Model prediction for reactor control
Ardell, G.G.; Gumowski, B.
1983-06-01T23:59:59.000Z
Model prediction is offered as a substitute to lengthy analysis of sample procedures to control product properties not amendable to direct measurement during chemical processing. A computer model of a reactor is set up, and control actions, based on current predicted values, are established. The control is based on predicted ''measurements'' which are derived using a dynamic process model solved on-line. The model is corrected by real measurements in the process operation. A two phase exothermic catalyzed reaction, with the objective of producing material with specified properties, is tested in this paper. The model prediction performance was very good. Model systems enable a more effective control to be exercised than the sample method.
Model Predictive Control Wind Turbines
Model Predictive Control of Wind Turbines Martin Klauco Kongens Lyngby 2012 IMM-MSc-2012-65 #12;Summary Wind turbines are the biggest part of the green energy industry. Increasing interest control strategies. Control strategy has a significant impact on the wind turbine operation on many levels
Optimization Online - Nonlinear Model Predictive Control via ...
M. J. Tenny
2002-08-15T23:59:59.000Z
Aug 15, 2002 ... Nonlinear Model Predictive Control via Feasibility-Perturbed Sequential Quadratic Programming. M. J. Tenny (tenny ***at*** bevo.che.wisc.edu)
Robust constrained model predictive control
Richards, Arthur George, 1977-
2005-01-01T23:59:59.000Z
(cont.) multiple Uninhabited Aerial Vehicles (UAVs) demonstrate that the new DMPC algorithm offers significant computational improvement compared to its centralized counterpart. The controllers developed in this thesis are ...
Autonomous Helicopter Formation using Model Predictive Control
Sastry, S. Shankar
Autonomous Helicopter Formation using Model Predictive Control Hoam Chung and S. Shankar Sastry are required to fly in tight formations and under harsh conditions. The starting point for safe autonomous into a formation, so that each vehicle can safely maintain sufficient space between it and all other vehicles
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01T23:59:59.000Z
Learning Control for Thermal Energy Storage Systems”. In:Predictive Control of Thermal Energy Storage in Buildingmaking use of building thermal energy storage, and this work
Model Predictive Control of Variable Density Multiphase Flows Governed by
Hinze, Michael
of model predictive control (MPC) consists in steering or keeping the state of a dynamical systemModel Predictive Control of Variable Density Multiphase Flows Governed by Diffuse Interface Models appearing in the model predictive control strategy. The resulting control concept is known as instantaneous
Model Predictive Control for Smooth Distributed Power Adaptation
Boyer, Edmond
1 Model Predictive Control for Smooth Distributed Power Adaptation Virgile Garcia1,2,3 , Nikolai the variations of other BS powers. The trajectories are then updated using a Model Predictive Control (MPC-based power control, no inter-cell cooperation, power trajectory, model predictive control, smooth power
NONLINEAR MODEL PREDICTIVE CONTROL VIA FEASIBILITYPERTURBED SEQUENTIAL QUADRATIC
Wright, Steve
NONLINEAR MODEL PREDICTIVE CONTROL VIA FEASIBILITYÂPERTURBED SEQUENTIAL QUADRATIC PROGRAMMINGÂ06, AUGUST 2002, COMPUTER SCIENCES DEPT, UNIV. OF WISCONSIN TEXASÂWISCONSIN MODELING AND CONTROL CONSORTIUM REPORT TWMCCÂ2002Â02 Abstract. Model predictive control requires the solution of a sequence of continuous
Model Predictive Control of a Kaibel Distillation Column
Skogestad, Sigurd
Model Predictive Control of a Kaibel Distillation Column Martin Kvernland Ivar Halvorsen Sigurd (e-mail: skoge@ntnu.no) Abstract: This is a simulation study on controlling a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared
Nonlinear Model Predictive Control of an Omnidirectional Mobile Robot
Zell, Andreas
, University of TĂĽbingen, Sand 1, 72076 TĂĽbingen, Germany Abstract. This paper focuses on motion controlNonlinear Model Predictive Control of an Omnidirectional Mobile Robot Xiang LI a,1 , Kiattisin problems of an omnidirectional robot based on the Nonlinear Model Predictive Control (NMPC) method
Plug-and-Play Decentralized Model Predictive Control Stefano Riverso
Ferrari-Trecate, Giancarlo
Plug-and-Play Decentralized Model Predictive Control Stefano Riverso , Marcello Farina. When this is possible, we show how to automatize the design of local controllers so that it can information with neighboring subsystems. In particular, local controllers exploit tube-based Model Predictive
Model Predictive Control based Real Time Power System Protection Schemes
Kumar, Ratnesh
1 Model Predictive Control based Real Time Power System Protection Schemes Licheng Jin, Member by controlling the production, absorption as well as flow of reactive power at various locations in the system predictive control, trajectory sensitivity, voltage stabilization, switching control, power system I
Optimal Control of Distributed Energy Resources using Model Predictive Control
Mayhorn, Ebony T.; Kalsi, Karanjit; Elizondo, Marcelo A.; Zhang, Wei; Lu, Shuai; Samaan, Nader A.; Butler-Purry, Karen
2012-07-22T23:59:59.000Z
In an isolated power system (rural microgrid), Distributed Energy Resources (DERs) such as renewable energy resources (wind, solar), energy storage and demand response can be used to complement fossil fueled generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation. The problem is formulated as a multi-objective optimization problem with the goals of minimizing fuel costs and changes in power output of diesel generators, minimizing costs associated with low battery life of energy storage and maintaining system frequency at the nominal operating value. Two control modes are considered for controlling the energy storage to compensate either net load variability or wind variability. Model predictive control (MPC) is used to solve the aforementioned problem and the performance is compared to an open-loop look-ahead dispatch problem. Simulation studies using high and low wind profiles, as well as, different MPC prediction horizons demonstrate the efficacy of the closed-loop MPC in compensating for uncertainties in wind and demand.
Chance Constrained Model Predictive Control Alexander T. Schwarm
Nikolaou, Michael
through a simulation case study on a high-purity distillation column. Suggestions for further improvements@uh.edu #12;2 Abstract This work focuses on robustness of model predictive control (MPC) with respect such property, particularly important for constrained model predictive control (MPC) systems
Nonlinear Model Predictive Control of Municipal Solid Waste Combustion Plants
Van den Hof, Paul
Nonlinear Model Predictive Control of Municipal Solid Waste Combustion Plants M. Leskens , R.h.Bosgra@tudelft.nl, p.m.j.vandenhof@tudelft.nl Keywords : nonlinear model predictive control, municipal solid waste combus- tion Abstract : Combustion of municipal solid waste (MSW; = household waste) is used to reduce
A two-timescale approach to nonlinear Model Predictive Control
Buescher, K.L.; Baum, C.C.
1994-10-01T23:59:59.000Z
Model Predictive Control (MPC) schemes generate controls by using a model to predict the plant`s response to various control strategies. A problem arises when the underlying model is obtained by fitting a general nonlinear function, such as a neural network, to data: an exorbitant amount of data may be required to obtain accurate enough predictions. We describe a means of avoiding this problem that involves a simplified plant model which bases its predictions on averages of past control inputs. This model operates on a timescale slower than- the rate at which the controls are updated and the plant outputs are sampled. Not only does this technique give better closed-loop performance from the same amount of open-loop data, but it requires far less on-line computation as well. We illustrate the usefulness of this two-timescale approach by applying it to a simulated exothermic continuously stirred tank reactor with jacket dynamics.
