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Note: This page contains sample records for the topic "model predictive control" from the National Library of EnergyBeta (NLEBeta).
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they are not comprehensive nor are they the most current set.
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1

Model Predictive Control for Energy Efficient Buildings  

E-Print Network (OSTI)

P. Haves et al. “Model Predictive Control of HVAC Systems:Bilinear Model Predictive Control of a HVAC System Usingof model predictive control algorithms for HVAC systems.

Ma, Yudong

2012-01-01T23:59:59.000Z

2

Training of neural models for predictive control  

Science Conference Proceedings (OSTI)

This paper emphasises the link between neural model training and its role in model predictive control (MPC) algorithms. This role is of fundamental importance since in MPC at each sampling instant a model is used on-line to calculate predictions of future ... Keywords: Identification, Model predictive control, Neural networks, Optimisation

Maciej ?awry?czuk

2010-03-01T23:59:59.000Z

3

Randomized Model Predictive Control for HVAC Systems  

Science Conference Proceedings (OSTI)

Heating, Ventilation and Air Conditioning (HVAC) systems play a fundamental role in maintaining acceptable thermal comfort and Indoor Air Quality (IAQ) levels, essentials for occupants well-being. Since performing this task implies high energy requirements, ... Keywords: Copulas, Learning, Randomized Model Predictive Control, Smart Buildings, Sustainable Control Systems

Alessandra Parisio, Damiano Varagnolo, Daniel Risberg, Giorgio Pattarello, Marco Molinari, Karl H. Johansson

2013-11-01T23:59:59.000Z

4

Model Predictive Control of Thermal Energy Storage in Building...  

NLE Websites -- All DOE Office Websites (Extended Search)

Model Predictive Control of Thermal Energy Storage in Building Cooling Systems Title Model Predictive Control of Thermal Energy Storage in Building Cooling Systems Publication Type...

5

Nonlinear model predictive control of a reactive distillation column.  

E-Print Network (OSTI)

??Model Predictive Control (MPC) is an optimal-control based method to select control inputs by minimizing the predicted error from setpoint for the future. Industrially popular… (more)

Kawathekar, Rohit

2004-01-01T23:59:59.000Z

6

Brief A probabilistically constrained model predictive controller  

Science Conference Proceedings (OSTI)

We propose a novel control algorithm, probabilistically constrained predictive control, to deal with the uncertainties of system disturbances. The output is to be controlled in the constrained range with a desired probability. Under the assumption of ... Keywords: Multivariate normal distribution, Nonlinear programming, Predictive control, Probabilistic constraints, Uncertainty

Pu Li; Moritz Wendt; GüNter Wozny

2002-07-01T23:59:59.000Z

7

Model predictive control of a Kaibel distillation column.  

E-Print Network (OSTI)

?? Model predictive control (MPC) of a Kaibel distillation column is the main focus of this thesis. A model description together with a model extension… (more)

Kvernland, Martin Krister

2009-01-01T23:59:59.000Z

8

Model Predictive Control with Repeated Model Fitting for Ramp Metering  

E-Print Network (OSTI)

1 Model Predictive Control with Repeated Model Fitting for Ramp Metering Tom Bellemans, Bart De Schutter, Bart De Moor Abstract--- Ramp metering is a dynamic traffic control measure that has often shown to be very effective. There are several possible methods to determine appropriate ramp metering signals

9

Computationally efficient nonlinear predictive control based on neural Wiener models  

Science Conference Proceedings (OSTI)

This paper describes a computationally efficient nonlinear model predictive control (MPC) algorithm based on neural Wiener models and its application. The model contains a linear dynamic part in series with a steady-state nonlinear part which is realised ... Keywords: Linearisation, Model predictive control, Neural networks, Optimisation, Process control, Wiener systems

Maciej ?awry?czuk

2010-12-01T23:59:59.000Z

10

Multivariable model predictive control for a gas turbine power plant  

Science Conference Proceedings (OSTI)

In this brief, constrained multi variable model predictive control (MPC) strategy is investigated for a GE9001E gas turbine power plant. So the rotor speed and exhaust gas temperature are controlled manipulating the fuel command and compressor inlet ... Keywords: ARX, gas turbine, identification, modeling, multivariable control, power plant, predictive control

Hadi Ghorbani; Ali Ghaffari; Mehdi Rahnama

2008-05-01T23:59:59.000Z

11

Optimal Control of Distributed Energy Resources using Model Predictive Control  

Science Conference Proceedings (OSTI)

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

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

2012-07-22T23:59:59.000Z

12

Power flow management of microgrid networks using model predictive control  

Science Conference Proceedings (OSTI)

In this paper, we present a power flow management method for a network of cooperating microgrids within the context of a smart grid by formulating the problem in a model predictive control framework. In order to reliably and economically provide the ... Keywords: Microgrid, Model predictive control, Renewable energy sources, Smart grid, Storage devices

A. Hooshmand; H. A. Malki; J. Mohammadpour

2012-09-01T23:59:59.000Z

13

Preliminary results of model predictive control of shading systems (WIP)  

Science Conference Proceedings (OSTI)

Shades in buildings are widely installed and are an effective technique for managing solar gains and occupant comfort. A model of a typical office space located in Ottawa, Ontario has been created and the model was developed for analysis under variable ... Keywords: energy management system, model predictive control, reactive control, shades

Brent Huchuk; William O'Brien; Cynthia A. Cruickshank

2013-04-01T23:59:59.000Z

14

Model Predictive Control for Energy Efficient Buildings  

E-Print Network (OSTI)

to reduce the electricity bills associated with HVACto reduce the electricity bills. The control design of thisin (3.12) penalizes total electricity bill and the deviation

Ma, Yudong

2012-01-01T23:59:59.000Z

15

Control Engineering Practice 14 (2006) 757767 Model predictive control for ramp metering of motorway traffic  

E-Print Network (OSTI)

Control Engineering Practice 14 (2006) 757­767 Model predictive control for ramp metering metering implemented. Two types of controllers are compared: a traditional ALINEA based controller and a model predictive control based ramp metering controller. In order to evaluate the controllers

16

HVAC Room Temperature Prediction Control Based on Neural Network Model  

Science Conference Proceedings (OSTI)

HVAC (Heating Ventilating &Air-conditioning) system is a nonlinear complex system with delay. It is very difficult to build a mathematical model of HVAC and implement model-based control. Since a BP (Back Propagation) neural network can fully approximate ... Keywords: BP neural network, predictive control, HVAC, least squares method

Shujiang Li, Shuang Ren, Xiangdong Wang

2013-01-01T23:59:59.000Z

17

Provably Safe and Robust Learning-Based Model Predictive Control  

E-Print Network (OSTI)

Controller design for systems typically faces a trade-off between robustness and performance, and the reliability of linear controllers has caused many control practitioners to focus on the former. However, there is a renewed interest in improving system performance to deal with growing energy and pollution constraints. This paper describes a learning-based model predictive control (MPC) scheme. The MPC provides deterministic guarantees on robustness and safety, and the learning is used to identify richer models of the system to improve controller performance. Our scheme uses a linear model with bounds on its uncertainty to construct invariant sets which help to provide the guarantees, and it can be generalized to other classes of models and to pseudo-spectral methods. This framework allows us to handle state and input constraints and optimize system performance with respect to a cost function. The learning occurs through the use of an oracle which returns the value and gradient of unmodeled dynamics at discr...

Aswani, Anil; Sastry, S Shankar; Tomlin, Claire

2011-01-01T23:59:59.000Z

18

Variational Bayesian learning of nonlinear hidden state-space models for model predictive control  

Science Conference Proceedings (OSTI)

This paper studies the identification and model predictive control in nonlinear hidden state-space models. Nonlinearities are modelled with neural networks and system identification is done with variational Bayesian learning. In addition to the robustness ... Keywords: Model predictive control, Neural network, Nonlinear system, Partially observable Markov decision process, State-space method, Stochastic optimal control, Variational methods

Tapani Raiko; Matti Tornio

2009-10-01T23:59:59.000Z

19

Model Predictive Control of Integrated Gasification Combined Cycle Power Plants  

SciTech Connect

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

20

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

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

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

22

Model Predictive Control for the Operation of Building Cooling Systems  

E-Print Network (OSTI)

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

Ma, Yudong

2010-01-01T23:59:59.000Z

23

Decentralized-coordinated model predictive control for a hydro-power valley  

Science Conference Proceedings (OSTI)

This paper aims at improving control systems for hydro-power production, by combining model predictive control techniques with decomposition-coordination methods for a global optimization over a whole hydro-power valley. It first recalls the model predictive ... Keywords: Case-study validation, Control optimization, Decomposition-coordination, Hydroelectricity, Model predictive control

J. ZáRate FlóRez, J. Martinez, G. BesançOn, D. Faille

2013-05-01T23:59:59.000Z

24

Constrained model predictive control implementation for a heavy-duty gas turbine power plant  

Science Conference Proceedings (OSTI)

In this paper, model predictive control (MPC) strategy is implemented to a GE9001E gas turbine power plant. A linear model is developed for the gas turbine using conventional mathematical models and ARX identification procedure. Also a process control ... Keywords: ARX, PID, gas turbine, identification, modeling, multivariable control, power plant, predictive control

Hadi Ghorbani; Ali Ghaffari; Mehdi Rahnama

2008-06-01T23:59:59.000Z

25

Continuous-time nonlinear model predictive control of time-delayed Wiener-type systems  

Science Conference Proceedings (OSTI)

This paper deals with a novel method of continuous-time model predictive control for nonlinear time-delayed systems. The problems regarding time delays are solved by incorporating delayed and undelayed model outputs in the control-law derivation. Nonlinear-mapping ... Keywords: Wiener-type model, continuous system, nonlinear predictive control, time-delayed system

Simon Oblak; Igor Škrjanc

2006-02-01T23:59:59.000Z

26

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

E-Print Network (OSTI)

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

Haves, Phillip

2010-01-01T23:59:59.000Z

27

Weight optimisation for iterative distributed model predictive control applied to power networks  

Science Conference Proceedings (OSTI)

This paper presents a weight tuning technique for iterative distributed Model Predictive Control (MPC). Particle Swarm Optimisation (PSO) is used to optimise both the weights associated with disturbance rejection and those associated with achieving consensus ... Keywords: Distributed model predictive control, Multi-agent, Particle swarm optimisation, Power networks, Smart grids, Weight tuning

Paul Mc Namara; Rudy R. Negenborn; Bart De Schutter; Gordon Lightbody

2013-01-01T23:59:59.000Z

28

Model predictive control of a Kaibel distillation column  

E-Print Network (OSTI)

A Kaibel distillation column separates a feed into four products with significant lower energy consumption than a conventional sequence of binary columns. Optimal operation and control of such systems is an important task in order to obtain the potential energy savings. A laboratory column has been built at NTNU, Department of Chemical Engineering. At the time of the diploma work the laboratory column has unfortunately not been available for MPC experiments. In practical operation a control structure based on temperature measurements is chosen for the given case. This structure gives a four-by-four multivariable system. The candidate shall base his work on a model developed by Jens Strandberg. Tasks: 1. Describe the model and extend it to include an efficiency parameter describing insufficient mixing at stages 2. Describe a general linear MPC approach for the system 3. Analyze sensitivity of model errors 4. Evaluate alternative MPC approaches 5. Implement the MPC in MATLAB and illustrate the performance by simulations 6. Prepare a setup for connecting the MPC to the actual laboratory column

Martin Krister Kvernland; Supervisor Ole; Morten Aamo; Co-supervisor Ivar Halvorsen; Sigurd Skogestad Ikp; Jim Morrison Vii

2009-01-01T23:59:59.000Z

29

Nonlinear model predictive control for dosing daily anticancer agents using a novel saturating-rate cell-cycle model  

Science Conference Proceedings (OSTI)

A nonlinear model predictive control (NMPC) algorithm was developed to dose the chemotherapeutic agent tamoxifen based on a novel saturating-rate, cell-cycle model (SCM). Using daily tumor measurements, the algorithm decreased tumor volume along a specified ... Keywords: Biomedical systems, Cancer, Nonlinear model, Nonlinear model predictive control, Pharmacodynamics, Pharmacokinetics

Jeffry A. Florian, Jr.; Julie L. Eiseman; Robert S. Parker

2008-03-01T23:59:59.000Z

30

PREDICTIVE MODELS  

Science Conference Proceedings (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

31

Constrained model predictive control, state estimation and coordination  

E-Print Network (OSTI)

control, Springer Verlag. Fukushima, H. & Bitmead, R. (Control’, Maui, Hawaii USA. Fukushima, H. & Bitmead, R. (Hessen & Bosgra 2002, Fukushima & Bitmead 2003, Fukushima &

Yan, Jun

2006-01-01T23:59:59.000Z

32

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

E-Print Network (OSTI)

Multimedia applications over the Internet are getting more and more popular. While non-real-time streaming services, such as YouTube and Megavideo, are attracting millions of visiting per day, real-time conferencing applications, of which some instances are Skype and Yahoo Voice Chat, provide an interesting experience of communication. Together, they make the fancy Internet world become more and more amusing. Undoubtedly, multimedia flows will eventually dominate the computer network in the future. As the population of multimedia flows increases gradually on the Internet, quality of their service (QoS) is more of a concern. At the moment, the Internet does not have any guarantee on the quality of multimedia services. To completely surpass this limitation, modifications to the network structure is a must. However, it will take years and billions of dollars in investment to achieve this goal. Meanwhile, it is essential to find alternative ways to improve the quality of multimedia services over the Internet. In the past few years, many endeavors have been carried on to solve the problem. One interesting approach focuses on the development of end-to-end congestion control strategies for UDP multimedia flows. Traditionally, packet losses and delays have been commonly used to develop many known control schemes. Each of them only characterizes some different aspects of network congestion; hence, they are not ideal as feedback signals alone. In this research, the flow accumulation is the signal used in feedback for flow control. It has the advantage of reflecting both packet losses and delays; therefore, it is a better choice. Using network simulations, the accumulations of real-time audio applications are collected to construct adaptive flow controllers. The reason for choosing these applications is that they introduce more control challenges than non-real-time services. One promising flow control strategy was proposed by Bhattacharya and it was based on Model Predictive Control (MPC). The controller was constructed from an ARX predictor. It was demonstrated that this control scheme delivers a good QoS while reducing bandwidth use in the controlled flows by 31 percent to 44 percent. However, the controller sometime shows erratic response and bandwidth usage jumps frequently between lowest and highest values. This is not desirable. For an ideal controller, the controlled bandwidth should vary near its mean. To eliminate the deficiency in the strategy proposed by Bhattacharya, it is proposed to introduce a feed forward term into the MPC formulation, in addition to the feedback terms. Simulations show that the modified MPC strategy maintains the benefits of the Bhattacharya strategy. Furthermore, it increases the probability of bandwidth savings from 58 percent for the case of Bhattacharya model to about 99 percent for this work.

Duong, Thien Chi

2010-12-01T23:59:59.000Z

33

Original Article: Simulation-based weight factor selection and FPGA prediction core implementation for finite-set model based predictive control of power electronics  

Science Conference Proceedings (OSTI)

Model-based predictive control (MBPC) for power-electronic converters offers fast and accurate control. Based on the prediction of the future system states the optimal control input sequence is obtained by calculating a cost for each sequence. The control ... Keywords: FPGA, Multilevel inverters, Parallel calculation, Pipelining, Predictive control

Thomas J. Vyncke, Steven Thielemans, Jan A. A. Melkebeek

2013-05-01T23:59:59.000Z

34

PREDICTIVE MODELS  

SciTech Connect

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

35

Embedded Online Optimization for Model Predictive Control at ...  

E-Print Network (OSTI)

College London, SW7 2AZ, United Kingdom, e.kerrigan@imperial.ac.uk ...... tion [ 19] to implement an input-constrained MPC controller for a real-world, highly ...

36

Predictive models of procedural human supervisory control behavior  

E-Print Network (OSTI)

Human supervisory control systems are characterized by the computer-mediated nature of the interactions between one or more operators and a given task. Nuclear power plants, air traffic management and unmanned vehicles ...

Boussemart, Yves, 1980-

2011-01-01T23:59:59.000Z

37

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

38

A Local Model Networks Based Multivariable Long-Range Predictive Control Strategy for Thermal Power Plants  

Science Conference Proceedings (OSTI)

Load-cycling operation of thermal power plants leads to changes in operating point right across the whole operating range. This results in non-linear variations in most of the plant variables. This paper investigates methods to account for non-linearities ... Keywords: Constrained multivariable control, local model networks, long range predictive control, thermal power plant boiler

G. PRASAD; E. SWIDENBANK; B. W. HOGG

1998-10-01T23:59:59.000Z

39

Development and Testing of Model Predictive Control for a Campus Chilled  

NLE Websites -- All DOE Office Websites (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

40

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

DOE Patents (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

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

Model Predictive Control of a Permanent Magnet Synchronous Motor with Experimental Validation  

E-Print Network (OSTI)

Model Predictive Control of a Permanent Magnet Synchronous Motor with Experimental Validation Shan to regulate the speed of a permanent magnet synchronous motor where the design is based on a linearized state rejection, constraints, quadratic programming. 1. Introduction Permanent Magnet Synchronous Motors (PMSMs

42

Intelligent predictive control of micro heat exchanger  

Science Conference Proceedings (OSTI)

An intelligent predictive control to temperature control of a micro heat exchanger is addressed. First, the dynamics of the micro heat exchanger is identified using a locally linear model. Then, the predictive control strategy based on this model of ...

Mehdi Galily; Farzad Habibipour Roudsari; Masoum Fardis; Ali Yazdian

2005-06-01T23:59:59.000Z

43

Model predictive control of a wet limestone flue gas desulfurization pilot plant  

SciTech Connect

A model predictive control (MPC) strategy based on a dynamic matrix (DMC) is designed and applied to a wet limestone flue gas desulfurization (WLFGD) pilot plant to evaluate what enhancement in control performance can be achieved with respect to a conventional decentralized feedback control strategy. The results reveal that MPC can significantly improve both reference tracking and disturbance rejection. For disturbance rejection, the main control objective in WLFGD plants, selection of tuning parameters and sample time, is of paramount importance due to the fast effect of the main disturbance (inlet SO{sub 2} load to the absorber) on the most important controlled variable (outlet flue gas SO{sub 2} concentration). The proposed MPC strategy can be easily applied to full-scale WLFGD plants.

Perales, A.L.V.; Ollero, P.; Ortiz, F.J.G.; Gomez-Barea, A. [University of Seville, Seville (Spain). Dept. of Chemical & Environmental Engineering

2009-06-15T23:59:59.000Z

44

Model Predictive Control-based Optimal Coordination of Distributed Energy Resources  

SciTech Connect

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

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

2013-01-07T23:59:59.000Z

45

Advanced Control Technology Update: Multi-Loop Tuning and Model Predictive Control  

Science Conference Proceedings (OSTI)

This technical update provides information on two projects in the advanced control area. The first project is a study of control system tuning methods for multiple interacting proportional-integral-derivative PID control loops. The traditional method for tuning such systems, common on power plant boiler control systems, is to tune each loop in a specified sequence. An alternative method, in which all loops are tuned simultaneously, is being developed in this study and will be compared to the traditional ...

2008-03-30T23:59:59.000Z

46

Nonlinear predictive control to track deviated power of an identified NNARX model of a hydro plant  

Science Conference Proceedings (OSTI)

This paper presents the performance study of predictive control approach in application to hydro plant. The tracking on deviated power as reference signal for identified neural network nonlinear autoregressive with exogenous signal (NNARX) hydro plant ... Keywords: Deviated power, Hydro plant, Identification, Predictive control, Random load

Nand Kishor

2008-11-01T23:59:59.000Z

47

Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming  

Science Conference Proceedings (OSTI)

This work presents a new algorithm for solving the explicit/multi-parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques. The ... Keywords: Dynamic programming, Explicit Model Predictive Control, Model Predictive Control, Multi-parametric control, Multi-parametric programming

K. I. Kouramas; N. P. Faísca; C. Panos; E. N. Pistikopoulos

2011-08-01T23:59:59.000Z

48

Model Predictive Control of HVAC Systems: Design and Implementation on a Real Case Study.  

E-Print Network (OSTI)

??The final aim of this work is to design, implement and test a controller on a real testbed kindly provided by KTH. The control paradigm… (more)

Pattarello, Giorgio

2013-01-01T23:59:59.000Z

49

A model-based predictive supervisory controller for multi-evaporator HVAC systems  

Science Conference Proceedings (OSTI)

Multi-evaporator vapor compression cooling systems are representative of the complex, distributed nature of modern HVAC systems. Earlier research efforts focused on the development of a decentralized control architecture for individual evaporators that ...

Matthew S. Elliott; Bryan P. Rasmussen

2009-06-01T23:59:59.000Z

50

Stability of Multiobjective Predictive Control: An Utopia-Tracking ...  

E-Print Network (OSTI)

Jan 18, 2012 ... Abstract: We propose a multiobjective strategy for model predictive control (MPC) that we term utopia-tracking MPC. The controller minimizes ...

51

The ECPC Coupled Prediction Model  

Science Conference Proceedings (OSTI)

This paper presents a new Experimental Climate Prediction Center (ECPC) Coupled Prediction Model (ECPM). The ECPM includes the Jet Propulsion Laboratory (JPL) version of the Massachusetts Institute of Technology (MIT) ocean model coupled to the ...

E. Yulaeva; M. Kanamitsu; J. Roads

2008-01-01T23:59:59.000Z

52

Predictive LPV control of a liquid-gas separation process  

Science Conference Proceedings (OSTI)

The problem of controlling a liquid-gas separation process is approached by using LPV control techniques. An LPV model is derived from a nonlinear model of the process using differential inclusion techniques. Once an LPV model is available, an LPV controller ... Keywords: BMIs, LMIs, LPV controllers, LPV systems, Nonlinear systems, Predictive control

J. V. Salcedo; M. Martínez; C. Ramos; J. M. Herrero

2007-07-01T23:59:59.000Z

53

A multivariable predictive fuzzy PID control system  

Science Conference Proceedings (OSTI)

In this paper, a novel multivariable predictive fuzzy-proportional-integral-derivative (F-PID) control system is developed by incorporating the fuzzy and PID control approaches into the predictive control framework. The developed control system has two ... Keywords: BPTT, Control, Fuzzy, LM, Multivariable, PID, Predictive

Aydogan Savran

2013-05-01T23:59:59.000Z

54

Predictive control of supply temperature in district heating systems  

E-Print Network (OSTI)

Predictive control of supply temperature in district heating systems Torben Skov Nielsen Henrik This report considers a new concept for controlling the supply temperature in district heating systems using stochastic modelling, prediction and control. A district heating systems is a di#30;cult system to control

55

Building simulation weather forecast files for predictive control strategies  

Science Conference Proceedings (OSTI)

Model-Based Predictive Control (MPC) has received significant attention in recent years as a tool for load management in buildings. MPC is based on predicting the response of a system based on knowledge of future inputs, such as weather and occupancy. ... Keywords: EPW files, building simulation, predictive control, weather forecast

José. A. Candanedo; Éric Paradis; Meli Stylianou

2013-04-01T23:59:59.000Z

56

NETL: Computer Software & Databases - Predictive Models  

NLE Websites -- All DOE Office Websites (Extended Search)

Predictive Models DOEBC-881SP. EOR Predictive Models: Handbook for Personal Computer Versions of Enhanced Oil Recovery Predictive Models. BPO Staff. February 1988. 76 pp. NTIS...

57

PREDICTIVE MODELS. Enhanced Oil Recovery Model  

SciTech Connect

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

58

Online prediction and control nonlinear stochastic systems  

E-Print Network (OSTI)

temperature in district heat- ing systems. · Prediction of power production from the wind turbines located and their application to prediction and control within district heating systems and for prediction of wind power. Here temperature in district heating systems', Techni- cal Report IMM-REP-2002-23, Informatics and Mathematical

59

PREDICTIVE MODELS. Enhanced Oil Recovery Model  

SciTech Connect

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

60

Integrated Predictive Demand Response Controller Research Project |  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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

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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.


61

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":"

62

Supervisory predictive control and on-line set-point optimization  

Science Conference Proceedings (OSTI)

The subject of this paper is to discuss selected effective known and novel structures for advanced process control and optimization. The role and techniques of model-based predictive control (MPC) in a supervisory (advanced) control layer are first shortly ... Keywords: Constrained Control, Linearization, Model Uncertainty, Nonlinear Control, Predictive Control, Set-Point Optimization

Piotr Tatjewski

2010-09-01T23:59:59.000Z

63

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

SciTech Connect

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

64

Control physical models  

Science Conference Proceedings (OSTI)

This paper describes design of model physical model of rectification column. Physical model is appointed as a demonstration system control for distillation by means of control system SIMATIC PCS7 from company SIEMENS. The SIMATIC PCS7 Process control ... Keywords: description, distillation, physical model, process control system

Tomáš Dvo?ák; Jan Bílek

2005-03-01T23:59:59.000Z

65

Distributed Processing of a Regional Prediction Model  

Science Conference Proceedings (OSTI)

This paper describes the parallelization of a mesoscale-cloud-scale numerical weather prediction model and experiments conducted to assess its performance. The model used is the Advanced Regional Prediction System (ARPS), a limited-area ...

Kenneth W. Johnson; Jeff Bauer; Gregory A. Riccardi; Kelvin K. Droegemeier; Ming Xue

1994-11-01T23:59:59.000Z

66

A Consensus Model for Seasonal Hurricane Prediction  

Science Conference Proceedings (OSTI)

The authors apply a procedure called Bayesian model averaging (BMA) for examining the utility of a set of covariates for predicting the distribution of U.S. hurricane counts and demonstrating a consensus model for seasonal prediction. Hurricane ...

Thomas H. Jagger; James B. Elsner

2010-11-01T23:59:59.000Z

67

Temperature Control of Continued Hyperthermic Celiac Perfusion Based on Generalized Predictive Self-Tuning Control  

Science Conference Proceedings (OSTI)

On the basis of the characteristic and requirement of the continued hyperthermic celiac perfusion (CHCP) temperature process. A model is set up, the generalized predictive self-tuning control (GPSC) algorithm is used to control the whole system to get ... Keywords: CHCP, GPSC, Modeling

Xing-hui Zhang; Hui-min Jiang; Zhao-lin Gu; Zeng-qiang Chen

2008-10-01T23:59:59.000Z

68

Model-free Model-fitting and Predictive Distributions  

E-Print Network (OSTI)

Politis, D.N. (2007a). Model-free vs. model-based volatilityPolitis, D.N. (2007b). Model-free prediction, in Bulletin ofFurthermore, the model-free prediction principle can be

Politis, Dimitris N

2010-01-01T23:59:59.000Z

69

A Nonlinear Model Based (NMPC) Control Strategy for the ...  

Science Conference Proceedings (OSTI)

New advanced process control systems imply utilizing state of the art process control systems as e.g. Nonlinear Model Predictive Control (NMPC). Although the

70

A predictive model for MSSW student success.  

E-Print Network (OSTI)

??Ph. D. This study tested a hypothetical model for predicting both graduate GPA and graduation of University of Louisville Kent School of Social Work Master… (more)

Napier, Angela Michele

2011-01-01T23:59:59.000Z

71

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

72

Greenhouse air temperature predictive control using the particle swarm optimisation algorithm  

Science Conference Proceedings (OSTI)

The particle swarm optimisation algorithm is proposed as a new method to design a model-based predictive greenhouse air temperature controller subject to restrictions. Its performance is compared with the ones obtained by using genetic and sequential ... Keywords: Agriculture, Greenhouse climate, Model predictive control, Particle swarm optimisation algorithms

J. P. Coelho; P. B. de Moura Oliveira; J. Boaventura Cunha

2005-12-01T23:59:59.000Z

73

Neural network predictive control of UPFC for improving transient stability performance of power system  

Science Conference Proceedings (OSTI)

This paper presents a neural network predictive controller for the UPFC to improve the transient stability performance of the power system. A neural network model for the power system is trained using the backpropagation learning method employing the ... Keywords: Identification, Neural networks, Power system transient stability, Predictive control, Unified power flow controller (UPFC)

Sheela Tiwari; Ram Naresh; R. Jha

2011-12-01T23:59:59.000Z

74

Intelligent predictive control of a power plant with evolutionary programming optimizer and neuro-fuzzy identifier  

Science Conference Proceedings (OSTI)

An intelligent predictive controller is implemented to control a fossil fuel power unit. This controller is a non-model based system that uses a self-organized neuro-fuzzy identifier to predict the response of the plant in a future time interval. The ...

H. Ghezelayagh; K. Y. Lee

2002-05-01T23:59:59.000Z

75

Neural network learning of optimal Kalman prediction and control  

Science Conference Proceedings (OSTI)

Although there are many neural network (NN) algorithms for prediction and for control, and although methods for optimal estimation (including filtering and prediction) and for optimal control in linear systems were provided by Kalman in 1960 (with nonlinear ... Keywords: Kalman control, Kalman filter, Local cortical circuit, Recurrent neural network

Ralph Linsker

2008-11-01T23:59:59.000Z

76

Predict-prevent control method for perturbed excitable systems  

E-Print Network (OSTI)

We present a control method based on two steps: prediction and prevention. For prediction we use the anticipated synchronization scheme, considering unidirectional coupling between excitable systems in a master-slave configuration. The master is the perturbed system to be controlled, meanwhile the slave is an auxiliary system which is used to predict the master's behavior. We demonstrate theoretically and experimentally that an efficient control may be achieved.

