

Cho, Huidae

2009-05-15T23:59:59.000Z

100

LLNL-TR-411072 A Predictive Model  

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

072 072 A Predictive Model of Fragmentation using Adaptive Mesh Refinement and a Hierarchical Material Model A. E. Koniges, N. D. Masters, A. C. Fisher, R. W. Anderson, D. C. Eder, D. Benson, T. B. Kaiser, B. T. Gunney, P. Wang, B. R. Maddox, J. F. Hansen, D. H. Kalantar, P. Dixit, H. Jarmakani, M. A. Meyers March 5, 2009 -2- Disclaimer This document was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor Lawrence Livermore National Security, LLC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights.

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

Predictable SCR co-benefits for mercury control  

SciTech Connect (OSTI)

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.

Pritchard, S. [Cormtech Inc. (USA)

2009-01-15T23:59:59.000Z

102

Open problem: Dynamic Relational Models for Improved Hazardous Weather Prediction  

E-Print Network [OSTI]

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

McGovern, Amy

103

Predictive Models of Li-ion Battery Lifetime (Presentation)  

SciTech Connect (OSTI)

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.

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

2014-09-01T23:59:59.000Z

104

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

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

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

105

A Predictive power control of Doubly Fed Induction Generator for Wave Energy Converter  

E-Print Network [OSTI]

using a linearized state- space model. The DFIG-based WEC power tracking performances further converter (WEC), irregular wave, doubly-fed induction generator (DFIG), predictive power control, I rotational motion for connection to a conventional rotating electrical generator as a DFIG (Fig. 1). Fig.1

Brest, Université de

106

Model Predictive Control for Energy Efficient Buildings  

E-Print Network [OSTI]

is to minimize the total energy consumptions (1.1a) whilethe closed-loop total energy consumption u J = N ?1 |u ? (violation and total energy consumption. It is observed that

Ma, Yudong

2012-01-01T23:59:59.000Z

107

Model Predictive Control for Energy Efficient Buildings  

E-Print Network [OSTI]

towers water pumps thermal storage tank water supply water loop system weather low-level MPC Setpoints Solar

Ma, Yudong

2012-01-01T23:59:59.000Z

108

Model Predictive Control for Energy Efficient Buildings  

E-Print Network [OSTI]

precooling and spike in cooling power imme- diately beforeplateau in cooling power. . . . . . . . . . . . .and u is the heating and cooling power input to the space.

Ma, Yudong

2012-01-01T23:59:59.000Z

109

Model Predictive Control for Energy Efficient Buildings  

E-Print Network [OSTI]

Building thermal loadThe building thermal load predictor. . . . . . . .of Figures 1.1 Classification schematic for building MPC

Ma, Yudong

2012-01-01T23:59:59.000Z

110

Analysing earthquake slip models with the spatial prediction comparison test  

Science Journals Connector (OSTI)

......slip models with the spatial prediction comparison test Ling Zhang 1 P. Martin Mai 1 Kiran K.S. Thingbaijam...performance of the spatial prediction comparison test (SPCT), a statistical test developed to compare spatial (random) fields by......

Ling Zhang; P. Martin Mai; Kiran K.S. Thingbaijam; Hoby N.T. Razafindrakoto; Marc G. Genton

2015-01-01T23:59:59.000Z

111

Enhanced oil recovery data base analysis by simplified predictive models  

SciTech Connect (OSTI)

The U.S. Department of Energy, Bartlesville Energy Technology Center (BETC), has been developing computerized data bases and simplified predictive models to be used to predict enhanced oil recovery (EOR) potential in the U.S. The development phase of this work is nearing completion whereupon the models and data bases will be made available to the public. This paper describes the overall development phase for the models and data bases with analyses of selected EOR projects using the predictive models. Examples of model outputs are discussed and brief descriptions of the predictive algorithms are given.

Ray, R.M.; Wesson, T.C.

1982-11-01T23:59:59.000Z

112

Wind Speed Prediction Via Time Series Modeling.  

E-Print Network [OSTI]

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

Alexander, Daniel

2009-01-01T23:59:59.000Z

113

Reynolds-stress model prediction of 3-D duct flows  

E-Print Network [OSTI]

The paper examines the impact of different modelling choices in second-moment closures by assessing model performance in predicting 3-D duct flows. The test-cases (developing flow in a square duct [Gessner F.B., Emery A.F.: {\\em ASME J. Fluids Eng.} {\\bf 103} (1981) 445--455], circular-to-rectangular transition-duct [Davis D.O., Gessner F.B.: {\\em AIAA J.} {\\bf 30} (1992) 367--375], and \\tsn{S}-duct with large separation [Wellborn S.R., Reichert B.A., Okiishi T.H.: {\\em J. Prop. Power} {\\bf 10} (1994) 668--675]) include progressively more complex strains. Comparison of experimental data with selected 7-equation models (6 Reynolds-stress-transport and 1 scale-determining equations), which differ in the closure of the velocity/pressure-gradient tensor $\\Pi_{ij}$, suggests that rapid redistribution controls separation and secondary-flow prediction, whereas, inclusion of pressure-diffusion modelling improves reattachment and relaxation behaviour.

Gerolymos, G A

2014-01-01T23:59:59.000Z

114

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

E-Print Network [OSTI]

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

Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

2013-01-01T23:59:59.000Z

115

Markovian Models for Electrical Load Prediction in Smart Buildings  

E-Print Network [OSTI]

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

California at Santa Barbara, University of

116

Modeling and Predicting Pointing Errors in Two Dimensions  

E-Print Network [OSTI]

to complement Fitts' law's predictive model of pointing speed. However, their model was based on one-dimensional time, error prediction, error rates. ACM Classification Keywords: H.5.2 [Information interfaces and presentation]: User interfaces ­ theory and methods; H.1.2 [Models and principles]: User/machine systems

Anderson, Richard

117

Building a Statistical Model toBuilding a Statistical Model to Predict Reactor TemperaturesPredict Reactor Temperatures  

E-Print Network [OSTI]

Building a Statistical Model toBuilding a Statistical Model to Predict Reactor Temperatures.scarrott@lancaster.ac.uk g.tunnicliffe-wilson@lancaster.ac.uk #12;OutlineOutline l Objectives l Data l Statistical Model l temperatures ­ Physical model ­ Statistical model l How to identify and model physical effects? l How to model

Scarrott, Carl

118

Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory  

SciTech Connect (OSTI)

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 investigates the merits of harnessing both storage media concurrently in the context of predictive optimal control. This topical report describes the demonstration of the model-based predictive optimal control for active and passive building thermal storage inventory in a test facility in real-time using time-of-use differentiated electricity prices without demand charges. The laboratory testing findings presented in this topical report cover the second of three project phases. The novel supervisory controller successfully executed a three-step procedure consisting of (1) short-term weather prediction, (2) optimization of control strategy over the next planning horizon using a calibrated building model, and (3) post-processing of the optimal strategy to yield a control command for the current time step that can be executed in the test facility. The primary and secondary building mechanical systems were effectively orchestrated by the model-based predictive optimal controller in real-time while observing comfort and operational constraints. The findings reveal that when the optimal controller is given imperfect weather fore-casts and when the building model used for planning control strategies does not match the actual building perfectly, measured utility costs savings relative to conventional building operation can be substantial. This requires that the facility under control lends itself to passive storage utilization and the building model includes a realistic plant model. The savings associated with passive building thermal storage inventory proved to be small be-cause the test facility is not an ideal candidate for the investigated control technology. Moreover, the facility's central plant revealed the idiosyncratic behavior that the chiller operation in the ice-making mode was more energy efficient than in the chilled-water mode. Field experimentation (Phase III) is now required in a suitable commercial building with sufficient thermal mass, an active TES system, and a climate conducive to passive storage utilization over a longer testing period to support the laboratory findings presented in this topical report.

Gregor P. Henze; Moncef Krarti

2003-12-17T23:59:59.000Z

119

Data Assimilation for Idealised Mathematical Models of Numerical Weather Prediction  

E-Print Network [OSTI]

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

Wirosoetisno, Djoko

120

Modeling the spread of bird flu and predicting outbreak diversity  

Science Journals Connector (OSTI)

Avian influenza, commonly known as bird flu, is an epidemic caused by H5N1 virus that primarily affects birds like chickens, wild water birds, etc. On rare occasions, these can infect other species including pigs and humans. In the span of less than a year, the lethal strain of bird flu is spreading very fast across the globe mainly in South East Asia, parts of Central Asia, Africa and Europe. In order to study the patterns of spread of epidemic, we made an investigation of outbreaks of the epidemic in one week, that is from February 13–18, 2006, when the deadly virus surfaced in India. We have designed a statistical transmission model of bird flu taking into account the factors that affect the epidemic transmission such as source of infection, social and natural factors and various control measures are suggested. For modeling the general intensity coefficient f ( r ) , we have implemented the recent ideas given in the article Fitting the Bill, Nature [R. Howlett, Fitting the bill, Nature 439 (2006) 402], which describes the geographical spread of epidemics due to transportation of poultry products. Our aim is to study the spread of avian influenza, both in time and space, to gain a better understanding of transmission mechanism. Our model yields satisfactory results as evidenced by the simulations and may be used for the prediction of future situations of epidemic for longer periods. We utilize real data at these various scales and our model allows one to generalize our predictions and make better suggestions for the control of this epidemic.

Ranjit Kumar Upadhyay; Nitu Kumari; V. Sree Hari Rao

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

Climate Prediction: The Limits of Ocean Models  

E-Print Network [OSTI]

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

Stone, Peter H.

122

Biodiesel Density: Experimental Measurements and Prediction Models  

Science Journals Connector (OSTI)

Density is an important biodiesel parameter, with impact on fuel quality. Predicting density is of high relevance for a correct formulation of an adequate blend of raw materials that optimize the cost of biodiesel fuel production while allowing the ...

Maria Jorge Pratas; Samuel V. D. Freitas; Mariana B. Oliveira; Sílvia C. Monteiro; Álvaro S. Lima; João A. P. Coutinho

2011-04-19T23:59:59.000Z

123

Predictive current control of outer-rotor five-phase BLDC generators applicable for off-shore wind power plants  

Science Journals Connector (OSTI)

Abstract Model predictive control algorithms have recently gained more importance in the field of wind power generators. One of the important categories of model predictive control methods is improved deadbeat control in which the reverse model of generator is used to calculate the appropriate inputs for the next iteration of controlling process. In this paper, a new improved deadbeat algorithm is proposed to control the stator currents of an outer-rotor five-phase BLDC generator. Extended Kalman filter is used in the estimation step of proposed method, and generator equations are used to calculate the appropriate voltages for the next modulation period. Two aspects of proposed controlling method are evaluated including its sensitivity to generator parameter variations and its speed in following the reference values of required torque during transient states. Wind power generators are kept in mind, and proposed controlling method is both simulated and experimentally evaluated on an outer-rotor five-phase BLDC generator.

Jose Luis Romeral Martinez; Ramin Salehi Arashloo; Mehdi Salehifar; Juan Manuel Moreno

2014-01-01T23:59:59.000Z

124

predictive-models | netl.doe.gov  

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

are available. The five recovery processes modeled are Steamflood, In-Situ Combustion, Polymer, Chemical Flooding, and CO2 Miscible Flooding. The models are available...

125

Web Page Rank Prediction with Markov Models Michalis Vazirgiannis  

E-Print Network [OSTI]

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

Paris-Sud XI, Université de

126

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

E-Print Network [OSTI]

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

S. I. Eidelman

2009-04-21T23:59:59.000Z

127

Forecasting wave height probabilities with numerical weather prediction models  

E-Print Network [OSTI]

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

Stevenson, Paul

128

Title: Development of Statistical and Data Drive Models to Predict Flares for Space Weather Predictions  

E-Print Network [OSTI]

D and civilian assets in both space and ground. The current state of predictability of solar flares is basedTitle: Development of Statistical and Data Drive Models to Predict Solar Flares for Space Weather Collaborator: Dr. K. S. Balasubramaniam, Air Force Research Laboratory Summary: Solar flares impact Do

Johnson, Eric E.

129

NETL: Predictive Modeling and Evaluation - TVA Model Comparison  

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

Ozone/PM2.5 Formation & Transport Model Comparison Ozone/PM2.5 Formation & Transport Model Comparison Future regulatory actions for mitigating PM2.5 concentrations will rely, to some extent, on results from large-scale atmospheric models. The most efficient approach to evaluating regulatory actions is to use an integrated approach that examines multiple air quality impacts simultaneously. This is because of the strong linkage between PM2.5 levels, visibility degradation, ozone and acidic deposition. Thus, regional modeling of the impacts on PM2.5 levels from proposed emission reductions should be evaluated in terms of computed impacts not only on PM2.5 levels, but on ozone and acidic deposition as well. TVA is an active participant in the only ongoing assessment of this type, which is being done for the Southern Appalachian Mountains Initiative (SAMI) as part of its integrated assessment in the southeastern United States. SAMI, with its focus on protecting PSD Class I areas, is using a model called URM that can examine all the aforementioned phenomena at once. In addition, URM has the capability, which SAMI intends to use, of efficiently examining the sensitivity of model outputs to changes in emissions across the entire modeling domain. Finally, SAMI will use URM to test various emission management options (EMOs) for mitigating impacts in the southern Appalachians. These EMOs will include controls on various source sectors, including energy.

130

Cancer growth: Predictions of a realistic model  

Science Journals Connector (OSTI)

Simulations of avascular cancer growth are performed using experimental values of the relevant parameters. This permits a realistic assessment of the influence of these parameters on cancer growth dynamics. In general, an early exponential growth phase is followed by a linear regime (as observed in recent experiments), while the thickness of the viable cell layer remains approximately constant. Contrary to some predictions, a transition to latency is not observed.

S. A. Menchón and C. A. Condat

2008-08-08T23:59:59.000Z

131

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

E-Print Network [OSTI]

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

Stoffelen, Ad

132

MIT Emissions Prediction and Policy Analysis (EPPA) Model | Open Energy  

Open Energy Info (EERE)

MIT Emissions Prediction and Policy Analysis (EPPA) Model MIT Emissions Prediction and Policy Analysis (EPPA) Model Jump to: navigation, search LEDSGP green logo.png FIND MORE DIA TOOLS This tool is part of the Development Impacts Assessment (DIA) Toolkit from the LEDS Global Partnership. Tool Summary LAUNCH TOOL Name: MIT Emissions Prediction and Policy Analysis (EPPA) Model Agency/Company /Organization: Massachusetts Institute of Technology (MIT) Topics: Analysis Tools Complexity/Ease of Use: Not Available Website: dspace.mit.edu/handle/1721.1/29790 Cost: Free Related Tools IGES GHG Calculator For Solid Waste Energy and Power Evaluation Program (ENPEP) Regional Economic Models, Inc. (REMI) Model ... further results The part of the MIT Integrated Global Systems Model (IGSM) that represents human systems; a recursive-dynamic multi-regional general equilibrium model

133

Fast prediction of transient stability margin in systems with SVC control and HVDC link  

SciTech Connect (OSTI)

Recent developments in transient stability margin (TSM) prediction using the energy-based direct method have included excitation controllers, power system stabilizers (PSSs) and/or static VAr compensators (SVCs). These devices can be represented in their detailed dynamic models to desired degrees of complexity while the proposed extended equal-area criterion can still be effectively applied. This paper describes further development of this technique to incorporate an HVDC transmission into the test network for TSM prediction. The method is examined with a practical 17-machine power network representing the South China/Hong Kong system. An SVC control scheme is also installed in a weak bus of the test network for transient stability improvement. The results obtained show that there is no sacrifice in accuracy, speed or reliability of the TSM method with SVC and HVDC realistically incorporated into the study.

Tso, S.K. [City Univ. of Hong Kong (Hong Kong). Dept. of Manufacturing Engineering; Cheung, S.P. [ABB Transmission and Distribution Ltd., Hong Kong (Hong Kong). Dept. of Power Systems

1995-12-31T23:59:59.000Z

134

A predictive ocean oil spill model  

SciTech Connect (OSTI)

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.

Sanderson, J.; Barnette, D. [Sandia National Labs., Albuquerque, NM (United States); Papodopoulos, P. [Oak Ridge National Lab., TN (United States); Schaudt, K. [Marathon Oil Co., Littleton, CO (United States); Szabo, D. [Mobil Research and Development Corp., Dallas, TX (United States)

1996-07-01T23:59:59.000Z

135

Conformal Higgs model: predicted dark energy density  

E-Print Network [OSTI]

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

R. K. Nesbet

2014-11-03T23:59:59.000Z

136

Standard Model Prediction of the Muon Anomalous Magnetic Moment  

E-Print Network [OSTI]

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

Joaquim Prades

2010-02-18T23:59:59.000Z

137

Hospital Readmission in General Medicine Patients: A Prediction Model  

E-Print Network [OSTI]

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

2010-01-01T23:59:59.000Z

138

NETL: IEP - Air Quality Research: Predictive Modeling and Evaluation  

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

Predictive Modeling and Evaluation Predictive Modeling and Evaluation Predictive Modeling and Evaluation Map Click on a Project Name to Get More Information It is likely that most or all State Implementation Plans pertaining to PM2.5 will be developed with the aid of some type of atmospheric modeling to predict the reductions in PM2.5 attainable via reductions in power plant emissions. The accuracy of such predictions depends on how accurately the models represent the actual emissions and atmospheric chemistry/transport phenomena. Modeling studies supported by the NETL fine PM program include: (1) receptor-based (source apportionment) modeling pertinent to electric power sources; (2) model evaluation using ambient PM mass measurements; (3) methods for estimating the lifetime and transport distances of primary and secondary PM; (4) quantifying the relationships between PM (nitric acid and sulfate) and NOx and SO2 emissions in the modeling domain; and (5) quantifying the contribution of primary and secondary organic aerosol emissions from power sources to observed organic PM.

139

In silico modeling to predict drug-induced phospholipidosis  

SciTech Connect (OSTI)

Drug-induced phospholipidosis (DIPL) is a preclinical finding during pharmaceutical drug development that has implications on the course of drug development and regulatory safety review. A principal characteristic of drugs inducing DIPL is known to be a cationic amphiphilic structure. This provides evidence for a structure-based explanation and opportunity to analyze properties and structures of drugs with the histopathologic findings for DIPL. In previous work from the FDA, in silico quantitative structure–activity relationship (QSAR) modeling using machine learning approaches has shown promise with a large dataset of drugs but included unconfirmed data as well. In this study, we report the construction and validation of a battery of complementary in silico QSAR models using the FDA's updated database on phospholipidosis, new algorithms and predictive technologies, and in particular, we address high performance with a high-confidence dataset. The results of our modeling for DIPL include rigorous external validation tests showing 80–81% concordance. Furthermore, the predictive performance characteristics include models with high sensitivity and specificity, in most cases above ? 80% leading to desired high negative and positive predictivity. These models are intended to be utilized for regulatory toxicology applied science needs in screening new drugs for DIPL. - Highlights: • New in silico models for predicting drug-induced phospholipidosis (DIPL) are described. • The training set data in the models is derived from the FDA's phospholipidosis database. • We find excellent predictivity values of the models based on external validation. • The models can support drug screening and regulatory decision-making on DIPL.

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

2013-06-01T23:59:59.000Z

140

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

E-Print Network [OSTI]

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

Schiavon, Stefano; Lee, Kwang Ho

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

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

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

Carbon-cycle models for better long-term predictions Carbon-cycle models for better long-term predictions Reduced variation among models should improve precision Improved...

142

A support vector regression model for predicting tunnel boring machine penetration rates  

Science Journals Connector (OSTI)

Abstract With widespread increasing applications of mechanized tunneling in almost all ground conditions, prediction of tunnel boring machine (TBM) performance is required for time planning, cost control and choice of excavation method in order to make tunneling economical. Penetration rate is a principal measure of full-face TBM performance and is used to evaluate the feasibility of the machine and predict advance rate of excavation. This research aims at developing a regression model to predict penetration rate of TBM in hard rock conditions based on a new artificial intelligence (AI) algorithm namely support vector regression (SVR). For this purpose, the Queens Water Tunnel, in New York City, was selected as a case study to test the proposed model. In order to find out the optimum values of the parameters and prevent over-fitting, 80% of the total data were selected randomly for training set and the rest were kept for testing the model. According to the results, it can be said that the proposed model is a useful and reliable means to predict TBM penetration rate provided that a suitable dataset exists. From the prediction results of training and testing samples, the squared correlation coefficient (R2) between the observed and predicted values of the proposed model was obtained 0.99 and 0.95, respectively, which shows a high conformity between predicted and actual penetration rate.

Satar Mahdevari; Kourosh Shahriar; Saffet Yagiz; Mohsen Akbarpour Shirazi

2014-01-01T23:59:59.000Z

143

Predictive microfluidic control of regulatory ligand trajectories in individual pluripotent cells  

E-Print Network [OSTI]

Predictive microfluidic control of regulatory ligand trajectories in individual pluripotent cells microfluidic perfusion culture demonstrated that STAT3 activation and consequently mESC fate were manipulable

Zandstra, Peter W.

144

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

E-Print Network [OSTI]

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

Johansson, Karl Henrik

145

Adaptive hybrid predictive control for a combined cycle power plant optimization .  

E-Print Network [OSTI]

??The design and development of an adaptive hybrid predictive controller for the optimization of a real combined cycle power plant (CCPP) are presented. The real… (more)

Sáez, D.

2008-01-01T23:59:59.000Z

146

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

E-Print Network [OSTI]

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

Mather, Patrick T.

147

The Isospin Model prediction for multi-pion tau decays  

E-Print Network [OSTI]

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

Randall J. Sobie

1998-10-19T23:59:59.000Z

148

Penetration rate prediction for percussive drilling via dry friction model  

E-Print Network [OSTI]

Penetration rate prediction for percussive drilling via dry friction model Anton M. Krivtsov a. Similarly, an increased weight on bit in downhole drilling does not improve the penetration rates when hard- tration rate is presented. The inherent nonlinearity of the discontinuous impact process is modelled

Krivtsov, Anton M.

149

A NEW MODEL FOR PERFORMANCE PREDICTION OF HARD ROCK TBMS.  

E-Print Network [OSTI]

methods to accu- rately predict the penetration rate of a TBM in a given geology. These models are mainly, and the penetration rate. A good example of this is the Norwegian (NTH) hard rock diagnostic system and predictor penetration rate. This group of models 1.ResearchAssociakandGraduacStudentinMiningErrg.Dept. 2.Directorof

150

The origins of computer weather prediction and climate modeling  

Science Journals Connector (OSTI)

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 ... Keywords: Climate modelling, History of NWP, Numerical weather prediction

Peter Lynch

2008-03-01T23:59:59.000Z

151

Development of Chemical Model to Predict the Interactions between  

Open Energy Info (EERE)

Model to Predict the Interactions between Model to Predict the Interactions between Supercritical CO2 and Fluid, Rocks in EGS Reservoirs Geothermal Project Jump to: navigation, search Last modified on July 22, 2011. Project Title Development of Chemical Model to Predict the Interactions between Supercritical CO2 and Fluid, Rocks in EGS Reservoirs Project Type / Topic 1 Recovery Act: Enhanced Geothermal Systems Component Research and Development/Analysis Project Type / Topic 2 Supercritical Carbon Dioxide / Reservoir Rock Chemical Interactions Project Description In order to develop this model, databases will be assembled and/or updated for thermodynamic and kinetic rate laws for water/brine/rock/CO2 interactions at the pressures and temperatures common to EGS systems. In addition to a literature search, extrapolation of existing data and experimental laboratory work will be conducted to calibrate and verify the datasets.