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01T23:59:59.000Z
control logic for building energy systems. Most moderncontrol actuators. Modern digital building automation systemssystem in the lab. The lab is equipped with a modern digital control
Model Predictive Control For Wind Excited Buildings: A Benchmark Problem
Kareem, Ahsan
control force; W is the wind excitation vector of dimension 24; and are control output vec- tor , , , , , , , and were given by Yang et al (1999) and have appropriate dimensions. The wind force data acting1 Model Predictive Control For Wind Excited Buildings: A Benchmark Problem Gang Mei, Student M
Tuning Methods for Model Predictive Controllers
methods for tuning of a Gas-Oil Furnace, a Wood-Berry Distillation Column and a Cement Mill Circuit. #12 to develop a tuning toolbox for SISO systems, which visualizes the performance of control designs. A study systemer, som kan visualisere ydelsen af regulator designs. Der er undersřgt, hvorledes ydelsesm
Multiplexed Model Predictive Control Keck Voon Ling
Cambridge, University of
an established control technology in the petrochemical industry, and its use is currently being pioneered in an increasingly wide range of process industries [23, 34]. It is also being proposed for a range of higher. Only an initial portion of that plan is implemented, and the process is repeated, re-planning when new
Model Predictive Control of a Wind Lars Christian Henriksen
wind turbines is on the sea as their is a more stable wind. These water based wind farms are confined locations to become potential wind farms. This thesis investigates control of both wind turbines mountedModel Predictive Control of a Wind Turbine Lars Christian Henriksen Kongens Lyngby 2007 IMM
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01T23:59:59.000Z
T mixed T amb d OA ?T supply Cooling Fan Heating 20 Time (models for supply fan (5.6), cooling and heating coils (5.7)Solar radiation u cooling/heating coils supply fan dampers
Axis control using model predictive control: identification and friction effect reduction
Boyer, Edmond
Axis control using model predictive control: identification and friction effect reduction Pedro this numerical model is used to synthetize a predictive GPC controller reducing the impact of the friction Rodriguez-Ayerbe, Didier Dumur, Sylvain Lavernhe** * SUPELEC- E3S, Automatic Control, 3 rue Joliot Curie
Fast Nonconvex Model Predictive Control for Commercial Refrigeration
Fast Nonconvex Model Predictive Control for Commercial Refrigeration Tobias Gybel Hovgard , Lars F multi-zone refrigeration system, consisting of several cooling units that share a common compressor. This corresponds roughly to 2% of the entire electricity consumption in the country. Refrigerated goods constitute
Application of Sampling Based Model Predictive Control to an Autonomous
Collins, Emmanuel
Unmanned Underwater Vehicles (UUVs) can be utilized to perform difficult tasks in cluttered environments55 Application of Sampling Based Model Predictive Control to an Autonomous Underwater Vehicle for an autonomous underwater vehicle (AUV). The algorithm combines the benefits of sampling-based motion planning
Adaptive model predictive process control using neural networks
Buescher, Kevin L. (Los Alamos, NM); Baum, Christopher C. (Mazomanie, WI); Jones, Roger D. (Espanola, NM)
1997-01-01T23:59:59.000Z
A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.
Adaptive model predictive process control using neural networks
Buescher, K.L.; Baum, C.C.; Jones, R.D.
1997-08-19T23:59:59.000Z
A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.
Model Predictive Control of Integrated Gasification Combined Cycle Power Plants
B. Wayne Bequette; Priyadarshi Mahapatra
2010-08-31T23:59:59.000Z
The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.
Duong, Thien Chi
2011-02-22T23:59:59.000Z
FLOW CONTROL OF REAL TIME MULTIMEDIA APPLICATIONS USING MODEL PREDICTIVE CONTROL WITH A FEED FORWARD TERM A Thesis by THIEN CHI DUONG Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment... of the requirements for the degree of MASTER OF SCIENCE December 2010 Major Subject: Mechanical Engineering Flow Control of Real Time Multimedia Applications Using Model Predictive Control with Feed Forward Term...
Model Predictive Control for the Operation of Building Cooling Systems
Ma, Yudong
2010-01-01T23:59:59.000Z
predictive control of thermal energy storage in buildingsystems which use thermal energy storage. In particular thepredictive control of thermal energy storage in building
Model predictive control of a pilot-scale distillation column using a programmable automation). The controller is tested on a pilot-scale binary distillation column to track reference temperatures. A majorRIO) to control a pilot-scale binary distillation col- umn. Both the PI-controllers and the supervising online MPC
Trajectory Free Linear Model Predictive Control for Stable Walking in the Presence of Strong
Paris-Sud XI, Université de
Trajectory Free Linear Model Predictive Control for Stable Walking in the Presence of Strong of the dynamics of the robot and propose a new Linear Model Predictive Control scheme which is an improvement are unfortunately severely limited. Model Predictive Control, also known as Receding Horizon Control, is a general
Control of Airborne Wind Energy Systems Based on Nonlinear Model Predictive Control & Moving arising in the Airborne Wind Energy paradigm, an essential one is the control of the tethered airfoil], [3], the Airborne Wind Energy (AWE) paradigm shift proposes to get rid of the structural elements
VISUALIZING MODEL-BASED PREDICTIVE CONTROLLERS StephanieGuerlain Greg JamjesonandPeter Bullemer
Virginia, University of
-based predictive controllers (MPC) are becoming very popular in petrochemical refineries, as they simultaneously control ayd optimize large sections of a petrochemical process;yqng a predictive model. However, current
Distributed state estimation and model predictive control of linear interconnected system
Boyer, Edmond
requirements, modern control systems are becoming more and more complex. For these processes, different controlDistributed state estimation and model predictive control of linear interconnected system: In this paper, a distributed and networked control system architecture based on independent Model Predictive
Plug-and-play decentralized model predictive control for linear systems
Ferrari-Trecate, Giancarlo
1 Plug-and-play decentralized model predictive control for linear systems Stefano Riverso, Graduate to automatize the design of local controllers so that it can be carried out in parallel by smart actuators. In particular, local controllers exploit tube-based Model Predictive Control (MPC) in order to guarantee
An integrated system for real-time Model Predictive Control of humanoid robots
Todorov, Emanuel
this goal. The automatic controller is based on real-time model-predictive control (MPC) applied to the full. The resulting composite cost is sent to the MPC machinery which constructs a new locally-optimal time- varying-based optimal control is called Model-Predictive Control (MPC), an approach that relies on real-time trajectory
Julius, Anak Agung
-- The use of live microbial cells as microscale robots is an attractive premise, primarily because eukaryotic cell. Whitesides et al [10] demonstrated the biological propul- sion of microscale loadsMotion Control of Tetrahymena pyriformis Cells with Artificial Magnetotaxis: Model Predictive
Model Predictive Tracking Control for a Head-Positioning in a Hard-Disk-Drive
Paris-Sud XI, Université de
Model Predictive Tracking Control for a Head-Positioning in a Hard-Disk-Drive M. Taktak-Meziou, A generated from Model Predictive Control (MPC). The first approach consists of a classical linear MPC without/Write (R/W) head of a Hard-Disk-Drive (HDD) servo-system, which is resolved with two control algorithms
Fault-tolerant model predictive control of a wind turbine benchmark
Cambridge, University of
Fault-tolerant model predictive control of a wind turbine benchmark X. Yang J.M. Maciejowski tolerant control problem of a wind turbine benchmark. A hierarchical controller with model predictive pre component of the wind turbine. The global MPC is used to schedule the operation of the components
OPERATOR INTERACTION WITH MODEL-BASED PREDICTIVE CONTROLLERS IN PETROCHEMICAL REFINING
Virginia, University of
OPERATOR INTERACTION WITH MODEL-BASED PREDICTIVE CONTROLLERS IN PETROCHEMICAL REFINING Greg A success in the petrochemical industry, they have introduced new challenges for the operators and engineers
Haves, Phillip
2010-01-01T23:59:59.000Z
Model Predictive Control of HVAC Systems: Implementation and air conditioning (HVAC) account for 27% of the reduction potential of HVAC systems with active thermal
DECENTRALIZED ROBUST NONLINEAR MODEL PREDICTIVE CONTROLLER FOR UNMANNED AERIAL SYSTEMS
Garcia, Gonzalo Andres
2013-05-31T23:59:59.000Z
that enables the vehicle to follow an arbitrary trajectory shaped by moving points; 2 A formulation that embeds the guidance logic and trajectory information in the aircraft model, avoiding cross coupling and control degradation; 3 An artificial neural network...