Marzena Ciszak; Claudio R. Mirasso; Raul Toral; Oscar Calvo

2008-07-15T23:59:59.000Z

77

Predicting software bugs using ARIMA model  

Science Conference Proceedings (OSTI)

The number of software products available in market is increasing rapidly. Many a time, multiple companies develop software products of similar functionalities. Thus the competition among those owning companies is becoming tougher every day. Moreover, ... Keywords: ARIMA models, evaluation approach, information theory, prediction models

Lisham L. Singh; Al Muhsen Abbas; Flaih Ahmad; Srinivasan Ramaswamy

2010-04-01T23:59:59.000Z

78

A stable one-step-ahead predictive control of non-linear systems  

Science Conference Proceedings (OSTI)

In this paper stability of one-step ahead predictive controllers based on non-linear models is established. It is shown that, under conditions which can be fulfilled by most industrial plants, the closed-loop system is robustly stable in the presence ... Keywords: Input-output constraints, Neural networks, Nonlinear systems, Predictive control, RBFN's, Robust, Stability

C. Kambhampati; J. D. Mason; K. Warwick

2000-04-01T23:59:59.000Z

79

Prediction of Magnetic Storms by Nonlinear Models  

E-Print Network (OSTI)

The strong correlation between magnetic storms and southward interplanetary magnetic field (IMF) is well known from linear prediction filter studies using the Dst and IMF data. However, the linear filters change significantly from one storm to another and thus are limited in their predicting ability. Previous studies have indicated nonlinearity in the magnetospheric response as the ring current decay rate varies with the Dst value during storms. We present in this letter nonlinear models for the evolution of the Dst based on the OMNI database for 1964-1990. When solar wind data are available in advance, the evolution of storms can be predicted from the Dst and IMF data. Solar wind data, however, are not available most of the time or are available typically an hour or less in advance. Therefore, we have developed nonlinear predictive models based on the Dst data alone. In the absence of solar wind data, these models cannot predict the storm onset, but can predict the storm evolution, an...

J. A. Valdivia; A. S. Sharma; K. Papadopoulos

1996-01-01T23:59:59.000Z

80

Development of an Ocean Model Adjoint for Decadal Prediction | Argonne  

NLE Websites -- All DOE Office Websites (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

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

Combining Modeling and Gaming for Predictive Analytics  

SciTech Connect

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

Riensche, Roderick M.; Whitney, Paul D.

2012-08-22T23:59:59.000Z

82

Predictive modeling for collections of accounts receivable  

Science Conference Proceedings (OSTI)

It is commonly agreed that accounts receivable (AR) can be a source of financial difficulty for firms when they are not efficiently managed and are underperforming. Experience across multiple industries shows that effective management of AR and overall ... Keywords: accounts receivable, invoice to cash, knowledge discovery, order to cash, payment collection, predictive modeling

Sai Zeng; Ioana Boier-Martin; Prem Melville; Conrad Murphy; Christian A. Lang

2007-08-01T23:59:59.000Z

83

Comparing cost prediction models by resampling techniques  

Science Conference Proceedings (OSTI)

The accurate software cost prediction is a research topic that has attracted much of the interest of the software engineering community during the latest decades. A large part of the research efforts involves the development of statistical models based ... Keywords: Accuracy measure, Bootstrap, Confidence interval, Permutation test, Software cost estimation

Nikolaos Mittas; Lefteris Angelis

2008-05-01T23:59:59.000Z

84

Regression modeling method of space weather prediction  

E-Print Network (OSTI)

A regression modeling method of space weather prediction is proposed. It allows forecasting Dst index up to 6 hours ahead with about 90% correlation. It can also be used for constructing phenomenological models of interaction between the solar wind and the magnetosphere. With its help two new geoeffective parameters were found: latitudinal and longitudinal flow angles of the solar wind. It was shown that Dst index remembers its previous values for 2000 hours.

Parnowski, Aleksei

2009-01-01T23:59:59.000Z

85

Nonlinear multivariable predictive control of an autothermal reforming reactor for fuel cell applications  

Science Conference Proceedings (OSTI)

In this work, we present a computationally efficient nonlinear multivariable predictive controller (NMPC) for an autothermal reforming (ATR) reactor. The proposed NMPC scheme is based on a fast reduced order nonlinear model and consists of three parts. ...

Yongyou Hu; Donald J. Chmielewski

2009-06-01T23:59:59.000Z

86

Development of Rail Temperature Prediction Model SUMMARY  

E-Print Network (OSTI)

Preventing track buckling is important to the railroad industry’s goal of operational safety. It is a common practice for railroads to impose slow orders during hot weather when the risk of track buckling is high. Numerous factors affect track buckling, but the instantaneous rail temperatures and stress-free (neutral) rail temperatures are the most critical factors. Unfortunately, neither of these two temperatures is easily obtainable. Decisions for slow orders are often based on an arbitrary, ambient temperature limit. The Federal Railroad Administration (FRA) Office of Research and Development has initiated a research project to develop a model for predicting rail temperatures based on real-time meteorological forecast data. The rail temperature prediction model is based on the heat transfer process of a rail exposed to the sun. In developing such a model, a rail-weather station was established, composed of a portable weather station and a short segment of rail track with temperature sensors installed on both rails. The model has proven to be able to predict the maximum rail temperature within a few degrees and within 30 minutes of the actual time when the maximum rail temperature occurs during the day. The model is being validated for three locations where real-time weather data and rail temperature are collected. A prototype webbased

unknown authors

2008-01-01T23:59:59.000Z

87

Design, optimization and predictions of a coupled model of the cell cycle, circadian clock, DNA repair system, irinotecan metabolism and exposure control under temporal logic constraints  

Science Conference Proceedings (OSTI)

In systems biology, the number of available models of cellular processes has increased rapidly, but re-using models in different contexts or for different questions remains a challenging issue. In this paper, we study the coupling of different models ... Keywords: Cell cycle, Constraint solving, DNA damage, Irinotecan, Model checking, Model coupling, Parameter learning, Temporal logic

Elisabetta De Maria; François Fages; Aurélien Rizk; Sylvain Soliman

2011-05-01T23:59:59.000Z

88

Demand-side management in office buildings in Kuwait through an ice-storage assisted HVAC system with model predictive control.  

E-Print Network (OSTI)

??Examining methods for controlling the electricity demand in Kuwait was the main objective and motivation of this researchp roject. The extensiveu se of air-conditioning for… (more)

Al-Hadban, Yehya

2005-01-01T23:59:59.000Z

89

PreHeat: controlling home heating using occupancy prediction  

Science Conference Proceedings (OSTI)

Home heating is a major factor in worldwide energy use. Our system, PreHeat, aims to more efficiently heat homes by using occupancy sensing and occupancy prediction to automatically control home heating. We deployed PreHeat in five homes, three in the ... Keywords: energy, environment, home heating, prediction, sensing

James Scott; A.J. Bernheim Brush; John Krumm; Brian Meyers; Michael Hazas; Stephen Hodges; Nicolas Villar

2011-09-01T23:59:59.000Z

90

Process Mapping for Microstructure Prediction and Control in ...  

Science Conference Proceedings (OSTI)

The ability to predict and control the as-deposited microstructure can reduce the need for post-processing and speed up the qualification process. Ti-6Al-4V is a ...

91

New model accurately predicts reformate composition  

Science Conference Proceedings (OSTI)

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

Ancheyta-Juarez, J.; Aguilar-Rodriguez, E. (Inst. Mexicano del Petroleo, Mexico City (Mexico))

1994-01-31T23:59:59.000Z

92

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."

93

Predictive modelling of boiler fouling. Final report.  

SciTech Connect

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

Chatwani, A

1990-12-31T23:59:59.000Z

94

Application of support vector machines in scour prediction on grade-control structures  

Science Conference Proceedings (OSTI)

Research into the problem of predicting the maximum depth of scour on grade-control structures like sluice gates, weirs and check dams, etc., has been mainly of an experimental nature and several investigators have proposed a number of empirical relations ... Keywords: Back propagation neural network, Grade-control structures, Modeling, Scour, Support vector machines

Arun Goel; Mahesh Pal

2009-03-01T23:59:59.000Z

95

LLNL-TR-411072 A Predictive Model  

NLE Websites -- All DOE Office Websites (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.

96

Modeling and control of thermostatically controlled loads  

SciTech Connect

As the penetration of intermittent energy sources grows substantially, loads will be required to play an increasingly important role in compensating the fast time-scale fluctuations in generated power. Recent numerical modeling of thermostatically controlled loads (TCLs) has demonstrated that such load following is feasible, but analytical models that satisfactorily quantify the aggregate power consumption of a group of TCLs are desired to enable controller design. We develop such a model for the aggregate power response of a homogeneous population of TCLs to uniform variation of all TCL setpoints. A linearized model of the response is derived, and a linear quadratic regulator (LQR) has been designed. Using the TCL setpoint as the control input, the LQR enables aggregate power to track reference signals that exhibit step, ramp and sinusoidal variations. Although much of the work assumes a homogeneous population of TCLs with deterministic dynamics, we also propose a method for probing the dynamics of systems where load characteristics are not well known.

Backhaus, Scott N [Los Alamos National Laboratory; Sinitsyn, Nikolai [Los Alamos National Laboratory; Kundu, S. [UNIV OF MICHIGAN; Hiskens, I. [UNIV OF MICHIGAN

2011-01-04T23:59:59.000Z

97

The UCONABC usage control model  

Science Conference Proceedings (OSTI)

In this paper, we introduce the family of UCONABC models for usage control (UCON), which integrate Authorizations (A), oBligations (B), and Conditions (C). We call these core models because they address the essence of UCON, leaving ... Keywords: access control, digital rights management, privacy, trust, usage control

Jaehong Park; Ravi Sandhu

2004-02-01T23:59:59.000Z

98

Identification and predictive control for a circulation fluidized bed boiler  

Science Conference Proceedings (OSTI)

This paper introduces the design and presents the research findings of the identification and control application for an industrial Circulation Fluidized Bed (CFB) boiler. Linear Parameter Varying (LPV) model is used in the model identification where ... Keywords: CFB boilers, Identification, LPV model, Linear models interpolation, MPC

Guoli Ji, Jiangyin Huang, Kangkang Zhang, Yucai Zhu, Wei Lin, Tianxiao Ji, Sun Zhou, Bin Yao

2013-06-01T23:59:59.000Z

99

Experiences with collaborative, distributed predictive human performance modeling  

Science Conference Proceedings (OSTI)

Although predictive human performance modeling has been researched for 30 years in HCI, to our knowledge modeling has been conducted as a solitary task of one modeler or, occasionally, two modelers working in tight face-to-face collaboration. In contrast, ... Keywords: cogtool, efficiency, klm, predictive human performance modeling, usability evaluation

Bonnie John; Sonal Starr; Brian Utesch

2012-05-01T23:59:59.000Z

100

On the practice of artificial intelligence based predictive control scheme: a case study  

Science Conference Proceedings (OSTI)

This paper describes a novel artificial intelligence based predictive control scheme for the purpose of dealing with so many complicated systems. In the control scheme proposed here, the system has to be first represented through a multi-Takagi-Sugeno-Kang ... Keywords: Drum-type boiler-turbine system, GPC identifier, GPC scheme, Industrial tubular heat exchanger system, Linear model approximation, Multi-GPC scheme, Multi-TSK fuzzy-based model approach, NLGPC scheme, System operating points

A. H. Mazinan; M. Sheikhan

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).
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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  

Science Conference Proceedings (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

A Predictive Model of Geosynchronous Magnetopause Crossings  

E-Print Network (OSTI)

We have developed a model predicting whether or not the magnetopause crosses geosynchronous orbit at given location for given solar wind pressure Psw, Bz component of interplanetary magnetic field (IMF) and geomagnetic conditions characterized by 1-min SYM-H index. The model is based on more than 300 geosynchronous magnetopause crossings (GMCs) and about 6000 minutes when geosynchronous satellites of GOES and LANL series are located in the magnetosheath (so-called MSh intervals) in 1994 to 2001. Minimizing of the Psw required for GMCs and MSh intervals at various locations, Bz and SYM-H allows describing both an effect of magnetopause dawn-dusk asymmetry and saturation of Bz influence for very large southward IMF. The asymmetry is strong for large negative Bz and almost disappears when Bz is positive. We found that the larger amplitude of negative SYM-H the lower solar wind pressure is required for GMCs. We attribute this effect to a depletion of the dayside magnetic field by a storm-time intensification of t...

Dmitriev, A; Chao, J -K

2013-01-01T23:59:59.000Z

103

Model Predictive Control for Energy Efficient Buildings  

E-Print Network (OSTI)

Internal load profile (Pthe nominal internal load profile Time Figure 4.1: AmbientFigure 4.2: Internal load profile (P dn ). (P dn ) in our

Ma, Yudong

2012-01-01T23:59:59.000Z

104

Predictive control with Gaussian process models  

E-Print Network (OSTI)

Kocijan,J. Murray-Smith,R. Rasmussen,C.E. Likar,B. IEEE Eurocon 2003: The International Conference on Computer as a Tool, September, Ljubljana, Slovenia, IEEE

Kocijan, J.; Murray-Smith, R.

105

Nonlinear Predictive Control with Gaussian Process Model  

E-Print Network (OSTI)

Kocijan,J. Murray-Smith,R. Proceedings of the Hamilton Summer School on Switching and Learning in Feedback systems, Ed. R. Murray-Smith, R. Shorten, Springer-Verlag, Lecture Notes in Computing Science, Vol. 3355 pp p185-200 Springer Verlag

Kocijan, J.; Murray-Smith, R.

106

Optimization Online - Nonlinear Model Predictive Control via ...  

E-Print Network (OSTI)

Aug 15, 2002 ... Citation: Optimization Technical Report 02-06, August, 2002, Computer Sciences Department, University of Wisconsin. Texas-Wisconsin ...

107

Model Predictive Control for Energy Efficient Buildings  

E-Print Network (OSTI)

temperature. 2. I i : Solar radiation intensity of ith zone.load induced by occupancy, solar radiations, and electricalinduced by occupancy, solar radiation as well as electrical

Ma, Yudong

2012-01-01T23:59:59.000Z

108

Model Predictive Control for Energy Efficient Buildings  

E-Print Network (OSTI)

Energy Savings”. In: Energy and Buildings 40.7 (2008), pp.Thermal Dynamics”. In: Energy and Buildings 47 (Apr. 2011),Storage Systems”. In: Energy and Buildings 35.2 (2003), pp.

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

Model Predictive Control for Energy Efficient Buildings  

E-Print Network (OSTI)

Cooling tower modeltime of chillers and cooling towers. The sampling rate is 1of chillers (2.14), cooling towers (2.15)-(2.16), and

Ma, Yudong

2012-01-01T23:59:59.000Z

111

Grey-prediction self-organizing fuzzy controller for robotic motion control  

Science Conference Proceedings (OSTI)

A self-organizing fuzzy controller (SOFC) under system control has online learning capabilities; nevertheless, the SOFC may excessively modify its fuzzy rules when its learning rate and weighting distribution are inappropriately selected. This results ... Keywords: Grey-prediction algorithm, Robotic systems, Self-organizing fuzzy controller

Ruey-Jing Lian

2012-10-01T23:59:59.000Z

112

A beta regression model for improved solar radiation predictions  

Science Conference Proceedings (OSTI)

Predicting global solar radiation is an integral part of much environmental modeling. There are several approaches for predicting global solar radiation at a site where no instrumentation exists. One popular approach uses the difference between ...

Randall Mullen; Lucy Marshall; Brian McGlynn

113

Hurricane Track Prediction Using a Statistical Ensemble of Numerical Models  

Science Conference Proceedings (OSTI)

A new statistical ensemble prediction system for tropical cyclone tracks is presented. The system is based on a statistical analysis of the annual performance of numerical track prediction models, assuming that their position errors are ...

Harry C. Weber

2003-05-01T23:59:59.000Z

114

A Beta Regression Model for Improved Solar Radiation Predictions  

Science Conference Proceedings (OSTI)

Predicting global solar radiation is an integral part of much environmental modeling. There are several approaches for predicting global solar radiation at a site where no instrumentation exists. One popular approach uses the difference between ...

Randall Mullen; Lucy Marshall; Brian McGlynn

2013-08-01T23:59:59.000Z

115

A Nonlinear Artificial Intelligence Ensemble Prediction Model for Typhoon Intensity  

Science Conference Proceedings (OSTI)

A new nonlinear artificial intelligence ensemble prediction (NAIEP) model has been developed for predicting typhoon intensity based on multiple neural networks with the same expected output and using an evolutionary genetic algorithm (GA). The ...

Long Jin; Cai Yao; Xiao-Yan Huang

2008-12-01T23:59:59.000Z

116

A Coupled Soil Moisture and Surface Temperature Prediction Model  

Science Conference Proceedings (OSTI)

A model for soil moisture and soil surface temperature prediction for bare soil is considered in this paper. In describing evaporation rate. soil structure and moisture were taken into account as much as possible. Soil moisture prediction was ...

F. Ács; D. T. Mihailovi?; B. Rajkovi?

1991-06-01T23:59:59.000Z

117

Enhanced oil recovery data base analysis by simplified predictive models  

Science Conference Proceedings (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

118

A Comparison of Experimental Data and Model Predictions with ...  

Science Conference Proceedings (OSTI)

A Comparison of Experimental Data and Model Predictions with Constitutive Laws ... Friction Stir Welding and Processing of Advanced Materials for Coal and  ...

119

Predictability Mysteries in Cloud-Resolving Models  

Science Conference Proceedings (OSTI)

The rapid amplification of small-amplitude perturbations by the chaotic nature of the atmospheric dynamics intrinsically limits the skill of deterministic weather forecasts. In this study, limited-area cloud-resolving numerical weather prediction ...

Cathy Hohenegger; Daniel Lüthi; Christoph Schär

2006-08-01T23:59:59.000Z

120

Predictive modeling of reactive wetting and metal joining.  

SciTech Connect

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

van Swol, Frank B.

2013-09-01T23:59:59.000Z

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

A Linearized Convective Overturning Model for Prediction of Thunderstorm Movement  

Science Conference Proceedings (OSTI)

A linearized model of convective overturning in shear for prediction of storm propagation is presented. Good correspondence between the model and observation is found for a number of case studies of real storms. Supercell storms, however, are an ...

Adrian Marroquin; David J. Raymond

1982-01-01T23:59:59.000Z

122

Prediction Models for Annual U.S. Hurricane Counts  

Science Conference Proceedings (OSTI)

The authors build on their efforts to understand and predict coastal hurricane activity by developing statistical seasonal forecast models that can be used operationally. The modeling strategy uses May–June averaged values representing the North ...

James B. Elsner; Thomas H. Jagger

2006-06-01T23:59:59.000Z

123

An Interpretable Stroke Prediction Model using Rules and Bayesian Analysis  

E-Print Network (OSTI)

We aim to produce predictive models that are not only accurate, but are also interpretable to human experts. Our models are decision lists, which consist of a series of if...then... statements (for example, if high blood ...

Letham, Benjamin

2013-11-15T23:59:59.000Z

124

NETL: Predictive Modeling and Evaluation - TVA Model Comparison  

NLE Websites -- All DOE Office Websites (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.

125

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

126

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

127

FEASIBILITY STUDY OF THE POTENTIAL USE OF CHEMISTRY BASED EMISSION PREDICTIONS FOR REAL-TIME CONTROL OF MODERN DIESEL ENGINES.  

E-Print Network (OSTI)

. Adding the model to the overall engine and aftertreatment control and diagnostics strategy. "NOx prediction in diesel engines for aftertreatment control," ASME 2003-41196. [5] Aithal SM. 2008-TIME CONTROL OF MODERN DIESEL ENGINES. S. M. Aithal Mathematics and Computer Science Division Argonne National

128

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

E-Print Network (OSTI)

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

Martin, A; Venkatesan, Dr V Prasanna

2011-01-01T23:59:59.000Z

129

Sugeno predictive neuro-fuzzy controller for improving dynamic performance of control systems of nonlinear plants under uncertainties  

Science Conference Proceedings (OSTI)

The aim is to develop simple Sugeno neuro-fuzzy predictive controller to improve the dynamic performance of control systems of nonlinear plants under uncertainties. The controller is designed by ANFIS of MATLAB and is successfully applied for the control ... Keywords: ANFIS, MATLAB, Sugeno neuro-fuzzy controller, anaerobic digestion of organic waste in waters, prediction, simulation

Snejana Yordanova; Rusanka Petrova; Valeri Mladenov

2006-07-01T23:59:59.000Z

130

Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory  

DOE Green Energy (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

131

Trajectory Design and Implementation for Multiple Autonomous Underwater Vehicles Based on Ocean Model Predictions  

E-Print Network (OSTI)

Underwater Vehicles Based on Ocean Model Predictions Ryan N.Trajectory Design based on Ocean Model Predictions PredictEffective tracking of ocean features Gather specific in situ

2009-01-01T23:59:59.000Z

132

Analytical Modeling and Performance Prediction of Remanufactured ...  

Science Conference Proceedings (OSTI)

The CLP tool assists in remanufacturing of high value, high demand rotorcraft, automotive and wind turbine gears. This paper will summarize the CLP models ...

133

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

E-Print Network (OSTI)

response HVAC control strategy," in proceedings of the 2nd ACM Workshop on Embedded Sensing SystemsA Occupancy Modeling and Prediction for Building Energy Management Varick L. Erickson, University into building conditioning system for usage based demand control conditioning strategies. Using strategies based

Cerpa, Alberto E.

134

A predictive ocean oil spill model  

SciTech Connect

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

The Integrated Environmental Control Model (IECM)  

NLE Websites -- All DOE Office Websites (Extended Search)

Innovations for Existing Plants The Integrated Environmental Control Model (IECM) The Integrated Environmental Control Model (IECM) was developed for the National Energy Technology...

136

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

137

LHC diphoton Higgs signal predicted by little Higgs models  

Science Conference Proceedings (OSTI)

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

Wang Lei [Department of Physics, Yantai University, Yantai 264005 (China); Yang Jinmin [Key Laboratory of Frontiers in Theoretical Physics, Institute of Theoretical Physics, Academia Sinica, Beijing 100190 (China)

2011-10-01T23:59:59.000Z

138

Prediction of turbulence control for arbitrary periodic spanwise wall movement  

E-Print Network (OSTI)

In order to generalize the well-known spanwise-oscillating-wall technique for drag reduction, non-sinusoidal oscillations of a solid wall are considered as a means to alter the skin-friction drag in a turbulent channel flow. A series of Direct Numerical Simulations is conducted to evaluate the control performance of nine different temporal waveforms, in addition to the usual sinusoid, systematically changing the wave amplitude and the period for each waveform. The turbulent average spanwise motion is found to coincide with the laminar Stokes solution that is constructed, for the generic waveform, through harmonic superposition. This allows us to define and compute, for each waveform, a new penetration depth of the Stokes layer which correlates with the amount of turbulent drag reduction, and eventually to predict both turbulent drag reduction and net energy saving rate for arbitrary waveforms. Among the waveforms considered, the maximum net energy saving rate is obtained by the sinusoidal wave at its optimal ...

Cimarelli, Andrea; Hasegawa, Yosuke; De Angelis, Elisabetta; Quadrio, Maurizio

2013-01-01T23:59:59.000Z

139

Numerical Ocean Prediction Models—Goal for the 1980s  

Science Conference Proceedings (OSTI)

Based on the experience of numerical weather prediction during the 1950s and 1960s as a model, a case is presented for the development of an ocean prediction capability during the 1980s. Examples selected from recent research at the Naval ...

Russell L. Elsberry; Roland W. Garwood Jr.

1980-12-01T23:59:59.000Z

140

Settlement Prediction, Gas Modeling and Slope Stability Analysis  

E-Print Network (OSTI)

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

Politècnica de Catalunya, Universitat

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

A Model to Predict the Probability of Precipitation  

Science Conference Proceedings (OSTI)

A model to predict the probability of a specific amount of accumulated precipitation at a point in an area of extended convective precipitation has been developed. The model has been used in conjunction with a large-scale numerical forecast model ...

Ulla Hammarstrand

1980-06-01T23:59:59.000Z

142

Hurricane Track Prediction with a New Barotropic Model  

Science Conference Proceedings (OSTI)

A new barotropic prediction system for the tracks of tropical cyclones is presented. The system (referred to as WBAR) consists of an initialization procedure, a vortex enhancement scheme, and a shallow water model, formulated in a geographical ...

Harry C. Weber

2001-08-01T23:59:59.000Z

143

Nonlinear predictive models: overview and possibilities in speaker recognition  

Science Conference Proceedings (OSTI)

In this paper we give a brief overview of speaker recognition with special emphasis on nonlinear predictive models, based on neural nets. Main challenges and possibilities for nonlinear feature extraction are described, and experimental results of several ...

Marcos Faundez-Zanuy; Mohamed Chetouani

2007-01-01T23:59:59.000Z

144

Forecasting Pacific SSTs: Linear Inverse Model Predictions of the PDO  

Science Conference Proceedings (OSTI)

A linear inverse model (LIM) is used to predict Pacific (30°S–60°N) sea surface temperature anomalies (SSTAs), including the Pacific decadal oscillation (PDO). The LIM is derived from the observed simultaneous and lagged covariance statistics of ...

Michael A. Alexander; Ludmila Matrosova; Cécile Penland; James D. Scott; Ping Chang

2008-01-01T23:59:59.000Z

145

Performance and prediction: bayesian modelling of fallible choice in chess  

Science Conference Proceedings (OSTI)

Evaluating agents in decision-making applications requires assessing their skill and predicting their behaviour. Both are well developed in Poker-like situations, but less so in more complex game and model domains. This paper addresses both tasks by ...

Guy Haworth; Ken Regan; Giuseppe Di Fatta

2009-05-01T23:59:59.000Z

146

Cloud Predictions Diagnosed from Global Weather Model Forecasts  

Science Conference Proceedings (OSTI)

The U.S. Air Force has a long history of investment in cloud analysis and prediction operations. Their need for accurate cloud cover information has resulted in routine production of global cloud analyses (from their RTNEPH analysis model) and ...

Donald C. Norquist

2000-10-01T23:59:59.000Z

147

Representing Convective Organization in Prediction Models by a Hybrid Strategy  

Science Conference Proceedings (OSTI)

The mesoscale organization of precipitating convection is highly relevant to next-generation global numerical weather prediction models, which will have an intermediate horizontal resolution (grid spacing about 10 km). A primary issue is how to ...

Mitchell W. Moncrieff; Changhai Liu

2006-12-01T23:59:59.000Z

148

Predictability Associated with Nonlinear Regimes in an Atmospheric Model  

Science Conference Proceedings (OSTI)

Atmospheric regimes are midlatitude flow patterns that persist for periods of time exceeding a few days. Here, the authors analyzed the output of an idealized atmospheric model (QG3) to examine the relationship between regimes and predictability.

John M. Peters; Sergey Kravtsov; Nicholas T. Schwartz

2012-03-01T23:59:59.000Z

149

Extended-Range Atmospheric Prediction and the Lorenz Model  

Science Conference Proceedings (OSTI)

The physical basis for extended-range prediction is explored using the famous three-component Lorenz convection model, taken as a conceptual representation of the chaotic extratropical circulation, and extended by coupling to a linear oscillator ...

T. N. Palmer

1993-01-01T23:59:59.000Z

150

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

NLE Websites -- All DOE Office Websites (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.

151

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

152

A generalized adaptive predictive controller design-based direct identification for district heating system  

Science Conference Proceedings (OSTI)

To realize accurate control for district heating system, a GPC (generalized predictive control) adaptive algorithm was presented that directly identified controller's parameters with two identifiers. The algorithm could adapt characteristics of district ... Keywords: adaptive, direct identification, district heating system, generalized predictive control

Zhao Youen

2009-06-01T23:59:59.000Z

153

Integrated model-based control and diagnostic monitoring for automotive catalyst systems  

Science Conference Proceedings (OSTI)

An integrated model-based automotive catalyst control and diagnostic monitoring system is presented. This system incorporates a simplified dynamic catalyst model that describes oxygen storage and release in the catalyst and predicts the post-catalyst ... Keywords: automotive catalyst, model predictive control, on-board diagnostic monitoring

Kenneth R. Muske; James C. Peyton Jones

2007-11-01T23:59:59.000Z

154

A prediction of energy savings resulting from building infiltration control  

E-Print Network (OSTI)

This thesis provides a description of the methods of application of theoretical models of heat transfer in computer simulations, to determine the energy performance of a wall or building. The heat transfer simulations include calculation equations which account for the interaction among conduction heat transfer, solar gain, and infiltration heat transfer in building walls. This interaction effect has received only limited previous study. The goal of modeling the behavior of a building with these simulations is to determine optimum arrangements of induced (or controlled) airflow direction and magnitude in building exterior walls, where the walls can be considered porous and can act, to an extent, like a heat exchanger. Recent research toward designing walls especially suited to this application has developed porous walls which are dubbed "dynamic walls." This study attempts to determine the optimum application of dynamic walls, or walls which behave in a similar fashion, in a building in a theoretical analysis. The computer simulations which apply the calculations to model the energy use of a building have been written especially for this study. The results of the theoretical analysis made for this thesis show that significant energy savings can be realized with the use of controlled airflow through non-airtight walls in a building. Comparing the energy use of a building which uses airflow control in dynamic walls with the energy use found with a standard calculation (where the interaction effect is not considered), annual energy savings were found in a warm climate as high as 17%, and as high as 30% in a cooler climate. The results were less promising when compared against the performance of a building experiencing natural, or not induced, airflow (and heat recovery) through its exterior walls: the best annual savings percentages were 10% in a warm climate and just 2% in a cooler climate. The specific building airflow arrangements which produce the best theoretical performances found in this study should be considered for application in future experimental tests, if the dynamic walls and/or building airflow control system are considered economically feasible in light of the projected energy savings they produce.