152

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

E-Print Network [OSTI]

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

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

2012-01-01T23:59:59.000Z

153

Model Based Torque Control and Estimation for Common Rail Diesel Engine  

Science Journals Connector (OSTI)

A rapid control prototyping based on torque control algorithm using V-cycle mode for common rail diesel engine was developed, and a torque prediction model was present which including a feed-forward mean value engine model and a feedback correction of ... Keywords: common rail diesel engine, control strategies, torque control, torque estimation

Wang Hongrong; Wang Yongfu; Liu Zhi

2010-11-01T23:59:59.000Z

154

Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory  

SciTech Connect (OSTI)

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 short-term prediction models to realize almost all of the theoretical potential of this control strategy. Further work evaluated the impact of modeling accuracy on the model-based closed-loop predictive optimal controller to minimize utility cost. The following guidelines have been derived: For an internal heat gain dominated commercial building, reasonable geometry simplifications are acceptable without a loss of cost savings potential. In fact, zoning simplification may improve optimizer performance and save computation time. The mass of the internal structure did not show a strong effect on the optimization. Building construction characteristics were found to impact building passive thermal storage capacity. It is thus advisable to make sure the construction material is well modeled. Zone temperature setpoint profiles and TES performance are strongly affected by mismatches in internal heat gains, especially when they are underestimated. Since they are a key factor in determining the building cooling load, efforts should be made to keep the internal gain mismatch as small as possible. Efficiencies of the building energy systems affect both zone temperature setpoints and active TES operation because of the coupling of the base chiller for building precooling and the icemaking TES chiller. Relative efficiencies of the base and TES chillers will determine the balance of operation of the two chillers. The impact of mismatch in this category may be significant. Next, a parametric analysis was conducted to assess the effects of building mass, utility rate, building location and season, thermal comfort, central plant capacities, and an economizer on the cost saving performance of optimal control for active and passive building thermal storage inventory. The key findings are: (1) Heavy-mass buildings, strong-incentive time-of-use electrical utility rates, and large on-peak cooling loads will likely lead to attractive savings resulting from optimal combined thermal storage control. (2) By using economizer to take advantage of the cool fresh air during the night, the bu

Gregor P. Henze; Moncef Krarti

2005-09-30T23:59:59.000Z

155

Intelligent Actuation Control Using Model-Free Adaptive Control Technology  

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

Intelligent Actuation Control Using Intelligent Actuation Control Using Model-Free Adaptive Control Technology Background The Advanced Research Sensors and Controls Program is leading the effort to develop sensing and control technologies and methods to achieve seamlessly integrated and intelligent power systems. The program is led by the U.S. Department of Energy (DOE) Office of Fossil Energy National Energy Technology Laboratory (NETL) and is implemented

156

Shadow prediction model for the International Space Station Alpha  

SciTech Connect (OSTI)

A Fortran computer model, SHADOW5, was developed to predict shadows on the solar arrays of the International Space Station Alpha (ISSA) for general flight modes. This shadow model was incorporated into the EPSOP-F (Electrical Power System On-Orbit Performance) program to conduct ISSA power analyses for various operating conditions. This paper describes the mathematical methods of the model and shows the typical results predicted with the model. Vector analyses with coordinate transformations were used to trace the shadows between the potential shadowing and shadowed components of the station during the sun portion of the orbit. Including the space shuttle orbiter, 40 components were modeled. The basic shapes of the components were assumed to be either planar or cylindrical. The elemental areas obtained from the Cartesian grid lines allocated on the component surfaces were projected in the sun vector direction to reconstruct shadows on the shadowed planar surface. Comparison of predicted results with other models showed good agreement. Ease of preparing input data and relatively short CPU time make this model suitable for shadow analyses required for the many design and flight configurations of the space station.

Chung, D.K. [Rockwell International, Canoga Park, CA (United States). Rocketdyne Division

1995-12-31T23:59:59.000Z

157

Predicting mesh density for adaptive modelling of the global atmosphere  

Science Journals Connector (OSTI)

...under investigation for atmospheric modelling for some time...atmosphere, using the shallow water equations-a necessary...to solve the shallow water equations on fixed meshes...discussed in 3. The mesh generator and the predictive adaptive...Solving the shallow water equations on polygons...

2009-01-01T23:59:59.000Z

158

The origins of computer weather prediction and climate modeling  

SciTech Connect (OSTI)

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.

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

2008-03-20T23:59:59.000Z

159

MBGP IN MODELLING AND PREDICTION Carlos OliverMorales  

E-Print Network [OSTI]

. Universitaria O4510 Mexico City, MEXICO Abstract. The paper describes a hybrid approach for dynamic system), relative humidity (H), solar radiation (R) and wind speed (V) and direction (D) were recorded. The time An alternative representation in GP for dynamic system modelling and prediction was presented. This MB

Fernandez, Thomas

160

MB GP IN MODELLING AND PREDICTION Carlos Oliver-Morales  

E-Print Network [OSTI]

. Universitaria O4510 Mexico City, MEXICO Abstract. The paper describes a hybrid approach for dynamic system), relative humidity (H), solar radiation (R) and wind speed (V) and direction (D) were recorded. The time system modelling and prediction was presented. This MB-GP approach has used small values of GP parameters

Fernandez, Thomas

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

A Simple Empirical Model for Decadal Climate Prediction  

Science Journals Connector (OSTI)

Decadal climate prediction is a challenging aspect of climate research. It has been and will be tackled by various modeling groups. This study proposes a simple empirical forecasting system for the near-surface temperature that can be used as a ...

Oliver Krueger; Jin-Song Von Storch

2011-02-01T23:59:59.000Z

162

Predicting solar cycle 24 with a solar dynamo model  

E-Print Network [OSTI]

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

Arnab Rai Choudhuri; Piyali Chatterjee; Jie Jiang

2007-01-18T23:59:59.000Z

163

Estimating Predictive Variance for Statistical Gas Distribution Modelling  

SciTech Connect (OSTI)

Recent publications in statistical gas distribution modelling have proposed algorithms that model mean and variance of a distribution. This paper argues that estimating the predictive concentration variance entails not only a gradual improvement but is rather a significant step to advance the field. This is, first, since the models much better fit the particular structure of gas distributions, which exhibit strong fluctuations with considerable spatial variations as a result of the intermittent character of gas dispersal. Second, because estimating the predictive variance allows to evaluate the model quality in terms of the data likelihood. This offers a solution to the problem of ground truth evaluation, which has always been a critical issue for gas distribution modelling. It also enables solid comparisons of different modelling approaches, and provides the means to learn meta parameters of the model, to determine when the model should be updated or re-initialised, or to suggest new measurement locations based on the current model. We also point out directions of related ongoing or potential future research work.

Lilienthal, Achim J.; Asadi, Sahar; Reggente, Matteo [AASS Research Center, Oerebro University (Sweden)

2009-05-23T23:59:59.000Z

164

A minimal and predictive $T_7$ lepton flavor 331 model  

E-Print Network [OSTI]

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

Hernández, A E Cárcamo

2015-01-01T23:59:59.000Z

165

A Prediction of Energy Savings Resulting from Building Infiltration Control  

E-Print Network [OSTI]

, working to reduce or increase it. This study uses simulation to evaluate the potential energy impact of the interaction when several different strategies for controlling air leakage direction and velocity in building envelope components are implemented...

McWatters, K.; Claridge, D. E.; Liu, M.

1996-01-01T23:59:59.000Z

166

ME EET Seminar: Real-time Predictive Control: From Automotive Systems to  

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

Real-time Predictive Control: From Automotive Systems to Real-time Predictive Control: From Automotive Systems to Energy Efficient Buildings Speaker(s): Francesco Borrelli Date: February 10, 2010 - 12:00pm Location: 90-3122 Hybrid systems are heterogeneous systems that exhibit both continuous and discrete dynamics. Over the last eight years we have focused on the development of systematic, real-time, predictive controller synthesis techniques for hybrid systems with constraints. In this talk I will first summarize our theoretical efforts starting from constrained optimal control design for hybrid systems with constraints. Then, I will show how these results can be used in order to develop a theory for distributed predictive control for large-scale systems. The second part of the talk presents a range of applications where the proposed techniques were used with great

167

Offshore pile driving noise—Prediction through comprehensive model development  

Science Journals Connector (OSTI)

Offshore wind energy is one of the most potent among renewables and thus the worldwide number of offshore wind turbines increases rapidly. The foundations of the wind turbines are typically fastened to the seabed by impact pile driving which comes along with a significant amount of waterborne noise. To protect the marine biosphere the use of noise mitigation systems like bubble curtains or cofferdams may become necessary. In this context the model-based prediction of underwater sound pressure levels as well as the design and optimization of effective sound mitigation measures by using numerical models is one of today’s challenges. The current work presents a modeling approach that consists of a near field finite element model and a far field propagation model. Furthermore it has been found necessary to generate a benchmark to allow for a qualitative and quantitative comparison between the manifold modeling approaches that are currently developed at various institutes and companies.

Marcel Ruhnau; Stephan Lippert

2013-01-01T23:59:59.000Z

168

A neural network based model for urban noise prediction  

Science Journals Connector (OSTI)

Noise is a global problem. In 1972 the World Health Organization (WHO) classified noise as a pollutant. Since then most industrialized countries have enacted laws and local regulations to prevent and reduce acoustic environmental pollution. A further aim is to alert people to the dangers of this type of pollution. In this context urban planners need to have tools that allow them to evaluate the degree of acoustic pollution. Scientists in many countries have modeled urban noise using a wide range of approaches but their results have not been as good as expected. This paper describes a model developed for the prediction of environmental urban noise using Soft Computing techniques namely Artificial Neural Networks (ANN). The model is based on the analysis of variables regarded as influential by experts in the field and was applied to data collected on different types of streets. The results were compared to those obtained with other models. The study found that the ANN system was able to predict urban noise with greater accuracy and thus was an improvement over those models. The principal component analysis (PCA) was also used to try to simplify the model. Although there was a slight decline in the accuracy of the results the values obtained were also quite acceptable.

N. Genaro; A. Torija; A. Ramos-Ridao; I. Requena; D. P. Ruiz; M. Zamorano

2010-01-01T23:59:59.000Z

169

A prediction of energy savings resulting from building infiltration control  

E-Print Network [OSTI]

, temperature ('C) Indoor, or room, temperature of building ('C) Temperature of exterior surface of a building wall, window or roof ( C) Sol-air temperature for a wall or other building surface ('C) Interchangeable with T, Difference between building room... infiltration Designating airflow into a building surface Maximum model Minimum Interaction heat transfer calculation model N North Pressure Surface South sa Sol-air Room tot Total CHAPTER I INTRODUCTION 1. 1 OBJECTIVES Heating and cooling...

McWatters, Kenneth Rob

1995-01-01T23:59:59.000Z

170

Prediction-based Iterative Learning Control (PILC) for Uncertain Dynamic Nonlinear Systems Using System Identification Technique  

Science Journals Connector (OSTI)

Prediction-based Iterative Learning Control (PILC) is proposed in this paper for a ... time varying nonlinear uncertain systems. Convergence of PILC is analyzed and the uniform boundedness of ... succeeding itera...

M. Arif; T. Ishihara; H. Inooka

2000-03-01T23:59:59.000Z

171

Control of household refrigerators. Part 1: Modeling temperature control performance  

SciTech Connect (OSTI)

Commercial household refrigerators use simple, cost-effective, temperature controllers to obtain acceptable control. A manually adjusted airflow damper regulates the freezer compartment temperature while a thermostat controls operation of the compressor and evaporator fan to regulate refrigerator compartment temperature. Dual compartment temperature control can be achieved with automatic airflow dampers that function independently of the compressor and evaporator fan thermostat, resulting in improved temperature control quality and energy consumption. Under dual control, freezer temperature is controlled by the thermostat while the damper controls refrigerator temperature by regulating airflow circulation. A simulation model is presented that analyzes a household refrigerator configured with a conventional thermostat and both manual and automatic dampers. The model provides a new paradigm for investigating refrigerator systems and temperature control performance relative to the extensive verification testing that is typically done by manufacturers. The effects of each type of control and damper configuration are compared with respect to energy usage, control quality, and ambient temperature shift criteria. The results indicate that the appropriate control configuration can have significant effects and can improve plant performance.

Graviss, K.J.; Collins, R.L.

1999-07-01T23:59:59.000Z

172

NETL: Predictive Modeling and Evaluation - CMU Regional Modeling Study  

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

Regional Source-Receptor Modeling Study Regional Source-Receptor Modeling Study The Pittsburgh Air Quality Study (PAQS) [PDF-744KB] is comprised of three inter-related components: 1) ambient PM measurements, 2) source characterization, and 3) deterministic and statistical air quality modeling. This effort will permit clarification of the contribution of coal-fired power plants to fine ambient PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 µm). The resources from the Department of Energy (DOE) will be leveraged with resources from the Environmental Protection Agency (EPA) and other organizations. Clarkson University (Hopke group) will apply advanced receptor models to identify the nature, location and contribution of the sources of particulate matter observed by the measurements made as part of the PAQS. Several forms of factor analysis including Positive Matrix Factorization (PMF) and UNMIX will be applied in order to identify the composition and contributions of the sources. Potential Source Contribution Function analysis as well as Residence Time Weighted Concentration analysis will be applied to the determination of the locations of the likely major contributing sources. The aforementioned factor analysis methods will also be applied to the spatially distributed data both on a single species and multiple species basis and to compare these results with those obtained utilizing the back-trajectory-based methods. The availability of highly time resolved data should permit greater source resolution and will be examined to determine how much increased source specificity can be obtained from the increased time resolution in the data. Assistance will be provided with the multivariate calibration that will permit the use of single-particle mass spectrometry data to estimate ambient concentrations of particulate species. These analyses should provide a better understanding of the source/receptor relationships that lead to the observed particle concentrations in the Pittsburgh area.

173

A dynamic prediction model for gas–water effective permeability based on coalbed methane production data  

Science Journals Connector (OSTI)

Abstract An understanding of the relative permeability of gas and water in coal reservoirs is vital for coalbed methane (CBM) development. In this work, a prediction model for gas–water effective permeability is established to describe the permeability variation within coal reservoirs during production. The effective stress and matrix shrinkage effects are taken into account by introducing the Palmer and Mansoori (PM) absolute permeability model. The endpoint relative permeability is calibrated through experimentation instead of through the conventional Corey relative permeability model, which is traditionally employed for the simulation of petroleum reservoirs. In this framework, the absolute permeability model and the relative permeability model are comprehensively coupled under the same reservoir pressure and water saturation conditions through the material balance equation. Using the Qinshui Basin as an example, the differences between the actual curve that is measured with the steady-state method and the simulation curve are compared. The model indicates that the effective permeability is expressed as a function of reservoir pressure and that the curve shape is controlled by the production data. The results illustrate that the PM–Corey dynamic prediction model can accurately reflect the positive and negative effects of coal reservoirs. In particular, the model predicts the matrix shrinkage effect, which is important because it can improve the effective permeability of gas production and render the process more economically feasible.

H. Xu; D.Z. Tang; S.H. Tang; J.L. Zhao; Y.J. Meng; S. Tao

2014-01-01T23:59:59.000Z

174

Fast prediction and evaluation of gravitational waveforms using surrogate models  

E-Print Network [OSTI]

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

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

2014-02-28T23:59:59.000Z

175

Modelling and Control of Activated Sludge Processes  

E-Print Network [OSTI]

Modelling and Control of Activated Sludge Processes Michela Mulas Dottorato di Ricerca of Activated Sludge Processes Michela Mulas Supervisors: Prof. Roberto Baratti Ing. Stefania Tronci Dottorato . . . . . . . . . . . . . . . . . . . . . . . . . 5 2 ASP Models and Simulations 7 2.1 The Activated Sludge Process

Skogestad, Sigurd

176

A Robust Model Control for Dynamic Systems  

Science Journals Connector (OSTI)

Analytical methods of polynomial algebra, heuristic techniques, and digital modeling are used to study the robustness domain of linear dynamic systems with model “input–output” controllers as a function of the mutual locations of zeros ...

S. V. Tararykin; V. V. Tyutikov

2002-05-01T23:59:59.000Z

177

Supporting technology for enhanced oil recovery: Polymer predictive model  

SciTech Connect (OSTI)

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

Not Available

1986-12-01T23:59:59.000Z

178

Combustion Modeling for Diesel Engine Control Design  

E-Print Network [OSTI]

Combustion Modeling for Diesel Engine Control Design Von der Fakult¨at f¨ur Maschinenwesen der Combustion Modeling for Diesel Engine Control Design WICHTIG: D 82 überprüfen !!! #12;Bibliographic research stays at General Motors R&D in Warren, MI, USA, possible. Furthermore, I would like thank Tom

Peters, Norbert

179

Modeling Control Mechanisms with Normative Multiagent Systems  

E-Print Network [OSTI]

. This paper is about control mechanisms for virtual organizations. As a case study, we discuss the Renewables of renewable energy. We apply a conceptual model based on normative multiagent systems (NMAS). We proposeModeling Control Mechanisms with Normative Multiagent Systems: the Case of the Renewables

van der Torre, Leon

180

Prerequisites: Control Systems I+II, System Modeling, Engine Class (Introduction to Modeling and Control of  

E-Print Network [OSTI]

Thesis IDSC-LG-FZ-05 Gas Diesel Engine Modeling and Control The gas diesel engine is a natural gas enginePrerequisites: Control Systems I+II, System Modeling, Engine Class (Introduction to Modeling and Control of Internal Combustion Engine Systems, IC Engines, ...), Optimization Course, Matlab

Lygeros, John

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

The Dynamics of Deterministic Chaos in Numerical Weather Prediction Models  

E-Print Network [OSTI]

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

A. Mary Selvam

2003-10-07T23:59:59.000Z

182

Predictive Modeling of fMRI Brain States using Functional Canonical Correlation Analysis  

E-Print Network [OSTI]

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

Smeulders, Arnold

183

Predictions  

Science Journals Connector (OSTI)

...Web jet aircraft, rocketry, space travel fax machines and mobile...London, UK/Bridgeman Art Library. Predictions generated by natural processes in astronomical space, and it is thought to supply...to be used in early 1999 as public transport in that city, is...

2001-01-01T23:59:59.000Z

184

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

E-Print Network [OSTI]

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

Cecconi, Fabio

185

Supporting technology for enhanced oil recovery: Chemical flood predictive model  

SciTech Connect (OSTI)

The Chemical Flood Predictive Model (CFPM) was developed by Scientific Software-Intercomp for the US Department of Energy and was used in the National Petroleum Council's (NPC) 1984 survey of US enhanced oil recovery potential (NPC, 1984). The CFPM models micellar (surfactant)-polymer (MP) floods in reservoirs which have been previously waterflooded to residual oil saturation. Thus, only true tertiary floods are considered. An option is available in the model which allows a rough estimate of oil recovery by caustic (alkaline) or caustic-polymer processes. This ''caustic'' option, added for the NPC survey, is not modeled as a separate process. Rather, the caustic and caustic-polymer oil recoveries are computed simply as 15% and 40%, respectively, of the MP oil recovery. In the CFPM, an oil rate versus time function for a single pattern is computed and the results are passed to the economic routines. To estimate multi-pattern project behavior, a pattern development schedule must be specified. After-tax cash flow is computed by combining revenues with capital costs for drilling, conversion and upgrading of wells, chemical handling costs, fixed and variable operating costs, injectant costs, depreciation, royalties, severance, state, federal, and windfall profit taxes, cost and price inflation rates, and the discount rate. A lumped parameter uncertainty routine is used to estimate risk, and allows for variation in computed project performance within an 80% confidence interval. The CFPM uses theory and the results of numerical simulation to predict MP oil recovery in five-spot patterns. Oil-bank and surfactant breakthrough and project life are determined from fractional flow theory. A Koval-type factor, based on the Dykstra-Parsons (1950) coefficient, is used to account for the effects of reservoir heterogeneity on surfactant and oil bank velocities. 18 refs., 17 figs., 27 tabs.

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

1986-12-01T23:59:59.000Z

186

Microcomputer programs for particulate control: section failure; baghouse; plume opacity prediction; and in-stack opacity calculator. Software  

SciTech Connect (OSTI)

IBM-PC usable versions of several computer models useful in particulate control are provided. The models were originally written for the TRS-80 Model I-III series of microcomputers and have been translated to run on the IBM-PC. The documentation for the TRS-80 versions applies to the IBM-PC versions. The programs are written in FORTRAN and are provided in both source (FORTRAN) and executable form. Some small machine language routines are used to format the screen for data entry. These routines limit the programs to IBM-PC and close clones. The minimum hardware requirements are 256K IBM-PC or close clone, a monochrome monitor, and a disk drive. A printer is useful but not required. The following computer programs are provided in the four-disk package: (1) ESP section failure model, (2) GCA/EPA baghouse model, (3) Plume opacity prediction model, and (4) In-stack opacity calculator. All the models are documented in EPA report Microcomputer Programs for Particulate Control, EPA-600/8-85-025a (PB86-146529). The models provide useful tools for those involved in particulate control.

Sparks, L.E.

1985-09-01T23:59:59.000Z

187

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

E-Print Network [OSTI]

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

Dacre, Helen

188

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

E-Print Network [OSTI]

USING LEARNING MACHINES TO CREATE SOLAR RADIATION MAPS FROM NUMERICAL WEATHER PREDICTION MODELS simulation by means of a Numerical Weather Prediction Model (NWP), Skiron. After that, we have made spatial solar resource map. 2.1. Meteorological simulation The numerical weather prediction model used is SKIRON

Paris-Sud XI, Université de

189

Modeling and control of top tensioned risers  

E-Print Network [OSTI]

1 Modeling and control of top tensioned risers Anne Marthine Rustad Department of Marine Technology increasing platform size · Constant high top tension is expensive and could result in wear and tear

Nørvåg, Kjetil

190

Access control models and security labelling  

Science Journals Connector (OSTI)

Security labels convey information that is utilised to perform access control decisions, specify protective measures, and aid in the determination of additional handling restrictions required by security policies. In discussing security labelling, one ... Keywords: access control, assurance, dynamic labelling model, open system, security label, security policy

Chuchang Liu; Angela Billard; Maris Ozols; Nikifor Jeremic

2007-01-01T23:59:59.000Z

191

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

E-Print Network [OSTI]

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

Hsieh, William

192

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

E-Print Network [OSTI]

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

193

RESIDUA UPGRADING EFFICIENCY IMPROVEMENT MODELS: COKE FORMATION PREDICTABILITY MAPS  

SciTech Connect (OSTI)

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.

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

2002-05-01T23:59:59.000Z

194

HVAC filtration for controlling infectious airborne disease transmission in indoor environments: Predicting risk reductions and operational costs  

Science Journals Connector (OSTI)

Abstract This work describes and applies a methodology for estimating the impact of recirculating heating, ventilating, and air-conditioning (HVAC) particle filters on the control of size-resolved infectious aerosols in indoor environments using a modified version of the Wells-Riley model for predicting risks of infectious disease transmission. Estimates of risk reductions and associated operational costs of both HVAC filtration and equivalent outdoor air ventilation are modeled and compared using a case study of airborne transmission of influenza in a hypothetical office space. Overall, recirculating HVAC filtration was predicted to achieve risk reductions at lower costs of operation than equivalent levels of outdoor air ventilation, particularly for MERV 13–16 filters. Medium efficiency filtration products (MERV 7–11) are also inexpensive to operate but appear less effective in reducing infectious disease risks.

Parham Azimi; Brent Stephens

2013-01-01T23:59:59.000Z

195

Predictive Model for Environmental Assessment in Additive Manufacturing Process  

Science Journals Connector (OSTI)

Abstract Additive Manufacturing is an innovative way to produce parts. However its environmental impact is unknown. To ensure the development of additive manufacturing processes it seems important to develop the concept of DFSAM (Design for Sustainable Additive Manufacturing). In fact, one of the objectives of environmental sustainable manufacturing is to minimize the whole flux consumption (electricity, material and fluids) during manufacturing step. To achieve this goal, it is interesting to get a predictive model of consumptions, integrated in the design step, allowing to evaluate the product's environmental impact during the manufacturing step. This paper presents a new methodology for electric, fluids and raw material consumptions assessment for additive manufacturing processes, in particular for a direct metal deposition process. The methodology will help engineers to design parts optimized for additive manufacturing with an environmental point of view.

Florent Le Bourhis; Olivier Kerbrat; Lucas Dembinski; Jean-Yves Hascoet; Pascal Mognol

2014-01-01T23:59:59.000Z

196

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

E-Print Network [OSTI]

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

Jung, Martin

2014-01-01T23:59:59.000Z

197

A heuristic predictive logic controller applied to hybrid solar air conditioning plant  

Science Journals Connector (OSTI)

This paper shows the development of a heuristic predictive logic controller (HPLoC) applied to a solar air conditioning plant. The plant uses two energy sources, solar and gas, in order to warm up the water. The hot water feeds a single-effect absorption ...

Darine Zambrano; Winston García-Gabín; Eduardo F. Camacho

2007-04-01T23:59:59.000Z

198

The dynamics, prediction, and control of wing rock in high–performance aircraft  

Science Journals Connector (OSTI)

...parameter and the simple procedure developed to predict...produce the undesirable handling quality of wing rock...accepted techniques often applied to stability and control...Air Force Institute of Technology (AU), Wright-Patterson...Air Force Institute of Technology (AU), Wright-Patterson...

1998-01-01T23:59:59.000Z

199

Application of CFD to Predict and Control Chemical and Biological Agent Dispersion in Buildings  

E-Print Network [OSTI]

1 Application of CFD to Predict and Control Chemical and Biological Agent Dispersion in Buildings Z, West Lafayette, IN 47907 Abstract Terrorist attack in buildings by chemical and biological agents (CBAs in an office building in order to find the best locations for CBA sensors and to develop effective ventilation

Chen, Qingyan "Yan"

200

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

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

Related Publications: Predicted thermochemistry for chemical conversions of 5-hydroxymethylfurfural Computational Studies of the Thermochemistry for Conversion of Glucose to...

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Dispersion modeling for prediction of emission factors for cattle feedyards  

E-Print Network [OSTI]

. , 45 SUMMARY AND CONCLUSIONS PROPOSED FUTURE RESEARCH . 47 . 49 REFERENCES APPENDICES APPENDIX A PREDICTED AVERAGE YEARLY CONCENTRATIONS OF PMio UTILIZING AMARILLO WEATHER DATA 51 54 . . 55 APPENDIX B PREDICTED AVERAGE YEARLY... CONCENTRATIONS OF PM)0 UTILIZING LUBBOCK WEATHER DATA 59 VII TABLE OF CONTENTS (Coutinued) Page APPENDIX C PREDICTED AVERAGE YEARLY CONCENTRATIONS OF PM|0 UTILIZING SAN ANGELO WEATHER DATA . . 63 APPENDIX D PREDICTED AVERAGE YEARLY CONCENTRATIONS OF PM|0...