Robust Constrained Model Predictive Control using Linear Matrix Inequalities \\Lambda
Balakrishnan, Venkataramanan "Ragu"
dynamical systems, such as those encountered in chemical process control in the petrochemical, pulp process models as well as many performance criteria of significance to the process industries can
Robust Constrained Model Predictive Control using Linear Matrix Inequalities
Balakrishnan, Venkataramanan "Ragu"
, such as those encountered in chemical process control in the petrochemical, pulp and paper industries, several process models as well as many performance criteria of significance to the process industries can
Reconfigurable autopilot design for a high performance aircraft using model predictive control
Ruiz, Jose Pedro, 1980-
2004-01-01T23:59:59.000Z
The losses of military and civilian aircraft due to control surface failures have prompted research into controllers with a degree of reconfiguration. This thesis will describe a design approach incorporating Model Predictive ...
Energy Savings Through Application of Model Predictive Control to an Air Separation Facility
Hanson, T. C.; Scharf, P. F.
Energy Savings Through Application of Model Predictive Control to an Air Separation Facility Thomas C. Hanson PauiF. Scharf Manager Senior Engineering Associate Process Development Process Control Technology Praxair, Inc., Tonawanda, New York...
Autonomous Reactor Control Using Model Based Predictive Control for Space Propulsion Applications
Bragg-Sitton, Shannon M.; Holloway, James Paul [University of Michigan, Nuclear Engineering and Radiological Sciences, Ann Arbor, MI 48109 (United States)
2005-02-06T23:59:59.000Z
Reliable reactor control is important to reactor safety, both in terrestrial and space systems. For a space system, where the time for communication to Earth is significant, autonomous control is imperative. Based on feedback from reactor diagnostics, a controller must be able to automatically adjust to changes in reactor temperature and power level to maintain nominal operation without user intervention. Model-based predictive control (MBPC) (Clarke 1994; Morari 1994) is investigated as a potential control methodology for reactor start-up and transient operation in the presence of an external source. Bragg-Sitton and Holloway (2004) assessed the applicability of MBPC to reactor start-up from a cold, zero-power condition in the presence of a time-varying external radiation source, where large fluctuations in the external radiation source can significantly impact a reactor during start-up operations. The MBPC algorithm applied the point kinetics model to describe the reactor dynamics, using a single group of delayed neutrons; initial application considered a fast neutron lifetime (10-3 sec) to simplify calculations during initial controller analysis. The present study will more accurately specify the dynamics of a fast reactor, using a more appropriate fast neutron lifetime (10-7 sec) than in the previous work. Controller stability will also be assessed by carefully considering the dependencies of each component in the defined cost (objective) function and its subsequent effect on the selected 'optimal' control maneuvers.
Interactive software for model predictive control with simultaneous identification
Echeverria Del Rio, Pablo
2000-01-01T23:59:59.000Z
and Internal Model Control (IMC) by Garcia and Morari (Garcia and Morari, 1982); the other one was about the stability of constrained MPC by Rawlings and Muske (Rawlings and Muske, 1993). Among the research papers and thesis that have been written about MPC... making process (Garcia, Prett and Morari, 1989). In order to obtain the maximum benefit from a process, several performance objectives should be specified and attained in the design and actual implementation of the plant. However, this condition...
Economic and Distributed Model Predictive Control of Nonlinear Systems
Heidarinejad, Mohsen
2012-01-01T23:59:59.000Z
hybrid systems. IEEE Transactions on Automatic Control, [6]nonlinear systems. IEEE Transactions on Automatic Control,of switched systems. IEEE Transactions on Automatic Control,
Adaptive Model Predictive Control of the Hybrid Dynamics of a Fuel Cell System.
Paris-Sud XI, Université de
Adaptive Model Predictive Control of the Hybrid Dynamics of a Fuel Cell System. M. Fiacchini, T operation of a fuel cell system is presented. The aim of the control design is to guarantee that the oxygen control to a fuel cell plant is presented. The fuel cell, located in the laboratory of the Department
Scenario-Based Fault-Tolerant Model Predictive Control for Diesel-Electric Marine Power Plant
Johansen, Tor Arne
Scenario-Based Fault-Tolerant Model Predictive Control for Diesel-Electric Marine Power Plant Email: torstein.bo@itk.ntnu.no, tor.arne.johansen@itk.ntnu.no Abstract--Diesel-electric propulsion generation control, Ma- rine safety, Optimal control. I. INTRODUCTION Diesel electric propulsion is a system
Embedded Online Optimization for Model Predictive Control at ...
2013-03-05T23:59:59.000Z
optimization-based control systems on low cost embedded platforms. ..... Modern computing platforms must allow for a wide range of applications that operate on.
Model Predictive Control for the Operation of Building Cooling Systems
Ma, Yudong
2010-01-01T23:59:59.000Z
storage in building cooling systems. Technical report,storage in building cooling systems. Decision and Control,for the Operation of Building Cooling Systems Yudong Ma ? ,
Coordinated Dynamic Voltage Stabilization based on Model Predictive Control
Kumar, Ratnesh
is very important for power system operations. This paper presents an approach for optimal coordination and operation [1], [2]. The deregulation of power industry has created an economical incentive to operate power devices, generator reactive power control, transformer tap changer control and load shedding. As shown
Decentralized model predictive control of a multiple evaporator HVAC system
Elliott, Matthew Stuart
2009-05-15T23:59:59.000Z
separate body of water, referred to as a cooling zone. The two evaporators are connected to a single condenser and variable speed compressor, and feature variable water flow and electronic expansion valves. The control problem lies in development of a...
Predictive models of procedural human supervisory control behavior
Boussemart, Yves, 1980-
2011-01-01T23:59:59.000Z
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 ...