McWatters, Kenneth Rob

1995-01-01T23:59:59.000Z

155

A Numerical Model for Prediction of Road Temperature and Ice  

Science Conference Proceedings (OSTI)

A numerical model for the prediction of road temperature and ice has been tested on data from a Danish road station. The model is based on the solution of the equation of heat conduction in the ground and the surface energy-balance equation.

Bent H. Sass

1992-12-01T23:59:59.000Z

156

Crude Oil Price Prediction Using Slantlet Denoising Based Hybrid Models  

Science Conference Proceedings (OSTI)

The accurate prediction of crude oil price movement has always been the central issue with profound implications across different levels of the economy. This study conducts empirical investigations into the characteristics of crude oil market and proposes ... Keywords: Slantlet Analysis, ARMA Model, Hybrid Forecasting Algorithm, Rrandom Walk Model, Support Vector Regression

Kaijian He; Kin Keung Lai; Jerome Yen

2009-04-01T23:59:59.000Z

157

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.

158

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

E-Print Network (OSTI)

of numerical weather prediction solar irradiance forecasts of numerical weather prediction for intra?day solar numerical weather prediction model for solar irradiance 

Mathiesen, Patrick; Collier, Craig; Kleissl, Jan

2013-01-01T23:59:59.000Z

159

Mathematical modeling to predict residential solid waste generation  

Science Conference Proceedings (OSTI)

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

Ojeda Benitez, Sara [Engineering Institute, UABC, Boulevard Benito Juarez y Calle de la Normal S/N, Col. Insurgentes Este, C.P. 21280, Mexicali, Baja California (Mexico)], E-mail: sojedab@uabc.mx; Lozano-Olvera, Gabriela [Engineering Institute, UABC, Boulevard Benito Juarez y Calle de la Normal S/N, Col. Insurgentes Este, C.P. 21280, Mexicali, Baja California (Mexico); Morelos, Raul Adalberto [CESUES Superior Studies Center, San Luis R.C. Sonora (Mexico); Vega, Carolina Armijo de [Engineering Faculty, UABC, Km 103, Carretera Tijuana-Ensenada, C.P. 22860, Ensenada, Baja California (Mexico)

2008-07-01T23:59:59.000Z

160

Lepton Flavor Violation in Predictive Supersymmetric GUT Models  

E-Print Network (OSTI)

There have been many theoretical models constructed which aim to explain the neutrino masses and mixing patterns. While many of the models will be eliminated once more accurate determinations of the mixing parameters, especially $\\sin^2 2\\theta_{13}$, are obtained, charged lepton flavor violation (LFV) experiments are able to differentiate even further among the models. In this paper, we investigate various rare LFV processes, such as $\\ell_{i} \\to \\ell_{j} + \\gamma$ and $\\mu-e$ conversion, in five predictive supersymmetric (SUSY) SO(10) models and their allowed soft-SUSY breaking parameter space in the constrained minimal SUSY standard model. Utilizing the Wilkinson Microwave Anisotropy Probe dark matter constraints, we obtain lower bounds on the branching ratios of these rare processes and find that at least three of the five models we consider give rise to predictions for $\\mu \\to e + \\gamma$ that will be tested by the MEG Collaboration at PSI. In addition, the next generation $\\mu-e$ conversion experiment has sensitivity to the predictions of all five models, making it an even more robust way to test these models. While generic studies have emphasized the dependence of the branching ratios of these rare processes on the reactor neutrino angle $\\theta_{13}$ and the mass of the heaviest right-handed neutrino $M_3$, we find very massive $M_3$ is more significant than large $\\theta_{13}$ in leading to branching ratios near to the present upper limits.

Carl H. Albright; Mu-Chun Chen

2008-02-28T23:59:59.000Z

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161

Lepton Flavor Violation in Predictive SUSY-GUT Models  

SciTech Connect

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

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

2008-02-01T23:59:59.000Z

162

Development of a Predictive Optimal Controller for Thermal Energy Storage Systems  

E-Print Network (OSTI)

This paper describes the development and simulation of a predictive optimal controller for thermal energy storage systems. The `optimal' strategy minimizes the cost of operating the cooling plant over the simulation horizon. The particular case of a popular ice storage system (ice-on-coil with internal melt) has been investigated in a simulation environment. Various predictor models have been analyzed with respect to their performance in forecasting cooling load data and information on ambient conditions (dry-bulb and wet-bulb temperatures). The predictor model provides load and weather information to the optimal controller in discrete time steps. An optimal storage charging and discharging strategy is planned at every time step over a fixed look-ahead time window utilizing newly available information. The first action of the optimal sequence of actions is executed over the next time step and the planning process is repeated at every following time step. The effect of the length of the...

Gregor Henze; Robert H. Dodier; Moncef Krarti

1996-01-01T23:59:59.000Z

163

Forecasting the Skill of a Regional Numerical Weather Prediction Model  

Science Conference Proceedings (OSTI)

It is demonstrated that the skill of short-term regional numerical forecasts can be predicted on a day-to-day basis. This was achieved by using a statistical regression scheme with the model forecast errors (MFE) as the predictands and the ...

L. M. Leslie; K. Fraedrich; T. J. Glowacki

1989-03-01T23:59:59.000Z

164

Hurricane Prediction with a High Resolution Global Model  

Science Conference Proceedings (OSTI)

A global spectral model is used to carry out a number of short to medium range prediction experiments with global datasets. The primary objective of these studies is to examine the formation and motion of the hurricanes/typhoons with a fairly ...

T. N. Krishnamurti; D. Oosterhof; Nancy Dignon

1989-03-01T23:59:59.000Z

165

Reference wind farm selection for regional wind power prediction models  

E-Print Network (OSTI)

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

Paris-Sud XI, Université de

166

Predictive discrete latent factor models for large scale dyadic data  

Science Conference Proceedings (OSTI)

We propose a novel statistical method to predict large scale dyadic response variables in the presence of covariate information. Our approach simultaneously incorporates the effect of covariates and estimates local structure that is induced by interactions ... Keywords: co-clustering, dyadic data, generalized linear regression, latent factor modeling

Deepak Agarwal; Srujana Merugu

2007-08-01T23:59:59.000Z

167

Rain Attenuation Prediction Model for Lagos at Millimeter Wave Bands  

Science Conference Proceedings (OSTI)

“Rain Attenuation Prediction Model for Lagos at Millimeter Wave bands” is the subject of this work. Lagos (geog. Lat. 6.350N and Long. 3.20E), is a coastal station in the rain forest area in the South-Western Nigeria with an altitude of 380 ...

Abayomi Isiaka Yussuff; Nor Hisham Haji Khamis

168

Behavioral dynamics on the web: Learning, modeling, and prediction  

Science Conference Proceedings (OSTI)

The queries people issue to a search engine and the results clicked following a query change over time. For example, after the earthquake in Japan in March 2011, the query japan spiked in popularity and people issuing the query were more likely ... Keywords: Behavioral analysis, predictive behavioral models

Kira Radinsky; Krysta M. Svore; Susan T. Dumais; Milad Shokouhi; Jaime Teevan; Alex Bocharov; Eric Horvitz

2013-07-01T23:59:59.000Z

169

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

170

Comprehensive fluence model for absolute portal dose image prediction  

SciTech Connect

Amorphous silicon (a-Si) electronic portal imaging devices (EPIDs) continue to be investigated as treatment verification tools, with a particular focus on intensity modulated radiation therapy (IMRT). This verification could be accomplished through a comparison of measured portal images to predicted portal dose images. A general fluence determination tailored to portal dose image prediction would be a great asset in order to model the complex modulation of IMRT. A proposed physics-based parameter fluence model was commissioned by matching predicted EPID images to corresponding measured EPID images of multileaf collimator (MLC) defined fields. The two-source fluence model was composed of a focal Gaussian and an extrafocal Gaussian-like source. Specific aspects of the MLC and secondary collimators were also modeled (e.g., jaw and MLC transmission factors, MLC rounded leaf tips, tongue and groove effect, interleaf leakage, and leaf offsets). Several unique aspects of the model were developed based on the results of detailed Monte Carlo simulations of the linear accelerator including (1) use of a non-Gaussian extrafocal fluence source function, (2) separate energy spectra used for focal and extrafocal fluence, and (3) different off-axis energy spectra softening used for focal and extrafocal fluences. The predicted energy fluence was then convolved with Monte Carlo generated, EPID-specific dose kernels to convert incident fluence to dose delivered to the EPID. Measured EPID data were obtained with an a-Si EPID for various MLC-defined fields (from 1x1 to 20x20 cm{sup 2}) over a range of source-to-detector distances. These measured profiles were used to determine the fluence model parameters in a process analogous to the commissioning of a treatment planning system. The resulting model was tested on 20 clinical IMRT plans, including ten prostate and ten oropharyngeal cases. The model predicted the open-field profiles within 2%, 2 mm, while a mean of 96.6% of pixels over all IMRT fields was in agreement with the 2%, 3 mm criteria. This model demonstrates accuracy commensurate to existing methods for IMRT pretreatment verification with portal dose image prediction of complex clinical examples (<2%, 3 mm).

Chytyk, K.; McCurdy, B. M. C. [Division of Medical Physics, CancerCare Manitoba, 675 McDermot Avenue, Winnipeg, Manitoba R3E 0V9 (Canada) and Department of Physics and Astronomy, University of Manitoba, Winnipeg, Manitoba R3T 2N2 (Canada); Division of Medical Physics, CancerCare Manitoba, 675 McDermot Avenue, Winnipeg, Manitoba R3E 0V9 (Canada); Department of Physics and Astronomy, University of Manitoba, Winnipeg, Manitoba R3T 2N2 (Canada) and Department of Radiology, University of Manitoba, Winnipeg, Manitoba R3A 1R9 (Canada)

2009-04-15T23:59:59.000Z

171

Engineering model for predicting rubble motion during blasting  

SciTech Connect

Recent applications of explosives and blasting agents to rubble rock have led to requirements for more elaborate design and analysis methods. In most blasting uses, it is necessary not only to fracture the rock, but also to move the broken rubble in a predictable manner. Many in-situ extraction techniques require rubblization to take place in a confined region where rock motion is a predominate factor in creating a permeable broken bed. In this paper, an engineering model is presented which describes the large rubble motion during blasting. This model is intended to provide the blast designer with a tool for evaluation and further refinement of blasting patterns and timing sequences. In this model the rock medium is represented by a discrete series of circular regions of fractured material. These regions are set in motion by pressure loads from the explosive. The motion of the regions is calculated using a step-wise, explicit, numerical time integration method. Interaction of adjacent regions is based on inelastic impact of spherical bodies. The derivation of this model is presented along with the background for selecting loading pressure based on explosive behavior. Three typical examples, including both cratering and bench geometries, are discussed which illustrate the use of this model to predict rubble motion. This engineering representation appears to provide a practical model for use in predicting rubble motion and a tool for design evaluation of blasting in confined geometries. 15 figures.

Schamaun, J.T.

1982-12-01T23:59:59.000Z

172

Engineering model for predicting rubble motion during blasting  

SciTech Connect

Recent applications of explosives and blasting agents to rubble rock have led to requirements for more elaborate design and analysis methods. In most blasting uses, it is necessary not only to fracture the rock, but also to move the broken rubble in a predictable manner. Many in situ extraction techniques require rubblization to take place in a confined region where rock motion is a predominate factor in creating a permeable broken bed. In this paper, an engineering model is presented which describes the large rubble motion during blasting. This model is intended to provide the blast designer with a tool for evaluation and further refinement of blasting patterns and timing sequences. In this model the rock medium is represented by a discrete series of circular regions of fractured material. These regions are set in motion by pressure loads from the explosive. The motion of the regions is calculated using a step-wise, explicit, numerical time integration method. Interaction of adjacent regions is based on inelastic impact of spherical bodies. The derivation of this model is presented along with the background for selecting loading pressure based on explosive behavior. Three typical examples, including both cratering and bench geometries, are discussed which illustrate the use of this model to predict rubble motion. This engineering representation appears to provide a practical model for use in predicting rubble motion and a tool for design evaluation of blasting in confined geometries. 15 figures, 1 table.

Schamaun, J.T.

1983-01-01T23:59:59.000Z

173

Designing intelligent disaster prediction models and systems for debris-flow disasters in Taiwan  

Science Conference Proceedings (OSTI)

Effective disaster prediction relies on using correct disaster decision model to predict the disaster occurrence accurately. This study proposes three effective debris-flow prediction models and an inference engine to predict and decide the debris-flow ... Keywords: Back-propagation network, Debris-flow prediction models, Decision support system, Disaster prevention, Mobile multimedia communications

Hsu-Yang Kung; Chi-Hua Chen; Hao-Hsiang Ku

2012-04-01T23:59:59.000Z

174

Intelligent Actuation Control Using Model-Free Adaptive Control Technology  

NLE Websites -- All DOE Office Websites (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

175

The Influence of Hydrologic Modeling on the Predicted Local Weather: Two-Way Coupling of a Mesoscale Weather Prediction Model and a Land Surface Hydrologic Model  

Science Conference Proceedings (OSTI)

A two-way coupling of the operational mesoscale weather prediction model known as Lokal Modell (LM; German Weather Service) with the land surface hydrologic “TOPMODEL”-Based Land Surface–Atmosphere Transfer Scheme (TOPLATS; Princeton University) ...

G. Seuffert; P. Gross; C. Simmer; E. F. Wood

2002-10-01T23:59:59.000Z

176

Predictive model of nucleon-nucleus scattering cross sections  

DOE Green Energy (OSTI)

Nucleon total reaction and neutron total cross sections as well as differential (including spin) observables from 25 to 300 MeV for stable nuclei from 6Li to 238U have been predicted that are in good agreement with measured data. Those predictions have been made using non-local, energy dependent, and complex optical potentials in coordinate space formed by full folding of effective nucleon-nucleon interactions with realistic nuclear ground state densities. By inverse kinematics the same model prescription describes exotic (radioactive) nuclei scattering from hydrogen as a target and the results reveal the extended (neutron) distributions such nuclei can have.

Amos, K. (Ken); Deb, P. (Pradip); Karataglidis, S. (Steven); Madland, D. G.

2001-01-01T23:59:59.000Z

177

Prediction of Cooling of a Nocturnal Environment Using Two Atmospheric Models  

Science Conference Proceedings (OSTI)

A surface energy balance model and a boundary layer model were used to predict nocturnal cooling in an agricultural environment. The results from both models were compared with the observed temperatures to determine which model predicted the ...

Paul H. Heinemann; J. David Martsolf

1988-04-01T23:59:59.000Z

178

TherML: occupancy prediction for thermostat control  

Science Conference Proceedings (OSTI)

Reducing the large energy consumption of temperature regulation systems is a challenge for researchers and practitioners alike. In this paper, we explore and compare two common types of solutions: A manual systems that encourages reduced energy use, ... Keywords: energy, heating, location, machine learning, prediction

Christian Koehler, Brian D. Ziebart, Jennifer Mankoff, Anind K. Dey

2013-09-01T23:59:59.000Z

179

Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory  

SciTech Connect

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, t

Gregor P. Henze; Moncef Krarti

2005-09-30T23:59:59.000Z

180

Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory  

DOE Green Energy (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

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

A real models laboratory and an elevator model controlled through programmable controller (PLC)  

Science Conference Proceedings (OSTI)

The paper is focused on description of laboratory models that are used in the process of education at our faculty. The models are connected to programmable logical controllers (PLC) and through these equipments the models are controlled. As the first ... Keywords: PLC, automatic control, education, elevator, real control, real equipment models

Tomas Sysala; Ondrej Vrzal

2011-05-01T23:59:59.000Z

182

NETL: Predictive Modeling and Evaluation - CMU Regional Modeling Study  

NLE Websites -- All DOE Office Websites (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.

183

Structure-Based Predictive model for Coal Char Combustion.  

SciTech Connect

During the third quarter of this project, progress was made on both major technical tasks. Progress was made in the chemistry department at OSU on the calculation of thermodynamic properties for a number of model organic compounds. Modelling work was carried out at Brown to adapt a thermodynamic model of carbonaceous mesophase formation, originally applied to pitch carbonization, to the prediction of coke texture in coal combustion. This latter work makes use of the FG-DVC model of coal pyrolysis developed by Advanced Fuel Research to specify the pool of aromatic clusters that participate in the order/disorder transition. This modelling approach shows promise for the mechanistic prediction of the rank dependence of char structure and will therefore be pursued further. Crystalline ordering phenomena were also observed in a model char prepared from phenol-formaldehyde carbonized at 900{degrees}C and 1300{degrees}C using high-resolution TEM fringe imaging. Dramatic changes occur in the structure between 900 and 1300{degrees}C, making this char a suitable candidate for upcoming in situ work on the hot stage TEM. Work also proceeded on molecular dynamics simulations at Boston University and on equipment modification and testing for the combustion experiments with widely varying flame types at Ohio State.

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

1997-09-24T23:59:59.000Z

184

Comparison of models for predicting landfill methane recovery. Final report  

DOE Green Energy (OSTI)

Landfill methane models are tools used to project methane generation over time from a mass of landfilled waste. These models are used for sizing landfill gas (LFG) collection systems, evaluations and projections of LFG energy uses, and regulatory purposes. The objective of this project was to select various landfill methane models and to provide a comparison of model outputs to actual long-term gas recovery data from a number of well managed and suitable landfills. Another objective was to use these data to develop better estimates of confidence limits that can be assigned to model projections. This project assessed trial model forms against field data from available landfills where methane extraction was maximized, waste filling history was well-documented, and other pertinent site information was of superior quality. Data were obtained from 18 US landfills. Four landfill methane models were compared: a zero-order, a simple first order, a modified first order, and a multi-phase first order model. Models were adjusted for best fit to field data to yield parameter combinations based on the minimized residual errors between predicted and experienced methane recovery. The models were optimized in this way using two data treatments: absolute value of the differences (arithmetic error minimization) and absolute value of the natural log of the ratios (logarithmic error minimization).

Vogt, W.G. [SCS Engineers, Reston, VA (United States); Augenstein, D. [Institute for Environmental Management, Palo Alto, CA (United States)

1997-03-01T23:59:59.000Z

185

Homogeneous bubble nucleation predicted by a molecular interaction model  

SciTech Connect

The homogenous bubble nucleation of various hydrocarbons was estimated by the modified classical nucleation theory. In this modification, the kinetic formalism of the classical theory is retained while the surface energy needed for the bubble formation is calculated form the interaction energy between molecules. With a nucleation rate value of J{sub n{sub c}} = 10{sup 22} nuclei/cm{sup 3}s, this modified model gives a very good prediction of the superheat limits of liquids. In another test of the model the complete evaporation time of a butane droplet at its superheat limit is compared with experiments and found to be in good agreement.

Hoyoung Kwak; Sangbum Lee (Chung-Ang Univ., Seoul (Korea))

1991-08-01T23:59:59.000Z

186

Optimal Control Design with Limited Model Information  

E-Print Network (OSTI)

We introduce the family of limited model information control design methods, which construct controllers by accessing the plant's model in a constrained way, according to a given design graph. We investigate the achievable closed-loop performance of discrete-time linear time-invariant plants under a separable quadratic cost performance measure with structured static state-feedback controllers. We find the optimal control design strategy (in terms of the competitive ratio and domination metrics) when the control designer has access to the local model information and the global interconnection structure of the plant-to-be-controlled. At last, we study the trade-off between the amount of model information exploited by a control design method and the best closed-loop performance (in terms of the competitive ratio) of controllers it can produce.

Farokhi, F; Johansson, K H

2011-01-01T23:59:59.000Z

187

Southern Hemisphere Medium-Range Forecast Skill and Predictability: A Comparison of Two Operational Models  

Science Conference Proceedings (OSTI)

The skill of two global numerical weather prediction models, the National Centers for Environmental Prediction (NCEP) medium-range forecast model and the European Centre for Medium-Range Weather Forecasts (ECMWF) operational model, has been ...

James A. Renwick; Craig S. Thompson

2001-09-01T23:59:59.000Z

188

A Split Explicit Reformulation of the Regional Numerical Weather Prediction Model of the Japan Meteorological Agency  

Science Conference Proceedings (OSTI)

The split explicit integration scheme for numerical weather prediction models is employed in a version of the regional numerical weather prediction model of the Japan Meteorological Agency. The finite-difference scheme of the model is designed in ...

Dean G. Duffy

1981-05-01T23:59:59.000Z

189

A Prediction of Energy Savings Resulting from Building Infiltration Control  

E-Print Network (OSTI)

Heat transfer through building walls consists of three main components: conduction heat transfer, solar gain and infiltration heat transfer. An interaction among these three heat transfer components alters the effective heat transfer through a wall, 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. The simulations performed in this study show that significant energy savings can be realized with the use of controlled airflow through non-airtight walls in a building. Comparing the energy load of a building which uses airflow control in its walls with the energy load found with a standard calculation (where the interaction effect is not considered), annual energy load savings were found in a warm climate as high as 17%. The results were less promising when compared against the performance of a building experiencing simulated natural airflow (and heat recovery) through its exterior walls: the best annual load savings percentage was 10% in a warm climate. It was found that in a cooler climate, the natural flow configuration performed about as well as any of the artificial airflow configurations, so airflow control is not recommended in cool climates.

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

1996-01-01T23:59:59.000Z

190

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

NLE Websites -- All DOE Office Websites (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

191

NN-Based Near Real Time Load Prediction for Optimal Generation Control  

Science Conference Proceedings (OSTI)

In the environment of ongoing deregulated power industry, traditional automatic generation control (AGC) has become a set of ancillary services traded in separate markets which are different than the energy market. The performance of AGC is mandated ... Keywords: Automatic Generation Control (AGC), Control Performance Standard (CPS), Dynamic Economic Dispatch, Hierarchical Neural Network, Load Dynamics, Very Short Term Load Prediction (VSTLP)

Dingguo Chen

2008-09-01T23:59:59.000Z

192

Pyrometallurgical Process Modeling, Control & Instrumentation  

Science Conference Proceedings (OSTI)

Mar 14, 2012 ... In the current paper, comparisons are drawn between data from spent ... The model integrates submerged coal combustion and chemical ...

193

Smart Engines Via Advanced Model Based Controls  

DOE Green Energy (OSTI)

A ''new'' process for developing control systems - Less engine testing - More robust control system - Shorter development cycle time - ''Smarter'' approach to engine control - On-board models describe engine behavior - Shorter, systematic calibration process - Customer and legislative requirements designed-in.

Allain, Marc

2000-08-20T23:59:59.000Z

194

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 cost of generating EOB waveforms in 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 extremely 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

2013-08-16T23:59:59.000Z

195

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

Science Conference Proceedings (OSTI)

Enhanced software methodology and improved computing hardware have advanced the state of simulation technology to a point where large physics-based codes can be a major contributor in many systems analyses. This shift toward the use of computational methods has brought with it new research challenges in a number of areas including characterization of uncertainty, model validation, and the analysis of computer output. It is these challenges that have motivated the work described in this report. Approaches to and methods for model validation and (model-based) prediction have been developed recently in the engineering, mathematics and statistical literatures. In this report we have provided a fairly detailed account of one approach to model validation and prediction applied to an analysis investigating thermal decomposition of polyurethane foam. A model simulates the evolution of the foam in a high temperature environment as it transforms from a solid to a gas phase. The available modeling and experimental results serve as data for a case study focusing our model validation and prediction developmental efforts on this specific thermal application. We discuss several elements of the ''philosophy'' behind the validation and prediction approach: (1) We view the validation process as an activity applying to the use of a specific computational model for a specific application. We do acknowledge, however, that an important part of the overall development of a computational simulation initiative is the feedback provided to model developers and analysts associated with the application. (2) We utilize information obtained for the calibration of model parameters to estimate the parameters and quantify uncertainty in the estimates. We rely, however, on validation data (or data from similar analyses) to measure the variability that contributes to the uncertainty in predictions for specific systems or units (unit-to-unit variability). (3) We perform statistical analyses and hypothesis tests as a part of the validation step to provide feedback to analysts and modelers. Decisions on how to proceed in making model-based predictions are made based on these analyses together with the application requirements. Updating modifying and understanding the boundaries associated with the model are also assisted through this feedback. (4) We include a ''model supplement term'' when model problems are indicated. This term provides a (bias) correction to the model so that it will better match the experimental results and more accurately account for uncertainty. Presumably, as the models continue to develop and are used for future applications, the causes for these apparent biases will be identified and the need for this supplementary modeling will diminish. (5) We use a response-modeling approach for our predictions that allows for general types of prediction and for assessment of prediction uncertainty. This approach is demonstrated through a case study supporting the assessment of a weapons response when subjected to a hydrocarbon fuel fire. The foam decomposition model provides an important element of the response of a weapon system in this abnormal thermal environment. Rigid foam is used to encapsulate critical components in the weapon system providing the needed mechanical support as well as thermal isolation. Because the foam begins to decompose at temperatures above 250 C, modeling the decomposition is critical to assessing a weapons response. In the validation analysis it is indicated that the model tends to ''exaggerate'' the effect of temperature changes when compared to the experimental results. The data, however, are too few and to restricted in terms of experimental design to make confident statements regarding modeling problems. For illustration, we assume these indications are correct and compensate for this apparent bias by constructing a model supplement term for use in the model-based predictions. Several hypothetical prediction problems are created and addressed. Hypothetical problems are used because no guidance was provided concern

Dowding, Kevin J.; Rutherford, Brian Milne

2003-07-01T23:59:59.000Z

196

Design and Predictive Control of a Net Zero Energy Home  

E-Print Network (OSTI)

This paper analyzes two methods to reduce residential energy consumption for a Net Zero home in Austin, Texas. The first method seeks to develop a control algorithm that actively engages environmental conditioning. The home must preserve user-defined comfort while minimizing energy consumption. An optimization function governed by user input chooses the degree to which various comfort-defining systems are active, optimizing comfort while maintaining minimal energy usage. These systems include a geothermal heat pump and ceiling fans to effect convection, humidity, and dry bulb temperature. The second method reflects an analysis towards augmenting traditional home systems with modern and efficient counterparts. Electrochromic glass is used to attenuate heat transfer from outside the home envelope. A thermal chimney passively removes heat from the home while increasing convection. Replacing conventional incandescent bulbs with compact fluorescent and LED illumination reduces lighting energy waste.

Morelli, F.; Abbarno, N.; Boese, E.; Bullock, J.; Carter, B.; Edwards, R.; Lapite, O.; Mann, D.; Mulvihill, C.; Purcell, E.; Stein, M. IV; Rasmussen, B. P.

2013-01-01T23:59:59.000Z

197

Modeling and Control Interactive Networks  

E-Print Network (OSTI)

and disturbance-free electricity; bank- ing and finance systems depend on the robustness of elec- tric power aircraft and land and sea vessels, depend on communica- tion and energy networks. Links between the power to be a lynchpin of energy 22 IEEE Control Systems Magazine February 2002 0272-1708/02/$17.00©2002IEEE Theauthor

Amin, S. Massoud

198

Development of a fourth generation predictive capability maturity model.  

Science Conference Proceedings (OSTI)

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

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

2013-09-01T23:59:59.000Z

199

Structure-Based Predictive model for Coal Char Combustion.  

Science Conference Proceedings (OSTI)

During the second quarter of this project, progress was made on both major technical tasks. Three parallel efforts were initiated on the modeling of carbon structural evolution. Structural ordering during carbonization was studied by a numerical simulation scheme proposed by Alan Kerstein involving molecular weight growth and rotational mobility. Work was also initiated to adapt a model of carbonaceous mesophase formation, originally developed under parallel NSF funding, to the prediction of coke texture. This latter work makes use of the FG-DVC model of coal pyrolysis developed by Advanced Fuel Research to specify the pool of aromatic clusters that participate in the order/disorder transition. Boston University has initiated molecular dynamics simulations of carbonization processes and Ohio State has begun theoretical treatment of surface reactions. Experimental work has also begun on model compound studies at Brown and on pilot-scale combustion systems with widely varying flame types at OSE. The work on mobility / growth models shows great promise and is discussed in detail in the body of the report.