Parnell, Sarah Elizabeth

2012-06-07T23:59:59.000Z

202

Forecasting a Moving Target: Ensemble Models for ILI Case Count Predictions Prithwish Chakraborty  

E-Print Network [OSTI]

with official flu estimates. We also compare the prediction accuracy between model-level fusion of differentForecasting a Moving Target: Ensemble Models for ILI Case Count Predictions Prithwish Chakraborty using neighbor- hood embedding to predict flu case counts. Comparing our proposed ensemble method

Ryder, Barbara G.

203

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...

204

Flow Noise Prediction and Control in Steam Piping Systems for Nuclear Power Plants  

Science Journals Connector (OSTI)

The flow noise of steam in pipe lines particularly in power plants is a major noise source and contributor to OSHA noise problems. The ability to predict flow noise levels is vital to efficient and economical noise control. Octave?band measurements of flow noise in the main steam piping system of a nuclear power plant were made. To determine the effect of velocity measurements were conducted for a wide range of velocities during plant start?up. Results in the form of plots of measured flow noise as a function of velocity were compared with limited data that have been recently published. An empirical formula for prediction of flow noise and corresponding design techniques for control of noise by proper pipe sizing have been developed. Alternate methods of noise control are reviewed.

F. H. Brittain; S. W. Giampapa

1973-01-01T23:59:59.000Z

205

NETL: Advanced NOx Emissions Control: Control Technology - Model for NOx  

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

Model for NOx Emissions in Biomass Cofiring Model for NOx Emissions in Biomass Cofiring Southern Research Institute is developing a validated tool or methodology to accurately and confidently design and optimize biomass-cofiring systems for full-scale utility boilers to produce the lowest NOX emissions and the least unburned carbon. The computer model will be validated through an extensive set of tests at the 6 MMBtu/hr pilot combustor in the Southern Company/Southern Research Institute Combustion Research Facility. Full-scale demonstration testing can be compared to the model for further validation. The project is designed to balance the development of a systematic and expansive database detailing the effects of cofiring parameters on NOx formation with the complementary modeling effort that will yield a capability to predict, and therefore optimize, NOx reductions by the selection of those parameters. The database of biomass cofiring results will be developed through an extensive set of pilot-scale tests at the Southern Company/Southern Research Institute Combustion Research Facility. The testing in this program will monitor NOx, LOI, and other emissions over a broad domain of biomass composition, coal quality, and cofiring injection configurations to quantify the dependence of NOx formation and LOI on these parameters. This database of cofiring cases will characterize an extensive suite of emissions and combustion properties for each of the fuel and injection configuration combinations tested.

206

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

E-Print Network [OSTI]

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

Schiavon, Stefano; Lee, Kwang Ho

2013-01-01T23:59:59.000Z

207

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

E-Print Network [OSTI]

This study investigates the degree to which the cumulative risk index predicted school readiness in a Head Start population. In general, the reviewed studies indicated the cumulative risk model was efficacious in predicting adverse developmental...

Rodriguez-Escobar, Olga Lydia

2009-05-15T23:59:59.000Z

208

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,...

209

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

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

and Validating a Next Generation Model-Based Controller for Fuel Efficient, Low Emissions Diesel Engines Demonstrating and Validating a Next Generation Model-Based Controller for...

210

Micro-grid energy dispatch optimization and predictive control algorithms; A UC Irvine case study  

Science Journals Connector (OSTI)

Abstract Distributed power and energy resources are now being used to meet the combined electric power, heating, and cooling demands of many buildings. The addition of on-site renewables and their accompanying intermittency and non-coincidence requires even greater dynamic performance from the distributed power and energy system. Load following generators, energy storage devices, and predictive energy management are increasingly important to achieve the simultaneous goals of increased efficiency, reduced emissions, and sustainable economics. This paper presents two optimization strategies for the dispatch of a multi-chiller cooling plant with cold-water thermal storage. The optimizations aim to reduce both costs and emissions while considering real operational constraints of a plant. The UC Irvine campus micro-grid operation between January 2009 and December 2013 serves as a case study for how improved utilization of energy storage can buffer demand transients, reduce costs and improve plant efficiency. A predictive control strategy which forecasts campus demands from weather predictions, optimizes the plant dispatch, and applies feedback control to modify the plant dispatch in real-time is compared to best-practices manual operation. The dispatch optimization and predictive control algorithms are shown to reduce annual utility bill costs by 12.0%, net energy costs by 3.61%, and improve energy efficiency by 1.56%.

Dustin McLarty; Carles Civit Sabate; Jack Brouwer; Faryar Jabbari

2015-01-01T23:59:59.000Z

211

Modelling and control of satellite formations  

E-Print Network [OSTI]

MODELLING AND CONTROL OF SATELLITE FORMATIONS A Dissertation by VEERA VENKATA SESHA SAI VADDI Submitted to the O±ce of Graduate Studies of Texas A&M University in partial ful¯llment of the requirements for the degree of DOCTOR OF PHILOSOPHY May 2003... Major Subject: Aerospace Engineering MODELLING AND CONTROL OF SATELLITE FORMATIONS A Dissertation by VEERA VENKATA SESHA SAI VADDI Submitted to Texas A&M University in partial ful¯llment of the requirements for the degree of DOCTOR OF PHILOSOPHY Approved...

Vaddi, Veera Venkata Sesha Sai

2004-09-30T23:59:59.000Z

212

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

E-Print Network [OSTI]

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

Paltsev, Sergey.

213

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

E-Print Network [OSTI]

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

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

214

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

E-Print Network [OSTI]

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

Babiker, Mustafa M.H.

215

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

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

Studies of the Thermochemistry for Conversion of Glucose to Levulinic Acid Predicted thermochemistry for chemical conversions of 5-hydroxymethylfurfural Catalyst: Nichols Romero...

216

Model Predictive Control of Residential Energy Systems Using  

E-Print Network [OSTI]

such as air con- ditioners and refrigerators, is elastic or schedulable. Therefore, an alternate, P. Braun (k) + ui2 (k) (1) where xi is the state of charge of the battery in kWh, ui1 is the battery charge , and the definitions of f and h are obvious from (1). We assume constraints on the battery capacity and charge

Knobloch,Jürgen

217

Mixed Integer Model Predictive Control of Multiple Shale Gas Wells.  

E-Print Network [OSTI]

?? Horizontal wells with multistage hydraulic fracturing are today the most important drilling technology for shale gas extraction. Considered unprofitable before, the production has now… (more)

Nordsveen, Espen T

2012-01-01T23:59:59.000Z

218

Fast Nonconvex Model Predictive Control for Commercial Refrigeration  

E-Print Network [OSTI]

its capabil- ity to minimize the total cost of energy for a commercial refrigeration system while multi-zone refrigeration system, consisting of several cooling units that share a common compressor. This corresponds roughly to 2% of the entire electricity consumption in the country. Refrigerated goods constitute

219

Embedded Online Optimization for Model Predictive Control at ...  

E-Print Network [OSTI]

for both interior-point and active-set methods using reduced floating-point arithmetic in field programmable gate arrays (FPGAs), reporting minor speed-ups or ...

2013-03-05T23:59:59.000Z

220

Control GIS and geo-information modelling  

Science Journals Connector (OSTI)

The contribution deals with the contextual design of spatial-temporal data, distinguishes three GIS level for the purposes of the regional development, land management and government and describes the role of the GIS Web services architecture that makes ... Keywords: control GIS, geo-information modelling, spatial decision support, spatial temporal approach, uncertainty

Dana Klimešová

2006-03-01T23:59:59.000Z

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

Matchstick: a room-to-room thermal model for predicting indoor temperature from wireless sensor data  

Science Journals Connector (OSTI)

In this paper we present a room-to-room thermal model used to accurately predict temperatures in residential buildings. We evaluate the accuracy of this model with ground truth data from four occupied family homes (two in the UK and two in the US). The ... Keywords: forced air, home automation, prediction, radiators, thermal modelling, underfloor heating

Carl Ellis; Mike Hazas; James Scott

2013-04-01T23:59:59.000Z

222

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

E-Print Network [OSTI]

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

Lloyd, Alun

223

Model Identification for Optimal Diesel Emissions Control  

SciTech Connect (OSTI)

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.

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

2013-06-20T23:59:59.000Z

224

Subspace predictive repetitive control to mitigate periodic loads on large scale wind turbines  

Science Journals Connector (OSTI)

Abstract Manufacturing and maintenance costs arising out of wind turbine dynamic loading are one of the largest bottlenecks in the roll-out of wind energy. Individual Pitch Control (IPC) is being researched for cost reduction through load alleviation; it poses a challenging mechatronic problem due to its multi-input, multi-output (MIMO) nature and actuation constraints related to the wear of pitch bearings. To address these issues, Subspace Predictive Repetitive Control (SPRC), a novel repetitive control strategy based on the subspace identification paradigm, is presented. First, the Markov parameters of the system are identified online in a recursive manner. These parameters are used to build up the lifted matrices needed to predict the output over the next period. From these matrices an adaptive repetitive control law is derived. To account for actuator limitations, the known shape of wind-induced disturbances is exploited to perform repetitive control in a reduced-dimension basis function subspace. The SPRC methodology is implemented on a high-fidelity numerical aeroelastic environment for wind turbines. Load reductions are achieved similar to those obtained with classical IPC approaches, while considerably limiting the frequency content of the actuator signals.

S.T. Navalkar; J.W. van Wingerden; E. van Solingen; T. Oomen; E. Pasterkamp; G.A.M. van Kuik

2014-01-01T23:59:59.000Z

225

An invisible axion model with controlled FCNCs at tree level  

E-Print Network [OSTI]

We derive the necessary conditions to build a class of invisible axion models with Flavor Changing Neutral Currents at tree-level controlled by the fermion mixing matrices and present an explicit model implementation. A horizontal Peccei-Quinn symmetry provides a solution to the strong CP problem via the Peccei-Quinn mechanism and predicts a cold dark mater candidate, the invisible axion or familon. The smallness of active neutrino masses can be explained via a type I seesaw mechanism, providing a dynamical origin for the heavy seesaw scale. The possibility to avoid the domain wall problem stands as one of the most interesting features of the type of models considered. Experimental limits relying on the axion-photon coupling, astrophysical considerations and familon searches in rare kaon and muon decays are discussed.

Alejandro Celis; Javier Fuentes-Martin; Hugo Serodio

2014-10-23T23:59:59.000Z

226

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

E-Print Network [OSTI]

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

Schiavon, Stefano; Lee, Kwang Ho

2012-01-01T23:59:59.000Z

227

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

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

for the area-specific model, and recalibrate confidence interval... predictive logis- tic regression ... Source: Montana, University of - Cooperative Wildlife Research Unit...

228

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

229

Ecological Modelling 120 (1999) 349358 Use of artificial neural networks for predicting rice crop  

E-Print Network [OSTI]

Ecological Modelling 120 (1999) 349­358 Use of artificial neural networks for predicting rice crop of artificial neural networks (ANN) in predicting presence or absence of flamingo damages from 11 variables B.V. All rights reserved. Keywords: Flamingos; Rice; Damage; Artificial neural networks; Prediction

Lek, Sovan

230

A Discrete Event Simulation Model For Unstructured Supervisory Control  

E-Print Network [OSTI]

A Discrete Event Simulation Model For Unstructured Supervisory Control Of Unmanned Vehicles Committee #12;2 A Discrete Event Simulation Model For Unstructured Supervisory Control Of Unmanned multipleoperator multiplevehicle discrete event simulation model (MOMUVDES) is developed which captures

Cummings, Mary "Missy"

231

Model-Driven development of automation and control applications: modeling and simulation of control sequences  

Science Journals Connector (OSTI)

The scope and responsibilities of control applications are increasing due to, for example, the emergence of industrial internet. To meet the challenge, model-driven development techniques have been in active research in the application domain. Simulations ...

Timo Vepsäläinen, Seppo Kuikka

2014-01-01T23:59:59.000Z

232

Prediction of demand trends of coking coal in China based on grey linear regression composition model  

Science Journals Connector (OSTI)

The scarce of coking coal resources in China results in its short supply. By establishing a grey linear regression composition model, this paper has greatly improved the inadequacy of grey system prediction model and regression analysis method in trend prediction and finished the prediction of demand trends of coking coal in China with this model. As result of the prediction, it is estimated that in the next decade, the demand for coking coal in China will experience a growth trend; China's demand for coking coal will reach more than 1.535 billion tons by 2015, reach the maximum of 1.639 billion tons by 2020 and drop in 2025.

Hai-Dong Zhou; Qiang Wu; Min Fang; Zhong-Bao Ren; Li-Fei Jin

2013-01-01T23:59:59.000Z

233

A simple model to predict train-induced vibration: theoretical formulation and experimental validation  

SciTech Connect (OSTI)

No suitable handy tool is available to predict train-induced vibration on environmental impact assessment. A simple prediction model is proposed which has been calibrated for high speed trains. The model input data are train characteristics, train speed and track properties; model output data are soil time-averaged velocity and velocity level. Model results have been compared with numerous vibration data retrieved from measurement campaigns led along the most important high-speed European rail tracks. Model performances have been tested by comparing measured and predicted vibration values.

Rossi, Federico; Nicolini, Andrea

2003-05-01T23:59:59.000Z

234

Hydrodynamic Model with Binary Particle Diameters to Predict Axial Voidage Profile in a CFB Combustor  

Science Journals Connector (OSTI)

A hydrodynamic model with binary particle diameters was developed to better predict axial voidage profile in a CFB combustor. In the model, the CFB is regarded as a superposition of two ... field data of voidage ...

J. J. Li; H. Zhang; H. R. Yang; Y. X. Wu…

2010-01-01T23:59:59.000Z

235

Application of Scale-Selective Data Assimilation to Regional Climate Modeling and Prediction  

Science Journals Connector (OSTI)

A method referred to as scale-selective data assimilation (SSDA) is designed to inject the large-scale components of the atmospheric circulation from a global model into a regional model to improve regional climate simulations and predictions. ...

Shiqiu Peng; Lian Xie; Bin Liu; Fredrick Semazzi

2010-04-01T23:59:59.000Z

236

Global nuclear material flow/control model  

SciTech Connect (OSTI)

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.

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

1997-10-01T23:59:59.000Z

237

StatREC: a graphical user interface tool for visual hypothesis testing of cost prediction models  

Science Journals Connector (OSTI)

Background: During the previous decades there has been noted a significantly increased research interest on the construction of prediction models for accurate estimation of software cost. Despite the development of sophisticated methodologies, ... Keywords: REC curves, graphical comparison, graphical user interface, permutation test, prediction models, software cost estimation

Nikolaos Mittas; Ioannis Mamalikidis; Lefteris Angelis

2012-09-01T23:59:59.000Z

238

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

E-Print Network [OSTI]

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

Emmerich, Michael

239

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

E-Print Network [OSTI]

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

Wisconsin at Madison, University of

240

Letters: Neural network based hybrid computing model for wind speed prediction  

Science Journals Connector (OSTI)

This paper proposes a Neural Network based hybrid computing model for wind speed prediction in renewable energy systems. Wind energy is one of the renewable energy sources which lower the cost of electricity production. Due to the fluctuation and nonlinearity ... Keywords: Hybrid Model, Multilayer Perceptron, Neural Networks, Self Organizing Maps, Wind Speed Prediction

K. Gnana Sheela; S. N. Deepa

2013-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Efficient Direct Multiple Shooting for Nonlinear Model Predictive ...  

E-Print Network [OSTI]

Jul 4, 2011 ... full SQP controller shows better reaction to the nonlinearity of the process. 418 ... In this setup, an exothermic reaction of x2(·) takes place in.

2011-07-04T23:59:59.000Z

242

Predictive Modeling of Large-Scale Commercial Water Desalination Plants: Data-Based Neural Network and Model-Based Process  

E-Print Network [OSTI]

Predictive Modeling of Large-Scale Commercial Water Desalination Plants: Data-Based Neural Network for developing predictive models for large-scale commercial water desalination plants by (1) a data (MSF) and reverse osmosis (RO) desalination plants in the world. Our resulting neural network

Liu, Y. A.

243

Radial forging force prediction through MR, ANN, and ANFIS models  

Science Journals Connector (OSTI)

The application of finite element method and intelligent systems techniques to predict the applied force during the radial forging process is studied. Radial forging is a unique process used for the precision forging of round and tubular components, ... Keywords: ANFIS, ANN, Forging force, MR, Radial forging

A. Azari, M. Poursina, D. Poursina

2014-09-01T23:59:59.000Z

244

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...

245

Modeling and adaptive control of indoor unmanned aerial vehicles  

E-Print Network [OSTI]

The operation of unmanned aerial vehicles (UAVs) in constrained indoor environments presents many unique challenges in control and planning. This thesis investigates modeling, adaptive control and trajectory optimization ...

Michini, Bernard (Bernard J.)

2009-01-01T23:59:59.000Z

246

A novel mathematical model for controllable near-field electrospinning  

SciTech Connect (OSTI)

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.

Ru, Changhai, E-mail: rchhai@gmail.com, E-mail: luojun@shu.edu.cn [College of Automation, Harbin Engineering University, Harbin 150001 (China) [College of Automation, Harbin Engineering University, Harbin 150001 (China); Robotics and Microsystems Center, Soochow University, Suzhou 215021 (China); Chen, Jie; Shao, Zhushuai [Robotics and Microsystems Center, Soochow University, Suzhou 215021 (China)] [Robotics and Microsystems Center, Soochow University, Suzhou 215021 (China); Pang, Ming [College of Automation, Harbin Engineering University, Harbin 150001 (China)] [College of Automation, Harbin Engineering University, Harbin 150001 (China); Luo, Jun, E-mail: rchhai@gmail.com, E-mail: luojun@shu.edu.cn [School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072 (China)] [School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072 (China)

2014-01-15T23:59:59.000Z

247

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

SciTech Connect (OSTI)

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.

Watney, W.L.

1992-01-01T23:59:59.000Z

248

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

E-Print Network [OSTI]

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

249

THE SPATIAL AGGREGATION LANGUAGE FOR MODELING AND CONTROLLING DISTRIBUTED  

E-Print Network [OSTI]

important science and engineering applications, such as predicting weather patterns, controlling, high-level components that make explicit use of domain-speci#12;c physical knowledge, such as metrics

Bailey-Kellogg, Chris

250

Comparison of Predictive Models for Photovoltaic Module Performance: Preprint  

SciTech Connect (OSTI)

This paper examines three models used to estimate the performance of photovoltaic (PV) modules when the irradiances and PV cell temperatures are known. The results presented here were obtained by comparing modeled and measured maximum power (Pm) for PV modules that rely on different technologies.

Marion, B.

2008-05-01T23:59:59.000Z

251

Energy price prediction multi-step ahead using hybrid model in the Brazilian market  

Science Journals Connector (OSTI)

Abstract This paper proposes a new hybrid approach for short-term energy price prediction. This approach combines auto-regressive integrated moving average (ARIMA) and neural network (NN) models in a cascaded structure and uses explanatory variables. A two step procedure is applied. In the first step, the selected explanatory variables are predicted. In the second one, the energy prices are forecasted by using the explanatory variables prediction. Further, the proposed model considers a multi-step ahead price prediction (12 weeks-ahead) and is applied to Brazilian market, which adopts a cost-based centralized dispatch with unique characteristics of price behavior. The results show good ability to predict spikes and satisfactory accuracy according to error measures and tail loss test when compared with traditional techniques. Thus, the model can be an attractive tool to mitigate risks in purchasing power.

José C. Reston Filho; Carolina de M. Affonso; Roberto C.L. de Oliveira

2014-01-01T23:59:59.000Z

252

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

E-Print Network [OSTI]

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

Boyer, Edmond

253

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

E-Print Network [OSTI]

EVALUATION OF NUMERICAL WEATHER PREDICTION IN MODELING CLOUD- RADIATION INTERACTIONS OVER.bnl.gov ABSTRACT Numerical weather prediction (NWP) is the basis for present-day weather forecasts, and NWP- and satellite- based observations over the Southern Great Plains to evaluate how well cloud

Johnson, Peter D.

254

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

E-Print Network [OSTI]

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

Hornof, Anthony

255

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

SciTech Connect (OSTI)

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

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

1998-07-01T23:59:59.000Z

256

Predictive models for power dissipation in optical transceivers  

E-Print Network [OSTI]

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

Butler, Katherine, 1981-

2004-01-01T23:59:59.000Z

257

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

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

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

258

Nuclear fusion control-oriented plasma current linear models  

Science Journals Connector (OSTI)

The control of plasma in nuclear fusion has been revealed as a promising application of Control Engineering, with increasing interest in the control community during last years. In this paper it is developed a control-oriented linear model for the control ...

Aitor J. Garrido; Izaskun Garrido; M. Goretti Sevillano; Mikel Alberdi; Modesto Amundarain; Oscar Barambones; Manuel De La Sen

2010-07-01T23:59:59.000Z

259

Connecting Peptide Physicochemical and Antimicrobial Properties by a Rational Prediction Model  

E-Print Network [OSTI]

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

Pompeu Fabra, Universitat

260

Spectral barotropic model for the prediction of synoptic currents in the open part of the ocean  

Science Journals Connector (OSTI)

We consider a quasigeostrophic spectral model used for the prediction of synoptic currents in the barotropic ocean. The spectral method is based on the expansion of the current function in a double series in cosi...

I. I. Karpatovich

2006-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

Use of Rough Sets and Spectral Data for Building Predictive Models of Reaction Rate Constants  

Science Journals Connector (OSTI)

A model for predicting the log of the rate constants for alkaline hydrolysis of organic esters has been developed with the use of gas-phase mid-infrared library spectra and a...

Collette, Timothy W; Szladow, Adam J

1994-01-01T23:59:59.000Z

262

Comparisons of Transport and Dispersion Model Predictions of the URBAN 2000 Field Experiment  

Science Journals Connector (OSTI)

The tracer releases of the “URBAN 2000” urban tracer and meteorological field experiment conducted in Salt Lake City, Utah, in October 2000 provided a wealth of data for comparison with the predictions of transport and dispersion models. ...

Steve Warner; Nathan Platt; James F. Heagy

2004-06-01T23:59:59.000Z

263

Evaluation of Precipitation from Numerical Weather Prediction Models and Satellites Using Values Retrieved from Radars  

Science Journals Connector (OSTI)

Precipitation is evaluated from two weather prediction models and satellites, taking radar-retrieved values as a reference. The domain is over the central and eastern United States, with hourly accumulated precipitation over 21 days for the ...

Slavko Vasi?; Charles A. Lin; Isztar Zawadzki; Olivier Bousquet; Diane Chaumont

2007-11-01T23:59:59.000Z

264

Pollution Control in a Manufacturing System Stochastic Models for Analysis and Control of Air Pollution  

E-Print Network [OSTI]

Pollution Control in a Manufacturing System Stochastic Models for Analysis and Control of Air models that can be used for controlling pollution in a manufacturing system. The models are developed. Introduction Pollution of air resulting from toxic wastes emitted by large manufacturing plants and power

Gosavi, Abhijit

265

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

E-Print Network [OSTI]

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

266

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

E-Print Network [OSTI]

1 Ventilation performance prediction for buildings: Model Assessment Qingyan Chena,b,* , Kisup Leeb building, but cannot provide detailed flow information in a room. The zonal model can be useful when a user ventilation systems for buildings requires a suitable model to assess system performance. The performance can

Chen, Qingyan "Yan"

267

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

E-Print Network [OSTI]

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

Carle, Georg

268

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

E-Print Network [OSTI]

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

269

Dynamic modeling and optimal control strategy of waste heat recovery Organic Rankine Cycles  

Science Journals Connector (OSTI)

Organic Rankine Cycles (ORCs) are particularly suitable for recovering energy from low-grade heat sources. This paper describes the behavior of a small-scale ORC used to recover energy from a variable flow rate and temperature waste heat source. A traditional static model is unable to predict transient behavior in a cycle with a varying thermal source, whereas this capability is essential for simulating an appropriate cycle control strategy during part-load operation and start and stop procedures. A dynamic model of the ORC is therefore proposed focusing specifically on the time-varying performance of the heat exchangers, the dynamics of the other components being of minor importance. Three different control strategies are proposed and compared. The simulation results show that a model predictive control strategy based on the steady-state optimization of the cycle under various conditions is the one showing the best results.

Sylvain Quoilin; Richard Aumann; Andreas Grill; Andreas Schuster; Vincent Lemort; Hartmut Spliethoff

2011-01-01T23:59:59.000Z

270

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

SciTech Connect (OSTI)

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.

Wenzel, Mike

2013-10-14T23:59:59.000Z

271

A mathematical model to predict leaching of hazardous inorganic wastes from solidified/stabilized waste forms  

E-Print Network [OSTI]

A MATHEMATICAL MODEL TO PREDICT LEACHING OF HAZARDOUS INORGANIC WASTES FROM SOLIDIFIED/STABILIZED WASTE FORMS A Thesis by KRISHAN SABHARWAL Submitted to the Office of Graduate Studies of Texas AkM University in partial fulfillment...A MATHEMATICAL MODEL TO PREDICT LEACHING OF HAZARDOUS INORGANIC WASTES FROM SOLIDIFIED/STABILIZED WASTE FORMS A Thesis by KRISHAN SABHARWAL Submitted to the Office of Graduate Studies of Texas AkM University in partial fulfillment...