Model Predictive Control for the Operation of Building Cooling Systems
Ma, Yudong
2010-01-01T23:59:59.000Z
of the cooling towers while consuming less energy. Duringtowers, the thermal storage tank and the electricity energytowers, the thermal storage tank, the campus model and the electricity energy
Supervisory hybrid model predictive control for voltage stability of power networks
Paris-Sud XI, Université de
Supervisory hybrid model predictive control for voltage stability of power networks R.R. Negenborn voltage control problems in electric power networks have stimulated the interest for the imple- mentation dynamics to restore power consumption beyond the capability of the transmission and generation system
Johansson, Karl Henrik
Randomized Model Predictive Control for HVAC Systems Alessandra Parisio, Damiano Varagnolo, Daniel Conditioning (HVAC) sys- tems play a fundamental role in maintaining acceptable ther- mal comfort and Indoor. A possible solu- tion is to develop effective control strategies for HVAC sys- tems, but this is complicated
A Tutorial on Model Predictive Control for Spacecraft Rendezvous
Hartley, Edward N.
2015-05-26T23:59:59.000Z
sensors can be highly directional. However, unlike translation control, this can also be performed using reaction wheels, which expend only solar-generated electrical power, and therefore does not limit the lifetime of the mission. In Section II we... tailored software that exploits the structure of the problem. Examples include CVXGEN [53] and FORCES [54] which are online code-generators to generate custom structure-exploiting IP solvers. ECOS [55] is a library-free ANSI-C tool to solve SOCPs...
IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 8, NO. 6, DECEMBER 2000 665 Fuzzy Model Predictive Control
Huang, Yinlun
and petrochemical industries during the past decade. In MPC, a process dynamic model is used to predict future (FMPC) approach is introduced to design a control system for a highly nonlinear process. In this approach, a process system is described by a fuzzy convolution model that consists of a number of quasi
Kumar, Aditya; Shi, Ruijie; Kumar, Rajeeva; Dokucu, Mustafa
2013-04-09T23:59:59.000Z
Control system and method for controlling an integrated gasification combined cycle (IGCC) plant are provided. The system may include a controller coupled to a dynamic model of the plant to process a prediction of plant performance and determine a control strategy for the IGCC plant over a time horizon subject to plant constraints. The control strategy may include control functionality to meet a tracking objective and control functionality to meet an optimization objective. The control strategy may be configured to prioritize the tracking objective over the optimization objective based on a coordinate transformation, such as an orthogonal or quasi-orthogonal projection. A plurality of plant control knobs may be set in accordance with the control strategy to generate a sequence of coordinated multivariable control inputs to meet the tracking objective and the optimization objective subject to the prioritization resulting from the coordinate transformation.
Advanced Models and Controls for Prediction and Extension of Battery Lifetime (Presentation)
Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Pesaran, A.
2014-02-01T23:59:59.000Z
Predictive models of capacity and power fade must consider a multiplicity of degradation modes experienced by Li-ion batteries in the automotive environment. Lacking accurate models and tests, lifetime uncertainty must presently be absorbed by overdesign and excess warranty costs. To reduce these costs and extend life, degradation models are under development that predict lifetime more accurately and with less test data. The lifetime models provide engineering feedback for cell, pack and system designs and are being incorporated into real-time control strategies.
Economic Nonlinear Model Predictive Control for the Optimization of Gas Pipeline Networks
Grossmann, Ignacio E.
/ 24 #12;Natural Gas Industry Motivation Natural Gas Industry Globally increasing demand & production of natural gas. Demand distribution (as of 2008) 21 % residential, 13 % Commercial, 34 % Industrial, 29 - Regulated, Deregulated markets Applying Economic Model Predictive Control to gas transportation. 1Zheng et
Johansen, Tor Arne
Pumps (ESP) can be in- stalled in oil wells to create artificial lift, in order to increase recovery system knowledge is assumed. In [12], [13], a model of an ESP-lifted well is developed, the control and stability, while the MPC controller improves the performance of the overall multivari- able system
A Simulation Study on Model Predictive Control and Extremum Seeking Control for
Braslavsky, Julio H.
. Recently, it has been proposed to use feedback control to improve the rate of mineral extraction Control (ESC), to improve copper extraction in a heap bioleaching process. Simplified linear models of the process show that similar copper extraction rates can be obtained using either strategy. While better
Evaluation of Transport and Dispersion Models: A Controlled Comparison of HPAC and NARAC Predictions
Warner, S; Heagy, J F; Platt, N; Larson, D; Sugiyama, G; Nasstrom, J S; Foster, K T; Bradley, S; Bieberbach, G
2001-05-01T23:59:59.000Z
During fiscal year 2000, a series of studies in support of the Defense Threat Reduction Agency (DTRA) was begun. The goal of these studies is to improve the verification, validation, and accreditation (VV&A) of hazard prediction and assessment models and capabilities. These studies are part of a larger joint VV&A collaborative effort that DTRA and the Department of Energy (DOE), via the Lawrence Livermore National Laboratory (LLNL), are conducting. This joint effort includes comparisons of the LLNL and DTRA transport and dispersion (T&D) modeling systems, NARAC and HPAC, respectively. The purpose of this work is to compare, in a systematic way, HPAC and NARAC model predictions for a set of controlled hypothetical release scenarios. Only ''model-versus-model'' comparisons are addressed in this work. Model-to-field trial comparisons for HPAC and NARAC have been addressed in a recent companion study, in support of the same joint VV&A effort.
Unified model of voltage/current mode control to predict subharmonic oscillation
Fang, Chung-Chieh
2012-01-01T23:59:59.000Z
A unified model of voltage mode control (VMC) and current mode control (CMC) is proposed to predict the subharmonic oscillation. In the unified model, based on the sampled-data slope-based analysis, the subharmonic oscillation boundary conditions for VMC/CMC have similar forms. The boundary conditions are exact, and can be further simplified in various approximate closed forms for design purpose. Harmonic balance analysis is also applied. Both the slope-based and harmonic balance analysis are applied to analyze five different VMC/CMC control schemes. A new "HB plot" and an equivalent "M plot" are proposed to accurately predict the subharmonic oscillation. The relation between the crossover frequency and the subharmonic oscillation is also analyzed.
Goodrich, Michael A.
Logic Control Michael A. Goodrich, Wynn C. Stirling, and Richard L. Frost Abstract-- Model constrained and nonlinear control problems. However, even when a good model is available, it may be necessary employs a fuzzy description of system consequences via model predictions. This controller considers
Kohler, Christian
2012-08-01T23:59:59.000Z
Complex glazing systems such as venetian blinds, fritted glass and woven shades require more detailed optical and thermal input data for their components than specular non light-redirecting glazing systems. Various methods for measuring these data sets are described in this paper. These data sets are used in multiple simulation tools to model the thermal and optical properties of complex glazing systems. The output from these tools can be used to generate simplified rating values or as an input to other simulation tools such as whole building annual energy programs, or lighting analysis tools. I also describe some of the challenges of creating a rating system for these products and which factors affect this rating. A potential future direction of simulation and building operations is model based predictive controls, where detailed computer models are run in real-time, receiving data for an actual building and providing control input to building elements such as shades.