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

1997-06-25T23:59:59.000Z

200

Human error modeling predictions: increasing occupational safety using human performance modeling tools  

E-Print Network (OSTI)

Abstract: The use of computer-aided job analysis tools has been increasing in the recent past as a result of decreases in computational costs, augmentations in the reality of the computer-aided job analysis tools, and usefulness of the output generated from these tools. One tool set known as integrated Human Performance Modeling (HPM) is a humanout-of-the-loop (HOOTL) computational methodology used to generate predictions of complex human-automation integration and system flow patterns. These tools provide computational representations of humans incorporating physical, cognitive, perceptual, and environmental characteristics. Increasingly complex automation leads to a new class of errors and error vulnerabilities. Hollnagel’s (1993) Contextual Control Model (CoCoM) will be used as the human error theory behind a HOOTL simulation using Air Man-machine Integration Design and Analysis System (Air MIDAS) to evaluate complex humanautomation integration considerations currently underway at NASA Ames Research Center. This paper will highlight the importance of the physical and cognitive link of a specific task and will outline attempts being made to understand the factors underlying human error, a critical consideration of human-complex system performance.

Edited B. Das; Brian F. Gore; Kevin M. Corker

2001-01-01T23:59:59.000Z

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.


201

Hybrid Model for Building Performance Diagnosis and Optimal Control  

E-Print Network (OSTI)

Modern buildings require continuous performance monitoring, automatic diagnostics and optimal supervisory control. For these applications, simplified dynamic building models are needed to predict the cooling and heating requirement viewing the building as a whole system. This paper proposes a new hybrid model. Half of the model is represented by detailed physical parameters and another half is described by identified parameters. 3R2C thermal network model, which consists of three resistances and two capacitances, is used to simulate building envelope whose parameters are determined in frequency domain using the theoretical frequency characteristics of the envelope. Internal mass is represented by a 2R2C thermal network model, which consists of three resistances and two capacitances. The resistances and capacitances of the 2R2C model are assumed to be constant. A GA (genetic algorithm)-based method is developed for model parameter identification by searching the optimal parameters of 3R2C models of envelopes in frequency domain and that of the 2R2C model of the building internal mass in time domain. As the model is based on the physical characteristics, the hybrid model can be used to predict the cooling and heating energy consumption of buildings accurately in wide range of operation conditions.

Wang, S.; Xu, X.

2003-01-01T23:59:59.000Z

202

Source of Seasonality and Scale Dependence of Predictability in a Coupled Ocean–Atmosphere Model  

Science Conference Proceedings (OSTI)

The seasonality of predictability of ENSO (related to the so-called spring predictability barrier) is investigated using the Cane–Zebiak coupled model. Observed winds are used to force the ocean component of the model to generate analyzed initial ...

B. N. Goswami; K. Rajendran; D. Sengupta

1997-05-01T23:59:59.000Z

203

STRUCTURE-BASED PREDICTIVE MODEL FOR COAL CHAR COMBUSTION  

Science Conference Proceedings (OSTI)

Progress was made this period on a number of tasks. A significant advance was made in the incorporation of macrostructural ideas into high temperature combustion models. Work at OSU by R. Essenhigh in collaboration with the University of Stuttgart has led to a theory that the zone I / II transition in char combustion lies within the range of conditions of interest for pulverized char combustion. The group has presented evidence that some combustion data, previously interpreted with zone II models, in fact takes place in the transition from zone II to zone 1. This idea was used at Brown to make modifications to the CBK model (a char kinetics package specially designed for carbon burnout prediction, currently used by a number of research and furnace modeling groups in academia and industry). The resulting new model version, CBK8, shows improved ability to predict extinction behavior in the late stages of combustion, especially for particles with low ash content. The full development and release of CBK8, along with detailed descriptions of the role of the zone 1/2 transition will be reported on in subsequent reports. ABB-CE is currently implementing CBK7 into a special version of the CFD code Fluent for use in the modeling and design of their boilers. They have been appraised of the development, and have expressed interest in incorporating the new feature, realizing full CBK8 capabilities into their combustion codes. The computational chemistry task at OSU continued to study oxidative pathways for PAH, with emphasis this period on heteroatom containing ring compounds. Preliminary XPS studies were also carried out. Combustion experiments were also carried out at OSU this period, leading to the acquisition of samples at various residence times and the measurement of their oxidation reactivity by nonisothermal TGA techniques. Several members of the project team attended the Carbon Conference this period and made contacts with representatives from the new FETC Consortium for Premium Carbon Products from Coal. Possibilities for interactions with this new center will be explored. Also this period, an invited review paper was prepared for the 27th International Symposium on Combustion, to be held in Boulder, Colorado in August. The paper is entitled; "Structure, Properties, and Reactivity of Solid Fuels," and reports on a number of advances made in this collaborative project.

CHRISTOPHER M. HADAD; JOSEPH M. CALO; ROBERT H. ESSENHIGH; ROBERT H. HURT

1998-09-11T23:59:59.000Z

204

Design of a grey-prediction self-organizing fuzzy controller for active suspension systems  

Science Conference Proceedings (OSTI)

Self-organizing fuzzy controllers (SOFCs) have excellent learning capabilities. They have been proposed for the manipulation of active suspension systems. However, it is difficult to select the parameters of an SOFC appropriately, and an SOFC may extensively ... Keywords: Active suspension systems, Grey-prediction algorithm, Self-organizing fuzzy controller

Jeen Lin, Ruey-Jing Lian

2013-10-01T23:59:59.000Z

205

Modelling Monsoons: Understanding and Predicting Current and Future Behaviour  

SciTech Connect

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

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

2008-09-16T23:59:59.000Z

206

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

E-Print Network (OSTI)

Matchstick: A Room-to-Room Thermal Model for Predicting Indoor Temperature from Wireless Sensor present a room-to-room thermal model used to accurately predict temperatures in residential buildings. We that our model can predict future indoor temperature trends with a 90th percentile aggregate error between

Hazas, Mike

207

Development of Control Models and a Robust Multivariable Controller for Surface Shape Control  

SciTech Connect

Surface shape control techniques are applied to many diverse disciplines, such as adaptive optics, noise control, aircraft flutter control and satellites, with an objective to achieve a desirable shape for an elastic body by the application of distributed control forces. Achieving the desirable shape is influenced by many factors, such as, actuator locations, sensor locations, surface precision and controller performance. Building prototypes to complete design optimizations or controller development can be costly or impractical. This shortfall, puts significant value in developing accurate modeling and control simulation approaches. This thesis focuses on the field of adaptive optics, although these developments have the potential for application in many other fields. A static finite element model is developed and validated using a large aperture interferometer system. This model is then integrated into a control model using a linear least squares algorithm and Shack-Hartmann sensor. The model is successfully exercised showing functionality for various wavefront aberrations. Utilizing a verified model shows significant value in simulating static surface shape control problems with quantifiable uncertainties. A new dynamic model for a seven actuator deformable mirror is presented and its accuracy is proven through experiment. Bond graph techniques are used to generate the state space model of the multi-actuator deformable mirror including piezo-electric actuator dynamics. Using this verified model, a robust multi-input multi-output (MIMO) H{sub {infinity}} controller is designed and implemented. This controller proved superior performance as compared to a standard proportional-integral controller (PI) design.

Winters, S

2003-06-18T23:59:59.000Z

208

LIFETIME PREDICTION FOR MODEL 9975 O-RINGS IN KAMS  

SciTech Connect

The Savannah River Site (SRS) is currently storing plutonium materials in the K-Area Materials Storage (KAMS) facility. The materials are packaged per the DOE 3013 Standard and transported and stored in KAMS in Model 9975 shipping packages, which include double containment vessels sealed with dual O-rings made of Parker Seals compound V0835-75 (based on Viton{reg_sign} GLT). The outer O-ring of each containment vessel is credited for leaktight containment per ANSI N14.5. O-ring service life depends on many factors, including the failure criterion, environmental conditions, overall design, fabrication quality and assembly practices. A preliminary life prediction model has been developed for the V0835-75 O-rings in KAMS. The conservative model is based primarily on long-term compression stress relaxation (CSR) experiments and Arrhenius accelerated-aging methodology. For model development purposes, seal lifetime is defined as a 90% loss of measurable sealing force. Thus far, CSR experiments have only reached this target level of degradation at temperatures {ge} 300 F. At lower temperatures, relaxation values are more tolerable. Using time-temperature superposition principles, the conservative model predicts a service life of approximately 20-25 years at a constant seal temperature of 175 F. This represents a maximum payload package at a constant ambient temperature of 104 F, the highest recorded in KAMS to date. This is considered a highly conservative value as such ambient temperatures are only reached on occasion and for short durations. The presence of fiberboard in the package minimizes the impact of such temperature swings, with many hours to several days required for seal temperatures to respond proportionately. At 85 F ambient, a more realistic but still conservative value, bounding seal temperatures are reduced to {approx}158 F, with an estimated seal lifetime of {approx}35-45 years. The actual service life for O-rings in a maximum wattage package likely lies higher than the estimates due to the conservative assumptions used for the model. For lower heat loads at similar ambient temperatures, seal lifetime is further increased. The preliminary model is based on several assumptions that require validation with additional experiments and longer exposures at more realistic conditions. The assumption of constant exposure at peak temperature is believed to be conservative. Cumulative damage at more realistic conditions will likely be less severe but is more difficult to assess based on available data. Arrhenius aging behavior is expected, but non-Arrhenius behavior is possible. Validation of Arrhenius behavior is ideally determined from longer tests at temperatures closer to actual service conditions. CSR experiments will therefore continue at lower temperatures to validate the model. Ultrasensitive oxygen consumption analysis has been shown to be useful in identifying non-Arrhenius behavior within reasonable test periods. Therefore, additional experiments are recommended and planned to validate the model.

Hoffman, E.; Skidmore, E.

2009-11-24T23:59:59.000Z

209

Passive millimeter-wave retrieval of global precipitation utilizing satellites and a numerical weather prediction model  

E-Print Network (OSTI)

This thesis develops and validates the MM5/TBSCAT/F([lambda]) model, composed of a mesoscale numerical weather prediction (NWP) model (MM5), a two-stream radiative transfer model (TBSCAT), and electromagnetic models for ...

Surussavadee, Chinnawat

2007-01-01T23:59:59.000Z

210

Application of RBF-type ARX Modeling and Control to Gas Turbine Combined Cycle SCR Systems  

E-Print Network (OSTI)

Application of RBF-type ARX Modeling and Control to Gas Turbine Combined Cycle SCR Systems Y, nonlinear model-based predictive control, energy saving. 1. INTRODUCTION In Japan, GTCC(Gas Turbine Combined gas-firing GTCC power plant is most effective in terms of thermal efficiency and lower CO2 energy

Ozaki, Tohru

211

Predictability of Precipitation in a Cloud-Resolving Model  

Science Conference Proceedings (OSTI)

An ensemble methodology is developed and tested to objectively isolate and quantify meso-?-scale predictability limitations in numerical weather prediction (NWP). The methodology involves conducting an ensemble of limited-area simulations with ...

André Walser; Daniel Lüthi; Christoph Schär

2004-02-01T23:59:59.000Z

212

The North American Multi-Model Ensemble (NMME): Phase-1 Seasonal to Interannual Prediction, Phase-2 Toward Developing Intra-Seasonal Prediction  

Science Conference Proceedings (OSTI)

The recent US National Academies report “Assessment of Intraseasonal to Interannual Climate Prediction and Predictability” was unequivocal in recommending the need for the development of a North American Multi-Model Ensemble (NMME) operational predictive ...

Ben P. Kirtman; Dughong Min; Johnna M. Infanti; James L. Kinter III; Daniel A. Paolino; Qin Zhang; Huug van den Dool; Suranjana Saha; Malaquias Pena Mendez; Emily Becker; Peitao Peng; Patrick Tripp; Jin Huang; David G. DeWitt; Michael K. Tippett; Anthony G. Barnston; Shuhua Li; Anthony Rosati; Siegfried D. Schubert; Michele Rienecker; Max Suarez; Zhao E. Li; Jelena Marshak; Young-Kwon Lim; Joseph Tribbia; Kathleen Pegion; William J. Merryfield; Bertrand Denis; Eric F. Wood

213

MODELING AND CONTROL OF A O2/CO2 GAS TURBINE CYCLE FOR CO2 CAPTURE  

E-Print Network (OSTI)

MODELING AND CONTROL OF A O2/CO2 GAS TURBINE CYCLE FOR CO2 CAPTURE Lars Imsland Dagfinn Snarheim and control of a semi-closed O2/CO2 gas turbine cycle for CO2 capture. In the first part the process predictive control, Gas turbines, CO2 capture 1. INTRODUCTION Gas turbines are widely used for power

Foss, Bjarne A.

214

The Dark Gravity model predictions for Gravity Probe B  

E-Print Network (OSTI)

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

Frederic Henry-Couannier

2005-09-05T23:59:59.000Z

215

Predictability and reduced order modeling in stochastic reaction networks.  

SciTech Connect

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

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

2008-10-01T23:59:59.000Z

216

Modeling the air traffic controller's cognitive projection process  

E-Print Network (OSTI)

Cognitive projection enables the operator of a supervisory control system, such as air traffic control, to use predicted future behavior of the system to make decisions about if and how to control the system. New procedures ...

Reynolds, Hayley J. Davison (Hayley Jaye Davison)

2006-01-01T23:59:59.000Z

217

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

NLE Websites -- All DOE Office Websites (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.

218

Uncertainties in Predicted Ozone Concentrations Due to Input Uncertainties for the UAM-V Photochemical Grid Model  

Science Conference Proceedings (OSTI)

Based on studies of ozone episodes in the eastern United States using the photochemical grid model, UAM-V, regulatory agencies have made decisions concerning emissions controls. This project analyzes effects of uncertainties in UAM-V input variables (emissions, initial and boundary conditions, meteorological variables, and chemical reactions) on uncertainties in UAM-V ozone predictions for the July 1995 episode.

2000-11-06T23:59:59.000Z

219

Quantifying Predictability Variations in a Low-Order Occan-Atmosphere Model: A Dynamical Systems Approach  

Science Conference Proceedings (OSTI)

A dynamical systems approach is used to quantify the predictability of weather and climatic states of a low order, moist general circulation model. The effects on predictability of incorporating a simple oceanic circulation are evaluated. The ...

Jon M. Nese; John A. Dutton

1993-02-01T23:59:59.000Z

220

Southeast US Rainfall prediction in the North American Multi-Model Ensemble  

Science Conference Proceedings (OSTI)

The present study investigates the predictive skill of the North American Multi-Model Ensemble (NMME) System for Intra-seasonal to Interannual (ISI) Prediction with focus on southeast US precipitation. The southeast US is of particular interest ...

Johnna M. Infanti; Ben P. Kirtman

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

Prediction of Tropical Atlantic Sea Surface Temperatures Using Linear Inverse Modeling  

Science Conference Proceedings (OSTI)

The predictability of tropical Atlantic sea surface temperature on seasonal to interannual timescales by linear inverse modeling is quantified. The authors find that predictability of Caribbean Sea and north tropical Atlantic sea surface ...

Cécile Penland; Ludmila Matrosova

1998-03-01T23:59:59.000Z

222

A Comparison of General Circulation Model Predictions to Sand Drift and Dune Orientations  

Science Conference Proceedings (OSTI)

The growing concern over climate change and desertification stresses the importance of aeolian process prediction. In this paper the use of a general circulation model to predict current aeolian features is examined. A GCM developed at NASA/...

Dan G. Blumberg; Ronald Greeley

1996-12-01T23:59:59.000Z

223

Implementation of the Cloud Prediction Scheme in the Eta Model at NCEP  

Science Conference Proceedings (OSTI)

An explicit cloud prediction scheme has been developed and incorporated into the Eta Model at the National Centers for Environmental Prediction (NCEP) to improve the cloud and precipitation forecasts. In this scheme, the cloud liquid water and ...

Qingyun Zhao; Thomas L. Black; Michael E. Baldwin

1997-09-01T23:59:59.000Z

224

Use of a Mixed-Layer Model to Investigate Problems in Operational Prediction of Return Flow  

Science Conference Proceedings (OSTI)

Inaccuracy in the numerical prediction of the moisture content of return-flow air over the Gulf of Mexico continues to plague operational forecasters. At the Environmental Modeling Center/National Centers for Environmental Prediction in the ...

John M. Lewis

2007-07-01T23:59:59.000Z

225

Predictability of SST in a Stochastic Climate Model and Its Application to the Kuroshio Extension Region  

Science Conference Proceedings (OSTI)

The influence of deterministic forcing on SST predictability is investigated in a zero-dimensional, stochastic, coupled atmosphere–ocean climate model. The SST anomaly predictability time is found to be very sensitive to the properties of the ...

Robert B. Scott; Bo Qiu

2003-01-01T23:59:59.000Z

226

The Impact of Tropical Forcing on Extratropical Predictability in a Simple Global Model  

Science Conference Proceedings (OSTI)

The impact of tropical forcing on the predictability of the extratropical atmosphere is studied. Using a two-layer spectral model, numerical experiments and diagnostic analyses have been carried out to examine the enhancement of predictability ...

Jianchun Qin; Walter A. Robinson

1995-11-01T23:59:59.000Z

227

The Nature of Predictability Enhancement in a Low-Order Ocean-Atmosphere Model  

Science Conference Proceedings (OSTI)

A low-order moist general circulation model of the coupled ocean-atmosphere system is reexamined to determine the source of short-term predictability enhancement that occurs when an oceanic circulation is activated. The predictability enhancement ...

Jon M. Nese; Arthur J. Miller; John A. Dutton

1996-09-01T23:59:59.000Z

228

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

229

Air Leakage of U.S. Homes: Model Prediction  

Science Conference Proceedings (OSTI)

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

Sherman, Max H.; McWilliams, Jennifer A.

2007-01-01T23:59:59.000Z

230

Model Uncertainty in a Mesoscale Ensemble Prediction System: Stochastic versus Multiphysics Representations  

Science Conference Proceedings (OSTI)

A multiphysics and a stochastic kinetic-energy backscatter scheme are employed to represent model uncertainty in a mesoscale ensemble prediction system using the Weather Research and Forecasting model. Both model-error schemes lead to significant ...

J. Berner; S.-Y. Ha; J. P. Hacker; A. Fournier; C. Snyder

2011-06-01T23:59:59.000Z

231

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.

232

An Efficient Stochastic Bayesian Approach to Optimal Parameter and Uncertainty Estimation for Climate Model Predictions  

Science Conference Proceedings (OSTI)

One source of uncertainty for climate model predictions arises from the fact that climate models have been optimized to reproduce observational means. To quantify the uncertainty resulting from a realistic range of model configurations, it is ...

Charles Jackson; Mrinal K. Sen; Paul L. Stoffa

2004-07-01T23:59:59.000Z

233

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.

234

Fully automated smart wireless frost prediction and protection system using a fuzzy logic controller  

Science Conference Proceedings (OSTI)

A smart fuzzy logic controller system is presented to protect the crops from frost damage that occurs every year. The system is a fully automated system to predict the frost and to protect the crops using wireless sensor network technology. The sensors ...

Shadi A. Alboon; Amin T. Alqudah; Hussein R. Al-Zoubi; Abedalgany A. Athamneh

2012-09-01T23:59:59.000Z

235

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

E-Print Network (OSTI)

Predictive control and thermal energy storage for optimizing a multi- energy district boiler Julien of the OptiEnR research project, the present paper deals with optimizing the multi-energy district boiler to the complexity of the district boiler as a whole and the strong interactions between the sub-systems, previous

Paris-Sud XI, Université de

236

Rapid load following of an SOFC power system via stable fuzzy predictive tracking controller  

Science Conference Proceedings (OSTI)

The solid oxide fuel cell (SOFC) is widely accepted for clean and distributed power generation use, but critical operation problems often occur when the stand-alone fuel cell is directly connected to the electricity grid or the dc electric user. In order ... Keywords: fuel cell, fuzzy systems, identification, input-tostate stability, load following, output tracking, predictive control

Tiejun Zhang; Gang Feng

2009-04-01T23:59:59.000Z

237

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

Science Conference Proceedings (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

238

STRUCTURE-BASED PREDICTIVE MODEL FOR COAL CHAR COMBUSTION  

Science Conference Proceedings (OSTI)

During the past quarter of this project, significant progress continued was made on both major technical tasks. Progress was made at OSU on advancing the application of computational chemistry to oxidative attack on model polyaromatic hydrocarbons (PAHs) and graphitic structures. This work is directed at the application of quantitative ab initio molecular orbital theory to address the decomposition products and mechanisms of coal char reactivity. Previously, it was shown that the ?hybrid? B3LYP method can be used to provide quantitative information concerning the stability of the corresponding radicals that arise by hydrogen atom abstraction from monocyclic aromatic rings. In the most recent quarter, these approaches have been extended to larger carbocyclic ring systems, such as coronene, in order to compare the properties of a large carbonaceous PAH to that of the smaller, monocyclic aromatic systems. It was concluded that, at least for bond dissociation energy considerations, the properties of the large PAHs can be modeled reasonably well by smaller systems. In addition to the preceding work, investigations were initiated on the interaction of selected radicals in the ?radical pool? with the different types of aromatic structures. In particular, the different pathways for addition vs. abstraction to benzene and furan by H and OH radicals were examined. Thus far, the addition channel appears to be significantly favored over abstraction on both kinetic and thermochemical grounds. Experimental work at Brown University in support of the development of predictive structural models of coal char combustion was focused on elucidating the role of coal mineral matter impurities on reactivity. An ?inverse? approach was used where a carbon material was doped with coal mineral matter. The carbon material was derived from a high carbon content fly ash (Fly Ash 23 from the Salem Basin Power Plant. The ash was obtained from Pittsburgh #8 coal (PSOC 1451). Doped samples were then burned in a high temperature flame reactor fitted with rapid quench extractive sampling. It was found that the specific reaction rate decreased with increasing ash content by about an order of magnitude over the ash content range investigated. In this case, it was concluded that at least one of the primary reasons for the resultant observation was that an increasing amount of carbon becomes inaccessible to oxygen by being covered with a fused, ?protective,? ash layer. Progress continued on equipment modification and testing for the combustion experiments with widely varying flame types at OSU.

CHRISTOPHER M. HADAD; JOSEPH M. CALO; ROBERT H. ESSENHIGH; ROBERT H. HURT

1998-06-04T23:59:59.000Z

239

Constrained model predictive control, state estimation and coordination  

E-Print Network (OSTI)

24, 829–834. Li, P. , Wendt, M. & Wozny, G. (2002), ‘AUSA, pp. 2968–2973. Li, P. , Wendt, M. & Wozny, G. (2000), ‘Nickolaou 1998), (Li, Wendt & Wozny 2000) and (Li, Wendt &

Yan, Jun

2006-01-01T23:59:59.000Z

240

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

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

Model predictive control equalization for high-speed IO links  

E-Print Network (OSTI)

The demand for bandwidth in chip-to-chip communication has been increasing as the industry demands higher quantity and quality of information. Serial links provide a suitable architecture for this kind of transmission, ...

Suleiman, Amr S. (Amr AbdulZahir)

2013-01-01T23:59:59.000Z

242

Model Predictive Control for the Operation of Building Cooling Systems  

E-Print Network (OSTI)

of the chillers and cooling towers, the thermal storage tankthe chillers and cooling towers, the thermal storage tank,of thermal energy storage in building cooling systems.

Ma, Yudong

2010-01-01T23:59:59.000Z

243

Model predictive control for energy efficient cooling and dehumidification  

E-Print Network (OSTI)

Energy has become a primary concern in countries worldwide, and is a focus of debates on national security, climate change, global economy, and the developing world. With more people in developing countries adopting the ...

Zakula, Tea

2013-01-01T23:59:59.000Z

244

Model Predictive Control for the Operation of Building Cooling Systems  

E-Print Network (OSTI)

COP) and $1205 daily electricity bill saving. The actuala reduction of electricity bill compared to currentlyformance of MPC: the electricity bills and the coef?cient of

Ma, Yudong

2010-01-01T23:59:59.000Z

245

Model Predictive Control for the Operation of Building Cooling Systems  

E-Print Network (OSTI)

of the chillers and cooling towers, the thermal storage tankin parallel), an array of cooling towers, a 7000 m 3 chilledthe chillers and cooling towers, the thermal storage tank,

Ma, Yudong

2010-01-01T23:59:59.000Z

246

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… (more)

Elliott, Matthew Stuart

2009-01-01T23:59:59.000Z

247

Economic model predictive control for building energy systems.  

E-Print Network (OSTI)

??In the United States, buildings account for nearly three quarters of electricity consumption and about 40% of greenhouse gas emissions. The heating, ventilation and air-conditioning… (more)

Ma, Jingran

2012-01-01T23:59:59.000Z

248

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

E-Print Network (OSTI)

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

Pedram, Massoud

249

Defining and applying prediction performance metrics on a recurrent NARX time series model  

Science Conference Proceedings (OSTI)

Nonlinear autoregressive moving average with exogenous inputs (NARMAX) models have been successfully demonstrated for modeling the input-output behavior of many complex systems. This paper deals with the proposition of a scheme to provide time series ... Keywords: NARX models, Prediction performance metrics, Recurrent radial basis function network, Time series prediction

Ryad Zemouri; Rafael Gouriveau; Noureddine Zerhouni

2010-08-01T23:59:59.000Z

250

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

Science Conference Proceedings (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

251

Predictive geochemical modeling of interactions between uranium-mill-tailings solutions and sediments in a flow-through system: model formulations and preliminary results  

Science Conference Proceedings (OSTI)

An equilibrium thermodynamic conceptual model consisting of minerals and solid phases was developed to represent a soil column. A computer program was used as a tool to solve the system of mathematical equations imposed by the conceptual chemical model. The combined conceptual model and computer program were used to predict aqueous phase compositions of effluent solutions from permeability cells packed with geologic materials and percolated with uranium mill tailings solutions. Initial calculations of ion speciation and mineral solubility and our understanding of the chemical processes occurring in the modeled system were used to select solid phases for inclusion in the conceptual model. The modeling predictions were compared to the analytically determined column effluent concentrations. Hypotheses were formed, based on modeling predictions and laboratory evaluations, as to the probable mechanisms controlling the migration of selected contaminants. An assemblage of minerals and other solid phases could be used to predict the concentrations of several of the macro constituents (e.g., Ca, SO/sub 4/, Al, Fe, and Mn) but could not be used to predict trace element concentrations. These modeling conclusions are applicable to situations where uranium mill tailings solutions of low pH and high total dissolved solids encounter either clay liners or natural geologic materials that contain inherent acid neutralizing capacities. 116 references, 22 figures, 6 tables.

Peterson, S.R.; Felmy, A.R.; Serne, R.J.; Gee, G.W.

1983-08-01T23:59:59.000Z

252

Quantifying the Predictive Skill in Long-Range Forecasting. Part I: Coarse-Grained Predictions in a Simple Ocean Model  

Science Conference Proceedings (OSTI)

An information-theoretic framework is developed to assess the long-range coarse-grained predictive skill in a perfect-model environment. Central to the scheme is the notion that long-range forecasting involves regimes; specifically, that the ...

Dimitrios Giannakis; Andrew J. Majda

2012-03-01T23:59:59.000Z

253

A Climatic Model for the Prediction of Percentile Statistics for Ambient Temperature  

Science Conference Proceedings (OSTI)

The probability density function (pdf) for ambient temperature is predicted from daily maximum and daily minimum temperature and sunshine, data by means of a climatic model.

Aleck J. Hunter

1981-04-01T23:59:59.000Z

254

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

E-Print Network (OSTI)

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

Lee, Kwang Ho; Schiavon, Stefano

2013-01-01T23:59:59.000Z

255

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

256

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

DOE Green Energy (OSTI)

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

Bosco, N.

2012-02-01T23:59:59.000Z

257

Assessing phylogenetic motif models for predicting transcription factor binding sites  

Science Conference Proceedings (OSTI)

Motivation: A variety of algorithms have been developed to predict transcription factor binding sites (TFBSs) within the genome by exploiting the evolutionary information implicit in multiple alignments of the genomes of related species. One such ...

John Hawkins; Charles Grant; William Stafford Noble; Timothy L. Bailey

2009-06-01T23:59:59.000Z

258

Application of a computer model for predicting remote noise levels  

Science Conference Proceedings (OSTI)

The prediction of noise levels at selected remote locations is an integral part of estimating the environmental impact of new stationary sources or of noise reduction for existing facilities. A three?dimensional computermodel

S. H. Judd; S. L. Dryden

1975-01-01T23:59:59.000Z

259

Implicit Versus Explicit Convective Heating in Numerical Weather Prediction Models  

Science Conference Proceedings (OSTI)

The ability of several explicit formulations of convective heating to predict the precipitation associated with a mesoscale convective complex was compared to that of a cumulus parameterization on a ½ deg latitude-longitude mesh. In the explicit ...

John Molinari; Michael Dudek

1986-10-01T23:59:59.000Z

260

Predictions of Saturation Ratio for Cloud Microphysical Models  

Science Conference Proceedings (OSTI)

The saturation development equation is solved analytically to give a solution that is more general than the existing analytical solution. This analytical solution provides accurate predictions of the saturation ratio and allows the use of ...