Sabharwal, Krishan

2012-06-07T23:59:59.000Z

272

NETL: Predictive Modeling and Evaluation - Evaluation of the Emission,  

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

Evaluation of the Emission, Transport, and Deposition of Mercury, Arsenic, and Fine Particulate Matter from Coal Based Power Plants in the Ohio River Valley Region Evaluation of the Emission, Transport, and Deposition of Mercury, Arsenic, and Fine Particulate Matter from Coal Based Power Plants in the Ohio River Valley Region Ohio University, in collaboration with CONSOL Energy, Advanced Technology Systems, Inc (ATS) and Atmospheric Environmental Research, Inc. (AER) as subcontractors will evaluate the impact of emissions from coal-fired power plants in the Ohio River Valley region as they relate to the transport and deposition of mercury, arsenic, and associated fine particulate matter. This evaluation will involve two interrelated areas of effort: regional-scale modeling analysis and ambient air monitoring. The scope of work for the modeling analysis will include (1) development of updated inventories of mercury and arsenic emissions from coal plants and other important sources in the modeled domain; (2) adapting an existing 3-D atmospheric chemical transport model to incorporate recent advancements in the understanding of mercury transformations in the atmosphere; (3) analyses of the flux of Hg0, RGM, arsenic, and fine particulate matter in the different sectors of the study region to identify key transport mechanisms; (4) comparison of cross correlations between species from the model results to observations in order to evaluate characteristics of specific air masses associated with long-range transport from a specified source region; and (5) evaluation of the sensitivity of these correlations to emissions from regions along the transport path. This will be accomplished by multiple model runs with emissions simulations switched on and off from the various source regions.

273

Risk prediction models for melanoma: A systematic review  

E-Print Network [OSTI]

and Armstrong (35) point out, if a screening programme is to be directed towards a high risk group and is to have an impact on the disease as a whole, three criteria must be satisfied in addition to those for all screening programmes (41): People at high risk... :1000129. 35. English, DR, Armstrong, BK. Identifying people at high risk of cutaneous malignant melanoma: Results from a case-control study in Western Australia. Br. Med. J. (Clin. Res. Ed). 1988; 296: 1285–1288. 36. Amir, E, Freedman, OC, Seruga...

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

2014-06-03T23:59:59.000Z

274

Bayesian System Identification and Response Predictions Robust to Modeling Uncertainty  

E-Print Network [OSTI]

uncertainties, both prior (e.g. design based on reliability or life-cycle cost optimization), & posterior (e reliability of treating excitation uncertainty under wind and earthquakes (random vibrations, stochastic in the development and use of Bayesian methods in the last decade or so · Allows analysis that is robust to modeling

Beck, James L.

275

Lurking Pathway Prediction And Pathway ODE Model Dynamic Analysis  

E-Print Network [OSTI]

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

Zhang, Rengjing

2013-11-18T23:59:59.000Z

276

Should we believe model predictions of future climate change?  

E-Print Network [OSTI]

equations are derived from first principles (e.g. equations of motion, and conservation of energy, mass deficiencies in the attempt to provide useful information to the public and policy-makers. Keywords: climate to communicate what we know and what is uncertain about future climate change? Why are climate model projections

Fischlin, Andreas

277

Design of spatial experiments: Model fitting and prediction  

SciTech Connect (OSTI)

The main objective of the paper is to describe and develop model oriented methods and algorithms for the design of spatial experiments. Unlike many other publications in this area, the approach proposed here is essentially based on the ideas of convex design theory.

Fedorov, V.V.

1996-03-01T23:59:59.000Z

278

An electrochemical model for prediction of CO{sub 2} corrosion  

SciTech Connect (OSTI)

A predictive model of CO{sub 2} corrosion, based on modelling of individual electrochemical reactions occurring in a water CO{sub 2} system, is presented. The model takes into account the following electrochemical reactions: hydrogen ion reduction, carbonic acid reduction, direct water reduction, oxygen reduction and anodic dissolution of iron. The required electrochemical parameters in the model such as: exchange current densities and Tafel slopes for different reactions are determined from experiments conducted in glass cells. In those experiments the corrosion process was monitored with the following electrochemical measuring techniques: polarization resistance, potentiodynamic sweep, electrochemical impedance in addition to weight loss measurements. The model has been calibrated for two different mild steels over a wide range of parameters: t = 20--80C, pH 3--6, p(CO{sub 2})= 0--1 bar, {omega} = 0--5,000 rpm. In its present stage of development the model applies for the case of uniform corrosion with no protective films present. Performance of the model is validated by comparing the predictions with results from independent loop experiments. The predictions made with the present model were also compared with performance of other CO{sub 2} corrosion prediction models. Compared to the previous largely empirical models, the present model gives a much clearer picture of the corrosion mechanisms and of the effect of key parameters.

Nesic, S.; Postlethwaite, J. [Inst. for Energiteknikk, Kjeller (Norway); Olsen, S. [Statoil, Trondheim (Norway)

1995-10-01T23:59:59.000Z

279

Predictions from an Ising-like Statistical Mechanical Model on the Dynamic and Thermodynamic Effects of Protein Surface Electrostatics  

Science Journals Connector (OSTI)

Predictions from an Ising-like Statistical Mechanical Model on the Dynamic and Thermodynamic Effects of Protein Surface Electrostatics ...

Athi N. Naganathan

2012-10-05T23:59:59.000Z

280

Predictive Models of Biohydrogen and Biomethane Production Based on the Compositional and Structural Features of Lignocellulosic Materials  

Science Journals Connector (OSTI)

Predictive Models of Biohydrogen and Biomethane Production Based on the Compositional and Structural Features of Lignocellulosic Materials ...

Florian Monlau; Cecilia Sambusiti; Abdellatif Barakat; Xin Mei Guo; Eric Latrille; Eric Trably; Jean-Philippe Steyer; Hélène Carrere

2012-10-10T23:59:59.000Z

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Fuzzy Control Strategies in Human Operator and Sport Modeling  

E-Print Network [OSTI]

The motivation behind mathematically modeling the human operator is to help explain the response characteristics of the complex dynamical system including the human manual controller. In this paper, we present two different fuzzy logic strategies for human operator and sport modeling: fixed fuzzy-logic inference control and adaptive fuzzy-logic control, including neuro-fuzzy-fractal control. As an application of the presented fuzzy strategies, we present a fuzzy-control based tennis simulator.

Ivancevic, Tijana T; Markovic, Sasa

2009-01-01T23:59:59.000Z

282

A soil moisture availability model for crop stress prediction  

E-Print Network [OSTI]

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

Gay, Roger Franklin

1983-01-01T23:59:59.000Z

283

Model-based Controllers for Semi-active Control  

E-Print Network [OSTI]

damper Base isolation TLCD Semi-active Control Active mass driver Active tendon Variable orifice damper/13/2012Page 11 Linearized explicit approximation Small perturbations Accuracy of the assumed rappresentation

284

Feedback Control RealTime Scheduling: Framework, Modeling, and Algorithms *  

E-Print Network [OSTI]

1 Feedback Control Real­Time Scheduling: Framework, Modeling, and Algorithms * Chenyang Lu John A}@virginia.edu Abstract This paper presents a feedback control real­time scheduling (FCS) framework for adaptive real. In particular, we establish a dynamic model and performance analysis of several feedback control scheduling

Son, Sang H.

285

Feedback Control Real-Time Scheduling: Framework, Modeling, and Algorithms*  

E-Print Network [OSTI]

1 Feedback Control Real-Time Scheduling: Framework, Modeling, and Algorithms* Chenyang Lu John A}@virginia.edu Abstract This paper presents a feedback control real-time scheduling (FCS) framework for adaptive real. In particular, we establish a dynamic model and performance analysis of several feedback control scheduling

Son, Sang H.

286

Topics in Modeling, Control, and Implementation in Automotive Systems  

E-Print Network [OSTI]

on inclusion of the dynamics of load transfer, which are of importance in active yaw-control and rollTopics in Modeling, Control, and Implementation in Automotive Systems #12;#12;Topics in Modeling, Control, and Implementation in Automotive Systems Magnus Gäfvert Lund 2003 #12;To my Mother (1943 ­ 1995

287

An electrochemical model for prediction of corrosion of mild steel in aqueous carbon dioxide solutions  

SciTech Connect (OSTI)

A predictive model was developed for uniform carbon dioxide corrosion, based on modeling of individual electrochemical reactions in a water-CO{sub 2} system. The model takes into account the electrochemical reactions of hydrogen ion reduction, carbonic acid reduction, direct water reduction, oxygen reduction, and anodic dissolution of iron. The required electrochemical parameters (e.g., exchange current densities and Tafel slopes) for different reactions were determined from experiments conducted in glass cells. The corrosion process was monitored using polarization resistance, potentiodynamic sweep, electrochemical impedance, and weight-loss measurements. The model was calibrated for two mild steels over a range of parameters: temperature (t) = 20 C to 80 C, pH = 3 to 6, partial pressure of CO{sub 2} (P{sub CO{sub 2}}) = 0 bar to 1 bar (0 kPa to 100 kPa), and {omega} = 0 rpm to 5,000 rpm (v{sub p} = 0 m/s to 2.5 m/s). The model was applicable for uniform corrosion with no protective films present. Performance of the model was validated by comparing predictions to results from independent loop experiments. Predictions also were compared to those of other CO{sub 2} corrosion prediction models. Compared to the previous largely empirical models, the model gave a clearer picture of the corrosion mechanisms by considering the effects of pH, temperature, and solution flow rate on the participating anodic and cathodic reactions.

Nesic, S. [Inst. for Energiteknikk, Kjeller (Norway); Postlethwaite, J. [Univ. of Saskatchewan, Saskatoon (Canada); Olsen, S. [Statoil, Trondheim (Norway)

1996-04-01T23:59:59.000Z

288

In-situ prediction on sensor networks using distributed multiple linear regression models  

E-Print Network [OSTI]

Within sensor networks for environmental monitoring, a class of problems exists that requires in-situ control and modeling. In this thesis, we provide a solution to these problems, enabling model-driven computation where ...

Basha, Elizabeth (Elizabeth Ann)

2010-01-01T23:59:59.000Z

289

Intercomparison of Single-Column Numerical Models for the Prediction of Radiation Fog  

E-Print Network [OSTI]

layers of the atmosphere. Current NWP models poorly forecast the life cycle of fog, and improved NWP models exist in the surface boundary layer before the fog onset, particularly in cases with light winds before improving the analysis and prediction of fog (e.g., Benjamin et al. 2004; Fowler et al. 2006

Ribes, Aurélien

290

CROSS SHORE SANDBAR MIGRATION PREDICTED BY A TIME DOMAIN BOUSSINESQ MODEL INCORPORATING  

E-Print Network [OSTI]

CROSS SHORE SANDBAR MIGRATION PREDICTED BY A TIME DOMAIN BOUSSINESQ MODEL INCORPORATING UNDERTOW Wen Long1 , James T. Kirby2 and T.-J. Hsu3 An existing Boussinesq wave model is modified and erosional cross-shore sediment transport processes. INTRODUCTION Long and Kirby (2003) have used Boussinesq

Kirby, James T.

291

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

E-Print Network [OSTI]

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

Chaubey, Indrajeet

292

User-click Modeling for Understanding and Predicting Search-behavior  

E-Print Network [OSTI]

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

Yang, Qiang

293

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

E-Print Network [OSTI]

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

294

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

E-Print Network [OSTI]

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

Herbert, Bruce

295

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

E-Print Network [OSTI]

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

Ritchie, Robert

296

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

Broader source: Energy.gov [DOE]

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

297

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

E-Print Network [OSTI]

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

298

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

E-Print Network [OSTI]

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

Weston, Ken

299

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

E-Print Network [OSTI]

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

Istrail, Sorin

300

Comparison of the predictions of two models with dose measurements in a  

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

Comparison of the predictions of two models with dose measurements in a Comparison of the predictions of two models with dose measurements in a case of children exposed to the emissions of a lead smelter Title Comparison of the predictions of two models with dose measurements in a case of children exposed to the emissions of a lead smelter Publication Type Journal Article LBNL Report Number LBNL-2397E Year of Publication 2009 Authors Bonnard, Roseline, and Thomas E. McKone Journal Journal of Human and Environmental Risk Assessment Volume 15 Issue 6 Pagination 1203-1226 ISSN 1080-7039 Keywords environmental chemistry, exposure & risk group, exposure and health effects, exposure assessment, ieubk, indoor environment department, lead, multimedia models, probabilistic risk assessment Abstract 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 improvedin 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.

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While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Control Oriented Dynamic Modeling of a Turbocharged Diesel Engine  

Science Journals Connector (OSTI)

To build a precise model is a key issue in fulfilling on optimal control of the turbocharged diesel engine. Meanvalue model has been extensively used for engine control, but neglects the scavenging efficiency. On the basis of carefully considering air-fuel ... Keywords: Diesel engine, mean-value model, AFR

Haiyan Wang; Jundong Zhang

2006-10-01T23:59:59.000Z

302

Development and validation of regression models to predict monthly heating demand for residential buildings  

Science Journals Connector (OSTI)

The present research work concerns development of regression models to predict the monthly heating demand for single-family residential sector in temperate climates, with the aim to be used by architects or design engineers as support tools in the very first stage of their projects in finding efficiently energetic solutions. Another interest to use such simplified models is to make it possible a very quick parametric study in order to optimize the building structure versus environmental or economic criteria. All the energy prediction models were based on an extended database obtained by dynamic simulations for 16 major cities of France. The inputs for the regression models are the building shape factor, the building envelope U-value, the window to floor area ratio, the building time constant and the climate which is defined as function of the sol-air temperature and heating set-point. If the neural network (NN) methods could give precise representations in predicting energy use, with the advantage that they are capable of adjusting themselves to unexpected pattern changes in the incoming data, the multiple regression analysis was also found to be an efficient method, nevertheless with the requirement that an extended database should be used for the regression. The validation is probably the most important level when trying to find prediction models, so 270 different scenarios are analysed in this research work for different inputs of the models. It has been established that the energy equations obtained can do predictions quite well, a maximum deviation between the predicted and the simulated is noticed to be 5.1% for Nice climate, with an average error of 2%. In this paper, we also show that is possible to predict the building heating demand even for more complex scenarios, when the construction is adjacent to non-heated spaces, basements or roof attics.

Tiberiu Catalina; Joseph Virgone; Eric Blanco

2008-01-01T23:59:59.000Z

303

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

E-Print Network [OSTI]

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

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

2014-04-14T23:59:59.000Z

304

Extension of NORSOK CO2 corrosion prediction model for elbow geometry  

Science Journals Connector (OSTI)

Internal corrosion of flowlines and pipelines is inevitable when transporting oil and gas that contains corrosive species. The consequences of corrosion such as material failure, loss of production, plant shutdown, and environmental pollution result in extra cost that negatively affect the project economics. Early prediction of corrosion severity is, therefore, very important to propose proper measures to avoid or eliminate corrosion. The prediction is normally carried on using a selected model for corrosion prediction. One of these models is NORSOK model, an empirical model developed by NORSOK for CO2 corrosion prediction in straight pipes. Norsk Sokkels Konkuranseposisjon or, in English, The Competitive Standing of the Norwegian Offshore Sector (NORSOK) is number of standards developed by Norwegian industry groups covering different topics that related to offshore industry. In this paper, NORSOK model has been modified to make it applicable to elbows geometries by introducing the equivalent length concept. A friendly graphical user interface computational package is developed for corrosion prediction in both straight pipes and elbows. The package is validated against measured data and acceptable accuracy is attained.

Mysara Eissa Mohyaldin; Noaman Elkhatib; Mokhtar Che Ismail

2013-01-01T23:59:59.000Z

305

Artificial Neural Network Meta Models To Enhance the Prediction and Consistency of Multiphase Reactor Correlations  

Science Journals Connector (OSTI)

Artificial Neural Network Meta Models To Enhance the Prediction and Consistency of Multiphase Reactor Correlations ... Artificial neural networks (ANNs), as correlation tools, have gained wide acceptance in the field because of their inherent ability to map nonlinear relationships that tie up independent variables (either as dimensional inputs, e.g., pressure, diameter, etc., or as dimensionless inputs, e.g., Reynolds, Weber, and Froude numbers, etc.) to the reactor characteristics to be predicted, i.e., dimensional or dimensionless output. ...

Laurentiu A. Tarca; Bernard P. A. Grandjean; Faïçal Larachi

2003-03-19T23:59:59.000Z

306

Prediction modeling of physiological responses and human performance in the heat  

Science Journals Connector (OSTI)

Over the last two decades, our laboratory has been establishing the data base and developing a series of predictive equations for deep body temperature, heart rate and sweat loss responses of clothed soldiers performing physical work at various environmental extremes. Individual predictive equations for rectal temperature, heart rate and sweat loss as a function of the physical work intensity, environmental conditions and particular clothing ensemble have been published in the open literature. In addition, important modifying factors such as energy expenditure, state of heat acclimation and solar heat load have been evaluated and appropriate predictive equations developed. Currently, we have developed a comprehensive model which is programmed on a Hewlett-Packard 41 CV hand held calculator. The primary physiological inputs are deep body (rectal) temperature and sweat loss while the predicted outputs are the expected physical work-rest cycle, the maximum single physical work time if appropriate, and the associated water requirements. This paper presents the mathematical basis employed in the development of the various individual predictive equations of our heat stress model. In addition, our current heat stress prediction model as programmed on the HP 41 CV is discussed from the standpoint of propriety in meeting the Army's needs and therefore assisting in military mission accomplishment.

Kent B. Pandolf; Leander A. Stroschein; Lawrence L. Drolet; Richard R. Gonzalez; Michael N. Sawka

1986-01-01T23:59:59.000Z

307

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

E-Print Network [OSTI]

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

Paris-Sud XI, Université de

308

Modeling Combustion Control for High Power Diesel Mode Switching  

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

and Emissions Research Conference 2010 Modeling Combustion Control for High Power Diesel Mode Switching P-20 Motivation * High power LTC-diesel mode operation * Transient...

309

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

Office of Science (SC) Website

Predictive Theory and Modeling 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 Peer Review Policies EFRCs FOA Applications from Universities and Other Research Institutions Construction Review EPSCoR DOE Office of Science Graduate Fellowship (DOE SCGF) External link Early Career Research Program Basic Energy Sciences Advisory Committee (BESAC) News & Resources Contact Information Basic Energy Sciences U.S. Department of Energy SC-22/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-3081 F: (301) 903-6594 E: sc.bes@science.doe.gov More Information » Funding Opportunities Predictive Theory and Modeling

310

A predictive model for the combustion process in dual fuel engines  

SciTech Connect (OSTI)

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

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

1995-12-31T23:59:59.000Z

311

Comparison of model predicted to observed winds in the coastal zone  

SciTech Connect (OSTI)

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

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

1982-06-01T23:59:59.000Z

312

Artificial neural network models for predicting condition of offshore oil and gas pipelines  

Science Journals Connector (OSTI)

Abstract Pipelines daily transport and distribute huge amounts of oil and gas across the world. They are considered the safest method of transporting oil and gas because of their limited number of failures. However, pipelines are subject to deterioration and degradation. It is therefore important that pipelines be effectively monitored to optimize their operation and to reduce their failures to an acceptable safety limit. Numerous models have been developed recently to predict pipeline conditions. Nevertheless, most of these models have used corrosion features alone to assess the condition of pipelines. Hence, this paper presents the development of models that evaluate and predict the condition of offshore oil and gas pipelines based on several factors besides corrosion. The models were developed using artificial neural network (ANN) technique based on historical inspection data collected from three existing offshore oil and gas pipelines in Qatar. The models were able to successfully predict pipeline conditions with an average percent validity above 97% when applied to the validation data set. The models are expected to help pipeline operators to assess and predict the condition of existing oil and gas pipelines and hence prioritize the planning of their inspection and rehabilitation.

Mohammed S. El-Abbasy; Ahmed Senouci; Tarek Zayed; Farid Mirahadi; Laya Parvizsedghy

2014-01-01T23:59:59.000Z

313

Modeling control room crews for accident sequence analysis  

E-Print Network [OSTI]

This report describes a systems-based operating crew model designed to simulate the behavior of an nuclear power plant control room crew during an accident scenario. This model can lead to an improved treatment of potential ...

Huang, Y. (Yuhao)

1991-01-01T23:59:59.000Z

314

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

SciTech Connect (OSTI)

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 fouling). In parallel, an MPC solution was initially developed using ideal sensing to optimize the plant operation during startup pre-heating as well as steady state and transient operation under normal high-pressure conditions, e.g. part-load, base-load, load transition and fuel changes. The MPC simulation studies showed significant improvements both for startup pre-heating and for normal operation. Finally, the EKF and MPC solutions were coupled to achieve the integrated sensing and control solution and its performance was studied through extensive steady state and transient simulations in the presence of sensor and modeling errors. The results of each task in the program and overall conclusions are summarized in this final report.

Aditya Kumar

2010-12-30T23:59:59.000Z

315

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

SciTech Connect (OSTI)

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.

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

2011-12-05T23:59:59.000Z

316

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

SciTech Connect (OSTI)

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

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

1980-01-01T23:59:59.000Z

317

Smart Structures: Model Development and Control Applications  

E-Print Network [OSTI]

advances in material science have produced a class of systems termed smart, intelligent or adaptive; 1 Introduction Increased demands for high performance control design in combination with recent are dictated by the design requirements for the system. For aeronautic and aerospace systems, control

318

Transformer Thermal Modeling: Improving Reliability Using Data Quality Control  

E-Print Network [OSTI]

1 Transformer Thermal Modeling: Improving Reliability Using Data Quality Control Daniel J. Tylavsky--Eventually all large transformers will be dynamically loaded using models updated regularly from field measured data. Models obtained from measured data give more accurate results than models based on transformer

319

Modeling and Control of High-Velocity Oxygen-Fuel (HVOF) Thermal Spray: A Tutorial Review  

E-Print Network [OSTI]

vs. Fuzzy Logic: Simple Tools to Predict and Control Complexfuzzy logic (Ref 73, 74). For the HVOF thermal spray process, a feedback control

Li, Mingheng; Christofides, Panagiotis D.

2009-01-01T23:59:59.000Z

320

Integrated Modeling and Design of Nonlinear Control Systems  

E-Print Network [OSTI]

Integrated Modeling and Design of Nonlinear Control Systems Gilmer L. Blankenship Harry G. Kwatny building, simulation, control system design and real time implementation. Software Environment Overview: A summary description of a symbolic computing environment for nonlinear control system design is provided

Kwatny, Harry G.

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

PROCESS MODELING AND CONTROL The Department of Chemical Engineering  

E-Print Network [OSTI]

) · S. Ziaii ­ CO2 absorption process modeling and control/power plant energy integration (Joint research in our department #12;· Ensure safe plant operation · Meet product specifications · Optimize/Control · B. Gill ­ Virtual sensors in etch processes (Texas Instruments) · X. Jiang ­ Controller performance

Lightsey, Glenn

322

A STOCHASTIC CONTROL MODEL OF INVESTMENT, PRODUCTION AND CONSUMPTION  

E-Print Network [OSTI]

A STOCHASTIC CONTROL MODEL OF INVESTMENT, PRODUCTION AND CONSUMPTION BY WENDELL H. FLEMING is to choose investment and consumption controls which maximize total expected discounted HARA utility of consumption. Optimal control policies are found using the method of dynamic programming. In case

Pang, Tao

323

TRBAC: A temporal role-based access control model  

Science Journals Connector (OSTI)

Role-based access control (RBAC) models are receiving increasing attention as a generalized approach to access control. Roles may be available to users at certain time periods, and unavailable at others. Moreover, there can be temporal dependencies among ... Keywords: Role triggers, role-based access control, temporal constraints

Elisa Bertino; Piero Andrea Bonatti; Elena Ferrari

2001-08-01T23:59:59.000Z

324

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

SciTech Connect (OSTI)

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

Lovley, Derek R.

2012-10-31T23:59:59.000Z

325

Modeling a Wind Turbine System Using DFIG and Realization of Current Control on the Model with Fuzzy Logic Controller  

Science Journals Connector (OSTI)

In this work, the modeling of wind turbine systems applying Doubly Fed Induction Generator is proposed. The mathematical model and control are investigated by analyzing theory and simulating performed in LabVI...

Ho-Ling Fu; Huynh Thanh Thien

2014-01-01T23:59:59.000Z

326

Identification and Control Problems in Petroleum and Groundwater Modeling \\Lambda  

E-Print Network [OSTI]

Identification and Control Problems in Petroleum and Groundwater Modeling \\Lambda R.E. Ewing, y , M.S. Pilant, y J.G. Wade, z and A.T. Watson x Abstract The petroleum industry has well­established partial differential equation models for multi­phase fluid flow through porous media, but the use of control

Ewing, Richard E.

327

Model based rail pressure control of GDI engine  

Science Journals Connector (OSTI)

This paper proposes a model-based rail pressure control (RPC) scheme for GDI engines. First, a control-oriented first-principle physics model is established for the rail pressure system. The backstepping technique is then used to derive a non-linear controller with guaranteed stability. For an engineering application, some compensations and corrections are further considered, such as input shaping, non-linear correction, anti-windup of integrator, battery voltage correction, etc. Finally, the proposed rail pressure controller is tested on the pump test rig and engine test bench. The results show the control performance is satisfactory.