Nazarathy, Yoni
2013-01-01T23:59:59.000Z
al., 1996). The more recent works on traffic control systems have adopted results of modern control responsibility of Delft University of Technology Keywords: Model Predictive Control, Intelligent Transport System, Congestion Control 1. Introduction Increasing population and economic activities in modern societies have led
Haves, Phillip
2010-01-01T23:59:59.000Z
heat exchangers, the models calibrated using the manufacturer performance curves predicted power consumption within 10%. The data
Joshi, Praveen Sudhakar
1999-01-01T23:59:59.000Z
Predictive Variable Structure and Fuzzy Logic based controllers for the same benchmark problem. Evaluation criteria consist of closed-loop system performance, activity level of the VFC nozzles, ease of controller synthesis, time required to synthesize...
ghMulti-Level Approach for Model-Based Predictive Control (MPC) in Buildings: A Preliminary Overview
Candanedo, J. A.; Dehkordi, V. R.
2013-01-01T23:59:59.000Z
Model-based predictive control (MPC) has emerged in recent years as a promising approach to building operation. MPC uses models of the system(s) under control -and knowledge about future disturbances- to select an optimal set of actions. Despite its...
Haves, Phillip; Hencey, Brandon; Borrell, Francesco; Elliot, John; Ma, Yudong; Coffey, Brian; Bengea, Sorin; Wetter, Michael
2010-06-29T23:59:59.000Z
A Model Predictive Control algorithm was developed for the UC Merced campus chilled water plant. Model predictive control (MPC) is an advanced control technology that has proven successful in the chemical process industry and other industries. The main goal of the research was to demonstrate the practical and commercial viability of MPC for optimization of building energy systems. The control algorithms were developed and implemented in MATLAB, allowing for rapid development, performance, and robustness assessment. The UC Merced chilled water plant includes three water-cooled chillers and a two million gallon chilled water storage tank. The tank is charged during the night to minimize on-peak electricity consumption and take advantage of the lower ambient wet bulb temperature. The control algorithms determined the optimal chilled water plant operation including chilled water supply (CHWS) temperature set-point, condenser water supply (CWS) temperature set-point and the charging start and stop times to minimize a cost function that includes energy consumption and peak electrical demand over a 3-day prediction horizon. A detailed model of the chilled water plant and simplified models of the buildings served by the plant were developed using the equation-based modeling language Modelica. Steady state models of the chillers, cooling towers and pumps were developed, based on manufacturers performance data, and calibrated using measured data collected and archived by the control system. A detailed dynamic model of the chilled water storage tank was also developed and calibrated. Simple, semi-empirical models were developed to predict the temperature and flow rate of the chilled water returning to the plant from the buildings. These models were then combined and simplified for use in a model predictive control algorithm that determines the optimal chiller start and stop times and set-points for the condenser water temperature and the chilled water supply temperature. The report describes the development and testing of the algorithm and evaluates the resulting performance, concluding with a discussion of next steps in further research. The experimental results show a small improvement in COP over the baseline policy but it is difficult to draw any strong conclusions about the energy savings potential for MPC with this system only four days of suitable experimental data were obtained once correct operation of the MPC system had been achieved. These data show an improvement in COP of 3.1% {+-} 2.2% relative to a baseline established immediately prior to the period when the MPC was run in its final form. This baseline includes control policy improvements that the plant operators learned by observing the earlier implementations of MPC, including increasing the temperature of the water supplied to the chiller condensers from the cooling towers. The process of data collection and model development, necessary for any MPC project, resulted in the team uncovering various problems with the chilled water system. Although it is difficult to quantify the energy savings resulting from these problems being remedied, they were likely on the same order as the energy savings from the MPC itself. Although the types of problems uncovered and the level of energy savings may differ significantly from other projects, some of the benefits of detecting and diagnosing problems are expected from the use of MPC for any chilled water plant. The degree of chiller loading was found to be a key factor for efficiency. It is more efficient to operate the chillers at or near full load. In order to maximize the chiller load, one would maximize the temperature difference across chillers and the chilled water flow rate through the chillers. Thus, the CHWS set-point and the chilled water flow-rate can be used to limit the chiller loading to prevent chiller surging. Since the flow rate has an upper bound and the CHWS set point has a lower bound, the chiller loading is constrained and often determined by the chilled water return temperature (CHWR). The CHWR temperature
Pappas, George J.
regulating the fraction of induction of a colony of Escherichia coli. We use the abstract model to designHybrid model predictive control of induction of Escherichia coli A. Agung Julius, M. Selman Sakar a feedback controller based on model predictive control strategy. Upon simulation, we show that the model
Maasoumy, Mehdi; Sangiovanni-Vincentelli, Alberto
2012-01-01T23:59:59.000Z
optimal control design for HVAC systems,’’ in Proc. Dynamicelectricity consumption in hvac using learning- based model-algorithm design for hvac systems in energy efficient
Handling model uncertainty in model predictive control for energy efficient buildings
Maasoumy, Mehdi; Razmara, M; Shahbakhti, M; Sangiovanni-Vincentelli, Alberto
2014-01-01T23:59:59.000Z
trol for the operation of building cooling systems, IEEEK. Wirth, Energy ef?cient building climate control usingSagerschnig, E. Z ? á?ceková, Building [8] J. Prí vara, S.
MULTIPLE ARX MODEL-BASED AIR-FUEL RATIO PREDICTIVE CONTROL FOR SI
Johansen, Tor Arne
strategy for combustion engines. The mix- ture quality is essential for efficiency of a three- way control problems. One of the most popular approaches to combustion engine modeling is based on neural where the amount of the fuel is a function of the control action. It was demonstrated by simulation
Johansen, Tor Arne
Embedded Model Predictive Control on a PLC Using a Primal-Dual First-Order Method for a Subsea. Eikrem3 Abstract-- The results of a PLC implementation of embedded Model Predictive Control (MPC to underline its potential. The embedded MPC was implemented on the ABB AC500 PLC, and its performance
Distributed Model Predictive Control of Nonlinear and Two-Time-Scale Process Networks
Chen, Xianzhong
2012-01-01T23:59:59.000Z
process . . . . . . . . . . . . Process and control problem147 Process description and control systemof benzene pro- cess Process and control problem description
Distributed Model Predictive Control of Nonlinear and Two-Time-Scale Process Networks
Chen, Xianzhong
2012-01-01T23:59:59.000Z
layer) employs automatic feedback control systems to forcenonlinear systems. IEEE Transactions on Automatic Control,dynamical systems. IEEE Transactions on Automatic Control,
Mittelmann, Hans D.
is shown by applying it to a case study involving composition control of a binary distillation column. I is demonstrated in a binary high-purity distillation column case study by Weischedel and McAvoy [7], a demandingOptimization-based Design of Plant-Friendly Input Signals for Model-on-Demand Estimation and Model
Model predictive adaptive control of process systems using recurrent neural networks
Parthasarathy, Sanjay
1993-01-01T23:59:59.000Z
- tling time, approximately to half of the system settling time for a controller without the gain adaptation, at the expense of a minor increase in the peak control effort. The proposed control algorithm is then evaluated on a complex, nonlinear plant... controller structures are widely used in industry for control of complex, nonlinear systems [20]. The use of constant gain controllers for computa; tion of the control input is not always desirable since the plant parameters may drift with time and the set...