Jen-Ping Chen

1994-05-01T23:59:59.000Z

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

Predicted costs of environmental controls for a commercial oil shale industry. Volume 1. An engineering analysis  

SciTech Connect

The pollution control costs for a commercial oil shale industry were determined in a joint effort by Denver Research Institute, Water Purification Associates of Cambridge, and Stone and Webster Engineering of Boston and Denver. Four commercial oil shale processes were considered. The results in terms of cost per barrel of syncrude oil are predicted to be as follows: Paraho Process, $0.67 to $1.01; TOSCO II Process, $1.43 to $1.91; MIS Process, $2.02 to $3.03; and MIS/Lurgi-Ruhrgas Process, $1.68 to $2.43. Alternative pollution control equipment and integrated pollution control strategies were considered and optimal systems selected for each full-scale plant. A detailed inventory of equipment (along with the rationale for selection), a detailed description of control strategies, itemized costs and predicted emission levels are presented for each process. Capital and operating cost data are converted to a cost per barrel basis using detailed economic evaluation procedures. Ranges of cost are determined using a subjective self-assessment of uncertainty approach. An accepted methodology for probability encoding was used, and cost ranges are presented as subjective probability distributions. Volume I presents the detailed engineering results. Volume II presents the detailed analysis of uncertainty in the predicted costs.

Nevens, T.D.; Culbertson, W.J. Jr.; Wallace, J.R.; Taylor, G.C.; Jovanovich, A.P.; Prien, C.H.; Hicks, R.E.; Probstein, R.F.; Domahidy, G.

1979-07-01T23:59:59.000Z

262

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

E-Print Network (OSTI)

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

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

2013-01-01T23:59:59.000Z

263

An engineering model for prediction of in situ oil shale retort blasting  

SciTech Connect

The in situ extraction of oil from most oil shale beds is highly dependent upon explosive fracturing and rubbling of rock in a controlled and predictable manner. In blasting, it is necessary not only to fracture the rock, but also to move the broken rubble in a predictable manner. Most in situ extraction techniques require rubblization to take place in a confined region where rock motion is a predominate factor in creating a permeable broken bed. In this paper, an engineering model is presented which describes the large rubble motion during blasting. In this model the rock medium is represented by a discrete series of circular regions of fractured material. These regions are set in motion by pressure loads from the explosive. The motion of the regions is calculated using a step-wise, explicit, numerical time integration method. Interaction of adjacent regions is based on inelastic impact of spherical bodies. The derivation of this model is presented along with the background for selecting loading pressure based on explosive behavior.

Quong, R.

1983-04-01T23:59:59.000Z

264

Snow Model Verification Using Ensemble Prediction and Operational Benchmarks  

Science Conference Proceedings (OSTI)

Hydrologic model evaluations have traditionally focused on measuring how closely the model can simulate various characteristics of historical observations. Although advancing hydrologic forecasting is an often-stated goal of numerous modeling ...

Kristie J. Franz; Terri S. Hogue; Soroosh Sorooshian

2008-12-01T23:59:59.000Z

265

Modeling and prediction of nonlinear environmental system using Bayesian methods  

Science Conference Proceedings (OSTI)

An environmental dynamic system is usually modeled as a nonlinear system described by a set of nonlinear ODEs. A central challenge in computational modeling of environmental systems is the determination of the model parameters. In these cases, estimating ... Keywords: Extended Kalman filter, Leaf area index and soil moisture model, Nonlinear environmental system, Particle filter, State and parameter estimation, Variational filter

Majdi Mansouri; Benjamin Dumont; Marie-France Destain

2013-03-01T23:59:59.000Z

266

Operational Convective-Scale Numerical Weather Prediction with the COSMO Model: Description and Sensitivities  

Science Conference Proceedings (OSTI)

Since April 2007, the numerical weather prediction model, COSMO (Consortium for Small Scale Modelling), has been used operationally in a convection-permitting configuration, named COSMO-DE, at the Deutscher Wetterdienst (DWD; German weather ...

Michael Baldauf; Axel Seifert; Jochen Förstner; Detlev Majewski; Matthias Raschendorfer; Thorsten Reinhardt

2011-12-01T23:59:59.000Z

267

Sea Surface Height Predictions from the Global Navy Coastal Ocean Model during 1998–2001  

Science Conference Proceedings (OSTI)

A ?° global version of the Navy Coastal Ocean Model (NCOM), operational at the Naval Oceanographic Office (NAVOCEANO), is used for prediction of sea surface height (SSH) on daily and monthly time scales during 1998–2001. Model simulations that ...

Charlie N. Barron; A. Birol Kara; Harley E. Hurlburt; C. Rowley; Lucy F. Smedstad

2004-12-01T23:59:59.000Z

268

A Vertically Nested Regional Numerical Weather Prediction Model with Second-Order Closure Physics  

Science Conference Proceedings (OSTI)

The model we describe involves a unique strategy in which a high vertical resolution grid is nested within the coarse vertical resolution grid of a regional numerical weather prediction (NWP) model. Physics computations performed on the high ...

Stephen D. Burk; William T. Thompson

1989-11-01T23:59:59.000Z

269

Empirical Probability Models to Predict Precipitation Levels over Puerto Rico Stations  

Science Conference Proceedings (OSTI)

A new algorithm is proposed to predict the level of rainfall (above normal, normal, and below normal) in Puerto Rico that relies on probability and empirical models. The algorithm includes a theoretical probability model in which parameters are ...

Nazario D. Ramirez-Beltran; William K. M. Lau; Amos Winter; Joan M. Castro; Nazario Ramirez Escalante

2007-03-01T23:59:59.000Z

270

Two Tales of Initializing Decadal Climate Prediction Experiments with the ECHAM5/MPI-OM Model  

Science Conference Proceedings (OSTI)

This paper investigates the impact of different ocean initialization strategies on the forecast skill of decadal prediction experiments performed with the ECHAM5/Max Planck Institute Ocean Model (MPI-OM) coupled model. The ocean initializations ...

Daniela Matei; Holger Pohlmann; Johann Jungclaus; Wolfgang Müller; Helmuth Haak; Jochem Marotzke

2012-12-01T23:59:59.000Z

271

Numerical Prediction of Convectively Driven Mesoscale Pressure Systems. Part II. Mesoscale Model  

Science Conference Proceedings (OSTI)

A 20-level, three-dimensional, primitive equation model with 20 km horizontal resolution is used to predict the development of convectively driven mesoscale pressure systems. Systems produced by the model have life histories and structural ...

J. M. Fritsch; C. F. Chappell

1980-08-01T23:59:59.000Z

272

Localized Precipitation Forecasts from a Numerical Weather Prediction Model Using Artificial Neural Networks  

Science Conference Proceedings (OSTI)

Although the resolution of numerical weather prediction models continues to improve, many of the processes that influence precipitation are still not captured adequately by the scales of present operational models, and consequently precipitation ...

Robert J. Kuligowski; Ana P. Barros

1998-12-01T23:59:59.000Z

273

A Simple Empirical Model for Predicting the Decay of Tropical Cyclone Winds after Landfall  

Science Conference Proceedings (OSTI)

An empirical model for predicting the maximum wind of landfalling tropical cyclones is developed. The model is based upon the observation that the wind speed decay rate after landfall is proportional to the wind speed. Observations also indicate ...

John Kaplan; Mark DeMaria

1995-11-01T23:59:59.000Z

274

QNH: Design and Test of a Quasi-Nonhydrostatic Model for Mesoscale Weather Prediction  

Science Conference Proceedings (OSTI)

A new mesoscale weather prediction model, called QNH, is described. It is characterized by a parameter that multiplies the hydrostatic terms in the vertical equation of motion. Models of this type are referred to generically as “quasi-...

A. E. MacDonald; J. L. Lee; S. Sun

2000-04-01T23:59:59.000Z

275

The National Meteorological Center's Quasi-Lagrangian Model for Hurricane Prediction  

Science Conference Proceedings (OSTI)

A description is presented of the National Meteorological Center's Quasi-Lagrangian Model (QLM), which is used for operational hurricane prediction. The model uses the primitive equations with high horizontal and vertical resolution, and includes ...

Mukut B. Mathur

1991-06-01T23:59:59.000Z

276

A Minimal Model for the Short-Term Prediction of Rainfall in the Tropics  

Science Conference Proceedings (OSTI)

A “minimal” model is proposed here for the short-term prediction (up to 12 h ahead) of precipitation occurrence in the tropics. The model is purely statistical, consisting of an optimally weighted linear combination of a Markov chain and ...

K. Fraedrich; L. M. Leslie

1988-09-01T23:59:59.000Z

277

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

Science Conference Proceedings (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

278

Models for the Prediction of Tropical Cyclone Motion over the North Atlantic: An Operational Evaluation  

Science Conference Proceedings (OSTI)

This study provides an operational evaluation of the seven prediction models-five statistical and two dynamical-used at the National Hurricane Center. Following a brief description of the rationale for each model, various performance ...

Charles J. Neumann; Joseph M. Pelissier

1981-03-01T23:59:59.000Z

279

Comparison of Structure Parameter Scaling Expressions with Turbulence Closure Model Predictions  

Science Conference Proceedings (OSTI)

The convective boundary-layer scaling expressions presented by Wyngaard and LeMone (1980) are compared with predictions from a turbulence closure model. We first examine a model experiment involving a clear-air, convectively driven boundary layer ...

Stephen D. Burk

1981-04-01T23:59:59.000Z

280

Initialization of Soil-Water Content in Regional-Scale Atmospheric Prediction Models  

Science Conference Proceedings (OSTI)

The purpose of this study is to demonstrate the feasibility of determining the soil-water content fields required as initial conditions for land surface components within atmospheric prediction models. This is done using a model of the hydrologic ...

Christopher B. Smith; Mercedes N. Lakhtakia; William J. Capehart; Toby N. Carlson

1994-04-01T23:59:59.000Z

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.


281

Potential Predictability and AMIP Implications of Midlatitude Climate Variability in Two General Circulation Models  

Science Conference Proceedings (OSTI)

Ensembles of extended Atmospheric Model Intercomparison Project (AMIP) runs from the general circulation models of the National Centers for Environmental Prediction (formerly the National Meteorological Center) and the Max-Planck Institute (...

T. P. Barnett; K. Arpe; L. Bengtsson; M. Ji; A. Kumar

1997-09-01T23:59:59.000Z

282

Ability of a Regional-Scale Model to Predict the Genesis of Intense Mesoscale Convective Systems  

Science Conference Proceedings (OSTI)

This paper presents the mesoscale part of a two-part evaluation of thirty forecasts produced by a mesoscalenumerical weather prediction model (MASS 2.0). The general approach taken to evaluate the mesoscale predictivecapabilities of the model is ...

Steven E. Koch

1985-10-01T23:59:59.000Z

283

Identification, Modelling and Prediction of Non-periodic Bursts in Workloads  

Science Conference Proceedings (OSTI)

Non-periodic bursts are prevalent in workloads of large scale applications. Existing workload models do not predict such non-periodic bursts very well because they mainly focus on repeatable base functions. We begin by showing the necessity to include ... Keywords: data management, distributed system, workload modeling, burst prediction

Mario Lassnig; Thomas Fahringer; Vincent Garonne; Angelos Molfetas; Miguel Branco

2010-05-01T23:59:59.000Z

284

Estimation and regularization techniques for regression models with multidimensional prediction functions  

Science Conference Proceedings (OSTI)

Boosting is one of the most important methods for fitting regression models and building prediction rules. A notable feature of boosting is that the technique can be modified such that it includes a built-in mechanism for shrinking coefficient estimates ... Keywords: Count data model, Gradient boosting, Multidimensional prediction function, Scale parameter estimation, Variable selection

Matthias Schmid; Sergej Potapov; Annette Pfahlberg; Torsten Hothorn

2010-04-01T23:59:59.000Z

285

Financial health prediction models using artificial neural networks, genetic algorithm and multivariate discriminant analysis: Iranian evidence  

Science Conference Proceedings (OSTI)

The purpose of this study is to design a model to predict financial health of companies. Financial ratios for 180 manufacturing companies quoted in Tehran Stock Exchange for one year (year ended March 21, 2008) have been used. Three models; based on ... Keywords: Artificial neural networks, Discriminant analysis, Financial health prediction, Financial ratios, Genetic algorithm, Iranian company

F. Mokhatab Rafiei; S. M. Manzari; S. Bostanian

2011-08-01T23:59:59.000Z

286

Local vs. global models for effort estimation and defect prediction  

Science Conference Proceedings (OSTI)

Data miners can infer rules showing how to improve either (a) the effort estimates of a project or (b) the defect predictions of a software module. Such studies often exhibit conclusion instability regarding what is the most effective action for different ...

Tim Menzies; Andrew Butcher; Andrian Marcus; Thomas Zimmermann; David Cok

2011-11-01T23:59:59.000Z

287

Introduction to the model-free control of microgrids  

E-Print Network (OSTI)

This letter presents the application of the model-free control approach to the microgrid control. We show in simulation that the method allows to control, with a simple controller, voltage, current and power of inverter-based microgrids.

Michel, Loïc

2011-01-01T23:59:59.000Z

288

Virtual Model Control of a Biped Walking Robot  

E-Print Network (OSTI)

The transformation from high level task specification to low level motion control is a fundamental issue in sensorimotor control in animals and robots. This thesis develops a control scheme called virtual model control ...

Pratt, Jerry E.

1995-12-01T23:59:59.000Z

289

PII-39: A Microstructure-strength Calculation Model for Predicting ...  

Science Conference Proceedings (OSTI)

Based on the temperature field simulation by FT-STAR, an MCA model was used ... Model Validation for Microstructural Sensitivities Using High Energy Diffraction Microscopy ... PI-8: Building 3D Microstructure Database using an Advanced ...

290

ENSO Prediction with Markov Models: The Impact of Sea Level  

Science Conference Proceedings (OSTI)

A series of seasonally varying linear Markov models are constructed in a reduced multivariate empirical orthogonal function (MEOF) space of observed sea surface temperature, surface wind stress, and sea level analysis. The Markov models are ...

Yan Xue; Ants Leetmaa; Ming Ji

2000-02-01T23:59:59.000Z

291

Gridpoint Predictions of High Temperature from a Mesoscale Model  

Science Conference Proceedings (OSTI)

Mesoscale model gridpoint temperature data from simulations in the southwestern United States during the summer of 1990 are compared with both observations and statistical guidance from large-scale models over a 32-day period. Although the raw ...

David J. Stensrud; Jon A. Skindlov

1996-03-01T23:59:59.000Z

292

Human walking model predicts joint mechanics, electromyography and mechanical economy  

E-Print Network (OSTI)

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

Endo, Ken

293

Multi-Scale Modeling to Predict Properties of Thermoplastic ...  

Science Conference Proceedings (OSTI)

A Continuum General Noise Brownian Thermostat with Applications to Film Morphology · A Multiscale, Nonlinear, Modeling Framework Enabling the Design and ...

294

Efficient Direct Multiple Shooting for Nonlinear Model Predictive ...  

E-Print Network (OSTI)

Jul 4, 2011 ... controlled by u(t) ? R3 such that this energy–conserving system returns to ... ( blue), 320 (green), 640 (black), and ultimate point mass positions ...

295

BIRD FATALITY ASSOCIATIONS AND PREDICTIVE MODELS FOR THE APWRA  

E-Print Network (OSTI)

at those models in our sample in the APWRA Micon 65 Bonus Danwin Flowind Windmatic Enertech KCS-56 KVS-33 Enertech KCS-56 KVS-33 Howden Nordtank W.E.G. 25002000150010005000 N Effort Turbine model Sum proportion Predictor Variable df GOEA RTHA AMKE BUOW BAOW GHOW Turbine model 10 17.98t 20.70* 78.59** 44.59** 7.23 5

296

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

297

The Ellie Caulkins Opera House: A study in simplified predictive modeling  

Science Conference Proceedings (OSTI)

Recent advances in predictive modeling and experience in understanding and interpreting the significance of the data provided by such models have given rise to a spate of wonderful new performance spaces. However the models ? whether computermodels or physical scale models ? demand an investment in time

Robert Mahoney

2008-01-01T23:59:59.000Z

298

Predicting the potential habitat of oaks with data mining models and the R system  

Science Conference Proceedings (OSTI)

Oak forests are essential for the ecosystems of many countries, particularly when they are used in vegetal restoration. Therefore, models for predicting the potential habitat of oaks can be a valuable tool for work in the environment. In accordance with ... Keywords: Classification trees, Data mining models, Ensemble models, Habitat modelling, Neural networks, Oaks, R system, Supervised classification, Support vector machines

Rafael Pino-Mejías; María Dolores Cubiles-de-la-Vega; María Anaya-Romero; Antonio Pascual-Acosta; Antonio Jordán-López; Nicolás Bellinfante-Crocci

2010-07-01T23:59:59.000Z

299

CFD Model for Prediction of Liquid Steel Temperature in Ladle ...  

Science Conference Proceedings (OSTI)

2D and 3D Numerical Modeling of Solidification Benchmark of Sn-3% Pb Wt. Alloy under ... 3D CAFE Simulation of a Macrosegregation Benchmark Experiment.

300

The Neural Network Model using for Predictions Mechanical ...  

Science Conference Proceedings (OSTI)

Study of Composite Materials Application for Horizontal Axis Wind Turbine Blades ... Using the Computational Modelling to Improve Durability of Diesel Engine ...

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.


301

Application of a noninhibitory growth model to predict the transient response in a chemostat  

SciTech Connect

A method of adapting a kinetic model based on steady-state chemostat data to predict the transient performance of a chemostat culture is presented. The proposal provides for a time delay which can be considered equivalent to a period of reduced activity of the organism subsequent to the introduction of a step change in operating conditions. The adapted kinetic model gives substantially better performance in predicting the transient response of an experimental system than the unmodified kinetic model.

Chiam, H.F.; Harris, I.J.

1983-06-01T23:59:59.000Z

302

Development of Model to Predict Stress Corrosion Cracking and Corrosion Fatigue of Low Pressure Turbine Components  

Science Conference Proceedings (OSTI)

Most outage hours for steam turbines are the result of corrosion of low pressure (LP) blades and disks in the phase transition zone (PTZ). Developing an effective localized corrosion damage prediction model is essential to successfully avoid unscheduled outages of steam turbines. This report provides the latest analytical model for predicting failure and includes the electrochemical data for a blade material (17-4PH) that will be used in the model.

2007-02-26T23:59:59.000Z

303

Scale Interaction and Predictability in a Mesoscale Model  

Science Conference Proceedings (OSTI)

Scale interaction is examined in the limited-area PSU/NCAR mesoscale model, with emphasis on the forcing of small scales by the small-scale fields themselves. Output data from the model are filtered by expanding fields at each level in two-...

Andrew H. Van Tuyl; Ronald M. Errico

1989-03-01T23:59:59.000Z

304

Comparison of Predictive Models for Photovoltaic Module Performance: Preprint  

DOE Green Energy (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

305

Fuzzy adaptive control for the actuators position control and modeling of an expert system  

Science Conference Proceedings (OSTI)

In this paper, a heating, ventilating and air-conditioning (HVAC) system was designed and two different damper gap rates (actuators position) of the HVAC system were controlled by a conventional PID (proportional-integral-derivative) controller. One ... Keywords: Actuator position control, Air flow control, An expert system, Fuzzy adaptive control (FAC), Humidity control, Modeling, PID control, Software architecture

Servet Soyguder; Hasan Alli

2010-03-01T23:59:59.000Z

306

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

SciTech Connect

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

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

2013-12-18T23:59:59.000Z

307

A Global Numerical Weather Prediction Model with Variable Resolution  

Science Conference Proceedings (OSTI)

A conformal transformation suggested by F. Schmidt is followed to implement a global spectral model with variable resolution. A conformal mapping is defined from a physical sphere (like the earth) to a transformed (computational) sphere. The ...

Vivek Hardiker

1997-01-01T23:59:59.000Z

308

A transient model for data center thermal prediction  

Science Conference Proceedings (OSTI)

Fast thermal maps are a crucial component for many green data center design techniques. However, most state of the art work on thermal mapping ignores critical temporal aspects of thermal behavior and relies on modeling assumptions, such as the steady ...

Michael Jonas; Rose Robin Gilbert; Joshua Ferguson; Georgios Varsamopoulos; Sandeep K. S. Gupta

2012-06-01T23:59:59.000Z

309

A Study of Barotropic Model Flows: Intermittency, Waves and Predictability  

Science Conference Proceedings (OSTI)

The régime flows corresponding to the barotropic nondivergent equation with forcing, drag and subgrid-scale dissipation are studied using spectral model on the plane and on the sphere. The flow régimes obtained exhibit clear evidence of the ...

C. Basdevant; B. Legras; R. Sadourny; M. Béland

1981-11-01T23:59:59.000Z

310

Motif discovery through predictive modeling of gene regulation  

Science Conference Proceedings (OSTI)

We present MEDUSA, an integrative method for learning motif models of transcription factor binding sites PSSMs by incorporating promoter sequence and transcriptome gene expression data. We use a modern large-margin machine learning approach, based on ...

Manuel Middendorf; Anshul Kundaje; Mihir Shah; Yoav Freund; Chris H. Wiggins; Christina Leslie

2005-05-01T23:59:59.000Z

311

Prediction of Landfalling Hurricanes with the Advanced Hurricane WRF Model  

Science Conference Proceedings (OSTI)

Real-time forecasts of five landfalling Atlantic hurricanes during 2005 using the Advanced Research Weather Research and Forecasting (WRF) (ARW) Model at grid spacings of 12 and 4 km revealed performance generally competitive with, and ...

Christopher Davis; Wei Wang; Shuyi S. Chen; Yongsheng Chen; Kristen Corbosiero; Mark DeMaria; Jimy Dudhia; Greg Holland; Joe Klemp; John Michalakes; Heather Reeves; Richard Rotunno; Chris Snyder; Qingnong Xiao

2008-06-01T23:59:59.000Z

312

An Examination of the MOS Objective Temperature Prediction Model  

Science Conference Proceedings (OSTI)

In this study, the performance of the Model Output Statistics (MOS) objective temperature forecasting for Albany, NY, during the period 1975–81 is examined by using various statistical technique. Both paired and unpaired statistical analysis ...

Eli Jacks; S. Trivikrama Rao

1985-01-01T23:59:59.000Z

313

A Simple Model for Coastal Sea Level Prediction  

Science Conference Proceedings (OSTI)

Reliable forecasting of wind-forced coastal sea level on the synoptic scale is available for most of the coastal areas of the United States through the National Weather Service Extratropical Storm Surge Model (ESSM). However, in many coastal ...

Charles E. Tilburg; Richard W. Garvine

2004-06-01T23:59:59.000Z

314

Two-Time-Step Oscillations in Numerical Weather Prediction Models  

Science Conference Proceedings (OSTI)

Spurious, nonamplifying, two-time-step oscillations are present in several numerical models of the atmosphere where the vertical diffusion is parameterized using a nonlinear diffusion equation. The problems become particularly pronounced when the ...

Ulla Hammarstrand

1997-12-01T23:59:59.000Z

315

Impact of Rotor Surface Velocity, Leakage Models and Real Gas Properties on Rotordynamic Force Predictions of Gas Labyrinth Seals  

E-Print Network (OSTI)

Rotordynamic coefficients of a gas labyrinth seal are assumed to be frequency independent. However, this assumption loses its validity as rotor surface velocity approaches Mach 1. The solution procedure of 1CV model by Childs and Scharrer which assumes frequency independent force coefficients is modified to allow for calculating frequency dependent force coefficients. A comparative study of the impact of using frequency-dependent model and the original frequency-independent model on stability analysis is made. The results indicate that frequency dependency of force coefficients should be accounted for in stability analysis as rotor surface velocity approaches a significant fraction of Mach number. The bulk flow rotordynamic analysis model by Childs and Scharrer is modified to investigate the impact of leakage-flow models on predictions. A number of leakage models are incorporated in the one-control volume model, and a comparative study is made. Kinetic energy carryover factor of a leakage equation is one of the dominant factors in seal cross-force generation. A leakage equation based on a model proposed by Gamal which uses Hodkinson?s kinetic energy carryover factor is found to improve predictions of direct damping and cross-coupled stiffness. A test case is implemented to study the impact of variation of seal axial radial clearance on stability characteristics. The 1CV model by Childs and Scharrer and subsequent bulk flow models are based on the assumption of isothermal flow across the labyrinth seal. The 1CV model by Childs and Scharrer is modified to include energy equation, and the flow process is assumed to be adiabatic. However, predicted cross-coupled stiffness and direct damping coefficients using the new model do not compare well with the experimental results by Picardo as compared to the isothermal model. The impact of using real gas properties on static and rotordynamic characteristics of the seal is studied.

Thorat, Manish R.

2010-05-01T23:59:59.000Z

316

The LHC di-photon Higgs signal predicted by little Higgs models  

E-Print Network (OSTI)

Little Higgs theory naturally predicts a light Higgs boson whose most important discovery channel at the LHC is the di-photon signal $pp\\to h\\to \\gamma\\gamma$. In this work we perform a comparative study for this signal in some typical little Higgs models, namely the littlest Higgs model (LH), two littlest Higgs models with T-parity (named LHT-I and LHT-II) and the simplest little Higgs modes (SLH). We find that compared with the Standard Model prediction, the di-photon signal rate is always suppressed and the suppression extent can be quite different for different models. The suppression is mild ($\\lsim 10%$) in the LH model but can be quite severe ($\\simeq 90%$) in other three models. This means that discovering the light Higgs boson predicted by the little Higgs theory through the di-photon channel at the LHC will be more difficult than discovering the SM Higgs boson.

Lei Wang; Jin Min Yang

2011-06-20T23:59:59.000Z

317

Propagation prediction model and performance analysis of RFID system under metallic container production circumstance  

Science Conference Proceedings (OSTI)

Radio-wave attenuation negatively affects RF communications in a RFID system. In order to ensure the reliability of RFID system, one must predict the radio-wave path-loss accurately before detailed design. However, it is infeasible to estimate the path-loss ... Keywords: Metallic container, Propagation prediction model, RFID

Cao Xiaohua; Xiao Hanbin

2011-02-01T23:59:59.000Z

318

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

E-Print Network (OSTI)

`TVLSI-00029-2003.R1 1 An Analytical Model for Predicting the Remaining Battery Capacity of Lithium-Ion Batteries Peng Rong, Student Member, IEEE and Massoud Pedram, Fellow, IEEE Abstract -- Predicting the residual energy of the battery source that powers a portable electronic device is imperative in designing

Pedram, Massoud

319

The Operating Regime Approach to Nonlinear Modelling and Control  

E-Print Network (OSTI)

Johansen,T.A. Murray-Smith,R. Multiple Model Approaches to Modelling and Control pp 3-72 Taylor and Francis

Johansen, T.A.; Murray-Smith, R.

320

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

NLE Websites -- All DOE Office Websites (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.

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

Development of a Procedure for the Predictive Control Strategy of a Chilled Water Storage System  

E-Print Network (OSTI)

Thermal energy storage systems store the thermal energy produced by the chiller plant in periods of off-peak electrical demand or when cheaper electricity is available. The stored thermal energy is then withdrawn from the reservoir to satisfy cooling load during peak demand periods. This paper discusses the development of a simplified predictive control strategy for a 7000 ton-hour chilled water storage system serving a hospital. Control strategies are developed for both on-peak and off-peak months to minimize demand charges. By optimizing the operation of the building air handling units (AHUs), chilled water pumps, chiller plant and the thermal storage system, the storage tank is better charged while chiller run time is reduced. Both on-peak and off-peak electrical demands are expected to be reduced significantly.

Wei, G.; Sakuri, Y.; Claridge, D. E.; Turner, W. D.; Liu, M.