Jialing Li; Pengyuan Sun; Tonghao Song; Jun Li; Baiyu Xin

2013-01-01T23:59:59.000Z

328

Flow control techniques for real-time media applications in best-effort networks using fluid models  

E-Print Network [OSTI]

at the application layer. An end-to-end ?uid model is used, including the source bu?er, the network and the destination bu?er. Traditional con- trol techniques, along with more advanced adaptive predictive control methods, are considered in order to provide... OF THE END-TO-END FLOW TRANSPORT SYSTEM : : : : : : : : : : : : : : : : : : : : : : 25 A. Source Bu?er Model . . . . . . . . . . . . . . . . . . . . . 25 B. Network Dynamic Model . . . . . . . . . . . . . . . . . . . 27 1. Time-Varying Time Delay Model...

Konstantinou, Apostolos

2004-11-15T23:59:59.000Z

329

UAV Cooperative Control with Stochastic Risk Models  

E-Print Network [OSTI]

Risk and reward are fundamental concepts in the cooperative control of unmanned systems. This paper focuses on a constructive relationship between a cooperative planner and a learner in order to mitigate the learning risk ...

Geramifard, Alborz

330

Dynamic Modelling and Control of MEA.  

E-Print Network [OSTI]

??Greenhouse gas (GHG) emission control has been extensively studied over the past decade. One GHG mitigation alternative is post-combustion carbon dioxide (CO2) capture using chemical… (more)

Nittaya, Thanita

2014-01-01T23:59:59.000Z

331

Subtask 2.4 - Integration and Synthesis in Climate Change Predictive Modeling  

SciTech Connect (OSTI)

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.

Jaroslav Solc

2009-06-01T23:59:59.000Z

332

The impact of global nuclear mass model uncertainties on $r$-process abundance predictions  

E-Print Network [OSTI]

Rapid neutron capture or `$r$-process' nucleosynthesis may be responsible for half the production of heavy elements above iron on the periodic table. Masses are one of the most important nuclear physics ingredients that go into calculations of $r$-process nucleosynthesis as they enter into the calculations of reaction rates, decay rates, branching ratios and Q-values. We explore the impact of uncertainties in three nuclear mass models on $r$-process abundances by performing global monte carlo simulations. We show that root-mean-square (rms) errors of current mass models are large so that current $r$-process predictions are insufficient in predicting features found in solar residuals and in $r$-process enhanced metal poor stars. We conclude that the reduction of global rms errors below $100$ keV will allow for more robust $r$-process predictions.

Mumpower, M; Aprahamian, A

2014-01-01T23:59:59.000Z

333

Prediction of Ice Crystal Number in Community Atmospheric Model (CAM3.0)  

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

Prediction of Ice Crystal Number in Community Atmospheric Model (CAM3.0) Prediction of Ice Crystal Number in Community Atmospheric Model (CAM3.0) Liu, Xiaohong Pacific Northwest National Laboratory Ghan, Steven Pacific Northwest National Laboratory Wang, M University of Michigan Penner, Joyce University of Michigan Category: Modeling A prognostic equation of ice crystal number concentrations is implemented in the Community Atmospheric Model (CAM3.0) with the aim to study the aerosol effects on climate through changing the ice cloud properties. The microphysical processes affecting the ice number concentration include ice nucleation, secondary production of crystals, and the conversion of ice to snow. For ice nucleation process, Liu and Penner (2005) parameterization of homogeneous nucleation of sulfate and heterogeneous immersion nucleation on

334

Comparison of predictions of the Hybrid Plume Dispersion Model with observations at the Kincaid power plant  

Science Journals Connector (OSTI)

The Hybrid Plume Dispersion Model (HPDM) has been evaluated with observations from a field experiment at the Kincaid power plant. HPDM is a dispersion model for buoyant plumes that employs parameterisations of boundary-layer wind, temperature, and turbulence profiles and Lagrangian time-scales. The model accounts for the bimodal distribution of turbulent velocities in the convective boundary layer and contains an algorithm for calculating the lofting of a buoyant plume against a capping inversion. The model predictions of maximum plume centreline concentrations show a mean bias of less than l0%, a typical error that is about 50% of the mean, and a correlation of about 0.5.

S.R. Hanna; J.C. Chang

1995-01-01T23:59:59.000Z

335

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

E-Print Network [OSTI]

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

Politécnica de Madrid, Universidad

336

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

E-Print Network [OSTI]

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

Paris-Sud XI, Université de

337

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

E-Print Network [OSTI]

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

338

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

E-Print Network [OSTI]

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

Kuzmanov, Georgi

339

A Predictive Model of Bacterial Foraging by Means of Freely Released Extracellular Enzymes  

E-Print Network [OSTI]

A Predictive Model of Bacterial Foraging by Means of Freely Released Extracellular Enzymes Y T Extracellular enzymes are important agents for microbial foraging and material cycling in diverse natural immobile microbe, of freely releasing extracellular enzymes into a fluid- bathed, stable matrix of both

Jumars, Pete

340

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

E-Print Network [OSTI]

expansion near the Sun and the solar wind speed observed at earth was first noted by Levine, AltschulerDiscrepancies in the Prediction of Solar Wind using Potential Field Source Surface Model between the magnetic flux tube expansion factor (FTE) at the source surface and the solar wind speed

Zhao, Xuepu

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology  

Science Journals Connector (OSTI)

...calibration methods [22]. 4. A mini-review The adoption of POM...explicitly refer to POM. This mini-review shows that POM can be...ecology than captured by our mini-review: many highly predictive...model in this field includes a grid of cells that can be empty or...

2012-01-01T23:59:59.000Z

342

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

E-Print Network [OSTI]

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

Herr, Hugh

343

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

E-Print Network [OSTI]

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

McLachlan, Geoff

344

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

E-Print Network [OSTI]

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

Martín, Pino

345

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

E-Print Network [OSTI]

ventilation rate due to the pulsating flow and eddy penetration of single-sided, wind-driven natural Normal to the opening q Fluctuating flow rate e Eddy penetration Wang, H. and Chen, Q. 2012. "A new buildings. A new empirical model was developed that can predict the mean ventilation rate and fluctuating

Chen, Qingyan "Yan"

346

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

E-Print Network [OSTI]

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

Fernandez, Thomas

347

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

E-Print Network [OSTI]

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

348

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

E-Print Network [OSTI]

Model-predicted distribution of wind-induced internal wave energy in the world's oceans Naoki 9 July 2008; published 30 September 2008. [1] The distribution of wind-induced internal wave energy-scaled kinetic energy are all consistent with the available observations in the regions of significant wind

Miami, University of

349

C H A P T E R Patch-based Models to Predict  

E-Print Network [OSTI]

3 2 7 C H A P T E R 26 Patch-based Models to Predict Species Occurrence: Lessons from Salmonid localized peaks of abundance (Maurer 1999). This is particularly obvi- ous in stream ecosystems, where patch. To be most useful, patches should be clearly defined by associations between a biological response (e.g., re

350

Dasatinib (BMS-354825) Pharmacokinetics and Pharmacodynamic Biomarkers in Animal Models Predict Optimal Clinical Exposure  

Science Journals Connector (OSTI)

...Bristol-Myers Squibb Company, Princeton, New Jersey The costs...inhibition correlated with the plasma levels of dasatinib in...inhibition correlated with the plasma levels of dasatinib in...modeling predicted that the plasma concentration of dasatinib...Bristol-Myers Squibb Company, Princeton, New Jersey 08543...

Feng R. Luo; Zheng Yang; Amy Camuso; Richard Smykla; Kelly McGlinchey; Krista Fager; Christine Flefleh; Stephen Castaneda; Ivan Inigo; David Kan; Mei-Li Wen; Robert Kramer; Anne Blackwood-Chirchir; and Francis Y. Lee

2006-12-01T23:59:59.000Z

351

Predicting Protein Folds with Structural Repeats Using a Chain Graph Model  

E-Print Network [OSTI]

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

Xing, Eric P.

352

Bayesian modeling to unmask and predict influenza A/H1N1pdm dynamics in London  

Science Journals Connector (OSTI)

...unmask and predict influenza...Centre for Outbreak Analysis...age-structured model into a Bayesian...presence of any flu virus (SI...strength of any model used to predict or assess...class of models. Two separate...the swine-flu pandemic...responses to the outbreak: Results...

Paul J. Birrell; Georgios Ketsetzis; Nigel J. Gay; Ben S. Cooper; Anne M. Presanis; Ross J. Harris; André Charlett; Xu-Sheng Zhang; Peter J. White; Richard G. Pebody; Daniela De Angelis

2011-01-01T23:59:59.000Z

353

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

E-Print Network [OSTI]

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

354

Prediction of gas solubilities using the LCVM equation of state/excess Gibbs free energy model  

SciTech Connect (OSTI)

A recently developed EoS/G{sup E} model, the LCVM one, is applied to the prediction of Henry constants of nine gases (O{sub 2}, N{sub 2}, CO{sub 2}, CO, H{sub 2}S, CH{sub 4}, C{sub 2}H{sub 6}, C{sub 3}H{sub 8}, C{sub 4}H{sub 10}) in a wide range of pure and mixed solvents, including heavy hydrocarbons, polar solvents, and water. When not available, LCVM interaction parameters are estimated by correlating vapor-liquid equilibrium data. LCVM yields very good predictions for Henry constants in pure solvents, with typical errors less than 8%; it also performs very satisfactorily in the prediction of high-pressure vapor-liquid equilibria. On the other hand, widely-used EoS/G{sup E} models, such as PSRK and MHV2, are shown to result in progressively poorer behavior with increasing system asymmetry. Finally, LCVM predictions for Henry constants in mixed solvents are also satisfactory, especially when combined with the method of Catte et al. The results presented here, combined with those from previous ones, render LCVM a valuable tool for predicting vapor-liquid equilibria.

Apostolou, D.A.; Kalospiros, N.S.; Tassios, D.P. [National Technical Univ. of Athens, Zographos (Greece)

1995-03-01T23:59:59.000Z

355

Online Simultaneous State Estimation and Parameter Adaptation for Building Predictive Control  

E-Print Network [OSTI]

and E. ekov, “Building Modeling as a Crucial Part forthe designed adaptive building modeling framework is testedThe details of building thermal modeling and estimation of

Maasoumy, Mehdi; Moridian, Barzin; Razmara, Meysam; Shahbakhti, Mahdi; Sangiovanni-Vincentelli, Alberto

2014-01-01T23:59:59.000Z

356

Website link prediction using a Markov chain model based on multiple time periods  

Science Journals Connector (OSTI)

Growing size and complexity of many websites have made navigation through these sites increasingly difficult. Attempting to automatically predict the next page for a website user to visit has many potential benefits, for example in site navigation, automatic tour generation, adaptive web applications, recommendation systems, web server optimisation, web search and web pre-fetching. This paper describes an approach to link prediction using a Markov chain model based on an exponentially smoothed transition probability matrix which incorporates site usage statistics collected over multiple time periods. The improved performance of this approach compared to earlier methods is also discussed.

Shantha Jayalal; Chris Hawksley; Pearl Brereton

2007-01-01T23:59:59.000Z

357

Modeling and performance prediction for water production in CBM wells of an Eastern India coalfield  

Science Journals Connector (OSTI)

Dewatering of coal bed methane (CBM) reservoirs is a very important part of methane production. Efficient production depends very much on the proper designing of the wells. In the present study, a comprehensive testing is conducted on 17 wells of a particular block in Eastern India and a general reservoir flow equation is modeled. Prediction of the water flow potential of a particular well using the derived flow equation helps in monitoring the variables of the artificial lift facility. The outcome of work can be used comprehensively to predict the future water and gas flow rates of simulated wells under the designed test.

A. Agarwal; A. Mandal; B. Karmakar; K. Ojha

2013-01-01T23:59:59.000Z

358

Prediction of siRNA knockdown efficiency using artificial neural network models  

SciTech Connect (OSTI)

Selective knockdown of gene expression by short interference RNAs (siRNAs) has allowed rapid validation of gene functions and made possible a high throughput, genome scale approach to interrogate gene function. However, randomly designed siRNAs display different knockdown efficiencies of target genes. Hence, various prediction algorithms based on siRNA functionality have recently been constructed to increase the likelihood of selecting effective siRNAs, thereby reducing the experimental cost. Toward this end, we have trained three Back-propagation and Bayesian neural network models, previously not used in this context, to predict the knockdown efficiencies of 180 experimentally verified siRNAs on their corresponding target genes. Using our input coding based primarily on RNA structure thermodynamic parameters and cross-validation method, we showed that our neural network models outperformed most other methods and are comparable to the best predicting algorithm thus far published. Furthermore, our neural network models correctly classified 74% of all siRNAs into different efficiency categories; with a correlation coefficient of 0.43 and receiver operating characteristic curve score of 0.78, thus highlighting the potential utility of this method to complement other existing siRNA classification and prediction schemes.

Ge Guangtao [Department of Computer Science, Tufts University, 161 College Avenue, Medford, MA 02155 (United States) and Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142 (United States)]. E-mail: guge@eecs.tufts.edu; Wong, G.William [Whitehead Institute for Biomedical Research, 9 Cambridge Center, Cambridge, MA 02142 (United States)]. E-mail: wong@wi.mit.edu; Luo Biao [RNAi Consortium, Broad Institute, Massachusetts Institute of Technology, 320 Bent Street, Cambridge, MA 02142 (United States)]. E-mail: bluo@broad.mit.edu

2005-10-21T23:59:59.000Z

359

Low Clouds Contribute to Weather Prediction Model Bias | U.S. DOE Office of  

Office of Science (SC) Website

2 2 » Low Clouds Contribute to Weather Prediction Model Bias Biological and Environmental Research (BER) BER Home About Research Facilities Science Highlights Searchable Archive of BER Highlights External link Benefits of BER Funding Opportunities Biological & Environmental Research Advisory Committee (BERAC) News & Resources Contact Information Biological and Environmental Research U.S. Department of Energy SC-23/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-3251 F: (301) 903-5051 E: sc.ber@science.doe.gov More Information » November 2012 Low Clouds Contribute to Weather Prediction Model Bias Long-term measurement records improve the representation of clouds in climate and weather forecast models. Print Text Size: A A A Subscribe

360

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

E-Print Network [OSTI]

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

Furlani, E J

2006-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

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

SciTech Connect (OSTI)

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

Lipscomb, William [Los Alamos National Laboratory

2012-06-19T23:59:59.000Z

362

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

E-Print Network [OSTI]

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

M. K. Parida; Sudhanwa Patra

2013-01-14T23:59:59.000Z

363

Reference Model for Control and Automation Systems in Electrical Power |  

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

Model for Control and Automation Systems in Electrical Model for Control and Automation Systems in Electrical Power Reference Model for Control and Automation Systems in Electrical Power Modern infrastructure automation systems are threatened by cyber attack. Their higher visibility in recent years and the increasing use of modern information technology (IT) components contribute to increased security risk. A means of analyzing these infrastructure automation systems is needed to help understand and study the many system relationships that affect the overall security of the system. Modeling these systems is a very cost effective means of addressing the problem of security from an overall system view. The model presented in the document below provides a structured, cost effective approach to address technical security in process control systems

364

Massage and the Gate Control Model  

E-Print Network [OSTI]

111 Figure 2. Flow diagram of participant recruitment and retention 112 Figure 3. Study timeline 113 Figure 4. Piecewise MLM analysis model 114 Figure 5. Group differences in pain unpleasantness and residual pain intensity across...

Karlson, Cynthia Windham

2010-08-31T23:59:59.000Z

365

Solar energy prediction using linear and non-linear regularization models: A study on AMS (American Meteorological Society) 2013–14 Solar Energy Prediction Contest  

Science Journals Connector (OSTI)

Abstract In 2013, American Meteorological Society Committees on AI (artificial intelligence) Applications organized a short-term solar energy prediction competition aiming at predicting total daily solar energy received at 98 solar farms based on the outputs of various weather patterns of a numerical weather prediction model. In this paper, a methodology to solve this problem has been explained and the performance of ordinary LSR (least-square regression), regularized LSR and ANN (artificial neural network) models has been compared. In order to improve the generalization capability of the models, more experiments like variable segmentation, subspace feature sampling and ensembling of models have been conducted. It is observed that model accuracy can be improved by proper selection of input data segments. Further improvements can be obtained by ensemble of forecasts of different models. It is observed that the performance of an ensemble of ANN and LSR models is the best among all the proposed models in this work. As far as the competition is concerned, Gradient Boosting Regression Tree has turned out to be the best algorithm. The proposed ensemble of ANN and LSR model is able to show a relative improvement of 7.63% and 39.99% as compared to benchmark Spline Interpolation and Gaussian Mixture Model respectively.

S.K. Aggarwal; L.M. Saini

2014-01-01T23:59:59.000Z

366

Integrating model-in-the-loop simulations to model-driven development in industrial control  

Science Journals Connector (OSTI)

Software applications are becoming increasingly important in automation and control systems. This has forced control system vendors and integrators to pursue new, more effective software development practices. One of the promising research paths has ... Keywords: Model-driven development, automation and control, model-in-the-loop, simulations

Timo Vepsäläinen, Seppo Kuikka

2014-12-01T23:59:59.000Z

367

Modeling and Feed?Forward Control of Structural Elastic Robots  

Science Journals Connector (OSTI)

In this paper an approach for modeling and control of robots with elasticities in power trains and in structural parts is presented and experimentally verified. For this purpose object?oriented nonlinear models are developed in the modeling language Modelica. A system theoretical study of the generated models shows that a direct inversion of the models due to the unstable zero dynamics is not possible. Therefore an algorithm for the approximate inversion is developed. With this inversion method an approximate inverse model considering structural elasticity for a 6?axis robot is created and verified for the control of the robot. The new control leads to a considerable improvement of the driving characteristics of the robot in the experiment.

M. Reiner; M. Otter; H. Ulbrich

2010-01-01T23:59:59.000Z

368

Neural Modeling and Control of Diesel Engine with Pollution Constraints  

E-Print Network [OSTI]

The paper describes a neural approach for modelling and control of a turbocharged Diesel engine. A neural model, whose structure is mainly based on some physical equations describing the engine behaviour, is built for the rotation speed and the exhaust gas opacity. The model is composed of three interconnected neural submodels, each of them constituting a nonlinear multi-input single-output error model. The structural identi?cation and the parameter estimation from data gathered on a real engine are described. The neural direct model is then used to determine a neural controller of the engine, in a specialized training scheme minimising a multivariable criterion. Simulations show the effect of the pollution constraint weighting on a trajectory tracking of the engine speed. Neural networks, which are ?exible and parsimonious nonlinear black-box models, with universal approximation capabilities, can accurately describe or control complex nonlinear systems, with little a priori theoretical knowledge. The present...

Ouladsine, Mustapha; Dovifaaz, Xavier; 10.1007/s10846-005-3806-y

2009-01-01T23:59:59.000Z

369

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

SciTech Connect (OSTI)

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

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

2011-05-31T23:59:59.000Z

370

Controlling search in constrained-object models  

Science Journals Connector (OSTI)

A constrained-object model is a collection of classes parameterized by constraints and connected through composition and inheritance relations. A class is classically a factory of objects, that correctly linked are able to smoothly capture the inherent ... Keywords: constraint satisfaction, search

Ricardo Soto

2010-11-01T23:59:59.000Z

371

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...

372

A poset framework to model decentralized control problems  

E-Print Network [OSTI]

In a previous paper, these authors showed that posets provide a useful modeling framework for a reasonably large class of decentralized control problems. In this paper we show more connections between posets and decentralized ...

Shah, Parikshit

373

Comparing Large-Scale Hydrological Model Predictions with Observed Streamflow in the Pacific Northwest: Effects of Climate and Groundwater  

Science Journals Connector (OSTI)

Assessing uncertainties in hydrologic models can improve accuracy in predicting future streamflow. Here, simulated streamflows using the Variable Infiltration Capacity (VIC) model at coarse (°) and fine (°) spatial resolutions were evaluated ...

Mohammad Safeeq; Guillaume S. Mauger; Gordon E. Grant; Ivan Arismendi; Alan F. Hamlet; Se-Yeun Lee

2014-12-01T23:59:59.000Z

374

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

E-Print Network [OSTI]

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

Wang, Chien.; Prinn, Ronald G.

375

Prediction of the wax content of the incipient wax-oil gel in a pipeline: An application of the controlled-stress rheometer  

Science Journals Connector (OSTI)

High molecular weight paraffins are known to form gels of complex morphology at low temperatures due to the low solubility of these compounds in aromatic or naphthene-base oil solvents. The characteristics of these gels are strong functions of the shear and thermal histories of these samples. A model system of wax and oil was used to understand the gelation process of these mixtures. A significant depression in the gel point of a wax-oil sample was observed by either decreasing the cooling rate or increasing the steady shear stress. The wax-oil sample separates into two layers of different characteristics a gel-like layer and a liquid-like layer when sheared with a controlled-stress rheometer at high steady shear stresses and low cooling rates. The phase diagram of the model wax-oil system obtained using a controlled-stress rheometer was verified by analyzing the wax content of the incipient gel deposits formed on the wall of a flow loop. Based on the rheological measurements a law has been suggested for the prediction of the wax content of the gel deposit on the laboratory flow loop walls. The wax content of the incipient gel formed on the wall of a field subsea pipeline was predicted to be much higher than that for the flow loop at similar operating conditions. This variation in the gel deposit characteristics is due to the significant differences in the cooling histories in the two cases.

Probjot Singh; H. Scott Fogler; Nagi Nagarajan

1999-01-01T23:59:59.000Z

376

A new thermodynamic model to predict wax deposition from crude oils  

E-Print Network [OSTI]

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

Loganathan, Narayanan

1993-01-01T23:59:59.000Z

377

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

SciTech Connect (OSTI)

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

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

1996-12-31T23:59:59.000Z

378

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

SciTech Connect (OSTI)

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

Mirdamadi, M.; Johnson, W.S.

1994-08-01T23:59:59.000Z

379

Predictions from the macrohomogeneous model of an aerospace Ni-Cd battery  

SciTech Connect (OSTI)

The mathematical porous-electrode model developed at Texas A and M University has been combined with a planar model for the surface active layer to formulate a pseudo two-dimensional model for a sealed nickel-cadmium cell. The porous electrode model is based on a macrohomogeneous description of the electrodes and takes into account various processes such as mass transport in the liquid phase and porosity and conductivity changes in the solid phase. The planar electrode model describes the processes occurring across the surface layer of active material, i.e., solid-state diffusion of protons and conductivity changes in the nickel oxide, and the charge-transfer across the film-electrolyte interface. Also, various routines have been added to the pseudo two-dimensional model thus integrated, to allow predictions for any nickel-cadmium battery under any desired charge-discharge schedule. From a comparison with the experimental data of an aerospace cell, the model parameters describing charge-discharge behavior of a Ni-Cd cell have been optimized to obtain a closer prediction with the experimental data. Upon optimizing the model parameters, the performance of the aerospace nickel-cadmium cell has been simulated under various experimental conditions, i.e., at different rates and temperatures. Also, generic Ragone plots for the cell and typical Tafel plots for cadmium and nickel electrodes at different states of charge have been constructed form the simulations. Finally, this model has been made available for any interested user through COSMIC NASA`s Computer Management and Information Center, along with documentation in six volumes describing the code, principles, and operating instructions.

Ratnakumar, B.V.; Timmerman, P.; Sanchez, C.; Di Stefano, S.; Halpert, G. [California Inst. of Tech., Pasadena, CA (United States). Jet Propulsion Lab.

1996-03-01T23:59:59.000Z

380

Inclusion of KI67 significantly improves performance of the PREDICT prognostication and prediction model for early breast cancer  

E-Print Network [OSTI]

subclasses with clinical implications. Proc Natl Acad Sci USA 2001, 98(19): 10869-10   74 11   12   3. Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, Speed D, Lynch 13   AG, Samarajiwa S, Yuan Y, Graf S, Ha G, Haffari G, Bashashati A... WH, Sonke GS, van’t Veer LJ, Rutgers EJT, van de Vijver MJ, Linn SC. 3   Optimized prediction of clinical outcome by the PREDICT plus tool and 70-gene 4   signature in early stage node-negative breast cancer [abstract]. 36th Annual San Antonio 5...

Wishart, G. C.; Rakha, E.; Green, A.; Ellis, I.; Ali, H. R.; Provenzano, E.; Blows, F. M.; Caldas, C.; Pharoah, P. D. P.

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Turbocharged spark ignition engine modelling and control strategy  

Science Journals Connector (OSTI)

This paper deals with the non-linear modelling and control of a turbocharged spark ignition engine. In the automotive industry, downsizing-based turbocharging is considered as a powerful technique to improve engine performances as fuel economy, pumping loss reduction to increase engine efficiency or driveability optimisation. This method is largely used for diesel engines. For gasoline engines, it is more complex in terms of control. In this work, a simplified control-oriented model is presented and validated using a Smart MCC three cylinders engine data. Then, based on this model, a fuzzy non-linear control law is calculated to achieve the fuel consumption and pumping losses reduction by setting the engine states to a given profile.