Haves, Phillip
2010-01-01T23:59:59.000Z
13] Wetter, M.. 2009. “Modelica?based Modeling and 14] Wetter, M.. 2009. “Modelica?based Modeling and modeling language Modelica. Steady state models of
Multiplexed Model Predictive Control Keck Voon Ling a, Jan Maciejowski b
Cambridge, University of
Control (MPC) has become an established control technol- ogy in the petrochemical industry, and its use is currently being pioneered in an increasingly wide range of process industries. It is also being proposed
area prediction models: Topics by E-print Network
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared Skogestad, Sigurd 159 Model predictive...
Reduced order modeling for prediction and control of large-scale systems.
Kalashnikova, Irina; Arunajatesan, Srinivasan; Barone, Matthew Franklin; van Bloemen Waanders, Bart Gustaaf; Fike, Jeffrey A.
2014-05-01T23:59:59.000Z
This report describes work performed from June 2012 through May 2014 as a part of a Sandia Early Career Laboratory Directed Research and Development (LDRD) project led by the first author. The objective of the project is to investigate methods for building stable and efficient proper orthogonal decomposition (POD)/Galerkin reduced order models (ROMs): models derived from a sequence of high-fidelity simulations but having a much lower computational cost. Since they are, by construction, small and fast, ROMs can enable real-time simulations of complex systems for onthe- spot analysis, control and decision-making in the presence of uncertainty. Of particular interest to Sandia is the use of ROMs for the quantification of the compressible captive-carry environment, simulated for the design and qualification of nuclear weapons systems. It is an unfortunate reality that many ROM techniques are computationally intractable or lack an a priori stability guarantee for compressible flows. For this reason, this LDRD project focuses on the development of techniques for building provably stable projection-based ROMs. Model reduction approaches based on continuous as well as discrete projection are considered. In the first part of this report, an approach for building energy-stable Galerkin ROMs for linear hyperbolic or incompletely parabolic systems of partial differential equations (PDEs) using continuous projection is developed. The key idea is to apply a transformation induced by the Lyapunov function for the system, and to build the ROM in the transformed variables. It is shown that, for many PDE systems including the linearized compressible Euler and linearized compressible Navier-Stokes equations, the desired transformation is induced by a special inner product, termed the “symmetry inner product”. Attention is then turned to nonlinear conservation laws. A new transformation and corresponding energy-based inner product for the full nonlinear compressible Navier-Stokes equations is derived, and it is demonstrated that if a Galerkin ROM is constructed in this inner product, the ROM system energy will be bounded in a way that is consistent with the behavior of the exact solution to these PDEs, i.e., the ROM will be energy-stable. The viability of the linear as well as nonlinear continuous projection model reduction approaches developed as a part of this project is evaluated on several test cases, including the cavity configuration of interest in the targeted application area. In the second part of this report, some POD/Galerkin approaches for building stable ROMs using discrete projection are explored. It is shown that, for generic linear time-invariant (LTI) systems, a discrete counterpart of the continuous symmetry inner product is a weighted L2 inner product obtained by solving a Lyapunov equation. This inner product was first proposed by Rowley et al., and is termed herein the “Lyapunov inner product“. Comparisons between the symmetry inner product and the Lyapunov inner product are made, and the performance of ROMs constructed using these inner products is evaluated on several benchmark test cases. Also in the second part of this report, a new ROM stabilization approach, termed “ROM stabilization via optimization-based eigenvalue reassignment“, is developed for generic LTI systems. At the heart of this method is a constrained nonlinear least-squares optimization problem that is formulated and solved numerically to ensure accuracy of the stabilized ROM. Numerical studies reveal that the optimization problem is computationally inexpensive to solve, and that the new stabilization approach delivers ROMs that are stable as well as accurate. Summaries of “lessons learned“ and perspectives for future work motivated by this LDRD project are provided at the end of each of the two main chapters.
Fatemi, Ali
Application of bi-linear loglog SN model to strain-controlled fatigue data of aluminum alloyslog model is applied to stress amplitude versus fatigue life data of 14 aluminum alloys. It is shown-life curves are discussed. Life predictions of aluminum alloys based on linear and bi-linear models are also
Dynamic risk adjustment of prediction models using statistical process control methods
Chuo, John, 1969-
2004-01-01T23:59:59.000Z
Introduction. Models that represent mathematical relationships between clinical outcomes and their predictors are useful to the decision making process in patient care. Many models, such as the score of neonatal physiology ...
Model Predictive Control for Starvation Prevention in a Hybrid Fuel Cell System1
Stefanopoulou, Anna
and limits the power response of the fuel cell. In high-pressure fuel cells a compressor motor is used, avahidi@umich.edu Load Capa Â˘Âˇ ÂŁ or Â¤Â¦ÂĄÂ¨Â§Â© L Â¤ L MPC Controller Reference Constraints Ifc Vcm S Hydrogen Tank Fuel C Stack S Compressor Motor Current Demand ++- State of Charge Icapa!#" $ or Figure 1
Sanandaji, Borhan M.
for the sleeper cab on a long-haul truck. Depending upon the activities and appliances in the cab, the power incorporate physical knowledge of fuel-cell behavior into real-time multiple-inputmultiple-output (MIMO model that represents the physical and chemical processes responsible for fuel-cell function. However
Design of Predictive Control Strategies for Active BITIES Systems Using Frequency Domain Models
Chen, Y.; Athienitis, A. K.; Gala, K. E.
2013-01-01T23:59:59.000Z
. Source Layer Temperature and Thermal Energy Injection Using discrete frequency response modeling for an assembly consisting of ? layers of material (Figure 3), the oscillatory responses of heat flux ???? ?,? and temperature ???? ?,? at surface 0... top surface 1 2 N 0 l Layer index for the assembly Surface index for each layer 0 l 0 l boundary (e.g. the concrete underneath the source layer). The responses ???? ? and ???? ? at time interval ? at source layer can be calculated...
Predictive control of supply temperature in district heating systems
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
Chen, .Dake
Pacific; whereas the total linearized nonlinear advection brings a cooling effect controlling the negative Introduction ENSO is the strongest interannual variability in the global climate system. It happens impacts. Significant progress has been made in understanding and predicting ENSO over the past few decades
Intelligent Predictive Control Methods for Synchronous Power System
Rizvi, Syed Z.
Intelligent Predictive Control Methods for Synchronous Power System Muhammad S. Yousuf Electrical with the control of the system in case of perturbations. Optimal control theory for stabilizing SMIB power systems@kfupm.edu.sa Abstract--In this paper, an intelligent Model Predictive Con- troller (MPC) for a Synchronous Power Machine
Online prediction and control nonlinear stochastic systems
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
age prediction models: Topics by E-print Network
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared Skogestad, Sigurd 162 On biases in the...
accident prediction models: Topics by E-print Network
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared Skogestad, Sigurd 136 Title: Development of...
animal models predictive: Topics by E-print Network
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared Skogestad, Sigurd 222 Title: Development of...
accident prediction model: Topics by E-print Network
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared Skogestad, Sigurd 136 Title: Development of...