2000-01-01T23:59:59.000Z

322

Design of spatial experiments: Model fitting and prediction  

Science Conference Proceedings (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

323

Energy Consumption Models and Predictions for Large-Scale Systems  

Science Conference Proceedings (OSTI)

Responsible, efficient and well-planned power consumption is becoming a necessity for monetary returns and scalability of computing infrastructures. While there are numerous sources from which power data can be obtained, analyzing this data is an intrinsically ... Keywords: Energy model, Grid'5000, distrbuted systems

Taghrid Samak, Christine Morin, David Bailey

2013-05-01T23:59:59.000Z

324

Bootstrapping to Assess and Improve Atmospheric Prediction Models  

Science Conference Proceedings (OSTI)

Bootstrapping is a simple technique typically used to assess accuracy of estimates of model parameters by using simple plug-in principles and replacing sometimes unwieldy theory by computer simulation. Common uses include variance estimation and confidence ... Keywords: CART, bootstrap, classification, hurricanes, instability, supervised learning, weather data

J. Sunil Rao

2000-04-01T23:59:59.000Z

325

Hybridization of intelligent techniques and ARIMA models for time series prediction  

Science Conference Proceedings (OSTI)

Traditionally, the autoregressive moving average (ARMA) model has been one of the most widely used linear models in time series prediction. Recent research activities in forecasting with artificial neural networks (ANNs) suggest that ANNs can be a promising ... Keywords: ARIMA models, Fuzzy systems, Hybrid system, Neural networks, Time series

O. Valenzuela; I. Rojas; F. Rojas; H. Pomares; L. J. Herrera; A. Guillen; L. Marquez; M. Pasadas

2008-04-01T23:59:59.000Z

326

Mining subsidence prediction based on 3D stratigraphic model and visualization  

Science Conference Proceedings (OSTI)

3D phenomenon involved in mining subsidence was Classified, summarized and aggregated, established the hierarchical structure that describing the geologic phenomena and engineering phenomena of stratum structure. Proposed a 3D stratigraphic model that ... Keywords: 3D stratigraphic model, 3D visualization, DEMs-TEN model, mining subsidence prediction

Ruisheng Jia; Yanjun Peng; Hongmei Sun

2011-01-01T23:59:59.000Z

327

Development of a predictive kinetic model for homogeneous Hg oxidation data  

Science Conference Proceedings (OSTI)

Several researchers have developed kinetic models to predict the effects of various flue gas components on homogeneous mercury (Hg) oxidation. Most of these models make use of over 50 reversible reactions that involve radicals in a combustion or post-combustion ... Keywords: Chlorine gas, Homogeneous mercury oxidation, Kinetic model, Simulated flue gas

Hans Agarwal; Harvey G. Stenger

2007-01-01T23:59:59.000Z

328

Evaluation of a simulation model in predicting the drying parameters for deep-bed paddy drying  

Science Conference Proceedings (OSTI)

A simulation model for deep-bed batch drying of paddy was developed to predict the profiles of grain moisture content, grain temperature, air temperature and air humidity during the drying process. In order to evaluate the validity of this model, a laboratory-scale ... Keywords: Deep-bed, Energy optimization, Paddy, Simulation model

Dariush Zare; Guangnan Chen

2009-08-01T23:59:59.000Z

329

Thermoregulatory model to predict physiological status from ambient environment and heart rate  

Science Conference Proceedings (OSTI)

A real-time thermoregulatory model was developed for predicting real-time physiological responses of workers engaged in various tasks for prolonged time. The unique feature of the present model is primarily on metabolic activity inputs derived from minimum ... Keywords: Air temperature, Core temperature, Heart rate, Heat stress, Real-time modeling

Miyo Yokota; Larry Berglund; Samuel Cheuvront; William Santee; William Latzka; Scott Montain; Margaret Kolka; Daniel Moran

2008-11-01T23:59:59.000Z

330

A New Visibility Parameterization for Warm-Fog Applications in Numerical Weather Prediction Models  

Science Conference Proceedings (OSTI)

The objective of this work is to suggest a new warm-fog visibility parameterization scheme for numerical weather prediction (NWP) models. In situ observations collected during the Radiation and Aerosol Cloud Experiment, representing boundary ...

I. Gultepe; M. D. Müller; Z. Boybeyi

2006-11-01T23:59:59.000Z

331

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

Science Conference Proceedings (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

332

Operational Assimilation of GPS Zenith Total Delay Observations into the Met Office Numerical Weather Prediction Models  

Science Conference Proceedings (OSTI)

Zenith total delay (ZTD) observations derived from ground-based GPS receivers have been assimilated operationally into the Met Office North Atlantic and European (NAE) numerical weather prediction (NWP) model since 2007. Assimilation trials were ...

Gemma V. Bennitt; Adrian Jupp

2012-08-01T23:59:59.000Z

333

A Consolidated CLIPER Model for Improved August–September ENSO Prediction Skill  

Science Conference Proceedings (OSTI)

A prime challenge for ENSO seasonal forecast models is to predict boreal summer ENSO conditions at lead. August–September ENSO has a strong influence on Atlantic hurricane activity, Northwest Pacific typhoon activity, and tropical precipitation. ...

Benjamin Lloyd-Hughes; Mark A. Saunders; Paul Rockett

2004-12-01T23:59:59.000Z

334

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

Science Conference Proceedings (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

335

Dynamics of Prediction Errors under the Combined Effect of Initial Condition and Model Errors  

Science Conference Proceedings (OSTI)

The transient evolution of prediction errors in the short to intermediate time regime is considered under the combined effect of initial condition and model errors. Some generic features are brought out and connected with intrinsic properties. ...

C. Nicolis; Rui A. P. Perdigao; S. Vannitsem

2009-03-01T23:59:59.000Z

336

A Quasi-Lagrangian Regional Model Designed for Operational Weather Prediction  

Science Conference Proceedings (OSTI)

A regional numerical weather prediction model is designed using the quasi-Lagrangian method for operational forecasting of synoptic and mesoscale disturbances. The nonlinear advective terms and the total forcing experienced by a fluid parcel are ...

Mukut B. Mathur

1983-10-01T23:59:59.000Z

337

The Impact of Satellite Sounding Data on the Systematic Error of a Numerical Weather Prediction Model  

Science Conference Proceedings (OSTI)

The impact of satellite sounding data on the systematic errors of the numerical weather prediction model of the Israel Meteorological Service has been investigated. In general, satellite data have been shown to reduce systematic error, and in ...

Noah Wolfson; Albert Thomasell; Arnold Gruber; George Ohring

1985-06-01T23:59:59.000Z

338

Estimates of Cn2 from Numerical Weather Prediction Model Output and Comparison with Thermosonde Data  

Science Conference Proceedings (OSTI)

Area-averaged estimates of Cn2 from high-resolution numerical weather prediction (NWP) model output are produced from local estimates of the spatial structure functions of refractive index with corrections for the inherent smoothing and filtering ...

Rod Frehlich; Robert Sharman; Francois Vandenberghe; Wei Yu; Yubao Liu; Jason Knievel; George Jumper

2010-08-01T23:59:59.000Z

339

Modeling the Distribution of Precipitation Forecasts from the Canadian Ensemble Prediction System Using Kernel Density Estimation  

Science Conference Proceedings (OSTI)

Kernel density estimation is employed to fit smooth probabilistic models to precipitation forecasts of the Canadian ensemble prediction system. An intuitive nonparametric technique, kernel density estimation has become a powerful tool widely used ...

Syd Peel; Laurence J. Wilson

2008-08-01T23:59:59.000Z

340

A Comprehensive Radiation Scheme for Numerical Weather Prediction Models with Potential Applications in Climate Simulations  

Science Conference Proceedings (OSTI)

A comprehensive scheme for the parameterization of radiative transfer in numerical weather Prediction (NWP) models has been developed. The scheme is based on the solution of the ?-two-stream version of the radiative transfer equation ...

Bodo Ritter; Jean-Francois Geleyn

1992-02-01T23:59:59.000Z

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.


341

A Potential Predictability Study Conducted with an Atmospheric General Circulation Model  

Science Conference Proceedings (OSTI)

This paper describes a potential predictability study on the results of a 20.5 year simulation conducted with the Canadian Climate Centre (CCC) General Circulation Model (GCM). The CCC GCM is an atmosphere GCM with surface hydrology, soil ...

F. W. Zwiers

1987-12-01T23:59:59.000Z

342

Tropical Cyclone Prediction Using a Barotropic Model Initialized by a Generalized Inverse Method  

Science Conference Proceedings (OSTI)

A nested, nondivergent barotropic numerical weather prediction model for forecasting tropical cyclone motion out to 48 h is initialized at time t = 0 by assimilating data from the preceding 24 h. The assimilation scheme finds the generalized ...

A. F. Bennett; L. M. Leslie; C. R. Hagelberg; P. E. Powers

1993-06-01T23:59:59.000Z

343

Coupled Variability and Predictability in a Stochastic Climate Model of the Tropical Atlantic  

Science Conference Proceedings (OSTI)

The coupled variability and predictability of the tropical Atlantic ocean–atmosphere system were analyzed within the framework of a linear stochastic climate model. Despite the existence of a meridional dipole as the leading mode, tropical ...

Faming Wang; Ping Chang

2008-12-01T23:59:59.000Z

344

The Canadian Seasonal to Interannual Prediction System. Part I: Models and Initialization  

Science Conference Proceedings (OSTI)

The Canadian Seasonal to Interannual Prediction System (CanSIPS) became operational at Environment Canada's Canadian Meteorological Centre (CMC) in December 2011, replacing CMC's previous two-tier system. CanSIPS is a two-model forecasting system ...

William J. Merryfield; Woo-Sung Lee; George J. Boer; Viatcheslav V. Kharin; John F. Scinocca; Gregory M. Flato; R. S. Ajayamohan; John C. Fyfe; Youmin Tang; Saroja Polavarapu

2013-08-01T23:59:59.000Z

345

Application and Validation of a Seasonal Ensemble Prediction System Using a Dynamic Malaria Model  

Science Conference Proceedings (OSTI)

Seasonal multimodel forecasts from the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) project are used to drive a malaria model and create reforecasts of malaria incidence for Botswana, in ...

Anne E. Jones; Andrew P. Morse

2010-08-01T23:59:59.000Z

346

Use of Medium-Range Numerical Weather Prediction Model Output to Produce Forecasts of Streamflow  

Science Conference Proceedings (OSTI)

This paper examines an archive containing over 40 years of 8-day atmospheric forecasts over the contiguous United States from the NCEP reanalysis project to assess the possibilities for using medium-range numerical weather prediction model output ...

Martyn P. Clark; Lauren E. Hay

2004-02-01T23:59:59.000Z

347

Performance of the United Kingdom Meteorological Office Global Model in Predicting the Movement of Tropical Cyclones  

Science Conference Proceedings (OSTI)

A detailed evaluation of the performance of the United Kingdom Meteorological Office Global Model (UKMO) in predicting the movement of 15 tropical cyclones (TCs) that occurred over the western North Pacific during 1987 is presented. The ...

Johnny C. L. Chan; Wai-Kau Kay

1993-09-01T23:59:59.000Z

348

Predicting Cloud-to-Ground and Intracloud Lightning in Weather Forecast Models  

Science Conference Proceedings (OSTI)

A new prognostic, spatially and temporally dependent variable is introduced to the Weather Research and Forecasting Model (WRF). This variable is called the potential electrical energy (Ep). It was used to predict the dynamic contribution of the ...

Barry H. Lynn; Yoav Yair; Colin Price; Guy Kelman; Adam J. Clark

2012-12-01T23:59:59.000Z

349

A novel 2-D model approach for the prediction of hourly solar radiation  

Science Conference Proceedings (OSTI)

In this work, a two-dimensional (2-D) representation of the hourly solar radiation data is proposed. The model enables accurate forecasting using image prediction methods. One year solar radiation data that is acquired and collected between August 1, ...

F. Onur Hocaoglu; Ö Nezih Gerek; Mehmet Kurban

2007-06-01T23:59:59.000Z

350

Model Estimates of Land-Driven Predictability in a Changing Climate from CCSM4  

Science Conference Proceedings (OSTI)

The climate system model of the National Center for Atmospheric Research is used to examine the predictability arising from the land surface initialization of seasonal climate ensemble forecasts in current, preindustrial, and projected future ...

Paul A. Dirmeyer; Sanjiv Kumar; Michael J. Fennessy; Eric L. Altshuler; Timothy DelSole; Zhichang Guo; Benjamin A. Cash; David Straus

2013-11-01T23:59:59.000Z

351

Using Temporal Modes of Rainfall to Evaluate the Performance of a Numerical Weather Prediction Model  

Science Conference Proceedings (OSTI)

The authors demonstrate that much can be learned about the performance of a numerical weather prediction (NWP) model by examining the temporal modes of its simulated rainfall. Observations from the Weather Surveillance Radar-1988 Doppler (WSR-88D)...

Jason C. Knievel; David A. Ahijevych; Kevin W. Manning

2004-12-01T23:59:59.000Z

352

Prediction Experiments of Hurricane Gloria (1985) Using a Multiply Nested Movable Mesh Model  

Science Conference Proceedings (OSTI)

The prediction capability of the GFDL triply nested, movable mesh model, with finest grid resolution of degree, was investigated using several case studies of Hurricane Gloria ( 1985) during the period that the storm approached and moved up the ...

Yoshio Kurihara; Morris A. Bender; Robert E. Tuleya; Rebecca J. Ross

1990-10-01T23:59:59.000Z

353

Spatial Predictions of Extreme Wind Speeds over Switzerland Using Generalized Additive Models  

Science Conference Proceedings (OSTI)

The purpose of this work is to present a methodology aimed at predicting extreme wind speeds over Switzerland. Generalized additive models are used to regionalize wind statistics for Swiss weather stations using a number of variables that ...

Christophe Etienne; Anthony Lehmann; Stéphane Goyette; Juan-Ignacio Lopez-Moreno; Martin Beniston

2010-09-01T23:59:59.000Z

354

Numerical Prediction of an Antarctic Severe Wind Event with the Weather Research and Forecasting (WRF) Model  

Science Conference Proceedings (OSTI)

This study initiates the application of the maturing Weather Research and Forecasting (WRF) model to the polar regions in the context of the real-time Antarctic Mesoscale Prediction System (AMPS). The behavior of the Advanced Research WRF (ARW) ...

Jordan G. Powers

2007-09-01T23:59:59.000Z

355

Evaluating Mesoscale Model Predictions of Clouds and Radiation with SGP ARM Data over a Seasonal Timescale  

Science Conference Proceedings (OSTI)

This study evaluates the predictions of radiative and cloud-related processes of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5). It is based on extensive comparison of ...

Françoise Guichard; David B. Parsons; Jimy Dudhia; James Bresch

2003-05-01T23:59:59.000Z

356

Interannual to Decadal Predictability in a Coupled Ocean–Atmosphere General Circulation Model  

Science Conference Proceedings (OSTI)

The predictability of the coupled ocean–atmosphere climate system on interannual to decadal timescales has been studied by means of ensemble forecast experiments with a global coupled ocean–atmosphere general circulation model. Over most parts of ...

A. Grötzner; M. Latif; A. Timmermann; R. Voss

1999-08-01T23:59:59.000Z

357

Microscale Numerical Prediction over Montreal with the Canadian External Urban Modeling System  

Science Conference Proceedings (OSTI)

The Canadian urban and land surface external modeling system (known as urban GEM-SURF) has been developed to provide surface and near-surface meteorological variables to improve numerical weather prediction and to become a tool for environmental ...

Sylvie Leroyer; Stéphane Bélair; Jocelyn Mailhot; Ian B. Strachan

2011-12-01T23:59:59.000Z

358

Calibrated Surface Temperature Forecasts from the Canadian Ensemble Prediction System Using Bayesian Model Averaging  

Science Conference Proceedings (OSTI)

Bayesian model averaging (BMA) has recently been proposed as a way of correcting underdispersion in ensemble forecasts. BMA is a standard statistical procedure for combining predictive distributions from different sources. The output of BMA is a ...

Laurence J. Wilson; Stephane Beauregard; Adrian E. Raftery; Richard Verret

2007-04-01T23:59:59.000Z

359

Comparison of a Two-Dimensional Wave Prediction Model with Synoptic Measurements in Lake Michigan  

Science Conference Proceedings (OSTI)

We compare results from a simple parametric, dynamical, deep-water wave prediction model with two sets of measured wave height maps of Lake Michigan. The measurements were made with an airborne laser altimeter under two distinctly different wind ...

Paul C. Liu; David J. Schwab; John R. Bennett

1984-09-01T23:59:59.000Z

360

Evolving Multisensor Precipitation Estimation Methods: Their Impacts on Flow Prediction Using a Distributed Hydrologic Model  

Science Conference Proceedings (OSTI)

This study investigates evolving methodologies for radar and merged gauge–radar quantitative precipitation estimation (QPE) to determine their influence on the flow predictions of a distributed hydrologic model. These methods include the National ...

David Kitzmiller; Suzanne Van Cooten; Feng Ding; Kenneth Howard; Carrie Langston; Jian Zhang; Heather Moser; Yu Zhang; Jonathan J. Gourley; Dongsoo Kim; David Riley

2011-12-01T23:59:59.000Z

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.


361

Skill of Operational Dynamical Models in Cyclone Prediction Out to Five-Days Range during ERICA  

Science Conference Proceedings (OSTI)

Investigating the skill of prediction of surface cyclones by operational models to ranges of five days, we studied the central and western North Atlantic region for the December 1988 through February 1989 period of the Experiment on Rapidly ...

Frederick Sanders

1992-03-01T23:59:59.000Z

362

The Use of Quasi-Nonhydrostatic Models for Mesoscale Weather Prediction  

Science Conference Proceedings (OSTI)

In recent years, there has been extensive study of the mathematical basis of weather prediction leading to a new system of continuous equations that are well posed, and a set of conditions that make discrete atmospheric and other models stable ...

A. E. MacDonald; J. L. Lee; Y. Xie

2000-08-01T23:59:59.000Z

363

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

E-Print Network (OSTI)

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

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

2013-06-19T23:59:59.000Z

364

Structure Based Predictive Model for Coal Char Combustion  

SciTech Connect

This unique collaborative project has taken a very fundamental look at the origin of structure, and combustion reactivity of coal chars. It was a combined experimental and theoretical effort involving three universities and collaborators from universities outside the U.S. and from U.S. National Laboratories and contract research companies. The project goal was to improve our understanding of char structure and behavior by examining the fundamental chemistry of its polyaromatic building blocks. The project team investigated the elementary oxidative attack on polyaromatic systems, and coupled with a study of the assembly processes that convert these polyaromatic clusters to mature carbon materials (or chars). We believe that the work done in this project has defined a powerful new science-based approach to the understanding of char behavior. The work on aromatic oxidation pathways made extensive use of computational chemistry, and was led by Professor Christopher Hadad in the Department of Chemistry at Ohio State University. Laboratory experiments on char structure, properties, and combustion reactivity were carried out at both OSU and Brown, led by Principle Investigators Joseph Calo, Robert Essenhigh, and Robert Hurt. Modeling activities were divided into two parts: first unique models of crystal structure development were formulated by the team at Brown (PI'S Hurt and Calo) with input from Boston University and significant collaboration with Dr. Alan Kerstein at Sandia and with Dr. Zhong-Ying chen at SAIC. Secondly, new combustion models were developed and tested, led by Professor Essenhigh at OSU, Dieter Foertsch (a collaborator at the University of Stuttgart), and Professor Hurt at Brown. One product of this work is the CBK8 model of carbon burnout, which has already found practical use in CFD codes and in other numerical models of pulverized fuel combustion processes, such as EPRI's NOxLOI Predictor. The remainder of the report consists of detailed technical discussion organized into chapters whose organization is dictated by the nature of the research performed. Chapter 2 is entitled 'Experimental Work on Char Structure, Properties, and Reactivity', and focuses on fundamental structural studies at Brown using both phenollformaldehyde resin chars as model carbons and real coal chars. This work includes the first known in site high resolution TEM studies of carbonization processes, and some intriguing work on 'memory loss', a form of interaction between annealing and oxidation phenomena in chars. Chapter 3 entitled 'Computational Chemistry of Aromatic Oxidation Pathways' presents in detail the OSU work targeted at understanding the elementary molecular pathways of aromatic oxidation. Chapter 4 describes the 'Mesoscale Structural Models', using a combination of thermodynamic (equilibrium) approaches based on liquid crystal theory and kinetic simulations accounting for the effects of limited layer mobility in many fossil fuel derived carbons containing cross-linking agents. Chapter 5 entitled 'Combustion Modeling' presents work on extinction in the late stages of combustion and the development and features of the CBK8 model.

Robert Hurt; Joseph Calo; Robert Essenhigh; Christopher Hadad

2000-12-30T23:59:59.000Z

365

Structure-Based Predictive Model for Coal Char Combustion  

Science Conference Proceedings (OSTI)

Progress was made this period on a number of separate experimental and modelling activities. At Brown, the models of carbon nanostructure evolution were expanded to consider high-rank materials with initial anisotropy. The report presents detailed results of Monte Carlo simulations with non-zero initial layer length and with statistically oriented initial states. The expanded simulations are now capable of describing the development of nanostructure during carbonization of most coals. Work next quarter will address the remaining challenge of isotropic coke-forming coals. Experiments at Brown yielded important data on the "memory loss" phenomenon in carbon annealing, and on the effect of mineral matter on high-temperature reactivity. The experimental aspects of the Brown work will be discussed in detail in the next report.

Christopher Hadad; Joseph Calo; Robert Essenhigh; Robert Hurt

1998-04-08T23:59:59.000Z

366

Predictivity of models with spontaneously broken non-Abelian discrete flavor symmetries  

E-Print Network (OSTI)

In a class of supersymmetric flavor models predictions are based on residual symmetries of some subsectors of the theory such as those of the charged leptons and neutrinos. However, the vacuum expectation values of the so-called flavon fields generally modify the K\\"ahler potential of the setting, thus changing the predictions. We derive simple analytic formulae that allow us to understand the impact of these corrections on the predictions for the masses and mixing parameters. Furthermore, we discuss the effects on the vacuum alignment and on flavor changing neutral currents. Our results can also be applied to non--supersymmetric flavor models.

Chen, Mu-Chun; Omura, Yuji; Ratz, Michael; Staudt, Christian

2013-01-01T23:59:59.000Z

367

Experimental Validation of Stochastic Wireless Urban Channel Model: Estimation and Prediction  

SciTech Connect

Stochastic differential equations (SDE) can be used to describe the time-varying nature of wireless channels. This paper validates a long-term fading channel model for estimation and prediction from solely using measured received signal strength measurements. Such channel models can be used for optimizing wireless networks deployed for industrial automation, public access, and communication. This paper uses two different sets of received signal measurement data to estimate an predict the signal strength based on past measurements. The realworld performance of the estimation and prediction algorithm is demonstrated.

Kuruganti, Phani Teja [ORNL; Ma, Xiao [ORNL; Djouadi, Seddik M [ORNL

2012-01-01T23:59:59.000Z

368

STRUCTURE BASED PREDICTIVE MODEL FOR COAL CHAR COMBUSTION  

SciTech Connect

This report is part on the ongoing effort at Brown University and Ohio State University to develop structure based models of coal combustion. A very fundamental approach is taken to the description of coal chars and their reaction processes, and the results are therefore expected to have broad applicability to the spectrum of carbon materials of interest in energy technologies. This quarter, the project was in a period no-cost extension and discussions were held about the end phase of the project and possible continuations. The technical tasks were essentially dormant this period, but presentations of results were made, and plans were formulated for renewed activity in the fiscal year 2001.

Robert Hurt; Joseph Calo; Robert Essenhigh; Christopher Hadad

2001-06-15T23:59:59.000Z

369

Bayesian methods for discontinuity detection in climate model predictions.  

Science Conference Proceedings (OSTI)

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

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

2010-06-01T23:59:59.000Z

370

Developing and Simulation Research of the Control Model and Control Strategy of Static Frequency Converter  

Science Conference Proceedings (OSTI)

a control model and control strategy of static frequency converter (SFC) for pumped storage power plant unit is presented. Control strategy of static start-up and its mathematical model is discussed in detail. And based on the 42 poles of synchronous ... Keywords: Pumped Storage Power Plant, Static Frequency Converter, SFC, Commutation, Control

Deshun Wang; Lichun Zhang; Bo Yang; Guanjun Li; Yibin Tao; Jianzhong Fu; Jianfeng Li; Liantao Ji

2012-01-01T23:59:59.000Z

371

STRUCTURE-BASED PREDICTIVE MODEL FOR COAL CHAR COMBUSTION  

SciTech Connect

This report is part on the ongoing effort at Brown University and Ohio State University to develop structure based models of coal combustion. A very fundamental approach is taken to the description of coal chars and their reaction processes, and the results are therefore expected to have broad applicability to the spectrum of carbon materials of interest in energy technologies. This quarter, our work on structure development in carbons continued. A combination of hot stage in situ and ex situ polarized light microscopy was used to identify the preferred orientational of graphene layers at gas interfaces in pitches used as carbon material precursors. The experiments show that edge-on orientation is the equilibrium state of the gas/pitch interface, implying that basal-rich surfaces have higher free energies than edge-rich surfaces in pitch. This result is in agreement with previous molecular modeling studies and TEM observations in the early stages of carbonization. The results may have important implications for the design of tailored carbons with edge-rich or basal-rich surfaces. In the computational chemistry task, we have continued our investigations into the reactivity of large aromatic rings. The role of H-atom abstraction as well as radical addition to monocyclic aromatic rings has been examined, and a manuscript is currently being revised after peer review. We have also shown that OH radical is more effective than H atom in the radical addition process with monocyclic rings. We have extended this analysis to H-atom and OH-radical addition to phenanthrene. Work on combustion kinetics focused on the theoretical analysis of the data previously gathered using thermogravametric analysis.

Robert H. Hurt; Eric M. Suuberg

2000-05-03T23:59:59.000Z

372

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

SciTech Connect

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

373

Assessment of emissions prediction capability of RANS based PDF models for lean premixed combustion of methane  

DOE Green Energy (OSTI)

The high computational cost of Large Eddy Simulation (LES) makes Reynolds Averaged Navier-Stokes (RANS) methods the current standard for turbulent combustion modeling. Empirical models for turbulence, turbulence-combustion interaction and chemical kinetics are, however, a major source of uncertainty in RANS based combustion simulation. While Probability Density Function (PDF) based models overcome some of these issues, most commercial codes do not take full advantage of these models. In this study, lean premixed combustion of methane in a bluff-body combustor is simulated using two different reduced chemical mechanisms (ARM9 and ARM19) combined with the composition PDF transport combustion model in the commercial code FLUENT. Two different turbulence models, namely the RNG k-? model and the Reynolds Stress Model (RSM) are used and the results of the simulations are compared to experimental data. For all the models tested, the prediction of temperature and major species (CH4, O2, CO2, CO, H2, and H2O) was good when compared to experiments. While all of the model predictions for the intermediate species OH showed an order magnitude difference (compared to the experiments) close to the bluff body surface; downstream axial locations showed good quantitative and qualitative agreement with the experiments. In a trend similar to the previous study (Nanduri et al., 2007) using the Eddy Dissipation Concept (EDC) model, predicted values for NO emission radial profiles showed an average difference of ±5 ppm when compared to experimental values. The results were also compared to the results of a velocity-composition joint PDF model developed by researchers at the University of Pittsburgh. In terms of emissions (NO and CO) predictions the relatively expensive composition PDF model in FLUENT did not give significant improvement when compared to the computationally cheaper EDC models. However, the velocity-composition joint PFD model used by researchers at the University of Pittsburgh did show significant improvement over EDC models in the prediction of NO. Both of the PDF models resulted in better qualitative and quantitative agreement in H2 prediction, thus showing the promise of PDF based models in simulating lean premixed combustion of fuel blends like hydrogen enriched natural gas.

Parsons, D.R.; Nanduri, J.R.; Celik, Ismail; Strakey, P.A.

2008-01-01T23:59:59.000Z

374

Motor Modeling and Position Control Lab Week 3: Closed Loop Control  

E-Print Network (OSTI)

Motor Modeling and Position Control Lab Week 3: Closed Loop Control 1. Review In the first week of motor modeling lab, a mathematical model of a DC motor from first principles was derived to obtain specifically for this motor model. In the second week, a physical DC motor (Quanser SRV-02) was used for open

Krovi, Venkat

375

Simple predictive model for performance of desiccant beds for solar dehumidification  

DOE Green Energy (OSTI)

A computer model is outlined for the absorption/desorption process that can be used to predict the performance of desiccant beds for solar regenerated dehumidification of passively cooled buildings. Instead of solving a set of coupled differential equations, the model uses simple algebraic equations for steady-state heat and mass exchangers. A comparison of computer predictions and experimental data demonstrate the validity and accuracy of the model. The physics of the adsorption process is discussed in terms of two psychrometric process lines, and planned research efforts at SERI are described.

Barlow, R.S.

1981-08-01T23:59:59.000Z

376

A Finite Mixture Logit Model to Segment and Predict Electronic Payments System Adoption  

Science Conference Proceedings (OSTI)

Despite much hype about electronic payments systems (EPSs), a 2004 survey establishes that close to 80% of between-business payments are still made using paper-based formats. We present a finite mixture logit model to predict likelihood of EPS adoption ... Keywords: clustering analysis, electronic payments systems, finite mixture model, hierarchical logit regression, logistic regression, market segmentation

Ravi Bapna; Paulo Goes; Kwok Kee Wei; Zhongju Zhang

2011-03-01T23:59:59.000Z

377

Neural network prediction model for the methane fraction in biogas from field-scale landfill bioreactors  

Science Conference Proceedings (OSTI)

In this study we present a neural network model for predicting the methane fraction in landfill gas originating from field-scale landfill bioreactors. Landfill bioreactors were constructed at the Odayeri Sanitary Landfill, Istanbul, Turkey, and operated ... Keywords: Anaerobic digestion, Landfill gas, Leachate, Methane fraction, Modeling, Neural network

Bestamin Ozkaya; Ahmet Demir; M. Sinan Bilgili

2007-06-01T23:59:59.000Z

378

A hybrid neural network and ARIMA model for water quality time series prediction  

Science Conference Proceedings (OSTI)

Accurate predictions of time series data have motivated the researchers to develop innovative models for water resources management. Time series data often contain both linear and nonlinear patterns. Therefore, neither ARIMA nor neural networks can be ... Keywords: ARIMA, Backpropagation, Hybrid model, Neural networks, Time series

Durdu Ömer Faruk

2010-06-01T23:59:59.000Z

379

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

380

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

NLE Websites -- All DOE Office Websites (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.

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

Quantifying the Predictive Skill in Long-Range Forecasting. Part II: Model Error in Coarse-Grained Markov Models with Application to Ocean-Circulation Regimes  

Science Conference Proceedings (OSTI)

An information-theoretic framework is developed to assess the predictive skill and model error in imperfect climate models for long-range forecasting. Here, of key importance is a climate equilibrium consistency test for detecting false predictive ...