D. Khiar; J. Lauber; T.M. Guerra; T. Floquet; G. Colin; Y. Chamaillard

2008-01-01T23:59:59.000Z

382

MODELING AND CONTROLLING PARALLEL TASKS IN DROPLET-BASED MICROFLUIDIC  

E-Print Network [OSTI]

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

383

Modeling and Control of Surge and Rotating Stall in Compressors  

E-Print Network [OSTI]

in connection with acceleration of the compressor. Finally, a model for a centrifugal compression systemModeling and Control of Surge and Rotating Stall in Compressors Dr.ing. thesis Jan Tommy Gravdahl of rotating stall and surge in compressors. A close coupled valve is included in the Moore

Gravdahl, Jan Tommy

384

Modeling of TCR and VSI Based FACTS Controllers  

E-Print Network [OSTI]

concentrates on presenting transient stability and power ow models of Thyristor Controlled Reactor TCR in static and dynamic analysis 3 . This report concentrates on describing in detail the most appropriate, STATCOM, SSSC and UPFC. These models allow to accurately and reliably carry out power ow and transient

Cañizares, Claudio A.

385

Analysis and Model-Based Control of Servomechanisms With Friction  

E-Print Network [OSTI]

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

Papadopoulos, Evangelos

386

Development of a Computer Model for Prediction of PCB Degradation Endpoints  

SciTech Connect (OSTI)

Several researchers have demonstrated the transformation if polychlorinated biphenyls (PCBs) by both aerobic and anaerobic bacteria. This transformation, or conversion, is characteristic and often dependent on PCB congener structure and in addition, dictates the products or endpoints. Since transformation is linked to microbial activities, bioremediation has been hailed as a possible solution for PCB-contaminated soils and sediments, and several demonstration activities have verified laboratory results. This paper presents results from mathematical modeling of PCB transformation as a means of predicting possible endpoints of bioremediation. Since transformation can be influenced by both starting composition of the PCBs and microbial activity, this paper systematically evaluates several of the most common transformation patterns. The predicted data are also compared with experimental results. For example, the correlation between laboratory-observed and predicted endpoint data was, in some cases, as good as 0.98 (perfect correlation = 1.0). In addition to predicting chemical endpoints, the possible human effects of the PCBs are discussed through the use of documented dioxin-like toxicity and accumulation in humans before and after transformation.

Just, E.M.; Klasson, T.

1999-12-07T23:59:59.000Z

387

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

SciTech Connect (OSTI)

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.

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

2012-10-01T23:59:59.000Z

388

Modeling, Analysis, and Control of Demand Response Resources  

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

Modeling, Analysis, and Control of Demand Response Resources Modeling, Analysis, and Control of Demand Response Resources Speaker(s): Johanna Mathieu Date: April 27, 2012 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Sila Kiliccote While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can play an active role in power systems via Demand Response (DR). Recent DR programs have focused on peak load reduction in commercial buildings and industrial facilities (C&I facilities). We present a regression-based baseline model, which allows us to quantify DR performance. We use this baseline model to understand the performance of C&I facilities participating in an automated dynamic pricing DR program in California. In this program, facilities are

389

Modeling of hybrid control systems using the \\{DEVSLib\\} Modelica library  

Science Journals Connector (OSTI)

\\{DEVSLib\\} is a free Modelica library, developed by the authors, that supports the Parallel DEVS formalism. The library is mainly designed to model discrete-event systems. It also includes interfaces to communicate the \\{DEVSLib\\} models with the rest of the Modelica libraries. Thus, the library can be used in the development of multi-domain and multi-formalism hybrid models using the object-oriented methodology supported by Modelica. This manuscript presents the hybrid system modeling capabilities included in DEVSLib. In particular, these functionalities are applied to the description of hybrid control systems. A case study of a supermarket refrigeration system, using the traditional control approach, is discussed. Three implementations of the plant and its controllers have been developed and are described. The system is simulated reproducing the day and night conditions, and the results from the three implementations are compared. \\{DEVSLib\\} is freely available for download at http://www.euclides.dia.uned.es.

Victorino Sanz; Alfonso Urquia; François E. Cellier; Sebastian Dormido

2012-01-01T23:59:59.000Z

390

Parental Investment and the Control of Sexual Selection: Predicting the Direction of Sexual Competition  

Science Journals Connector (OSTI)

...March 1996 research-article Parental Investment and the Control of Sexual Selection...ratio, and the extent of collateral investment. Reproductive events can be complex, involving collateral investments from several individuals, either...

1996-01-01T23:59:59.000Z

391

TEXIN2: a model for predicting carbon monoxide concentrations near intersections  

E-Print Network [OSTI]

of the Journal of the Air Pollution Control Association emitted along straight roadways, where traffic is wel 1-def ined and flows uniformly at constant speeds. This scenario is extremely inap- propriate for intersections. A simple conversion from straight... are presented in Chapter V. CHAPTER II LITERATURE REVIEW The task of modeling pollutant concentrations near intersections has traditionally been approached by first enlisting an emissions model to estimate a composite emission rate for vehicular traffic...

Korpics, J. J

1985-01-01T23:59:59.000Z

392

Handling model uncertainty in model predictive control for energy efficient buildings  

E-Print Network [OSTI]

P f (t)] dt t=0 where cooling power P c , heating power P hnodes to node i cooling power (kW) fan power (kW) heating

Maasoumy, Mehdi; Razmara, M; Shahbakhti, M; Sangiovanni-Vincentelli, Alberto

2014-01-01T23:59:59.000Z

393

Energy saving by integrated control of natural ventilation and HVAC systems using model guide for comparison  

Science Journals Connector (OSTI)

Abstract Integrated control by controlling both natural ventilation and HVAC systems based on human thermal comfort requirement can result in significant energy savings. The concept of this paper differs from conventional methods of energy saving in HVAC systems by integrating the control of both these HVAC systems and the available natural ventilation that is based on the temperature difference between the indoor and the outdoor air. This difference affects the rate of change of indoor air enthalpy or indoor air potential energy storage. However, this is not efficient enough as there are other factors affecting the rate of change of indoor air enthalpy that should be considered to achieve maximum energy saving. One way of improvement can be through the use of model guide for comparison (MGFC) that uses physical-empirical hybrid modelling to predict the rate of change of indoor air potential energy storage considering building fabric and its fixture. Three methods (normal, conventional and proposed) are tested on an identical residential building model using predicted mean vote (PMV) sensor as a criterion test for thermal comfort standard. The results indicate that the proposed method achieved significant energy savings compared with the other methods while still achieving thermal comfort.

Raad Z. Homod; Khairul Salleh Mohamed Sahari; Haider A.F. Almurib

2014-01-01T23:59:59.000Z

394

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

SciTech Connect (OSTI)

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

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

2006-08-04T23:59:59.000Z

395

Reduced-order model based feedback control of the modified Hasegawa-Wakatani model  

SciTech Connect (OSTI)

In this work, the development of model-based feedback control that stabilizes an unstable equilibrium is obtained for the Modified Hasegawa-Wakatani (MHW) equations, a classic model in plasma turbulence. First, a balanced truncation (a model reduction technique that has proven successful in flow control design problems) is applied to obtain a low dimensional model of the linearized MHW equation. Then, a model-based feedback controller is designed for the reduced order model using linear quadratic regulators. Finally, a linear quadratic Gaussian controller which is more resistant to disturbances is deduced. The controller is applied on the non-reduced, nonlinear MHW equations to stabilize the equilibrium and suppress the transition to drift-wave induced turbulence.

Goumiri, I. R.; Rowley, C. W.; Ma, Z. [Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, New Jersey 08544 (United States); Gates, D. A.; Krommes, J. A.; Parker, J. B. [Princeton Plasma Physics Laboratory, Princeton, New Jersey 08544 (United States)

2013-04-15T23:59:59.000Z

396

Validation of a CFD Analysis Model for Predicting CANDU-6 Moderator Temperature Against SPEL Experiments  

SciTech Connect (OSTI)

A validation of a 3D CFD model for predicting local subcooling of the moderator in the vicinity of calandria tubes in a CANDU-6 reactor is performed. The small scale moderator experiments performed at Sheridan Park Experimental Laboratory (SPEL) in Ontario, Canada[1] is used for the validation. Also a comparison is made between previous CFD analyses based on 2DMOTH and PHOENICS, and the current analysis for the same SPEL experiment. For the current model, a set of grid structures for the same geometry as the experimental test section is generated and the momentum, heat and continuity equations are solved by CFX-4.3, a CFD code developed by AEA technology. The matrix of calandria tubes is simplified by the porous media approach. The standard k-{epsilon} turbulence model associated with logarithmic wall treatment and SIMPLEC algorithm on the body fitted grid are used. Buoyancy effects are accounted for by the Boussinesq approximation. For the test conditions simulated in this study, the flow pattern identified is the buoyancy-dominated flow, which is generated by the interaction between the dominant buoyancy force by heating and inertial momentum forces by the inlet jets. As a result, the current CFD moderator analysis model predicts the moderator temperature reasonably, and the maximum error against the experimental data is kept at less than 2.0 deg. C over the whole domain. The simulated velocity field matches with the visualization of SPEL experiments quite well. (authors)

Churl Yoon; Bo Wook Rhee; Byung-Joo Min [Korea Atomic Energy Research Institute, 150, Dukjin-Dong, Yusong-Gu, Taejon 305-353 (Korea, Republic of)

2002-07-01T23:59:59.000Z

397

A unified algorithm for predicting partition coefficients for PBPK modeling of drugs and environmental chemicals  

SciTech Connect (OSTI)

The algorithms in the literature focusing to predict tissue:blood PC (P{sub tb}) for environmental chemicals and tissue:plasma PC based on total (K{sub p}) or unbound concentration (K{sub pu}) for drugs differ in their consideration of binding to hemoglobin, plasma proteins and charged phospholipids. The objective of the present study was to develop a unified algorithm such that P{sub tb}, K{sub p} and K{sub pu} for both drugs and environmental chemicals could be predicted. The development of the unified algorithm was accomplished by integrating all mechanistic algorithms previously published to compute the PCs. Furthermore, the algorithm was structured in such a way as to facilitate predictions of the distribution of organic compounds at the macro (i.e. whole tissue) and micro (i.e. cells and fluids) levels. The resulting unified algorithm was applied to compute the rat P{sub tb}, K{sub p} or K{sub pu} of muscle (n = 174), liver (n = 139) and adipose tissue (n = 141) for acidic, neutral, zwitterionic and basic drugs as well as ketones, acetate esters, alcohols, aliphatic hydrocarbons, aromatic hydrocarbons and ethers. The unified algorithm reproduced adequately the values predicted previously by the published algorithms for a total of 142 drugs and chemicals. The sensitivity analysis demonstrated the relative importance of the various compound properties reflective of specific mechanistic determinants relevant to prediction of PC values of drugs and environmental chemicals. Overall, the present unified algorithm uniquely facilitates the computation of macro and micro level PCs for developing organ and cellular-level PBPK models for both chemicals and drugs.

Peyret, Thomas [DSEST, Universite de Montreal, Canada H3T 1A8 (Canada); Poulin, Patrick [Consultant, 4009 rue Sylvia Daoust, Quebec City, Quebec, G1X 0A6 (Canada); Krishnan, Kannan, E-mail: kannan.krishnan@umontreal.ca [DSEST, Universite de Montreal, H3T 1A8 (Canada)

2010-12-15T23:59:59.000Z

398

The probabilistic life time prediction model of oil pipeline due to local corrosion crack  

Science Journals Connector (OSTI)

Abstract A four-stage probabilistic damage model is proposed basis of cross-scale damage processes to deal with the local corrosion crack of oil pipeline. At first, some key parameters for life time prediction were determined; then the probabilistic damage model is formulated and numerically calculated by using Monte Carlo Simulation (MCS). Furthermore, the model is used to deal with an example in order to check its validity. The results show that the life-span of this pipeline is nearly 20.55 years, and the pipe wall thickness, operating pressure difference and corrosion electric current density are the three key parameters to determine the span-life of this pipeline; the longest examination and repair period should be less than 4.71 years for safety when the surface crack length of 10 mm can be detected reliably.

Jun Hu; Yangyang Tian; Haipeng Teng; Lijun Yu; Maosheng Zheng

2014-01-01T23:59:59.000Z

399

Effective index model predicts modal frequencies of vertical-cavity lasers  

SciTech Connect (OSTI)

Previously, an effective index optical model was introduced for the analysis of lateral waveguiding effects in vertical-cavity surface-emitting lasers. The authors show that the resultant transverse equation is almost identical to the one typically obtained in the analysis of dielectric waveguide problems, such as a step-index optical fiber. The solution to the transverse equation yields the lateral dependence of the optical field and, as is recognized in this paper, the discrete frequencies of the microcavity modes. As an example, they apply this technique to the analysis of vertical-cavity lasers that contain thin-oxide apertures. The model intuitively explains the experimental data and makes quantitative predictions in good agreement with a highly accurate numerical model.

SERKLAND,DARWIN K.; HADLEY,G. RONALD; CHOQUETTE,KENT D.; GEIB,KENT M.; ALLERMAN,ANDREW A.

2000-04-18T23:59:59.000Z

400

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

SciTech Connect (OSTI)

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.

Fok, Alex

2013-10-30T23:59:59.000Z

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Predicting construction cost and schedule success using artificial neural networks ensemble and support vector machines classification models  

Science Journals Connector (OSTI)

It is commonly perceived that how well the planning is performed during the early stage will have significant impact on final project outcome. This paper outlines the development of artificial neural networks ensemble and support vector machines classification models to predict project cost and schedule success, using status of early planning as the model inputs. Through industry survey, early planning and project performance information from a total of 92 building projects is collected. The results show that early planning status can be effectively used to predict project success and the proposed artificial intelligence models produce satisfactory prediction results.

Yu-Ren Wang; Chung-Ying Yu; Hsun-Hsi Chan

2012-01-01T23:59:59.000Z

402

Sorbent utilization prediction methodology: sulfur control in fluidized-bed combustors  

SciTech Connect (OSTI)

The United States Government has embarked on an ambitious program to develop and commercialize technologies to efficiently extract energy from coal in an environmentally acceptable manner. One of the more promising new technologies for steam and power generation is the fluidized-bed combustion of coal. In this process, coal is burned in a fluidized bed composed mainly of calcined limestone sorbent. The calcium oxide reacts chemically to capture the sulfur dioxide formed during the combustion and to maintain the stack gas sulfur emissions at acceptable levels. The spent sulfur sorbent, containing calcium sulfate, is a dry solid that can be disposed of along with coal ash or potentially used. Other major advantages of fluidized-bed combustion are the reduction in nitrogen oxide emissions because of the relatively low combustion temperatures, the capability of burning wide varieties of fuel, the high carbon combustion efficiencies, and the high heat-transfer coefficients. A key to the widespread commercialization of fluidized-bed technology is the ability to accurately predict the amount of sulfur that will be captured by a given sorbent. This handbook meets this need by providing a simple, yet reliable, user-oriented methodology (the ANL method) that allows performance of a sorbent to be predicted. The methodology is based on only three essential sorbent parameters, each of which can be readily obtained from standardized laboratory tests. These standard tests and the subsequent method of data reduction are described in detail.

Fee, D.C.; Wilson, W.I.; Shearer, J.A.; Smith, G.W.; Lenc, J.F.; Fan, L.S.; Myles, K.M.; Johnson, I.

1980-09-01T23:59:59.000Z

403

Reduced-Order Model Based Feedback Control For Modified Hasegawa-Wakatani Model  

SciTech Connect (OSTI)

In this work, the development of model-based feedback control that stabilizes an unstable equilibrium is obtained for the Modi ed Hasegawa-Wakatani (MHW) equations, a classic model in plasma turbulence. First, a balanced truncation (a model reduction technique that has proven successful in ow control design problems) is applied to obtain a low dimensional model of the linearized MHW equation. Then a modelbased feedback controller is designed for the reduced order model using linear quadratic regulators (LQR). Finally, a linear quadratic gaussian (LQG) controller, which is more resistant to disturbances is deduced. The controller is applied on the non-reduced, nonlinear MHW equations to stabilize the equilibrium and suppress the transition to drift-wave induced turbulence.

I.R. Goumiri, C.W. Rowley, Z. Ma, D.A. Gates, J.A. Krommes and J.B. Parker

2013-01-28T23:59:59.000Z

404

Predictive control and thermal energy storage for optimizing a multi-energy district boiler  

E-Print Network [OSTI]

and used when demand is high, instead of engaging the gas-fuel oil boiler. Keywords: multi-energy district believe that by 2015 the supply of oil and natural gas will be unable to keep up with demand [1 of La Rochelle (France) adding to the plant a controlled thermal storage tank. This plant supplies

Paris-Sud XI, Université de

405

Protein secondary structure prediction by combining hidden Markov models and sliding window scores  

Science Journals Connector (OSTI)

Instead of conformation states of single residues, refined conformation states of quintuplets are proposed to reflect conformation correlation. Simple hidden Markov models combined with sliding window scores are used to predict the secondary structure of a protein from its amino acid sequence. Since the length of protein conformation segments varies within a narrow range, we can ignore the duration effect of the length distribution. The window scores for residues are a window version of the Chou-Fasman propensities estimated under an approximation of conditional independency. Different window widths are examined, and the optimal width is found to be 17. A high accuracy of about 70% is achieved.

Wei-Mou Zheng

2005-01-01T23:59:59.000Z

406

Predicted Solar Neutrino Rates in the Q-Nuclear Solar Model  

Science Journals Connector (OSTI)

It is been shown previoulsy that the existence of a tiny abundance of nuclei which have an additional embedded hadronic particle, Q-nuclei, can solve the solar-neutrino problem. We present here detailed predictions of solar-neutrino detection rates for detectors of Cl37, Ga71, and In115. It is found that, while Q-nuclei could reduce the Cl37 detection rate from that of the standard model to the experimental value, they would also produce a dramatic increase in the rates for the Ga71 and In115 detectors.

B. Sur and R. N. Boyd

1985-02-04T23:59:59.000Z

407

Weather Regime Prediction Using Statistical Learning  

E-Print Network [OSTI]

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

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

2011-01-01T23:59:59.000Z

408

Dynamical and Microphysical Evolution during Mixed-Phase Cloud Glaciation Simulated Using the Bulk Adaptive Habit Prediction Model  

Science Journals Connector (OSTI)

A bulk microphysics scheme predicting ice particle habit evolution has been implemented in the Weather Research and Forecasting Model. Large-eddy simulations are analyzed to study the effects of ice habit and number concentration on the bulk ice ...

Kara J. Sulia; Hugh Morrison; Jerry Y. Harrington

2014-11-01T23:59:59.000Z

409

Development of analytical and numerical models predicting the deposition rate of electrically charged particles in turbulent channel flows  

E-Print Network [OSTI]

An analytical model is established to predict an electrostatically charged particle deposition as a function of particle size in fully-developed turbulent pipe flow. The convectivediffusion flux equation is solved for the particle concentration as a...

Ko, Hanseo

2012-06-07T23:59:59.000Z

410

Assimilation of Satellite Cloud and Precipitation Observations in Numerical Weather Prediction Models: Introduction to the JAS Special Collection  

Science Journals Connector (OSTI)

To date, the assimilation of satellite measurements in numerical weather prediction (NWP) models has focused on the clear atmosphere. But satellite observations in the visible, infrared, and microwave provide a great deal of information on clouds ...

Ronald M. Errico; George Ohring; Fuzhong Weng; Peter Bauer; Brad Ferrier; Jean-François Mahfouf; Joe Turk

2007-11-01T23:59:59.000Z

411

A Framework for Performance Modeling and Prediction Allan Snavely, Laura Carrington, Nicole Wolter of The San Diego Supercomputer Center with  

E-Print Network [OSTI]

a framework for performance modeling and prediction that is faster than cycle-accurate simulation, more combined with a network model. 0-7695-1524-X/02 $17.00 (c) 2002 IEEE #12;2 Existing network simulators can and then combine this information with a network simulator. To model single-processor performance, we separate

Snavely, Allan

412

Predictive Maintenance  

Broader source: Energy.gov [DOE]

Predictive maintenance aims to detect equipment degradation and address problems as they arise. The result indicates potential issues, which are controlled or eliminated prior to any significant system deterioration.

413

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

SciTech Connect (OSTI)

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).

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

1998-12-31T23:59:59.000Z

414

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

E-Print Network [OSTI]

THE APPLICATION OI' A CHEMICAL EQUILIBRIUM MODEL, SOLTEQ, TO PREDICT THK CHEMICAL SPKCIATIONS IN STABILIZED/SOLIDIFIED WASTE FORMS A Thesis by JOO-YANG PARK Submitted to the Office of Graduate Studies of Texas A&M University in partial... fulfillment of the requirements for the degree of MASTER OF SCIENCE December 1994 Major Subject: Civil Engineering THE APPLICATION OF A CHEMICAL EQUILIBRIUM MODEL, SOLTEQ, TO PREDICT THE CHEMICAL SPECIATIONS IN STABILIZED/SOLIDIFIED WASTE FORMS A Thesis...

Park, Joo-Yang

1994-01-01T23:59:59.000Z

415

The development of design factors for heat-strengthened and tempered glass based on the glass failure prediction model  

E-Print Network [OSTI]

THE DEVELOPMENT OF DESIGN FACTORS FOR HEAT-STRENGTHENED AND TEMPERED GLASS BASED ON THE GLASS FAILURE PREDICTION MODEL A Thesis by Timothy Andrew Oakes Submitted to the Office of Graduate Studies of Texas A&M University in partial... fulfillment of the requirements for the degree of MASTER OF SCIENCE Decypber 199$ Major Subject: Civil Engineering THE DEVELOPMENT OF DESIGN FACTORS FOR HEAT-STRENGTHENED AND TEMPERED GLASS BASED ON THE GLASS FAILURE PREDICTION MODEL A Thesis...

Oakes, Timothy Andrew

1991-01-01T23:59:59.000Z

416

Development of a rock mass characteristics model for TBM penetration rate prediction  

Science Journals Connector (OSTI)

The TBM tunneling process in hard rock is actually a rock or rock mass breakage process, which determines the efficiency of tunnel boring machine (TBM). On the basis of the rock breakage process, a rock mass conceptual model that identifies the effect of rock mass properties on TBM penetration rate is proposed. During the construction of T05 and T06 tunnels of DTSS project in Singapore, a comprehensive program was performed to obtain the relevant rock mass properties and TBM performance data. A database, including rock mass properties, TBM specifications and the corresponding TBM performance, was established. Combining the rock mass conceptual model for evaluating rock mass boreability with the established database, a statistical prediction model of TBM penetration rate is set up by performing a nonlinear regression analysis. The parametric studies of the new model showed that the rock uniaxial compressive strength and the volumetric joint count have predominantly effects on the penetration rate. These results showed good agreement with the numerical simulations. The model limitations were also discussed.

Q.M. Gong; J. Zhao

2009-01-01T23:59:59.000Z

417

Multiple models decentralized coordinated control of doubly fed induction generator  

Science Journals Connector (OSTI)

Abstract In this paper, a multiple model optimal tracking control (MOTC) design method for the double fed induction generator (DFIG) using correlative measured technique is proposed. The DFIG is represented by a third-order model, where electro-magnetic transients of stator are neglected. By using the correlative measured technique, the correlative measured matrix (CMM) of wind power system is obtained firstly. Then, a nonstandard state space equation of DFIG is obtained with the correlative measured vectors (CMVs), which reflect interactions between the \\{DFIGs\\} and grid. In order to cope with nonlinearities and continuous variation in the operating points, a multiple model design method is proposed in the discrete domain. The obtained control law, synthesized by using Bayesian probability, only depends on the local measured parameters. Hence, the MOTC can be regarded as a decentralized coordinated control, which can simplify the control structure and improve the transient stability of DFIG. To illustrate the effectiveness of the proposed MOTC strategy, simulations on a hybrid wind thermal power (HWTP) system are performed. The results show that the proposed MOTC strategy can provide acceptable performance throughout the whole operating region. Comparing to the conventional PID control, transient stability, damping, and fault ride-through capability of DFIG with the proposed MOTC design method have been improved effectively.

Yu-guang Niu; Xiao-ming Li; Zhong-wei Lin; Ming-yang Li

2015-01-01T23:59:59.000Z

418

Interface modeling to predict well casing damage for big hill strategic petroleum reserve.  

SciTech Connect (OSTI)

Oil leaks were found in well casings of Caverns 105 and 109 at the Big Hill Strategic Petroleum Reserve site. According to the field observations, two instances of casing damage occurred at the depth of the interface between the caprock and top of salt. This damage could be caused by interface movement induced by cavern volume closure due to salt creep. A three dimensional finite element model, which allows each cavern to be configured individually, was constructed to investigate shear and vertical displacements across each interface. The model contains interfaces between each lithology and a shear zone to examine the interface behavior in a realistic manner. This analysis results indicate that the casings of Caverns 105 and 109 failed by shear stress that exceeded shear strength due to the horizontal movement of the top of salt relative to the caprock, and tensile stress due to the downward movement of the top of salt from the caprock, respectively. The casings of Caverns 101, 110, 111 and 114, located at the far ends of the field, are predicted to be failed by shear stress in the near future. The casings of inmost Caverns 107 and 108 are predicted to be failed by tensile stress in the near future.