Tu, TungSheng
2013-01-01T23:59:59.000Z
operation. Journal of Process Control, [10] C. E. Garcia, D.sys- tems. Journal of Process Control, 23:404–414, 2013. [processes. Journal of Process Control, 21:501–509, 2011. [
Tu, TungSheng
2013-01-01T23:59:59.000Z
monomer process design. Chemical Engineering Communications,design/control study for the vinyl acetate monomer process. Computers & Chemical Engineering,
Maasoumy, Mehdi
2014-01-01T23:59:59.000Z
of commercial building HVAC fan as ancillary service foralgorithm design for hvac systems in energy efficientoptimal control design for HVAC systems,” in Dynamic System
Dimarogonas, Dimos
extensively used in the past for the autonomous operation of underwater robotic vehicles. Complex missions Robotic Vehicles Shahab Heshmati-Alamdari, Alina Eqtami, George C. Karras, Dimos V. Dimarogonas and Kostas Control (NMPC) scheme for an under- actuated underwater robotic vehicle. In this scheme, the control loop
Tang, Youmin
brings a cooling effect controlling the negative perturbation growth in the central Pacific. Keywords variability in the global climate system. It happens in the tropical Pacific Ocean with a period of 27 years and has world-wide climatic, ecological, and social impacts. Significant progress has been made
Mahapatra, P.; Zitney, S.; Bequette, B. Wayne
2012-01-01T23:59:59.000Z
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
Predicting Improved Chiller Performance Through Thermodynamic Modeling
Figueroa, I. E.; Cathey, M.; Medina, M. A.; Nutter, D. W.
This paper presents two case studies in which thermodynamic modeling was used to predict improved chiller performance. The model predicted the performance (COP and total energy consumption) of water-cooled centrifugal chillers as a function...
A Probabilistic Particle Control Approach to Optimal, Robust Predictive Control
Williams, Brian C.
Autonomous vehicles need to be able to plan trajectories to a specified goal that avoid obstacles; for example in the case of localization, the belief state about a vehicle's position can consist of highly non of predictive stochastic control is robust path planning for vehicles under un- certainty. Uncertainty arises
Productivity prediction model based on Bayesian analysis and productivity console
Yun, Seok Jun
2005-08-29T23:59:59.000Z
in poor planning and defies effective control of time and budgets in project management. In this research, we have built a productivity prediction model which uses productivity data from an ongoing project to reevaluate the initial productivity estimate...
Predictive Compensation for Communication Outages in Networked Control Systems
Johansson, Karl Henrik
Predictive Compensation for Communication Outages in Networked Control Systems Erik Henriksson Henrik Sandberg Karl Henrik Johansson Abstract-- A predictive outage compensator co time instance, the predictive outage compensator suggests a replacement command based on the history
Direct Manipulation for Comprehensible, Predictable and Controllable User Interfaces
Golbeck, Jennifer
Direct Manipulation for Comprehensible, Predictable and Controllable User Interfaces Ben that are comprehensible, predictable and controllable. Direct manipulation interfaces are seen as more likely candidates Research University of Maryland, College Park, MD 20742 Abstract: Direct manipulation user interfaces have
A Comparative Study of Two Predictive Current Controls for a Permanent Magnet Synchronous
Paris-Sud XI, UniversitĂ© de
Machines (PMSM) drives. The first tested control scheme is based on a model including the inverter and the PMSM and taking into account the discrete nature of the inverter leg states. It predicts the future time. The second tested control scheme uses a model of the PMSM to predict the output voltages which
Experimental results of a predictive neural network HVAC controller
Jeannette, E.; Assawamartbunlue, K.; Kreider, J.F. [Univ. of Colorado, Boulder, CO (United States); Curtiss, P.S. [Architectural Energy Corp., Boulder, CO (United States)
1998-12-31T23:59:59.000Z
Proportional, integral, and derivative (PID) control is widely used in many HVAC control processes and requires constant attention for optimal control. Artificial neural networks offer the potential for improved control of processes through predictive techniques. This paper introduces and shows experimental results of a predictive neural network (PNN) controller applied to an unstable hot water system in an air-handling unit. Actual laboratory testing of the PNN and PID controllers show favorable results for the PNN controller.
Prediction Markets Partition model of knowledge
Fiat, Amos
Prediction Markets Partition model of knowledge Distributed information markets Convergence time bounds Computational Aspects of Prediction Markets David M. Pennock and Rahul Sami December 5, 2012 Presented by: Rami Eitan David M. Pennock and Rahul Sami Computational Aspects of Prediction Markets #12
A distributed accelerated gradient algorithm for distributed model predictive
Como, Giacomo
of hydro power plants is to manage the available water resources efficiently, while following an optimal is applied to the power reference tracking problem of a hydro power valley (HPV) system. The applied power control, Distributed optimization, Accelerated gradient algorithm, Model predictive control
Accepted for Publication Simulation modeling combined with decision control can
Accepted for Publication ABSTRACT Simulation modeling combined with decision control can offer) with Model Predictive Control (MPC) paradigms using a Knowledge Interchange Broker (KIB). This environment uses the KIB to compose discrete event simulation and model predictive control models. This approach
Applying new optimization algorithms to more predictive control
Wright, S.J.
1996-03-01T23:59:59.000Z
The connections between optimization and control theory have been explored by many researchers and optimization algorithms have been applied with success to optimal control. The rapid pace of developments in model predictive control has given rise to a host of new problems to which optimization has yet to be applied. Concurrently, developments in optimization, and especially in interior-point methods, have produced a new set of algorithms that may be especially helpful in this context. In this paper, we reexamine the relatively simple problem of control of linear processes subject to quadratic objectives and general linear constraints. We show how new algorithms for quadratic programming can be applied efficiently to this problem. The approach extends to several more general problems in straightforward ways.
Latent feature models for dyadic prediction /
Menon, Aditya Krishna
2013-01-01T23:59:59.000Z
prediction . . . . . . . . . . . . . . . . . . . . . . . . .Response prediction . . . . . . . . . . . . . . . . . . .2.4.3 Weighted link prediction . . . . . .
Hot blast stove process model and model-based controller
Muske, K.R. [Villanova Univ., PA (United States). Dept. of Chemical Engineering; Howse, J.W.; Hansen, G.A.; Cagliostro, D.J. [Los Alamos National Lab., NM (United States). Computational Science Methods Group; Chaubal, P.C. [Inland Steel Industries, Inc., East Chicago, IN (United States). Research Labs.
1998-12-31T23:59:59.000Z
This paper describes the process model and model-based control techniques implemented on the hot blast stoves for the No. 7 Blast Furnace at the Inland Steel facility in East Chicago, Indiana. A detailed heat transfer model of the stoves is developed and verified using plant data. This model is used as part of a predictive control scheme to determine the minimum amount of fuel necessary to achieve the blast air requirements. The model is also used to predict maximum and minimum temperature constraint violations within the stove so that the controller can take corrective actions while still achieving the required stove performance.
Predictive wavefront control for Adaptive Optics with arbitrary control loop delays
Poyneer, L A; Veran, J
2007-10-30T23:59:59.000Z
We present a modification of the closed-loop state space model for AO control which allows delays that are a non-integer multiple of the system frame rate. We derive the new forms of the Predictive Fourier Control Kalman filters for arbitrary delays and show that they are linear combinations of the whole-frame delay terms. This structure of the controller is independent of the delay. System stability margins and residual error variance both transition gracefully between integer-frame delays.