Dimitrios Giannakis; Andrew J. Majda

2012-03-01T23:59:59.000Z

382

Regional Weather Prediction with a Model Combining Terrain-following and Isentropic Coordinates. Part I: Model Description  

Science Conference Proceedings (OSTI)

A short-range numerical prediction model, which is part of a real-time 3-h data assimilation and forecast system, is described. The distinguishing feature of the model is the use of terrain-following (?) coordinate surfaces in the lower ...

Rainer Bleck; Stanley G. Benjamin

1993-06-01T23:59:59.000Z

383

Access Control: Policies, Models, and Mechanisms  

Science Conference Proceedings (OSTI)

Access control is the process of mediating every request to resources and data maintained by a system and determining whether the request should be granted or denied. The access control decision is enforced by a mechanism implementing regulations established ...

Pierangela Samarati; Sabrina De Capitani di Vimercati

2000-09-01T23:59:59.000Z

384

An analytical model for predicting the remaining battery capacity of lithium-ion batteries  

E-Print Network (OSTI)

Abstract—Predicting the residual energy of the battery source that powers a portable electronic device is imperative in designing and applying an effective dynamic power management policy for the device. This paper starts up by showing that a 30 % error in predicting the battery capacity of a lithium-ion battery can result in up to 20 % performance degradation for a dynamic voltage and frequency scaling algorithm. Next, this paper presents a closed form analytical expression for predicting the remaining capacity of a lithium-ion battery. The proposed high-level model, which relies on online current and voltage measurements, correctly accounts for the temperature and cycle aging effects. The accuracy of the highlevel model is validated by comparing it with DUALFOIL simulation results, demonstrating a maximum of 5 % error between simulated and predicted data. Index Terms—Accelerated rate capacity, cycle aging and dynamic voltage scaling, remaining battery capacity, temperature. I.

Peng Rong; Student Member; Massoud Pedram

2003-01-01T23:59:59.000Z

385

Robust control design verification using the modular modeling system  

Science Conference Proceedings (OSTI)

The Modular Modeling System (B W MMS) is being used as a design tool to verify robust controller designs for improving power plant performance while also providing fault-accommodating capabilities. These controllers are designed based on optimal control theory and are thus model based controllers which are targeted for implementation in a computer based digital control environment. The MMS is being successfully used to verify that the controllers are tolerant of uncertainties between the plant model employed in the controller and the actual plant; i.e., that they are robust. The two areas in which the MMS is being used for this purpose is in the design of (1) a reactor power controller with improved reactor temperature response, and (2) the design of a multiple input multiple output (MIMO) robust fault-accommodating controller for a deaerator level and pressure control problem.

Edwards, R.M.; Ben-Abdennour, A.; Lee, K.Y.

1991-01-01T23:59:59.000Z

386

Catalyst Modeling and CLEERS - Emissions & Emission Controls...  

NLE Websites -- All DOE Office Websites (Extended Search)

Catalyst Modeling and CLEERS A large part of ORNL's efforts in catalyst research are geared toward model development of catalyst devices and engine systems. Experimental data...

387

Predictive models for emission of hydrogen powered car using various artificial intelligent tools  

Science Conference Proceedings (OSTI)

This paper investigates the use of artificial intelligent models as virtual sensors to predict relevant emissions such as carbon dioxide, carbon monoxide, unburnt hydrocarbons and oxides of nitrogen for a hydrogen powered car. The virtual sensors are ... Keywords: Adaptive neuro-fuzzy inference systems, Artificial intelligent techniques, Back-propagation neural networks with Levenberg–Marquardt algorithm, Hydrogen emission prediction, Hydrogen powered car, UTAS artificial neural networks

Vishy Karri; Tien Nhut Ho

2009-06-01T23:59:59.000Z

388

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

SciTech Connect

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

Langton, C.; Kosson, D.

2009-11-30T23:59:59.000Z

389

From model-based strategies to intelligent control systems  

Science Conference Proceedings (OSTI)

This paper presents the evolution of control systems and trends in the field of integrated computer, communication and cognitive sciences for control applications. There have been selected and presented the most efficient control strategies used in complex ... Keywords: intelligent control systems, model-based systems

Ioan Dumitrache

2008-06-01T23:59:59.000Z

390

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

391

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

SciTech Connect

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

392

APPLICATION OF MATHEMATICAL PROGRAMMING MODELS TO COAL QUALITY CONTROL.  

E-Print Network (OSTI)

??The problem of utilizing blending techniques to control coal quality at the production-consumption phase is considered. Three blending models were developed to provide coal of… (more)

BAAFI, ERNEST YAW.

1983-01-01T23:59:59.000Z

393

Modelling the dynamical baroreflex-feedback control  

Science Conference Proceedings (OSTI)

A comprehensive model of the baroreflex-feedback mechanism regulating the heart rate, the contractility of the ventricle and the peripheral vascular resistance is presented. The dynamics of the affector and the effector parts are modelled. For each of ... Keywords: Baroreceptor, Cardiovascular system, Mathematical modelling, Medical applications, Neural biology, Nonlinear feedback mechanism, Nonlinear oscillations

J. T. Ottesen

2000-02-01T23:59:59.000Z

394

Warehousing and inventory management: integrating simulation modeling and equipment condition diagnostics for predictive maintenance strategies -a case study  

Science Conference Proceedings (OSTI)

This paper presents results from a case study in predictive maintenance at a distribution warehouse. A simulation model was built with ARENATM 5.0 for integrating predictive maintenance strategies with production planning strategies, ...

Luis Rene Contreras; Chirag Modi; Arunkumar Pennathur

2002-12-01T23:59:59.000Z

395

Predictability of SST in an Idealized, One-Dimensional, Coupled Atmosphere–Ocean Climate Model with Stochastic Forcing and Advection  

Science Conference Proceedings (OSTI)

The predictability of sea surface temperature (SST) is examined through analysis of an idealized, one-dimensional, stochastically forced climate model. The influence on SST predictability of including advection by a constant mean current is ...

Robert B. Scott

2003-01-01T23:59:59.000Z

396

Meteorological Patterns Associated with Maximum 3-Hour Average Concentrations Predicted by the CRSTER Model for a Tall Stack Source  

Science Conference Proceedings (OSTI)

Regional meteorological patterns associated with maximum 3-hour average concentrations predicted by the U.S. EPA CRSTER model for emissions from a tall stack were examined for a limited sample. Causes of predicted peaks were the movements of weak ...

Paul N. Derezotes

1984-11-01T23:59:59.000Z

397

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

Science Conference Proceedings (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

398

Foundation for a time interval access control model  

Science Conference Proceedings (OSTI)

A new model for representing temporal access control policies is introduced. In this model, temporal authorizations are represented by time attributes associated with both subjects and objects, and a “time interval access graph.” The time ...

Francis B. Afinidad; Timothy E. Levin; Cynthia E. Irvine; Thuy D. Nguyen

2005-09-01T23:59:59.000Z

399

Assessment of RANS-based turbulent combustion models for prediction of gas turbine emissions: turbulence model and reaction mechanism effects  

DOE Green Energy (OSTI)

The goal of this study is to assess current, commonly applied turbulence and combustion models with respect to their performance in gas-turbine combustion (GTC). Reynolds Averaged Navier-Stokes (RANS)-based turbulence and chemistry models are two primary factors influencing the uncertainty in predicting turbulent combustion characteristics, especially for GTC. RANS-based methods are the design tools of choice in the gas turbine industry due to the high computational costs of LES (Large Eddy Simulation). In this study, lean premixed combustion of methane was simulated using two different reduced mechanisms (ARM9 and ARM19) along with the Eddy Dissipation Concept (EDC) turbulent chemistry interaction model to calculate the CO and NOx emissions. The effect of turbulence models was assessed by considering two different models. Both of the models tested performed well in the prediction of temperature and major species profiles. Predicted values of NO emission profiles showed an average difference of ±5 ppm compared to experimental values. Computed intermediate species profiles showed large qualitative and quantitative errors when compared with the experimental data. These discrepancies, especially the intermediate species hydrogen, indicate the challenges these reduced mechanisms and turbulence models can present when modeling pollutant emissions from gas turbine combustors.

Nanduri, J.R.; Celik, I.B.; Strakey, P.A.; Parsons, D.R.

2007-10-01T23:59:59.000Z

400

Understanding, Modeling and Predicting Hidden Solder Joint Shape Using Active Thermography  

E-Print Network (OSTI)

Characterizing hidden solder joint shapes is essential for electronics reliability. Active thermography is a methodology to identify hidden defects inside an object by means of surface abnormal thermal response after applying a heat flux. This research focused on understanding, modeling, and predicting hidden solder joint shapes. An experimental model based on active thermography was used to understand how the solder joint shapes affect the surface thermal response (grand average cooling rate or GACR) of electronic multi cover PCB assemblies. Next, a numerical model simulated the active thermography technique, investigated technique limitations and extended technique applicability to characterize hidden solder joint shapes. Finally, a prediction model determined the optimum active thermography conditions to achieve an adequate hidden solder joint shape characterization. The experimental model determined that solder joint shape plays a higher role for visible than for hidden solder joints in the GACR; however, a MANOVA analysis proved that hidden solder joint shapes are significantly different when describe by the GACR. An artificial neural networks classifier proved that the distances between experimental solder joint shapes GACR must be larger than 0.12 to achieve 85% of accuracy classifying. The numerical model achieved minimum agreements of 95.27% and 86.64%, with the experimental temperatures and GACRs at the center of the PCB assembly top cover, respectively. The parametric analysis proved that solder joint shape discriminability is directly proportional to heat flux, but inversely proportional to covers number and heating time. In addition, the parametric analysis determined that active thermography is limited to five covers to discriminate among hidden solder joint shapes. A prediction model was developed based on the parametric numerical data to determine the appropriate amount of energy to discriminate among solder joint shapes for up to five covers. The degree of agreement between the prediction model and the experimental model was determined to be within a 90.6% for one and two covers. The prediction model is limited to only three solder joints, but these research principles can be applied to generate more realistic prediction models for large scale electronic assemblies like ball grid array assemblies having as much as 600 solder joints.

Giron Palomares, Jose

2012-05-01T23:59:59.000Z

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.


401

Accurate Electrical Battery Model Capable of Predicting Runtime and I-V Performance  

E-Print Network (OSTI)

Abstract—Low power dissipation and maximum battery runtime are crucial in portable electronics. With accurate and efficient circuit and battery models in hand, circuit designers can predict and optimize battery runtime and circuit performance. In this paper, an accurate, intuitive, and comprehensive electrical battery model is proposed and implemented in a Cadence environment. This model accounts for all dynamic characteristics of the battery, from nonlinear open-circuit voltage, current-, temperature-, cycle number-, and storage time-dependent capacity to transient response. A simplified model neglecting the effects of self-discharge, cycle number, and temperature, which are nonconsequential in low-power Li-ion-supplied applications, is validated with experimental data on NiMH and polymer Li-ion batteries. Less than 0.4 % runtime error and 30-mV maximum error voltage show that the proposed model predicts both the battery runtime and I–V performance accurately. The model can also be easily extended to other battery and power sourcing technologies. Index Terms—Batteries, cadence simulation, electrical model, I–V performance, nickel-metal hydride battery, polymer lithiumion battery, runtime prediction, test system. I.

Min Chen; Student Member; Gabriel A. Rincón-mora; Senior Member

2006-01-01T23:59:59.000Z

402

An Empirical Model for Predicting the Decay of Tropical Cyclone Wind Speed after Landfall over the Indian Region  

Science Conference Proceedings (OSTI)

An empirical model for predicting the maximum surface wind speed associated with a tropical cyclone after crossing the east coast of India is described. The model parameters are determined from the database of 19 recent cyclones. The model is ...

S. K. Roy Bhowmik; S. D. Kotal; S. R. Kalsi

2005-01-01T23:59:59.000Z

403

Decadal Predictability of the Atlantic Ocean in a Coupled GCM: Forecast Skill and Optimal Perturbations Using Linear Inverse Modeling  

Science Conference Proceedings (OSTI)

The decadal predictability of three-dimensional Atlantic Ocean anomalies is examined in a coupled global climate model [the third climate configuration of the Met Office Unified Model (HadCM3)] using a linear inverse modeling (LIM) approach. It ...

Ed Hawkins; Rowan Sutton

2009-07-01T23:59:59.000Z

404

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

405

Nitrogen Controls on Climate Model Evapotranspiration  

Science Conference Proceedings (OSTI)

Most evapotranspiration over land occurs through vegetation. The fraction of net radiation balanced by evapotranspiration depends on stomatal controls. Stomates transpire water for the leaf to assimilate carbon, depending on the canopy carbon ...

Robert E. Dickinson; Joseph A. Berry; Gordon B. Bonan; G. James Collatz; Christopher B. Field; Inez Y. Fung; Michael Goulden; William A. Hoffmann; Robert B. Jackson; Ranga Myneni; Piers J. Sellers; Muhammad Shaikh

2002-02-01T23:59:59.000Z

406

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

Science Conference Proceedings (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

407

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

NLE Websites -- All DOE Office Websites (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

408

Three-dimensional Fast Flux Test Facility plenum model turbulent flow prediction and data comparison  

Science Conference Proceedings (OSTI)

Two- and three-dimensional numerical simulations of turbulent flow in a scaled Fast Flux Test Facility (FFTF) upper plenum model were performed using the TEMPEST hydrothermal code. A standard k-element of model was used to describe turbulence through an effective viscosity. Comparisons with previously reported mean velocity and turbulence field data measured in the plenum model and two-dimensional numerical simulations using the TEACH code were made. Predicted horizontal and vertical mean velocities and turbulent kinetic energy are shown to be in good agreement with available experimental data when inlet conditions of the dissipation of turbulent kinetic energy are appropriately prescribed. The three-dimensional quarter-symmetry simulation predicts the turbulent kinetic energy field significantly better than the two-dimensional centerplane simulations. These results lead to conclusions concerning deficiencies in the experimental data and the turbulence model.

Eyler, L.L.; Sawdye, R.W.

1981-01-01T23:59:59.000Z

409

Chapter 5 – Modeling Congestion Control Algorithms  

Science Conference Proceedings (OSTI)

... that standard slow start is replaced by limited ... In our model, estimated throughput is updated every UH ... in all graphs is denominated in 100 ms units. ...

2012-09-11T23:59:59.000Z

410

Postprocessing Model-Predicted Rainfall Fields in the Spectral Domain Using Phase Information from Radar Observations  

Science Conference Proceedings (OSTI)

In an attempt to combine the short-term skill of radar nowcasting and the long-term skill of numerical models, successive 15-min rainfall accumulations obtained from the U.S. national radar composites and predicted by the Weather Research and ...

Basivi Radhakrishna; Isztar Zawadzki; Frédéric Fabry

2013-04-01T23:59:59.000Z

411

Development of a linear predictive model for carbon dioxide sequestration in deep saline carbonate aquifers  

Science Conference Proceedings (OSTI)

CO"2 injection into deep saline aquifers is a preferred method for mitigating CO"2 emission. Although deep saline aquifers are found in many sedimentary basins and provide very large storage capacities, several numerical simulations are needed before ... Keywords: CO2 sequestration, Deep saline carbonate aquifer, Latin hypercube space filling design, Predictive model

Sultan Anbar; Serhat Akin

2011-11-01T23:59:59.000Z

412

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

E-Print Network (OSTI)

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

413

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

E-Print Network (OSTI)

on the type of energy harvesting technology, ECM1 can be either DC/DC or AC/DC converter. ECM2 is usually a DC/DCAccurate Modeling and Prediction of Energy Availability in Energy Harvesting Real-Time Embedded}@binghamton.edu Abstract -- Energy availability is the primary subject that drives the research innovations in energy

Qiu, Qinru

414

Prediction of spontaneous heating susceptibility of Indian coals using fuzzy logic and artificial neural network models  

Science Conference Proceedings (OSTI)

Coal mine fires due to spontaneous heating are a major concern worldwide. Most of these fires could be averted if suitable preventive measures are taken. Since the spontaneous heating potential of all types of coals are not the same, its accurate prediction ... Keywords: Artificial neural network, Coal, Crossing point temperature, Fuzzy expert system, Spontaneous heating, Sugeno model

H. B. Sahu; S. Padhee; S. S. Mahapatra

2011-03-01T23:59:59.000Z

415

Enhancing product performance in machining processes: statistical analysis and development of predictive models  

Science Conference Proceedings (OSTI)

Process parameters, tool geometry and operating conditions considerably influence the quality and the functional performance, including the service-life, of machined components. Surface characteristics of the machined products such as hardness and roughness ... Keywords: lubrication systems, predictive models, statistical analysis, sustainable machining

G. Rotella, S. Rizzuti, D. Umbrello

2013-07-01T23:59:59.000Z

416

DDoS attack detection method based on linear prediction model  

Science Conference Proceedings (OSTI)

Distributed denial of service (DDoS) attack is one of the major threats to the current Internet. The IP Flow feature value (FFV) algorithm is proposed based on the essential features of DDoS attacks, such as the abrupt traffic change, flow dissymmetry, ... Keywords: ARMA model, attack features, distributed denial of service, linear prediction, network security

Jieren Cheng; Jianping Yin; Chengkun Wu; Boyun Zhang; Yun Liu

2009-09-01T23:59:59.000Z

417

A logit model for predicting wetland location using ASTER and GIS  

Science Conference Proceedings (OSTI)

Data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to develop a logistic regression model to predict the location of wetlands in the Coastal Plain of Virginia. We used the first five bands from two ASTER scenes ...

E. Pantaleoni; R. H. Wynne; J. M. Galbraith; J. B. Campbell

2009-01-01T23:59:59.000Z

418

Formant tracking linear prediction model using HMMs and Kalman filters for noisy speech processing  

Science Conference Proceedings (OSTI)

This paper presents a formant tracking linear prediction (LP) model for speech processing in noise. The main focus of this work is on the utilization of the correlation of the energy contours of speech, along the formant tracks, for improved formant ...

Qin Yan; Saeed Vaseghi; Esfandiar Zavarehei; Ben Milner; Jonathan Darch; Paul White; Ioannis Andrianakis

2007-07-01T23:59:59.000Z

419

A support vector regression based prediction model of affective responses for product form design  

Science Conference Proceedings (OSTI)

In this paper, a state-of-the-art machine learning approach known as support vector regression (SVR) is introduced to develop a model that predicts consumers' affective responses (CARs) for product form design. First, pairwise adjectives were used to ... Keywords: Genetic algorithm, Kansei engineering, Neural network, Product form design, Support vector regression

Chih-Chieh Yang; Meng-Dar Shieh

2010-11-01T23:59:59.000Z

420

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

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.


421

LINSOL: a model for predicting the optical performance of parabolic trough solar thermal systems  

DOE Green Energy (OSTI)

A detailed model has been developed to predict the optical performance of parabolic trough solar energy systems. The model is one to two orders of magnitude faster than previous, less complete calculations and makes tractable investigation of a wide range of design and application alternatives for trough systems. Representative results are presented that show the dependence of the trough optical performance on field orientation and site latitude.

Dellin, T.A.

1981-01-01T23:59:59.000Z

422

References on Modelling and Control of Compressor. . .  

E-Print Network (OSTI)

2> Journal of Propulsion and Power, 5(3):375--381, 1989. [Takata72] H. Takata and S. Nagano. Nonlinear analysis of rotating stall. Journal of engineering for power, 94:279--293, 1972. [Takata77] H. Takata and Y. Tsukuda. Stall margin improvement by casing treatment -- its mechanism and effectiveness. Journal of engineering for power, pages 121--133, January 1977. [Tondel96] J.P. Tøndel. Control of gas turbine under transients. Master's thesis, Norwegian University of Science and Technology, Dept. of Engineering Cybernetics, 1996. (In Norwegian). [Tournes97] C. Tournes and Y.B. Shtessel. Controlling the transient deviations from adaption lines in turbojet engines compressor fields via sliding mode. In Proceedings of the 1997 International Conference on Control Applications, pages 791--796, Hartford, CT, 1997. [Toyama77] K. Toyama, P.W. Runstadtler, Jr., and R.C.Dean, Jr. An experimental study of surge in centrifugal compressors.

Jan Tommy Gravdahl

1998-01-01T23:59:59.000Z

423

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

SciTech Connect

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

424

DES modelling and control vs. problem solving methods  

Science Conference Proceedings (OSTI)

Modelling and control of a kind of Discrete-Event Systems (DES) having a character of Flexible Manufacturing Systems (FMS) are examined by means of methods used in applied artificial intelligence. While assembly and/or disassembly ... Keywords: DES modelling, FMS control, PNs, Petri nets, agent-based systems, artificial intelligence, control agents, decision making, discrete event systems, flexible manufacturing systems, intelligent information, multi-agent systems, ontology, problem solving, reachability graphs, vehicle crossroads

Frantisek Capkovic

2007-04-01T23:59:59.000Z

425

MODEL PREDICTIVE CONTROL OF A MICROGRID WITH PLUG-IN VEHICLES: ERROR MODELING AND THE ROLE OF PREDICTION HORIZON  

E-Print Network (OSTI)

typically covers a small geographic area and contains both loads and localized energy generation and storage, and the con- trol is optimized for minimum generator fuel usage. A variety of horizons and levels in increased use of battery storage, this does not necessarily pro- duce significant decreases in fuel usage

Papalambros, Panos

426

PREDICTIVE GEOSPATIAL MODELING FOR ARCHAEOLOGICAL RESEARCH AND CONSERVATION: CASE STUDIES FROM THE GALISTEO BASIN, VERMONT AND CHACO CANYON.  

E-Print Network (OSTI)

??Geospatial modeling of ancient landscapes for predictive scientific research and hypothesis testing is an important emerging approach in contemporary archaeology. This doctoral dissertation is comprised… (more)

Dorshow, Wetherbee Bryan

2012-01-01T23:59:59.000Z

427

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

Science Conference Proceedings (OSTI)

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

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

2012-03-01T23:59:59.000Z

428

Positron Emission Tomography (PET) Evaluation After Initial Chemotherapy and Radiation Therapy Predicts Local Control in Rhabdomyosarcoma  

Science Conference Proceedings (OSTI)

Purpose: 18-fluorodeoxyglucose positron emission tomography (PET) is already an integral part of staging in rhabdomyosarcoma. We investigated whether primary-site treatment response characterized by serial PET imaging at specific time points can be correlated with local control. Patients and Methods: We retrospectively examined 94 patients with rhabdomyosarcoma who received initial chemotherapy 15 weeks (median) before radiotherapy and underwent baseline, preradiation, and postradiation PET. Baseline PET standardized uptake values (SUVmax) and the presence or absence of abnormal uptake (termed PET-positive or PET-negative) both before and after radiation were examined for the primary site. Local relapse-free survival (LRFS) was calculated according to baseline SUVmax, PET-positive status, and PET-negative status by the Kaplan-Meier method, and comparisons were tested with the log-rank test. Results: The median patient age was 11 years. With 3-year median follow-up, LRFS was improved among postradiation PET-negative vs PET-positive patients: 94% vs 75%, P=.02. By contrast, on baseline PET, LRFS was not significantly different for primary-site SUVmax {7 (median), although the findings suggested a trend toward improved LRFS: 96% for SUVmax {7, P=.08. Preradiation PET also suggested a statistically insignificant trend toward improved LRFS for PET-negative (97%) vs PET-positive (81%) patients (P=.06). Conclusion: Negative postradiation PET predicted improved LRFS. Notably, 77% of patients with persistent postradiation uptake did not experience local failure, suggesting that these patients could be closely followed up rather than immediately referred for intervention. Negative baseline and preradiation PET findings suggested statistically insignificant trends toward improved LRFS. Additional study may further understanding of relationships between PET findings at these time points and outcome in rhabdomyosarcoma.

Dharmarajan, Kavita V., E-mail: dharmark@mskcc.org [Departments of Radiation Oncology, Pediatric Oncology, and Nuclear Medicine, Memorial Sloan-Kettering, New York, New York (United States); Wexler, Leonard H.; Gavane, Somali; Fox, Josef J.; Schoder, Heiko; Tom, Ashlyn K.; Price, Alison N.; Meyers, Paul A.; Wolden, Suzanne L. [Departments of Radiation Oncology, Pediatric Oncology, and Nuclear Medicine, Memorial Sloan-Kettering, New York, New York (United States)] [Departments of Radiation Oncology, Pediatric Oncology, and Nuclear Medicine, Memorial Sloan-Kettering, New York, New York (United States)

2012-11-15T23:59:59.000Z

429

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

430

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

SciTech Connect

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

431

Brief Min-max predictive control techniques for a linear state-space system with a bounded set of input matrices  

Science Conference Proceedings (OSTI)

Min-max predictive control of a linear state-space system with a bounded set of input matrices is studied based on a quadratic performance criterion. Systems with stable and integrating dynamics as well as time-varying and time-invariant uncertainties ... Keywords: Constraint satisfaction, Minimax techniques, Predictive control, Robust control

Jay H. Lee; Brian L. Cooley

2000-03-01T23:59:59.000Z

432

Handbook for personal computer versions enhanced oil recovery predictive models: Supporting technology for enhanced oil recovery  

SciTech Connect

The personal computer (PC) programs described in this handbook were adapted from the Tertiary Oil Recovery Information System (TORIS) enhanced oil recovery (EOR) predictive models. The models, both those developed for the Department of Energy and those developed for the National Petroleum Council (NPC), were designed by Scientific Software-Intercomp and were used in the 1984 NPC study on the national potential for enhanced oil recovery. The Department of Energy, Bartlesville Project Office, supported the NPC study and has maintained the models since the study was completed. 10 refs.

Allison, E.; Waldrop, R.; Ray, R.M.

1988-02-01T23:59:59.000Z

433

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

Science Conference Proceedings (OSTI)

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

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

2003-08-08T23:59:59.000Z

434

Controlled Nonlinear Stochastic Delay Equations: Part I: Modeling and Approximations  

SciTech Connect

This two-part paper deals with 'foundational' issues that have not been previously considered in the modeling and numerical optimization of nonlinear stochastic delay systems. There are new classes of models, such as those with nonlinear functions of several controls (such as products), each with is own delay, controlled random Poisson measure driving terms, admissions control with delayed retrials, and others. There are two basic and interconnected themes for these models. The first, dealt with in this part, concerns the definition of admissible control. The classical definition of an admissible control as a nonanticipative relaxed control is inadequate for these models and needs to be extended. This is needed for the convergence proofs of numerical approximations for optimal controls as well as to have a well-defined model. It is shown that the new classes of admissible controls do not enlarge the range of the value functions, is closed (together with the associated paths) under weak convergence, and is approximatable by ordinary controls. The second theme, dealt with in Part II, concerns transportation equation representations, and their role in the development of numerical algorithms with much reduced memory and computational requirements.

Kushner, Harold J., E-mail: hjk@dam.brown.edu [Brown University, Applied Math (United States)

2012-08-15T23:59:59.000Z

435

Reference Model for Control and Automation Systems in Electrical Power |  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

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

436

Development of a Multicomponent Prediction Model for Acute Esophagitis in Lung Cancer Patients Receiving Chemoradiotherapy  

SciTech Connect

Purpose: To construct a model for the prediction of acute esophagitis in lung cancer patients receiving chemoradiotherapy by combining clinical data, treatment parameters, and genotyping profile. Patients and Methods: Data were available for 273 lung cancer patients treated with curative chemoradiotherapy. Clinical data included gender, age, World Health Organization performance score, nicotine use, diabetes, chronic disease, tumor type, tumor stage, lymph node stage, tumor location, and medical center. Treatment parameters included chemotherapy, surgery, radiotherapy technique, tumor dose, mean fractionation size, mean and maximal esophageal dose, and overall treatment time. A total of 332 genetic polymorphisms were considered in 112 candidate genes. The predicting model was achieved by lasso logistic regression for predictor selection, followed by classic logistic regression for unbiased estimation of the coefficients. Performance of the model was expressed as the area under the curve of the receiver operating characteristic and as the false-negative rate in the optimal point on the receiver operating characteristic curve. Results: A total of 110 patients (40%) developed acute esophagitis Grade {>=}2 (Common Terminology Criteria for Adverse Events v3.0). The final model contained chemotherapy treatment, lymph node stage, mean esophageal dose, gender, overall treatment time, radiotherapy technique, rs2302535 (EGFR), rs16930129 (ENG), rs1131877 (TRAF3), and rs2230528 (ITGB2). The area under the curve was 0.87, and the false-negative rate was 16%. Conclusion: Prediction of acute esophagitis can be improved by combining clinical, treatment, and genetic factors. A multicomponent prediction model for acute esophagitis with a sensitivity of 84% was constructed with two clinical parameters, four treatment parameters, and four genetic polymorphisms.