Ehgartner, Brian L.; Park, Byoung Yoon

2012-02-01T23:59:59.000Z

419

Theoretical model for predicting thermodynamic behavior of thermal-lag Stirling engine  

Science Journals Connector (OSTI)

A theoretical model for predicting thermodynamic behavior of thermal-lag Stirling engine is presented in this study. Without a displacer and its link, the thermal-lag engine contains only a moving part (piston) and a static part (regenerative heater) in engine's cylinder and hence, is regarded as a unique type of Stirling engines that featuring rather simple mechanical structure. In this study, a numerical simulation of thermodynamic behavior of the thermal-lag Stirling engine is performed based on the theoretical model developed. Transient variations of temperatures, pressures, pressure difference, and working fluid masses in the individual working spaces of the engine are predicted. Dependence of indicated power and thermal efficiency on engine speed has been investigated. Then, optimal engine speeds at which the engine may reach its maximum power output and/or maximum thermal efficiency is determined. Furthermore, effects of geometrical and operating parameters, such as heating and cooling temperatures, volumes of the chambers, thermal resistances, stroke of piston, and bore size on indicated power output and thermal efficiency are also evaluated.

Chin-Hsiang Cheng; Hang-Suin Yang

2013-01-01T23:59:59.000Z

420

Electric Water Heater Modeling and Control Strategies for Demand Response  

SciTech Connect (OSTI)

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

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

2012-07-22T23:59:59.000Z

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
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421

Modeling for surge control of centrifugal compresssors: comparison with experiment  

E-Print Network [OSTI]

con- trol design, of a centrifugal compression system is vali- dated. Compressor surge is an unwanted to centrifugal compressors. Since compressors are vari- able speed machines, and surge is commonly encoun- teredModeling for surge control of centrifugal compresssors: comparison with experiment Jan Tommy

Gravdahl, Jan Tommy

422

Modeling and control of a PowerSail  

E-Print Network [OSTI]

connected to a host satellite by a pair of hollow links housing an electrical conductor. The mechanism connecting the sail and the host consists of seven active joints. This thesis addresses the modeling of the system dynamics and the design of control laws...

Naik, Kishore Shivdas

2012-06-07T23:59:59.000Z

423

RISK SENSITIVE CONTROL AND AN OPTIMAL INVESTMENT MODEL (II)  

E-Print Network [OSTI]

RISK SENSITIVE CONTROL AND AN OPTIMAL INVESTMENT MODEL (II) W. H. Fleming1 and S. J. Sheu2 Brown University and Academia Sinica Abstract. We consider an optimal investment problem proposed by Bielecki and Pliska. The goal of the investment problem is to optimize the long term growth of expected utility

Sheu, Shuenn-Jyi

424

ADAPTIVE MODEL BASED CONTROL FOR WASTEWATER TREATMENT PLANTS  

E-Print Network [OSTI]

ADAPTIVE MODEL BASED CONTROL FOR WASTEWATER TREATMENT PLANTS Arie de Niet1 , Maartje van de Vrugt2.j.boucherie@utwente.nl Abstract In biological wastewater treatment, nitrogen and phosphorous are removed by activated sludge considerably to the increase of energy-efficiency in wastewater treatment. To this end, we introduce

Boucherie, Richard J.

425

Dynamic Modelling for Control of Fuel Cells Federico Zenith  

E-Print Network [OSTI]

Dynamic Modelling for Control of Fuel Cells Federico Zenith Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science and Technology ( ntnu) Trondheim Abstract Fuel-cell dynamics have been investigated with a variable-resistance board applied to a high temperature polymer fuel cell

Skogestad, Sigurd

426

A nuclear data acquisition system flow control model  

SciTech Connect (OSTI)

A general Petri Net representation of a nuclear data acquisition system model is presented. This model provides for the unique requirements of a nuclear data acquisition system including the capabilities of concurrently acquiring asynchronous and synchronous data, of providing multiple priority levels of flow control arbitration, and of permitting multiple input sources to reside at the same priority without the problem of channel lockout caused by a high rate data source. Finally, a previously implemented gamma camera/physiological signal data acquisition system is described using the models presented.

Hack, S.N.

1988-02-01T23:59:59.000Z

427

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

E-Print Network [OSTI]

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

Frauholz, Sarah; Müller, Siegfried; Behr, Marek

2014-01-01T23:59:59.000Z

428

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

E-Print Network [OSTI]

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

Stancil, Daniel D.

429

A survey on control schemes for distributed solar collector fields. Part I: Modeling and basic control approaches  

Science Journals Connector (OSTI)

This article presents a survey of the different automatic control techniques that have been applied to control the outlet temperature of solar plants with distributed collectors during the last 25 years. Different aspects of the control problem involved in this kind of plants are treated, from modeling and simulation approaches to the different basic control schemes developed and successfully applied in real solar plants. A classification of the modeling and control approaches is used to explain the main features of each strategy.

E.F. Camacho; F.R. Rubio; M. Berenguel; L. Valenzuela

2007-01-01T23:59:59.000Z

430

Building a predictive model of indoor concentrations of outdoor PM-2.5 for  

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

Building a predictive model of indoor concentrations of outdoor PM-2.5 for Building a predictive model of indoor concentrations of outdoor PM-2.5 for a residential research house in Clovis, California Title Building a predictive model of indoor concentrations of outdoor PM-2.5 for a residential research house in Clovis, California Publication Type Report Year of Publication 2002 Authors Fischer, Marc L., Melissa M. Lunden, Tracy L. Thatcher, David Littlejohn, Thomas W. Kirchstetter, Susanne V. Hering, Richard G. Sextro, and Nancy J. Brown Abstract The prevalence of relocatable classrooms (RCs) at schools is rising due to federal and state initiatives to reduce K-3 class size, and limited capital resources. Concerns regarding inadequate ventilation and indoor air and environmental quality (IEQ) in RCs have been raised. Adequate ventilation is an important link between improved IEQ and energy efficiency for schools. Since students and teachers spend the majority of a 7-8 hour school day inside classrooms, indoor contaminant concentrations are assumed to drive personal school-day exposures. We conducted a demonstration project in new relocatable classrooms (RCs) during the 2001-02 school year to address these issues. Four new 24' x 40' (960 ft2) RCs were constructed and sited in pairs at an elementary school campus in each of two participant school districts (SD) in Northern California. Each RC was equipped with two heating, ventilation, and air conditioning (HVAC) systems, one per module. The two HVAC systems were a standard heat pump with intermittent 25-50% outdoor air ventilation and an energy-efficient advanced system, based on indirect-direct evaporative cooling with an integrated natural gas-fired hydronic heating loop and improved particle filtration, providing continuous 100% outdoor air ventilation at = 15 ft3 min-1 occupant-1. Alternate carpets, wall panels, and ceiling panels were installed in two classrooms -- one in each pair -- based on the results of a laboratory study of VOC emissions from standard and alternate materials. Numerous IEQ and outdoor air quality and meteorological parameters were measured either continuously over the school year or as integrated school day samples during the fall cooling and winter heating seasons. Details of the RC designs, the field monitoring methodology including handling, storage, transport and management of chemical samples and data, and analyses to be conducted are presented

431

The use of least squares methods in functional optimization of energy use prediction models  

Science Journals Connector (OSTI)

The least squares method (LSM) is used to optimize the coefficients of a closed-form correlation that predicts the annual energy use of buildings based on key envelope design and thermal parameters. Specifically annual energy use is related to a number parameters like the overall heat transfer coefficients of the wall roof and glazing glazing percentage and building surface area. The building used as a case study is a previously energy-audited mosque in a suburb of Kuwait City Kuwait. Energy audit results are used to fine-tune the base case mosque model in the VisualDOE{trade mark serif} software. Subsequently 1625 different cases of mosques with varying parameters were developed and simulated in order to provide the training data sets for the LSM optimizer. Coefficients of the proposed correlation are then optimized using multivariate least squares analysis. The objective is to minimize the difference between the correlation-predicted results and the VisualDOE-simulation results. It was found that the resulting correlation is able to come up with coefficients for the proposed correlation that reduce the difference between the simulated and predicted results to about 0.81%. In terms of the effects of the various parameters the newly-defined weighted surface area parameter was found to have the greatest effect on the normalized annual energy use. Insulating the roofs and walls also had a major effect on the building energy use. The proposed correlation and methodology can be used during preliminary design stages to inexpensively assess the impacts of various design variables on the expected energy use. On the other hand the method can also be used by municipality officials and planners as a tool for recommending energy conservation measures and fine-tuning energy codes.

2012-01-01T23:59:59.000Z

432

Comparison between nonlinear model-based controllers and gain-scheduling Internal Model Control based on identified model*  

E-Print Network [OSTI]

response behaviour make anti-slug control at offshore oil-fields an interesting control problem where slugging flow conditions in offshore multi- phase pipelines are undesirable and an effective solution time, because of inflow disturbances or plant changes. We aim to find a robust control solution

Skogestad, Sigurd

433

Multi-model Simulation for Optimal Control of Aeroacoustics.  

SciTech Connect (OSTI)

Flow-generated noise, especially rotorcraft noise has been a serious concern for bothcommercial and military applications. A particular important noise source for rotor-craft is Blade-Vortex-Interaction (BVI)noise, a high amplitude, impulsive sound thatoften dominates other rotorcraft noise sources. Usually BVI noise is caused by theunsteady flow changes around various rotor blades due to interactions with vorticespreviously shed by the blades. A promising approach for reducing the BVI noise isto use on-blade controls, such as suction/blowing, micro-flaps/jets, and smart struc-tures. Because the design and implementation of such experiments to evaluate suchsystems are very expensive, efficient computational tools coupled with optimal con-trol systems are required to explore the relevant physics and evaluate the feasibilityof using various micro-fluidic devices before committing to hardware.In this thesis the research is to formulate and implement efficient computationaltools for the development and study of optimal control and design strategies for com-plex flow and acoustic systems with emphasis on rotorcraft applications, especiallyBVI noise control problem. The main purpose of aeroacoustic computations is todetermine the sound intensity and directivity far away from the noise source. How-ever, the computational cost of using a high-fidelity flow-physics model across thefull domain is usually prohibitive and itmight also be less accurate because of thenumerical diffusion and other problems. Taking advantage of the multi-physics andmulti-scale structure of this aeroacoustic problem, we develop a multi-model, multi-domain (near-field/far-field) method based on a discontinuous Galerkin discretiza-tion. In this approach the coupling of multi-domains and multi-models is achievedby weakly enforcing continuity of normal fluxes across a coupling surface. For ourinterested aeroacoustics control problem, the adjoint equations that determine thesensitivity of the cost functional to changes in control are also solved with same ap-proach by weakly enforcing continuity ofnormal fluxes across a coupling surface.Such formulations have been validated extensively for several aeroacoustics state andcontrol problems.A multi-model based optimal control framework has been constructed and ap-plied to our interested BVI noise control problem. This model problem consists ofthe interaction of a compressible vortex with Bell AH-1 rotor blade with wall-normal3 velocity used as control on the rotor blade surface. The computational domain isdecomposed into the near-field and far-field. The near-field is obtained by numericalsolution of the Navier-Stokes equations while far away from the noise source, wherethe effect of nonlinearities is negligible, the linearized Euler equations are used tomodel the acoustic wave propagation. The BVI wave packet is targeted by definingan objective function that measures the square amplitude of pressure fluctuations inan observation region, at a time interval encompassing the dominant leading edgecompressibility waves. Our control results show that a 12dB reduction in the ob-servation region is obtained. Interestingly, the control mechanism focuses on theobservation region and only minimize the sound level in that region at the expense ofother regions. The vortex strength and trajectory get barely changed. However, theoptimal control does alter the interaction of the vortical and potential fields, whichis the source of BVI noise. While this results in a slight increase in drag, there is asignificant reduction in the temporal gradient of lift leading to a reduction in BVIsound levels.4

Collis, Samuel Scott; Chen, Guoquan

2005-05-01T23:59:59.000Z

434

Optimization of Computational Performance and Accuracy in 3?D Transient CFD Model for CFB Hydrodynamics Predictions  

Science Journals Connector (OSTI)

This work aims to present a pure 3?D CFD model accurate and efficient for the simulation of a pilot scale CFB hydrodynamics. The accuracy of the model was investigated as a function of the numerical parameters in order to derive an optimum model setup with respect to computational cost. The necessity of the in depth examination of hydrodynamics emerges by the trend to scale up CFBCs. This scale up brings forward numerous design problems and uncertainties which can be successfully elucidated by CFD techniques. Deriving guidelines for setting a computational efficient model is important as the scale of the CFBs grows fast while computational power is limited. However the optimum efficiency matter has not been investigated thoroughly in the literature as authors were more concerned for their models accuracy and validity. The objective of this work is to investigate the parameters that influence the efficiency and accuracy of CFB computational fluid dynamics models find the optimum set of these parameters and thus establish this technique as a competitive method for the simulation and design of industrial large scale beds where the computational cost is otherwise prohibitive. During the tests that were performed in this work the influence of turbulence modeling approach time and space density and discretization schemes were investigated on a 1.2 MWth CFB test rig. Using Fourier analysis dominant frequencies were extracted in order to estimate the adequate time period for the averaging of all instantaneous values. The compliance with the experimental measurements was very good. The basic differences between the predictions that arose from the various model setups were pointed out and analyzed. The results showed that a model with high order space discretization schemes when applied on a coarse grid and averaging of the instantaneous scalar values for a 20 sec period adequately described the transient hydrodynamic behaviour of a pilot CFB while the computational cost was kept low. Flow patterns inside the bed such as the core?annulus flow and the transportation of clusters were at least qualitatively captured.

I. Rampidis; A. Nikolopoulos; N. Koukouzas; P. Grammelis; E. Kakaras

2007-01-01T23:59:59.000Z

435

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

SciTech Connect (OSTI)

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.

Fisher, Jeffrey W., E-mail: jeffrey.fisher@fda.hhs.gov; Twaddle, Nathan C.; Vanlandingham, Michelle; Doerge, Daniel R.

2011-11-15T23:59:59.000Z

436

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

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

LA-UR-11-01857 LA-UR-11-01857 Approved for public release; distribution I unlimited. Title: Modeling the Number of Ignitions Following an Earthquake: Developing Prediction Limits for Overdispersed Count Data Authors: Elizabeth J. Kelly and Raymond N. Tell Intended Use: Deliverable to SB-TS: Safety Basis Technical Services Los Alamos National Laboratory, an affirmative action/equal opportunity employer, is operated by the Los Alamos National Security, LLC for the National Nuclear Security Administration of the U.S. Department of Energy under contract DE-AC52- 06NA25396. By acceptance of this article, the publisher recognizes that the U.S. Government retains a nonexclusive, royalty-free license to publish or reproduce the published form of this contribution, or to allow others to do so, for U.S.

437

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

SciTech Connect (OSTI)

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.

Duffy, Stephen

2013-09-09T23:59:59.000Z

438

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

SciTech Connect (OSTI)

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.

Apperson, Jason W [Los Alamos National Laboratory; Clemmons, James S [Los Alamos National Laboratory; Garcia, Michael D [Los Alamos National Laboratory; Sur, John C [Los Alamos National Laboratory; Zhang, Duan Z [Los Alamos National Laboratory; Romero, Michael J [Los Alamos National Laboratory

2008-01-01T23:59:59.000Z

439

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

E-Print Network [OSTI]

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

Enrique Gaztañaga; Rupert Croft; Gavin Dalton

1995-01-31T23:59:59.000Z

440

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

SciTech Connect (OSTI)

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.

Zhang, Pengpeng, E-mail: zhangp@mskcc.org [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Yorke, Ellen; Hu, Yu-Chi; Mageras, Gig [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Rimner, Andreas [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Deasy, Joseph O. [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States)

2014-02-01T23:59:59.000Z

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Computational modeling of the brain limbic system and its application in control engineering  

E-Print Network [OSTI]

of this thesis, Chapter IV, shows the utilization of the Brain Emotional Learning (BEL) model in different applications of control and signal fusion systems. The main effort is focused on applying the model to control systems where the model acts...

Shahmirzadi, Danial

2005-11-01T23:59:59.000Z

442

A heuristic model to predict earthworm biomass in agroecosystems based on selected management and soil properties  

Science Journals Connector (OSTI)

Earthworm burrows can be significant preferential flow paths for water and contaminants to move to subsurface drainage networks and groundwater. Thus earthworm biomass could serve as an indicator of such transport potential, and therefore, inform risk assessments associated with water contamination resulting from land application of fertilizer amendments. In this study, we evaluated relationships and interactions between earthworm biomass, soil properties (bulk density, particle size, organic matter, surface residue), land management (crop type, tillage approach), and soil hydraulic properties (field saturated hydraulic conductivity and air-entry tension) for the purpose of building regionally based models to predict earthworm biomass. Data were collected from 43 fields distributed throughout eastern Ontario, Canada. Earthworm biomass was measured using “hot mustard” methods (early autumn) and in situ soil hydraulic properties were determined using pressure infiltrometers (late summer/early fall). Classification and Regression Tree (CART) data mining techniques were used to develop tree-structured models to predict biomass from site environmental data. CART regression tree models had coefficients of determination between 0.50 (not including soil hydraulic properties) and 0.55 (including soil hydraulic properties). Both regression trees split all earthworm biomass data (N = 243) into two groupings defined on the basis of tillage treatment. No-tilled field biomass averaged 192.1 g m?2 (S.D. = 71.5 g m?2), and biomass data for conventionally tilled sites subdivided into terminal groupings on the basis of “higher surface residue cover” (biomass average = 107.9 g m?2 (S.D. = 81.1 g m?2) and ‘lower surface residue cover’ (62.4 g m?2 (S.D. = 54.6 g m?2)) classes. Soil physical and hydraulic data were not important predictors of biomass for tilled datasets; whereas they were more important for no-tilled datasets. For both regression trees, no-till biomass stratified into terminal biomass groupings defined on the basis of bulk density, clay content, and silt content; and for the model including soil hydraulic properties, additionally by soil air-entry tension and surface residue cover. However, bulk density was deemed in the model to be a proxy for years a field was in no-tillage; a positive relationship existed between bulk density and biomass. Overall, the terminal tree groups with the highest average earthworm biomasses were for no-till soils with bulk densities >1.4 g cm?3 (longer term no-tillage). Regression tree variance reductions associated with the in situ measurements of field saturated hydraulic conductivity and air-entry tension were insignificant or small. Generally, empirical models predicting earthworm biomass at large spatial scales in agroecosystems using soils and land management information, should consider utilizing variables that express tillage practice, surface residue coverage, years in no-tillage, and soil particle size; however, variable interactions should be considered.

G. Ouellet; D.R. Lapen; E. Topp; M. Sawada; M. Edwards

2008-01-01T23:59:59.000Z

443

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

SciTech Connect (OSTI)

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.

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

2014-06-01T23:59:59.000Z

444

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

E-Print Network [OSTI]

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

445

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

E-Print Network [OSTI]

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

Meirovitch, Hagai

446

Calendar ageing analysis of a LiFePO4/graphite cell with dynamic model validations: Towards realistic lifetime predictions  

Science Journals Connector (OSTI)

Abstract The present study aims at establishing a methodology for a comprehensive calendar ageing predictive model development, focusing specially on validation procedures. A LFP-based Li-ion cell performance degradation was analysed under different temperature and SOC storage conditions. Five static calendar ageing conditions were used for understanding the ageing trends and modelling the dominant ageing phenomena (SEI growth and the resulting loss of active lithium). The validation process included an additional test under other constant operating conditions (static validation) and other four tests under non–constant impact factors operating schemes within the same experiment (dynamic validation), in response to battery stress conditions in real applications. Model predictions are in good agreement with experimental results as the residuals are always below 1% for experiments run for 300–650 days. The model is able to predict dynamic behaviour close to real operating conditions and the level of accuracy corresponds to a root-mean-square error of 0.93%.

E. Sarasketa-Zabala; I. Gandiaga; L.M. Rodriguez-Martinez; I. Villarreal

2014-01-01T23:59:59.000Z

447

Reference Model for Control and Automation Systems in Electrical Power  

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

Reference Model 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 of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. 2 Contents 1 Executive Summary.................................................................................................3 2 Introduction..............................................................................................................4

448

Development of a control-oriented model to optimise fuel consumption and NOX emissions in a DI Diesel engine  

Science Journals Connector (OSTI)

Abstract This paper describes a predictive NOX and consumption model, which is oriented to control and optimisation of DI Diesel engines. The model applies the Response Surface Methodology following a two-step process: firstly, the relationship between engine inputs (intake charge conditions and injection settings) and some combustion parameters (peak pressure, indicated mean effective pressure and burn angles) is determined; secondly, engine outputs (NOX and consumption) are predicted from the combustion parameters using NOX and mechanical losses models. Splitting the model into two parts allows using either experimental or modelled combustion parameters, thus enhancing the model flexibility. If experimental in-cylinder pressure is used to obtain combustion parameters, the mean error of predicted NOX and consumption are 2% and 6% respectively, with a calculation time of 5.5 ms. Using modelled parameters reduces the calculation time to 1.5 ms, with a penalty in the accuracy. The model performs well in a multi-objective optimisation, reducing NOX and consumption in different amounts depending on the objective of the optimisation.

S. Molina; C. Guardiola; J. Martín; D. García-Sarmiento

2014-01-01T23:59:59.000Z

449

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

SciTech Connect (OSTI)

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

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

1995-12-31T23:59:59.000Z

450

Heterogeneous nuclear reactor models for optimal xenon control  

SciTech Connect (OSTI)

In this study a thermal nuclear reactor is modeled as a two-dimensional lattice of fuel and control rods placed in an infinite-moderator in plane geometry. The two-group diffusion theory approximation is used for neutron transport. Space-time neutron balance equations are written for two groups and reduced to one space-time algebraic equation by using the two-dimensional Fourier transform. This equation is written at all fuel and control rod locations. Iodine-xenon and promethium-samarium dynamic equations are also written at fuel rod locations only. These equations are then linearized about an equilibrium point which is determined from the steady-state form of the original nonlinear system equations. After studying poisonless criticality, with and without control, and the stability of the open-loop system and after checking its controllability, a performance criterion is defined for the xenon-induced spatial flux oscillation problem in the form of a functional to be minimized. Linear-quadratic optimal control theory is then applied to solve the problem.

Gondal, I.A.

1984-01-01T23:59:59.000Z

451

Virtual control system environment: A modeling and simulation tool for process control systems  

SciTech Connect (OSTI)

The development of tools and techniques for security testing and performance testing of Process Control Systems (PCS) is needed since those systems are vulnerable to the same classes of threats as other networked computer systems. In practice, security testing is difficult to perform on operational PCS because it introduces an unacceptable risk of disruption to the critical systems (e.g., power grids) that they control. In addition, the hardware used in PCS is often expensive, making full-scale mockup systems for live experiments impractical. A more flexible approach to these problems can be provided through test beds that provide the proper mix of real, emulated, and virtual elements to model large, complex systems such as critical infrastructures. This paper describes a 'Virtual Control System Environment' that addresses these issues. (authors)

Lee, E.; Michalski, J.; Sholander, P.; Van Leeuwen, B. [Sandia National Laboratories, Albuquerque, NM 87111 (United States)

2006-07-01T23:59:59.000Z

452

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

E-Print Network [OSTI]

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

Oliva, Aude

453

Fuzzy logic in process control: A new fuzzy logic controller and an improved fuzzy-internal model controller.  

E-Print Network [OSTI]

??Two fuzzy controllers are presented. A fuzzy controller with intermediate variable designed for cascade control purposes is presented as the FCIV controller. An intermediate variable… (more)

García Z., Yohn E

2006-01-01T23:59:59.000Z

454

A charging control strategy for active building-integrated thermal energy storage systems using frequency domain modeling  

Science Journals Connector (OSTI)

Abstract Primary space conditioning can be provided through active building-integrated thermal energy storage (BITES) systems, such as radiant space heating through concrete slabs. This approach can reduce peak space conditioning demand and energy costs while satisfying thermal comfort. However, thermal charging rates need to be predictively controlled due to the slow thermal response of BITES systems. This paper presents a charge control strategy using frequency domain models and room air temperature set-point profile as input. The models were previously verified with full-scale experiment data. The calculation procedures are demonstrated on active BITES systems with and without airflow to zone. Results show that the calculated charging rates satisfy the desired room air temperature set-point profiles. This control strategy is important for integrating the design and operation of active BITES systems because frequency domain models also provide important design information.

Yuxiang Chen; Andreas K. Athienitis; Khaled E. Galal

2014-01-01T23:59:59.000Z

455

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

SciTech Connect (OSTI)

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.

Laskowski, Gregory Michael

2005-12-01T23:59:59.000Z

456

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

SciTech Connect (OSTI)

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.

Maguire, J.; Burch, J.

2013-08-01T23:59:59.000Z

457

Modeling tip zones to predict the throw and length characteristics of faults  

SciTech Connect (OSTI)

A map of faults in a 60 km{sup 2} area of the southern North Sea has been produced from three-dimensional seismic data. The faults shown on the map obey power-law cumulative-frequency distributions for throw (power-law exponent, D, {approx} 2.7) and length (D {approx} 1.1). Simulations have been carried out to correct for sampling biases in the data and to make predictions of the throw the data and to make predictions of the throw and length scaling characteristics of the faults. The most important bias is caused by poor resolution of the small displacement tip zones of faults. The raw data show considerable scatter in their length: throw ratios, but they more closely fit a linar relationship if a length of 500 m is added to each fault, thereby making up for the zones near the fault tips with throws ({approx} 15 m) below seismic resolution. Further variability in the data may be caused by such geological factors as fault interaction. Tip lengths have been extended to simulate the actual fault pattern in the study area. Maps produced by this procedure can be used to estimate the true connectivity of the fault network. Extending the faults results in greater connectivity than shown by the raw data, which may cause greater compartmentalization of the rock mass. This greater compartmentalization has implications for hydrocarbon exploitation if the faults are sealing. A problem with the model, however, is that it does not deal effectively with the interaction of subparallel, noncoplanar faults. To test the reliability of the procedure, we analyzed exposure-scale faults in Somerset, United Kingdom, where the tips are well constrained. Both length-throw relationships and map-pattern connectivity for the simulated fault networks agree closely with the actual data.

Pickering, G.; Sanderson, D.J.; Bull, J.M. [Univ. of Southampton (United Kingdom)] [and others

1997-01-01T23:59:59.000Z

458

Diesel Aftertreatment Modeling:? A Systems Approach to NOx Control  

Science Journals Connector (OSTI)

Diesel Aftertreatment Modeling:? A Systems Approach to NOx Control ... Despite these challenges, the proposed system was able to make several advances:? (1) meeting the T2B5 CO, HC, and PM standards; (2) quantifying the ability to meet T2B5 NOx levels with a more durable DOC and a rapid warm-up strategy to heat the exhaust, especially during the initial cold-start portion of the Federal Test Procedure (FTP) drive cycle. ... The remainder of this work is organized as follows:? The formulation, calibration, and validation of the DOC and SCR models are presented in section 2. The DOC and SCR models are combined for an analysis of the AT system as a whole in section 3. The final section of the article summarizes the results and offers some general conclusions. ...

Santhoji R. Katare; Joseph E. Patterson; Paul M. Laing

2007-03-16T23:59:59.000Z

459

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

SciTech Connect (OSTI)

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

Paul, G.W.

1984-10-01T23:59:59.000Z

460

Development Of Control Oriented Electrical And Thermal Models Of An Electric Transit Bus Battery System.  

E-Print Network [OSTI]

??This thesis presents the insights derived from the empirical characterization, modeling, simulation, control-design, and verification tasks performed in developing energy storage system (ESS) controls for… (more)

Kunte, Harshad

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

Dynamic Modeling and Adaptive Neural-Fuzzy Control for Nonholonomic Mobile Manipulators Moving on a Slope 1 Dynamic Modeling and Adaptive Neural-Fuzzy Control for  

E-Print Network [OSTI]

robots [7]. A robust fuzzy logic controller was devised for a robotic manipulator with uncertainties [8Dynamic Modeling and Adaptive Neural-Fuzzy Control for Nonholonomic Mobile Manipulators Moving on a Slope 1 Dynamic Modeling and Adaptive Neural-Fuzzy Control for Nonholonomic Mobile Manipulators Moving

Li, Yangmin

462

A New Approach to Fuzzy Modeling and Control of Discrete-Time Systems  

E-Print Network [OSTI]

], the advantage of fuzzy logic in modeling and control is in the ability to combine modeling (constructingA New Approach to Fuzzy Modeling and Control of Discrete-Time Systems Michael Margaliot and Gideon Langholz #3; Abstract We present a new approach to fuzzy modeling and control of discrete-time sys- tems

Margaliot, Michael

463

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

E-Print Network [OSTI]

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

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

2013-11-29T23:59:59.000Z

464

Optimal SCR Control Using Data-Driven Models  

SciTech Connect (OSTI)

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.

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

2013-04-16T23:59:59.000Z

465

Integrated Numerical Modeling Process for Evaluating Automobile Climate Control Systems  

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

FCC-70 FCC-70 Integrated Numerical Modeling Process for Evaluating Automobile Climate Control Systems John Rugh National Renewable Energy Laboratory Copyright © 2002 Society of Automotive Engineers, Inc. ABSTRACT The air-conditioning (A/C) system compressor load can significantly impact the fuel economy and tailpipe emissions of conventional and hybrid electric automobiles. With the increasing emphasis on fuel economy, it is clear that the A/C compressor load needs to be reduced. In order to accomplish this goal, more efficient climate control delivery systems and reduced peak soak temperatures will be necessary to reduce the impact of vehicle A/C systems on fuel economy and tailpipe emissions. Good analytical techniques are important in identifying promising concepts. The goal at

466

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

SciTech Connect (OSTI)

Complex systems are made up of multiple interdependent parts, and the behavior of the entire system cannot always be directly inferred from the behavior of the individual parts. They are nonlinear and system responses are not necessarily additive. Examples of complex systems include energy, cyber and telecommunication infrastructures, human and animal social structures, and biological structures such as cells. To meet the goals of infrastructure development, maintenance, and protection for cyber-related complex systems, novel modeling and simulation technology is needed. Sandia has shown success using M&S in the nuclear weapons (NW) program. However, complex systems represent a significant challenge and relative departure from the classical M&S exercises, and many of the scientific and mathematical M&S processes must be re-envisioned. Specifically, in the NW program, requirements and acceptable margins for performance, resilience, and security are well-defined and given quantitatively from the start. The Quantification of Margins and Uncertainties (QMU) process helps to assess whether or not these safety, reliability and performance requirements have been met after a system has been developed. In this sense, QMU is used as a sort of check that requirements have been met once the development process is completed. In contrast, performance requirements and margins may not have been defined a priori for many complex systems, (i.e. the Internet, electrical distribution grids, etc.), particularly not in quantitative terms. This project addresses this fundamental difference by investigating the use of QMU at the start of the design process for complex systems. Three major tasks were completed. First, the characteristics of the cyber infrastructure problem were collected and considered in the context of QMU-based tools. Second, UQ methodologies for the quantification of model discrepancies were considered in the context of statistical models of cyber activity. Third, Bayesian methods for optimal testing in the QMU framework were developed. This completion of this project represent an increased understanding of how to apply and use the QMU process as a means for improving model predictions of the behavior of complex systems. 4

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

2010-09-01T23:59:59.000Z

467

Geothermal field case studies that document the usefulness of models in predicting reservoir and well behavior  

SciTech Connect (OSTI)

The geothermal industry has shown significant interest in case histories that document field production histories and demonstrate the techniques which work best in the characterization and evaluation of geothermal systems. In response to this interest, LBL has devoted a significant art of its geothermal program to the compilation and analysis of data from US and foreign fields (e.g., East Mesa, The Geysers, Susanville, and Long Valley in California; Klamath Falls in Oregon; Valles Caldera, New Mexico; Cerro Prieto and Los Azufres in Mexico; Krafla and Nesjavellir in Iceland; Larderello in Italy; Olkaria in Kenya). In each of these case studies we have been able to test and validate in the field, or against field data, the methodology and instrumentation developed under the Reservoir Technology Task of the DOE Geothermal Program, and to add to the understanding of the characteristics and processes occurring in geothermal reservoirs. Case study results of the producing Cerro Prieto and Olkaria geothermal fields are discussed in this paper. These examples were chosen because they illustrate the value of conceptual and numerical models to predict changes in reservoir conditions, reservoir processes, and well performance that accompany field exploitation, as well as to reduce the costs associated with the development and exploitation of geothermal resources. 14 refs., 6 figs.

Lippmann, M.J.

1989-03-01T23:59:59.000Z

468

Geothermal Field Case Studies that Document the Usefulness of Models in Predicting Reservoir and Well Behavior  

SciTech Connect (OSTI)

The geothermal industry has shown significant interest in case histories that document field production histories and demonstrate the techniques which work best in the characterization and evaluation of geothermal systems. In response to this interest, LBL has devoted a significant part of its geothermal program to the compilation and analysis of data from US and foreign fields (e.g., East Mesa, The Geysers, Susanville, and Long Valley in California; Klamath Fall in Oregon; Valles Caldera, New Mexico; Cerro Prieto and Los Azufres in Mexico; Krafla and Nesjavellir in Iceland; Larderello in Italy; Olkaria in Kenya). In each of these case studies we have been able to test and validate in the field, or against field data, the methodology and instrumentation developed under the Reservoir Technology Task of the DOE Geothermal Program, and to add to the understanding of the characteristics and processes occurring in geothermal reservoirs. Case study results of the producing Cerro Prieto and Olkaria geothermal fields are discussed in this paper. These examples were chosen because they illustrate the value of conceptual and numerical models to predict changes in reservoir conditions, reservoir processes, and well performance that accompany field exploitation, as well as to reduce the costs associated with the development and exploitation of geothermal resources.

Lippmann, Marcelo J.

1989-03-21T23:59:59.000Z

469

Development of a rock mass characteristics model for TBM penetration rate prediction.  

E-Print Network [OSTI]

??With the advances of technology, TBMs are becoming more versatile and TBM tunneling has become a common tunneling method. During project planning, the prediction of… (more)

Gong, Qiuming.

2008-01-01T23:59:59.000Z

470

Modeling of D/C motor driven synthetic jet acutators for flow separation control  

E-Print Network [OSTI]

to validate the jet exit velocities predicted by the theoretical model. The optimal jet exit velocity required to achieve maximum flow reattachment at reasonable blowing momentum coefficients is predicted. A dynamic electro-acoustic model of the D/C motor...

Balasubramanian, Ashwin Kumar

2004-11-15T23:59:59.000Z

471

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

SciTech Connect (OSTI)

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.

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

1996-08-09T23:59:59.000Z

472

Advanced Control Methodology for Biomass Combustion.  

E-Print Network [OSTI]

??This thesis presents a feasibility study for a low cost sensor-based combustion control system using a predictive chemical kinetic model that captures efficiencies and pollution… (more)

Bjornsson, Stefan

2014-01-01T23:59:59.000Z

473

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

SciTech Connect (OSTI)

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.

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

2011-04-20T23:59:59.000Z

474

Neural control of muscle force: indications from a simulation model Paola Contessa1,5  

E-Print Network [OSTI]

Neural control of muscle force: indications from a simulation model Paola Contessa1,5 and Carlo J control of muscle force: indications from a simulation model. J Neurophysiol 109: 1548­1570, 2013. First

De Luca, Carlo J.

475

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

SciTech Connect (OSTI)

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

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

2014-06-15T23:59:59.000Z

476

Modelling, Simulation, Control and Optimisation of Nonsmooth Systems http://www.inrialpes.fr/bipop/  

E-Print Network [OSTI]

Neural networks Modelling and simulation bipeds Optimization of energy production Masonry structuresBIPOP Modelling, Simulation, Control and Optimisation of Nonsmooth Systems Web Site http

477

Development and Validation of the 3-D Computational Fluid Dynamics Model for CANDU-6 Moderator Temperature Predictions  

SciTech Connect (OSTI)

A computational fluid dynamics (CFD) model for predicting the moderator circulation inside the Canada deuterium uranium (CANDU) reactor vessel has been developed to estimate the local subcooling of the moderator in the vicinity of the Calandria tubes. The buoyancy effect induced by internal heating is accounted for by Boussinesq approximation. The standard k-[curly epsilon] turbulence model associated with logarithmic wall treatment is applied to predict the turbulent jet flows from the inlet nozzles. The matrix of the Calandria tubes in the core region is simplified to porous media, in which anisotropic hydraulic impedance is modeled using an empirical correlation of the frictional pressure loss. The governing equations are solved by CFX-4.4, a commercial CFD code developed by AEA Technology. The CFD model has been successfully verified and validated against experimental data obtained at Stern Laboratories Inc. in Hamilton, Ontario, Canada.

Yoon, Churl; Rhee, Bo Wook; Min, Byung-Joo [Korea Atomic Energy Research Institute (Korea, Republic of)

2004-12-15T23:59:59.000Z

478

A predictive model of yellow spotted river turtle (Podocnemis unifilis) encounter rates at basking sites in lowland eastern Bolivia  

Science Journals Connector (OSTI)

Abstract This paper develops a model predicting encounter rates of the yellow-spotted river turtle (Podocnemis unifilis) based on human hunting pressure and an ecological classification of potential basking sites. We estimate Poisson regression models for turtles observed in basking surveys. Field surveys were conducted in eastern lowland Bolivia in 2000 and 2011. Our model predicts a significant correlation between turtle encounter rates and two ecological classifications – steep cliff with vegetation and muddy flats that we believe are important habitat types for these turtles. Additionally, our model supports the hypothesis that human population has a significant but less negative impact on observed turtle encounter rates. Analyses of turtle encounter rates and factors that influence it are critical for the conservation of P. unifilis turtles and the broader Amazonian ecological system.

Kristen Conway-Gómez; Michael Reibel; Christopher Mihiar

2014-01-01T23:59:59.000Z

479

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

SciTech Connect (OSTI)

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

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

1981-08-01T23:59:59.000Z

480

Why Do Continuum Gas-Solids Flow Models Predict Core-Annulus Flow?  

SciTech Connect (OSTI)

Core-annulus flow is an experimentally well established, industrially significant flow pattern of circulating fluidized beds. Several studies reported in the literature have shown that continuum gas-solids flow models are able to predict that flow pattern. But the crucial features of the model that give rise to the core-annulus flow structure have not been identified. To determine those features, we conduct transient simulations and analyze the results. Furthermore we time-average the results and investigate the formulation of time-averaged equations. We use transient, highly resolved, 1-D, grid-independent numerical solutions of a continuum model in this study. We show that the results could be even qualitatively incorrect (high solids concentration at the center of the channel) unless grid-independence is established. This explains why in certain coarse grid computations reported in the literature it was necessary to remove a dissipation term or to increase the particle size. Our simulations verify that the core-annulus structure arises in a time-averaged sense from unsteady gas-solids flow, as observed in experiments. We show that the key term that makes the flow unsteady is the dissipation term in the granular energy equation. Without that term the simulation yields a steady-state solution. The intuition based on steady-state solutions may not be valid. Unlike steady-state solutions, the transient solutions are not unduly sensitive to the restitution coefficient. The effect of restitution coefficient in transient simulations is remarkably different: a smaller restitution coefficient gives a higher average granular temperature. Both the micro-scale (clusters resolved) and meso-scale (clusters time-averaged) phenomena are important, unlike turbulent single-phase flows where the meso-scale (turbulent) stresses dominate. The prediction of core-annulus flow is strongly affected by the parameters used in the (micro-scale) wall boundary conditions; it is essential that the parameters are such that no granular energy is produced at the wall. The normal stress based on kinetic theory (Ps, micro) is an order of magnitude larger than normal stress arising from fluctuations (Ps, meso). Therefore, the granular temperature and solids fraction are approximately inversely correlated, just as shown by a steady-state analysis. However, the gradient of Ps, micro is of the same order of magnitude as the gradient of Ps, meso; those gradients adjust to ensure that the time averaged total Ps gradient in the radial direction is zero. The meso-scale shear stress is larger than the micro-scale shear stress. The meso-scale granular energy production term dominates the corresponding micro-scale term and must be included in time-averaged equations. That term is responsible for the maximum at the center in the granular temperature profile. The micro-scale granular energy production term is identically zero at the center because it is proportional to the gradient of solids velocity, which is zero at the center. The instantaneous gradient of solids velocity at the center, however, is not zero because of the down flow of clusters near the walls; it takes positive and negative values making the time-averaged velocity gradient exactly zero at the center. Therefore, the time-averaged square of the velocity gradient is non-zero at the center, which results in a production term in the time-averaged equations that is non-zero at the center. We find that the predictions are insensitive to the currently available k-å type turbulence models. The traditional k-å type models, based on the experience with single phase flow calculations, may not be adequate because meso-scale terms do not necessarily dominate the micro-scale terms. And certain parameters could behave counter to our intuition based on single phase flows: we compute and confirm with physical arguments that the gas-phase turbulent (meso-scale) viscosity could become negative.

Benyahia, S.; Syamlal, M.; O'Brien, T.J.

2006-11-01T23:59:59.000Z

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481

Optimization of a simplified sub-model for NO emission prediction by CFD in large 4-stroke marine diesel engines  

Science Journals Connector (OSTI)

A simplified sub-model for NO emission prediction at pressurized conditions has been put forth at Åbo Akademi University [7,9] including NO formation via the thermal NO path (3 reactions) and via the nitrous oxide intermediate paths (2 + 5 reactions). CFD simulations carried out with the sub-model for marine and off-road diesel engines showed, however, that it significantly – by an order of magnitude – over-predicted NO emission as compared to measurements. The objective of this work was to find the reasons to the discrepancy and to suggest and incorporate improvements. By detailed investigations, a number of programming technical errors and chemical kinetic shortcomings were identified. The improved sub-model and its sub-parts were then tested for CFD simulation of a medium-speed, four-stroke, direct-injection marine diesel engine for different loads and fuels. The importance of NO reduction by soot and hydrocarbons was also investigated. All the sub-models correctly predicted the trend of increasing NO emission with increasing load. In absolute amounts, NO emission was over-predicted by a factor of 2 to 4, if no fitting of rate constants was allowed. Including NO reduction by soot and hydrocarbons, decreased NO emission by ca 4–25% for the cases studied.

Pia Kilpinen

2010-01-01T23:59:59.000Z

482

Model Free Closed-Loop Flow Control ERCAN ATAM, LIONEL MATHELIN, LAURENT CORDIER  

E-Print Network [OSTI]

Model Free Closed-Loop Flow Control ERCAN ATAM, LIONEL MATHELIN, LAURENT CORDIER *CNRS- Mathelin-Cordier (LIMSI-CNRS,IP') Model Free Closed-Loop Flow Control ECCOMAS'12 1 / 21 #12;Outline 1 and some future work Atam- Mathelin-Cordier (LIMSI-CNRS,IP') Model Free Closed-Loop Flow Control ECCOMAS'12

Mathelin, Lionel

483

Model-based control strategies in the dynamic interaction of air supply and fuel cell  

E-Print Network [OSTI]

Model-based control strategies in the dynamic interaction of air supply and fuel cell M Grujicic1Ã? fuel cell temperature. The model is used to analyse the control of the fuel cell system with respect, University of Michigan, Ann Arbor, Michigan, USA Abstract: Model-based control strategies are utilized

Grujicic, Mica

484

A dynamic prediction model for gas-water effective permeability in unsaturated coalbed methane reservoirs based on production data  

Science Journals Connector (OSTI)

Abstract Effective permeability of gas and water in coalbed methane (CBM) reservoirs is vital during CBM development. However, few studies have investigated it for unsaturated CBM reservoirs rather than saturated CBM reservoirs. In this work, the dynamic prediction model (PM-Corey model) for average gas-water effective permeability in two-phase flow in saturated CBM reservoirs was improved to describe unsaturated CBM reservoirs. In the improved effective permeability model, Palmer et al. absolute permeability model segmented based on critical desorption pressure and Chen et al. relative permeability model segmented based on critical water saturation were introduced and coupled comprehensively under conditions with the identical reservoir pressures and the identical water saturations through production data and the material balance equations (MBEs) in unsaturated CBM reservoirs. Taking the Hancheng CBM field as an example, the differences between the saturated and unsaturated effective permeability curves were compared. The results illustrate that the new dynamic prediction model could characterize not only the stage of two-phase flow but also the stage of single-phase water drainage. Also, the new model can accurately reflect the comprehensive effects of the positive and negative effects (the matrix shrinking effect and the effective stress effect) and the gas Klinkenberg effect of coal reservoirs, especially for the matrix shrinkage effect and the gas Klinkenberg effect, which can improve the effective permeability of gas production and render the process more economically. The new improved model is more realistic and practical than previous models.

Junlong Zhao; Dazhen Tang; Hao Xu; Yanjun Meng; Yumin Lv; Shu Tao

2014-01-01T23:59:59.000Z

485

Geological controls on prediction of coalbed methane of No. 3 coal seam in Southern Qinshui Basin, North China  

Science Journals Connector (OSTI)

In order to better understand the geological controls on coalbed methane (CBM) in Southern Qinshui basin (SQB), North China, geological surveys and laboratory experiments, including coal petrology analysis, proximate analysis and methane adsorption/desorption, were conducted. Results show that the coals from the SQB contain 0.59–3.54% moisture, 3.5–15.54% ash yield, 73.62–88.92% fixed carbon and 2.14–4.04% hydrogen, with C/H ratios in the range of 19.96–36.25. The vitrinite reflectance (Ro,m) ranges from 1.95 to 3.49%. The coals are composed of 18.5–97.4% vitrinite and 2.4–81.4% inertinite. The geologic structures, coal-bearing strata and coal depositional environment were studied by both field geological research and laboratory tests. A positive relationship is found between CBM content and basin hydrodynamics, in which CBM easily concentrates in the groundwater stagnant zone because of the water pressure. Furthermore, integrated geographical information system (GIS) and analytical hierarchy fuzzy prediction method (AHP) were used to evaluate the CBM resources in the SQB. The results show that the amount of CBM associated with the No. 3 coal seam in the SQB is 3.62 × 1011 m3. The CBM resource concentration (gas-in-place per square kilometer) in the SQB is in the range of (0.72–2.88) × 108 m3/km2, with an average of 1.21 × 108 m3/km2, which decreases from Zhengzhuang coal district to Shitou fault and from Fanzhuang coal district to the margins of the basin. The best prospective targets for CBM production are likely located in the southwest/northwest Zhengzhuang and central Hudi coal districts.

Yidong Cai; Dameng Liu; Yanbin Yao; Junqian Li; Yongkai Qiu

2011-01-01T23:59:59.000Z

486

Oceanographers' contribution to climate modelling and prediction: progress to date and a future perspective  

Science Journals Connector (OSTI)

...atmosphere-ocean-ice models, and recently more comprehensive Earth system models, are the central tool for generating projections...reminder that in the drive for ever more realistic Earth system models, simplified models can still provide valuable insight...

2012-01-01T23:59:59.000Z

487

Skill of Direct Solar Radiation Predicted by the ECMWF Global Atmospheric Model over Australia  

Science Journals Connector (OSTI)

Prediction of direct solar radiation is key in sectors such as solar power and agriculture; for instance, it can enable more efficient production of energy from concentrating solar power plants. An assessment of the quality of the direct solar ...

Alberto Troccoli; Jean-Jacques Morcrette

2014-11-01T23:59:59.000Z

488

Artificial Neural Network Model for Prediction of Fatigue Lives of Composites Materials  

Science Journals Connector (OSTI)

The application of composites as engineering materials has become state of art and fatigue is one of the most complicated problems for fiber composites. The life prediction of a newly developed material is costly...

Sanjay Mathur; Prakash Chandra Gope…

2007-01-01T23:59:59.000Z

489

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

E-Print Network [OSTI]

mills. This paper de- scribes a paradigm for predicting the trajectory of odorous emissions from a CAFO: sss@acpub.duke.edu (S.S. Schiffman). long-distance dispersal of seeds by wind [1]. It is based

Katul, Gabriel

490

A predictive model of enhanced oil recovery by infill drilling and its application  

Science Journals Connector (OSTI)

Infill drilling is now recognized as a viable improved ... the reliable prediction of incremental recovery by infill drilling cannot be readily and accurately determined by ... calculates the geometries of stream...

Jianhong Xu; Linsong Cheng; Lili Ma

2007-08-01T23:59:59.000Z

491

Spatiotemporal Model for Short-Term Predictions of Air Pollution Data  

Science Journals Connector (OSTI)

Recently, the interest of many environmental agencies is on short-term air pollution predictions referred at high spatial resolution. This ... be informed with visual and easy access to air-quality assessment. We...

Francesca Bruno; Lucia Paci

2014-01-01T23:59:59.000Z

492

Developing Data-driven Models to Predict BEMS Energy Consumption for Demand Response Systems  

Science Journals Connector (OSTI)

Energy consumption prediction for building energy management systems (BEMS) is one of the key factors in the success of energy saving measures in modern building operation, either residential buildings or comm...

Chunsheng Yang; Sylvain Létourneau; Hongyu Guo

2014-01-01T23:59:59.000Z

493

Toward Random Sampling of Model Error in the Canadian Ensemble Prediction System  

Science Journals Connector (OSTI)

An updated global ensemble prediction system became operational at the Meteorological Service of Canada in July 2007. The new elements of the system include the use of 20 members instead of 16, a single dynamical core [the Global Environmental ...

Martin Charron; Gérard Pellerin; Lubos Spacek; P. L. Houtekamer; Normand Gagnon; Herschel L. Mitchell; Laurent Michelin

2010-05-01T23:59:59.000Z

494

Prediction and Uncertainty in Computational Modeling of Complex Phenomena: A Whitepaper  

SciTech Connect (OSTI)

This report summarizes some challenges associated with the use of computational science to predict the behavior of complex phenomena. As such, the document is a compendium of ideas that have been generated by various staff at Sandia. The report emphasizes key components of the use of computational to predict complex phenomena, including computational complexity and correctness of implementations, the nature of the comparison with data, the importance of uncertainty quantification in comprehending what the prediction is telling us, and the role of risk in making and using computational predictions. Both broad and more narrowly focused technical recommendations for research are given. Several computational problems are summarized that help to illustrate the issues we have emphasized. The tone of the report is informal, with virtually no mathematics. However, we have attempted to provide a useful bibliography that would assist the interested reader in pursuing the content of this report in greater depth.

Trucano, T.G.