De Ruyck, Kim, E-mail: kim.deruyck@UGent.be [Department of Basic Medical Sciences, Ghent University, Ghent (Belgium); Sabbe, Nick [Department of Applied Mathematics, Biometrics and Process Control, Ghent University, Ghent (Belgium); Oberije, Cary [Department of Radiation Oncology (MAASTRO Clinic), Research Institute of Growth and Development, Maastricht University Medical Center, Maastricht (Netherlands); Vandecasteele, Katrien [Department of Radiation Oncology, Ghent University Hospital, Ghent (Belgium); Thas, Olivier [Department of Applied Mathematics, Biometrics and Process Control, Ghent University, Ghent (Belgium); De Ruysscher, Dirk; Lambin, Phillipe [Department of Radiation Oncology (MAASTRO Clinic), Research Institute of Growth and Development, Maastricht University Medical Center, Maastricht (Netherlands); Van Meerbeeck, Jan [Department of Respiratory Medicine, Ghent University Hospital, Ghent (Belgium); De Neve, Wilfried [Department of Radiation Oncology, Ghent University Hospital, Ghent (Belgium); Thierens, Hubert [Department of Basic Medical Sciences, Ghent University, Ghent (Belgium)

2011-10-01T23:59:59.000Z

437

An Analysis of the Accuracy of 120-h Predictions by the National Meteorological Center's Medium-Range Forecast Model  

Science Conference Proceedings (OSTI)

An assessment was made of the 120-h predictions by the medium range forecast (MRF) run of the National Meteorological Center's (NMC's) global spectral model. The ability of the model to forecast surface cyclones and anticyclones was evaluated and ...

Mary A. Bedrick; Anthony J. Cristaldi III; Stephen J. Colucci; Daniel S. Wilks

1994-03-01T23:59:59.000Z

438

A Storm Surge Prediction Model for the Northern Bay of Bengal with Application to the Cyclone Disaster in April 1991  

Science Conference Proceedings (OSTI)

A numerical model for simulating and predicting tides and storm surges in regions that include areas of open sea combined with estuarine channels and intertidal banks is described. The model makes use of modified depth-averaged equations with a ...

Roger A. Flather

1994-01-01T23:59:59.000Z

439

Predictability of Linear Coupled Systems. Part II: An Application to a Simple Model of Tropical Atlantic Variability  

Science Conference Proceedings (OSTI)

A predictability analysis developed within a general framework of linear stochastic dynamics in a companion paper is applied to a simple coupled climate model of tropical Atlantic variability (TAV). The simple model extends the univariate ...

Ping Chang; R. Saravanan; Faming Wang; Link Ji

2004-04-01T23:59:59.000Z

440

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.

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

Medium Range Prediction by a GFDL Global Spectral Model: Results for Three Winter Cases and Sensitivity to Dissipation  

Science Conference Proceedings (OSTI)

A preliminary evaluation is made of the medium range predictive capability of a GFDL global spectral model of the atmosphere, based upon three winter blocking cases. Analogous forecasts by a GFDL global grid point model provide a background ...

Charles T. Gordon; William P. Stern

1984-02-01T23:59:59.000Z

442

Quark-mass dependence of the three-flavor QCD phase diagram at zero and imaginary chemical potential: Model prediction  

Science Conference Proceedings (OSTI)

We draw the three-flavor phase diagram as a function of light- and strange-quark masses for both zero and imaginary quark-number chemical potential, using the Polyakov-loop extended Nambu-Jona-Lasinio model with an effective four-quark vertex depending on the Polyakov loop. The model prediction is qualitatively consistent with 2+1 flavor lattice QCD prediction at zero chemical potential and with degenerate three-flavor lattice QCD prediction at imaginary chemical potential.

Sasaki, Takahiro; Sakai, Yuji; Yahiro, Masanobu [Department of Physics, Graduate School of Sciences, Kyushu University, Fukuoka 812-8581 (Japan); Kouno, Hiroaki [Department of Physics, Saga University, Saga 840-8502 (Japan)

2011-11-01T23:59:59.000Z

443

Distribution Efficiency: Modeling, Volt-Var Control, and Economics  

Science Conference Proceedings (OSTI)

As utilities strive to better utilize their distribution system assets and improve energy efficiency, improved distribution modeling and better economic models can help quantify economic gains. In order to improve efficiency modeling and economic planning, research efforts in this report have concentrated on the following tasks: distribution modeling for efficiency studies, volt-var control, and development of a framework to evaluate the economic benefit of reductions in average and peak energy reduction...

2010-12-31T23:59:59.000Z

444

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

DOE Green Energy (OSTI)

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

Cairelli, J.E.; Geng, S.M. [National Aeronautics and Space Administration, Cleveland, OH (United States). Lewis Research Center; Skupinski, R.C. [Sverdrup Technology, Inc., Cleveland, OH (United States). NASA Lewis Research Center Group

1994-09-01T23:59:59.000Z

445

Forest dynamics at regional scales: predictive models constrained with inventory data  

E-Print Network (OSTI)

infrequent but have extreme impacts. Models of the relationship between wind and fire events and vegetation have revealed impacts on species composition and stand biomass (Hickler et al., 2004), size structure (Liedloff and Cook, 2007; Uriarte et al., 2009... limitation, that resource use and supply are equal, birth and death rates are equal and that stems' allometry and demographic rates are as defined above, allowing predictions such as stand size distribution, canopy structure and resource use (West et al...

Lines, Emily

2012-06-12T23:59:59.000Z

446

MODELING CHEMICAL SPECIATION AND RELEASE FROM CEMENT ...  

System definition Input file (text) ... control? Water treatment Model with percolation ... MULTIELEMENT PREDICTIVE MODELLING OF pH

447

Numerical simulations and predictive models of undrained penetration in soft soils  

E-Print Network (OSTI)

There are two aspects in this study: cylinder penetrations and XBP (Expendable Bottom Penetrometer) interpretations. The cylinder studies firstly investigate the relationship between the soil resisting force and penetration depth by a series of rateindependent finite element analyses of pre-embedded penetration depths, and validate the results by upper and lower bound solutions from classical plasticity theory. Furthermore, strain rate effects are modeled by finite element simulations within a framework of rate-dependent plasticity. With all forces acting on the cylinder estimated, penetration depths are predicted from simple equations of motion for a single particle. Comparisons to experimental results show reasonable agreement between model predictions and measurements. The XBP studies follow the same methodology in investigating the soil shearing resistance as a function of penetration depth and velocity by finite element analyses. With the measurements of time decelerations during penetration of the XBP, sediment shear strength profile is inferred from a single particle kinetic model. The predictions compare favorably with experimental measurements by vane shear tests.

Shi, Han

2005-08-01T23:59:59.000Z

448

Collision-induced galaxy formation: semi-analytical model and multi-wavelength predictions  

E-Print Network (OSTI)

A semi-analytic model is proposed that couples the Press-Schechter formalism for the number of galaxies with a prescription for galaxy-galaxy interactions that enables to follow the evolution of galaxy morphologies along the Hubble sequence. Within this framework, we calculate the chemo-spectrophotometric evolution of galaxies to obtain spectral energy distributions. We find that such an approach is very successful in reproducing the statistical properties of galaxies as well as their time evolution. We are able to make predictions as a function of galaxy type: for clarity, we restrict ourselves to two categories of galaxies: early and late types that are identified with ellipticals and disks. In our model, irregulars are simply an early stage of galaxy formation. In particular, we obtain good matches for the galaxy counts and redshift distributions of sources from UV to submm wavelengths. We also reproduce the observed cosmic star formation history and the diffuse background radiation, and make predictions as to the epoch and wavelength at which the dust-shrouded star formation of spheroids begins to dominate over the star formation that occurs more quiescently in disks. A new prediction of our model is a rise in the FIR luminosity density with increasing redshift, peaking at about $z\\sim 3$, and with a ratio to the local luminosity density $\\rho_{L,\

Christophe Balland; Julien E. G. Devriendt; Joe Silk

2002-10-01T23:59:59.000Z

449

Computational model design and performance estimation in registration brake control  

Science Conference Proceedings (OSTI)

Electric motorcycles are applicable to both toys and real motorcycles, and also is a reference for constructing larger electrical vehicles. A design computational model of regenerative braking control of electric motorcycles and an experimental identification ...

P. S. Pa; S. C. Chang

2009-06-01T23:59:59.000Z

450

Modeling, Analysis, and Control of Demand Response Resources  

NLE Websites -- All DOE Office Websites (Extended Search)

Modeling, Analysis, and Control of Demand Response Resources Speaker(s): Johanna Mathieu Date: April 27, 2012 - 12:00pm Location: 90-3122 Seminar HostPoint of Contact: Sila...

451

A unified fuzzy model-based framework for modeling and control of complex systems: from flying vehicle control to brain-machine cooperative control  

Science Conference Proceedings (OSTI)

The invited lecture in 2012 IEEE World Congress on Computational Intelligence (WCCI 2012) presents an overview of a unified fuzzy model-based framework for modeling and control of complex systems. A number of practical applications, ranging from flying ...

Kazuo Tanaka

2012-06-01T23:59:59.000Z

452

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

SciTech Connect

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

Bittle, Joshua A. [Texas A& M University] [Texas A& M University; Gao, Zhiming [ORNL] [ORNL; Jacobs, Timothy J. [Texas A& M University] [Texas A& M University

2013-01-01T23:59:59.000Z

453

Use of Linear Predictive Control for a Solar Electric Generating System  

E-Print Network (OSTI)

that use parabolic troughs in order to produce electricity from sunlight5 . The parabolic troughs are long, the temperature of the HTF leaving the parabolic trough collector is controlled by a skilled operator. He. Automatic control of the HTF in a parabolic trough collector through proportional control has been attempted

Wisconsin at Madison, University of

454

Neural Predictive Controller Based Diesel Injection Management System for Emission Minimisation  

Science Conference Proceedings (OSTI)

Rapid growth in production of automobiles has increased emissions. Automotive control engineers use innovative control techniques to meet the upcoming emission standards. This paper proposes a novel method of employing artificial neural network ANN based ... Keywords: Artificial Neural Network ANN, Common Rail System CRS, Control System Simulation, Emission Minimisation, Fuel Injection System, Green System Design, Green Technology

C. N. Arunaa; S. Babu Devasenapati; K. I. Ramachandran; K. Vishnuprasad; C. Surendra

2011-07-01T23:59:59.000Z

455

Progress on building a predictive model of indoor concentrations of outdoor PM-2.5 in homes  

Science Conference Proceedings (OSTI)

The goal of this project is to develop a physically-based, semi-empirical model that describes the concentration of indoor concentration of PM-2.5 (particle mass that is less than 2.5 microns in diameter) and its sulfate, nitrate, organic and black carbon constituents, derived from outdoor sources. We have established the methodology and experimental plan for building the model. Experimental measurements in residential style houses, in Richmond and Fresno, California, are being conducted to provide parameters for and evaluation of this model. The model will be used to improve estimates of human exposures to PM-2.5 of outdoor origin. The objectives of this study are to perform measurement and modeling tasks that produce a tested, semi-mechanistic description of chemical species-specific and residential PM-2.5 arising from the combination of outdoor PM and gas phase sources (HNO{sub 3} and NH{sub 3}), and indoor gas phase (e.g. NH{sub 3}) sources. We specifically address how indoor PM is affected by differences between indoor and outdoor temperature and relative humidity. In addition, we are interested in losses of particles within the building and as they migrate through the building shell. The resulting model will be general enough to predict probability distributions for species-specific indoor concentrations of PM-2.5 based on outdoor PM, and gas phase species concentrations, meteorological conditions, building construction characteristics, and HVAC operating conditions. Controlled intensive experiments were conducted at a suburban research house located in Clovis, California. The experiments utilized a large suite of instruments including conventional aerosol, meteorological and house characterization devices. In addition, two new instruments were developed providing high time resolution for the important particulate species of nitrate, sulfate, and carbon as well as important gaseous species including ammonia and nitric acid. Important initial observations include the result that, with rare exceptions, there is virtually no nitrate found inside the house. This nitrate appears to dissociate into ammonia and nitric acid with the nitric acid quickly depositing out. Initial model development has included work on characterizing penetration and deposition rates, the dynamic behavior of the indoor/outdoor ratio, and predicting infiltration rates. Results from the exploration of the indoor/outdoor ratio show that the traditional assumption of steady state conditions does not hold in general. Many values of the indoor/outdoor ratio exist for any single value of the infiltration rate. Successful prediction of the infiltration rate from measured driving variables is important for extending the results from the Clovis house to the larger housing stock.

Lunden, Melissa M.; Thatcher, Tracy L.; Littlejohn, David; Fischer, Marc L.; Kirchstetter, Thomas W.; Brown, Nancy J.; Hering, Susanne

2001-09-01T23:59:59.000Z

456

A comparison of cloud microphysical quantities with forecasts from cloud prediction models  

SciTech Connect

Numerical weather prediction models (ECMWF, NCEP) are evaluated using ARM observational data collected at the Southern Great Plains (SGP) site. Cloud forecasts generated by the models are compared with cloud microphysical quantities, retrieved using a variety of parameterizations. Information gained from this comparison will be utilized during the FASTER project, as models are evaluated for their ability to reproduce fast physical processes detected in the observations. Here the model performance is quantified against the observations through a statistical analysis. Observations from remote sensing instruments (radar, lidar, radiometer and radiosonde) are used to derive the cloud microphysical quantities: ice water content, liquid water content, ice effective radius and liquid effective radius. Unfortunately, discrepancies in the derived quantities arise when different retrieval schemes are applied to the observations. The uncertainty inherent in retrieving the microphysical quantities using various retrievals is estimated from the range of output microphysical values. ARM microphysical retrieval schemes (Microbase, Mace) are examined along with the CloudNet retrieval processing of data from the ARM sites for this purpose. Through the interfacing of CloudNet and “ARM” processing schemes an ARMNET product is produced and employed as accepted observations in the assessment of cloud model predictions.

Dunn, M.; Jensen, M.; Hogan, R.; O’Connor, E.; Huang, D.

2010-03-15T23:59:59.000Z

457

A stochastic control model for optimal timing of climate policies  

Science Conference Proceedings (OSTI)

A stochastic control model is proposed as a paradigm for the design of optimal timing of greenhouse gas (GHG) emission abatement. The resolution of uncertainty concerning climate sensitivity and the technological breakthrough providing access to a carbon-free ... Keywords: Climate policies, Environmental hedging strategies, Piecewise deterministic Markov process, Stochastic control

O. Bahn; A. Haurie; R. Malhamé

2008-06-01T23:59:59.000Z

458

Modelling and Control of an Inverted Pendulum Turbine  

E-Print Network (OSTI)

. In this project the feasibility of a new kind of wind turbine is studied. This thesis deals with the achievement of getting a proper mathematical model of a new kind of wind turbine, called the inverted pendulum turbine is inherently unstable system. In order to control this wind turbine an optimal control has been investigated

459

A Method for Adaptive Habit Prediction in Bulk Microphysical Models. Part II: Parcel Model Corroboration  

Science Conference Proceedings (OSTI)

It is common for cloud microphysical models to use a single axis length to characterize ice crystals. These methods use either the diameter of an equivalent sphere or mass–size equations in conjunction with the capacitance model to close the ...

Jerry Y. Harrington; Kara Sulia; Hugh Morrison

2013-02-01T23:59:59.000Z

460

A Comparison of Isoconversional and Model-Fitting Approaches to Kinetic Parameter Estimation and Application Predictions  

SciTech Connect

Chemical kinetic modeling has been used for many years in process optimization, estimating real-time material performance, and lifetime prediction. Chemists have tended towards developing detailed mechanistic models, while engineers have tended towards global or lumped models. Many, if not most, applications use global models by necessity, since it is impractical or impossible to develop a rigorous mechanistic model. Model fitting acquired a bad name in the thermal analysis community after that community realized a decade after other disciplines that deriving kinetic parameters for an assumed model from a single heating rate produced unreliable and sometimes nonsensical results. In its place, advanced isoconversional methods (1), which have their roots in the Friedman (2) and Ozawa-Flynn-Wall (3) methods of the 1960s, have become increasingly popular. In fact, as pointed out by the ICTAC kinetics project in 2000 (4), valid kinetic parameters can be derived by both isoconversional and model fitting methods as long as a diverse set of thermal histories are used to derive the kinetic parameters. The current paper extends the understanding from that project to give a better appreciation of the strengths and weaknesses of isoconversional and model-fitting approaches. Examples are given from a variety of sources, including the former and current ICTAC round-robin exercises, data sets for materials of interest, and simulated data sets.

Burnham, A K

2006-05-17T23:59:59.000Z

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461

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

SciTech Connect

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

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

2010-07-01T23:59:59.000Z

462

A Study of Impacts of Coupled Model Initial Shocks and State–Parameter Optimization on Climate Predictions Using a Simple Pycnocline Prediction Model  

Science Conference Proceedings (OSTI)

A skillful decadal prediction that foretells varying regional climate conditions over seasonal–interannual to multidecadal time scales is of societal significance. However, predictions initialized from the climate-observing system tend to drift ...

S. Zhang

2011-12-01T23:59:59.000Z

463

Temperature decoupling control of double-level air flow field dynamic vacuum system based on neural network and prediction principle  

Science Conference Proceedings (OSTI)

Double-level air flow field dynamic vacuum (DAFDV) system is a strong coupling, large time-delay, and nonlinear multi-input-multi-output system. Decoupling and overcoming the impact of time-delay are two keys to obtain rapid, accurate and independent ... Keywords: ASSAVP, BP, DAFDV, Decoupling control, Double-level air flow field, EBTC, HX, IPSO, MIMO, Neural networks, OIF, PID, Particle swarm optimization, Prediction, RBF, SISO, TITO, WBTC

Li Jinyang; Meng Xiaofeng

2013-04-01T23:59:59.000Z

464

The WAM Model—A Third Generation Ocean Wave Prediction Model  

Science Conference Proceedings (OSTI)

A third generation wave model is presented that integrates the basic transport equation describing the evolution of a two-dimensional ocean wave spectrum without additional ad hoe assumptions regarding the spectral shape. The three source ...

The Wamdi Group

1988-12-01T23:59:59.000Z

465

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

Science Conference Proceedings (OSTI)

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

Watney, W.L.

1994-12-01T23:59:59.000Z

466

ADVANCED TECHNOLOGY FOR PREDICTING THE FLUID FLOW ATTRIBUTES OF NATURALLY FRACTURED RESERVOIRS FROM QUANTITATIVE GEOLOGIC DATA AND MODELING  

Science Conference Proceedings (OSTI)

This report summarizes the work carried out during the period of September 29, 2000 to January 15, 2004 under DOE Research Contract No. DE-FC26-00BC15308. High temperatures and reactive fluids in sedimentary basins dictate that interplay and feedback between mechanical and geochemical processes significantly influence evolving rock and fracture properties. Not only does diagenetic mineralization fill in once open fractures either partially or completely, it modifies the rock mechanics properties that can control the mechanical aperture of natural fractures. In this study, we have evolved an integrated methodology of fractured reservoir characterization and we have demonstrated how it can be incorporated into fluid flow simulation. The research encompassed a wide range of work from geological characterization methods to rock mechanics analysis to reservoir simulation. With regard to the characterization of mineral infilling of natural fractures, the strong interplay between diagenetic and mechanical processes is documented and shown to be of vital importance to the behavior of many types of fractured reservoirs. Although most recent literature emphasizes Earth stress orientation, cementation in fractures is likely a critically important control on porosity, fluid flow attributes, and even sensitivity to effective stress changes. The diagenetic processes of dissolution and partial cementation are key controls on the creation and distribution of open natural fractures within hydrocarbon reservoirs. The continuity of fracture-porosity is fundamental to how fractures conduct fluids. In this study, we have made a number of important discoveries regarding fundamental properties of fractures, in particular related to the prevalence of kinematically significant structures (crack-seal texture) within otherwise porous, opening-mode fractures, and the presence of an aperture size threshold below which fractures are completely filled and above which porosity is preserved. These observations can be linked to models of quartz cementation. Significant progress has been made as well in theoretical fracture mechanics and geomechanical modeling, allowing prediction of spatial distributions of fractures that mimic patterns observed in nature. Geomechanical modeling shows the spatial arrangement of opening mode fractures (joints and veins) is controlled by the subcritical fracture index of the material. In particular, we have been able to identify mechanisms that control the clustering of fractures in slightly deformed rocks. Fracture mechanics testing of a wide range of clastic rocks shows that the subcritical index is sensitive to diagenetic factors. We show geomechanical simulations of fracture aperture development can be linked to diagenetic models, modifying fracture porosity as fractures grow, and affect the dynamics of fracture propagation. Fluid flow simulation of representative fracture pattern realizations shows how integrated modeling can give new insight into permeability assessment in the subsurface. Using realistic, geomechanically generated fracture patterns, we propose a methodology for permeability estimation in nonpercolating networks.

Jon E. Olson; Larry W. Lake; Steve E. Laubach

2004-11-01T23:59:59.000Z

467

Modeling, Analysis, and Control of Demand Response Resources  

NLE Websites -- All DOE Office Websites (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

468

Experimental measurements and modeling prediction of flammability limits of binary hydrocarbon mixtures  

E-Print Network (OSTI)

Flammability limit is a significant safety issue for industrial processes. A certain amount of flammability limit data for pure hydrocarbons are available in the literature, but for industrial applications, there are conditions including different combinations of fuels at standard and non-standard conditions, in which the flammability limit data are scarce and sometimes unavailable. This research is two-fold: (i) Performing experimental measurements to estimate the lower flammability limits and upper flammability limits of binary hydrocarbon mixtures, conducting experimental data numerical analysis to quantitatively characterize the flammability limits of these mixtures with parameters, such as component compositions, flammability properties of pure hydrocarbons, and thermo-kinetic values; (ii) Estimating flammability limits of binary hydrocarbon mixtures through CFT-V modeling prediction (calculated flame temperature at constant volume), which is based on a comprehensive consideration of energy conservation. For the experimental part, thermal detection was used in this experiment. The experimental results indicate that the experimental results fit Le Chatelier’s Law within experimental uncertainty at the lower flammability limit condition. At the upper flammability limit condition, Le Chatelier’s Law roughly fits the saturated hydrocarbon mixture data, while with mixtures that contain one or more unsaturated components, a modification of Le Chatelier’s is preferred to fit the experimental data. The easy and efficient way to modify Le Chatelier’s Law is to power the molar percentage concentrations of hydrocarbon components. For modeling prediction part, the CFT-V modeling is an extended modification of CAFT modeling at constant volume and is significantly related to the reaction vessel configuration. This modeling prediction is consistent with experimental observation and Le Chatelier’s Law at the concentrations of lower flammability limits. When the quenching effect is negligible, this model can be simplified by ignoring heat loss from the reaction vessel to the external surroundings. Specifically, when the total mole changes in chemical reactions can be neglected and the quenching effect is small, CFTV modeling can be simplified to CAFT modeling.

Zhao, Fuman

2008-05-01T23:59:59.000Z

469

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

SciTech Connect

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

470

Modeling, design, and life performance prediction for energy production from geothermal reservoirs. Final report  

DOE Green Energy (OSTI)

System modeling supports the design and long-term, commercially successful operation of geothermal reservoirs. Modeling guides in the placement of the injection and production wells, in the stimulation of the reservoir, and in the operational strategies used to ensure continuing production. Without an understanding of the reservoir, it is possible to harm the reservoir by inappropriate operation (especially break-through of cold injection fluid) and the desired profitable lifetimes will not be reached. In this project the authors have continued to develop models for predicting the life of geothermal reservoirs. One of the goals has been to maintain and transfer existing Hot Dry Rock two-dimensional fractured reservoir analysis capability to the geothermal industry and to begin the extension of the analysis concepts to three dimensions. Primary focus has been on interaction with industry, maintenance of Geocrack2D, and development of the Geocrack3D model. It is important to emphasize that the modeling is complementary to current industry modeling, in that they focus on flow in fractured rock and on the coupled effect of thermal cooling. In the following sections the authors document activities as part of this research project: industry interaction; national and international collaboration; and model development.

Swenson, D.

1998-01-01T23:59:59.000Z

471

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

DOE Green Energy (OSTI)

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

Strobel, Calvin J.

1993-01-28T23:59:59.000Z

472

Nonlinear model identification and adaptive control of CO2 sequestration process in saline aquifers using artificial neural networks  

Science Conference Proceedings (OSTI)

In recent years, storage of carbon dioxide (CO"2) in saline aquifers has gained intensive research interest. The implementation, however, requires further research studies to ensure it is safe and secure operation. The primary objective is to secure ... Keywords: Carbon dioxide sequestration, Extended Kalman filter (EKF), GAP-RBF neural network, Nonlinear model predictive control (NMPC), System identification, Unscented Kalman filter (UKF)

Karim Salahshoor; Mohammad Hasan Hajisalehi; Morteza Haghighat Sefat

2012-11-01T23:59:59.000Z

473

Integrated Experimental and Modeling Studies to Predict the Impact Response of Explosives and Propellants  

DOE Green Energy (OSTI)

Understanding and predicting the impact response of explosives and propellants remains a challenging area in the energetic materials field. Efforts are underway at LLNL (and other laboratories) to apply modern diagnostic tools and computational analysis to move beyond the current level of imprecise approximations towards a predictive approach more closely based on fundamental understanding of the relevant mechanisms. In this paper we will discuss a set of underlying mechanisms that govern the impact response of explosives and propellants: (a) mechanical insult (impact) leading to material damage and/or direct ignition; (b) ignition leading to flame spreading; (c) combustion being driven by flame spreading, perhaps in damaged materials; (d) combustion causing further material damage; (e) combustion leading to pressure build-up or relief; (f) pressure changes driving the rates of combustion and flame spread; (g) pressure buildup leading to structural response and damage, which causes many of the physical hazards. We will briefly discuss our approach to modeling up these mechanistic steps using ALE 3D, the LLNL hydrodynamic code with fully coupled chemistry, heat flow, mass transfer, and slow mechanical motion as well as hydrodynamic processes. We will identify the necessary material properties needed for our models, and will discuss our experimental efforts to characterize these properties and the overall mechanistic steps, in order to develop and parameterize the models in ALE 3D and to develop a qualitative understanding of impact response.

Maienschein, J L; Nichols III, A L; Reaugh, J E; McClelland, M E; Hsu, P C

2005-05-25T23:59:59.000Z

474

Predicting essential components of signal transduction networks: a dynamic model of guard cell abscisic acid signaling  

E-Print Network (OSTI)

Plants both lose water and take in carbon dioxide through microscopic stomatal pores, each of which is regulated by a surrounding pair of guard cells. During drought, the plant hormone abscisic acid (ABA) inhibits stomatal opening and promotes stomatal closure, thereby promoting water conservation. Here we synthesize experimental results into a consistent guard cell signal transduction network for ABA-induced stomatal closure, and develop a dynamic model of this process. Our model captures the regulation of more than forty identified network components, and accords well with previous experimental results at both the pathway and whole cell physiological level. Our analysis reveals the novel predictions that the disruption of membrane depolarizability, anion efflux, actin cytoskeleton reorganization, cytosolic pH increase, the phosphatidic acid pathway or of K+ efflux through slowly activating K+ channels at the plasma membrane lead to the strongest reduction in ABA responsiveness. Initial experimental analysis assessing ABA-induced stomatal closure in the presence of cytosolic pH clamp imposed by the weak acid butyrate is consistent with model prediction. Our method can be readily applied to other biological signaling networks to identify key regulatory components in systems where quantitative information is limited.

Song Li; Sarah M. Assmann; Reka Albert

2006-10-05T23:59:59.000Z

475

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

Science Conference Proceedings (OSTI)

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

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

2009-03-03T23:59:59.000Z

476

A predictive model for the temperature relaxation rate in dense plasmas  

DOE Green Energy (OSTI)

We present and validate a simple model for the electron-ion temperature relaxation rate in plasmas that applies over a wide range of plasma temperatures and densities, including weakly-coupled, non-degenerate as well as strongly-coupled, degenerate plasmas. Electron degeneracy and static correlation effects between electrons and ions are shown to play a cumulative role that, at low temperature, lead to relaxation rates a few times smaller than when these effects are neglected. We predict the evolution of the relaxation in dense hydrogen plasmas from the fully degenerate to the non-degenerate limit.

Daligault, Jerome [Los Alamos National Laboratory; Dimonte, Guy [Los Alamos National Laboratory

2008-01-01T23:59:59.000Z

477

Electrostatic precipitator V-I (ESPVI 4.0) and performance prediction model (for microcomputers). Model-Simulation  

SciTech Connect

The microcomputer program ESPVI 4.0 was developed to provide a user-friendly interface to an advanced model of electrostatic precipitation (ESP) performance. The program is capable of modeling standard ESP configurations as well as those that might be proposed for improved performance. It incorporates many of the latest developments in prediction of ESP performance, including electrical waveform effects, non-rapping reentrainment, and electrode misalignment. The program is organized by a series of menu screens with increasing levels of detail provided as the menus become more specific. The user`s manual provides the documentation needed to load the program from its disk, set up the computer configuration for optimal operation, and introduces the operation of the program. The user is expected to be familiar with the operation of an ESP and know the important factors that affect it. An example ESP is provided with the program to help with the manual`s exposition. It is taken from a report describing measurement of the unit`s performance and so provides a direct comparison of the models predictions.

NONE

1996-02-01T23:59:59.000Z

478

Intelligent GPS-based predictive engine control for a motor vehicle  

Science Conference Proceedings (OSTI)

An intelligent Global Positioning System (GPS) based control system utilises information about the current vehicle position and upcoming terrain in order to reduce vehicle fuel consumption as well as improve road safety and comfort. The development of ...