Bastin, Georges
Nonlinear Predictive Control of Cement Mills Lalo Magni, Georges Bastin, and Vincent Wertz Abstract--A new multivariable controller for cement milling circuits is presented, which is based on a nonlinear model: a change of hardness of the raw material. Index Terms--Cement industry, multivariable control systems
Fuzzy predictive control for nitrogen removal in biological wastewater treatment
Fuzzy predictive control for nitrogen removal in biological wastewater treatment S. Marsili predictive control; wastewater treatment plant Introduction The problem of improving the nitrogen removal wastewater is too low, full denitrification is difficult to obtain and an additional source of organic carbon
Model Reference Adaptive Control Framework for Real Time Traffic
Minnesota, University of
Adaptive Control #12;12 Prescriptive Dynamic Traffic Assignment A Prediction Model and the Reference ModelModel Reference Adaptive Control Framework for Real Time Traffic Management Under Emergency Movement Volume Adaptive Controller Model Reference Adaptive Control (MRAC) Assumptions Super Zone Concept
THE SPATIAL AGGREGATION LANGUAGE FOR MODELING AND CONTROLLING DISTRIBUTED
Bailey-Kellogg, Chris
THE SPATIAL AGGREGATION LANGUAGE FOR MODELING AND CONTROLLING DISTRIBUTED PHYSICAL SYSTEMS study novel approaches to decentralized control de- sign, in the context of thermal regulation important science and engineering applications, such as predicting weather patterns, controlling
Voltage control in pulsed system by predict-ahead control
Payne, A.N.; Watson, J.A.; Sampayan, S.E.
1994-09-13T23:59:59.000Z
A method and apparatus for predict-ahead pulse-to-pulse voltage control in a pulsed power supply system is disclosed. A DC power supply network is coupled to a resonant charging network via a first switch. The resonant charging network is coupled at a node to a storage capacitor. An output load is coupled to the storage capacitor via a second switch. A de-Q-ing network is coupled to the resonant charging network via a third switch. The trigger for the third switch is a derived function of the initial voltage of the power supply network, the initial voltage of the storage capacitor, and the present voltage of the storage capacitor. A first trigger closes the first switch and charges the capacitor. The third trigger is asserted according to the derived function to close the third switch. When the third switch is closed, the first switch opens and voltage on the node is regulated. The second trigger may be thereafter asserted to discharge the capacitor into the output load. 4 figs.
Predictive modelling of boiler fouling
Not Available
1992-01-01T23:59:59.000Z
In this reporting period, efforts were initiated to supplement the comprehensive flow field description obtained from the RNG-Spectral Element Simulations by incorporating, in a general framework, appropriate modules to model particle and condensable species transport to the surface. Specifically, a brief survey of the literature revealed the following possible mechanisms for transporting different ash constituents from the host gas to boiler tubes as deserving prominence in building the overall comprehensive model: (1) Flame-volatilized species, chiefly sulfates, are deposited on cooled boiler tubes via the mechanism of classical vapor diffusion. This mechanism is more efficient than the particulate ash deposition, and as a result there is usually an enrichment of condensable salts, chiefly sulfates, in boiler deposits; (2) Particle diffusion (Brownian motion) may account for deposition of some fine particles below 0. 1 mm in diameter in comparison with the mechanism of vapor diffusion and particle depositions, however, the amount of material transported to the tubes via this route is probably small. (3) Eddy diffusion, thermophoretic and electrophoretic deposition mechanisms are likely to have a marked influence in transporting 0.1 to 5[mu]m particles from the host gas to cooled boiler tubes; (4) Inertial impaction is the dominant mechanism in transporting particles above 5[mu]m in diameter to water and steam tubes in pulverized coal fired boiler, where the typical flue gas velocity is between 10 to 25 m/s. Particles above 10[mu]m usually have kinetic energies in excess of what can be dissipated at impact (in the absence of molten sulfate or viscous slag deposit), resulting in their entrainment in the host gas.
Predictive tracking control of constrained nonlinear systems
Chisci, Luigi
"diffusive" and "constant" parameter dynamics, by means of a simulation example. Finally Section 6 draws some of constrained nonlinear systems are proposed. Simulation experiments demonstrate the good tracking properties, the controller directly synthesizes the plant control input and, hence, has more freedom than the RG which can
Predictive modelling of boiler fouling
Not Available
1992-01-01T23:59:59.000Z
As this study incorporates in a general framework, appropriate modules to model condensable species transport to the surface along with particles, the need for a suitable solver for the reaction component of the species equations with regard to issues of stability, stiffness, economy, etc. becomes obvious. It is generally agreed in the literature that the major problem associated with the simultaneous integration of large sets of chemical kinetic rate equations is that of stiffness. Although stiffness does not have a simple definition, it is characterized by widely varying time constants. For example, in hydrogen-air combustion, the induction time is of the order of microseconds whereas the nitric oxide formation time is of the order of milliseconds. These widely different time constants present classical methods (such as the popular explicit Runge-Kutta method) with the following difficulty: to ensure stability of the numerical solution, these methods are restricted to using very short time steps that are determined by the smallest time constant. However, the time for all chemical species to reach near-equilibrium values is determined by the longest time constant. As a result, classical methods require excessive amounts of computer time to solve stiff systems of ordinary differential equations (ODE's). Several approaches for the solution of stiff ODE's have been proposed. Of all these techniques, the general purpose codes EPISODE and LSODE are regarded as the best available packaged'' codes for the solution of stiff systems of ODE'S. However, although these codes may be the best available for solving an arbitrary systems ODE'S, it may be possible to construct superior methods for solving a particular system of ODE's governing the behavior of a specific problem. In this view, an exponentially fitted method, CREK1D, deserves a special mention and is described briefly.
Design and Certification of Industrial Predictive Controllers
Dutta, Abhishek
2014-09-24T23:59:59.000Z
Procedure . . . . . . . . . . . . . . 4-6 4.4 Test case: Non-collocated mass-spring-damper . . . . . . . . . . 4-8 4.4.1 Mass-spring-damper setup . . . . . . . . . . . . . . . . . 4-8 4.4.2 PID control . . . . . . . . . . . . . . . . . . . . . . . . . 4-10 4... by distributed NMPC and (b): PID control. . . . . . . . . . . . . . . . . . . . . 6-15 6.7 (a): Learning the true motor damping coefficients by the distributed RLS method and (b): Robust performance of the distributed NMPC after learning the correct damping...
Eulerian CFD Models to Predict Thermophoretic Deposition of Soot...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Eulerian CFD Models to Predict Thermophoretic Deposition of Soot Particles in EGR Coolers Eulerian CFD Models to Predict Thermophoretic Deposition of Soot Particles in EGR Coolers...
Bioreactors Modeling and Control
Grossmann, Ignacio E.
Bioreactors Modeling and Control: Dealing with Complexity Dep. Of Chemical Engineering Federal Federal University of Săo Carlos Brazil 1 DEQDEQ #12;First things first: What is a bio-reactor, anyway - Bioreactors: · Enzymatic reactors · Cultivation of microorganisms/cells ("fermenters") ThyssenKrupp Stainless
Direct Manipulation for Comprehensible, Predictable and Controllable User Interfaces
Shneiderman, Ben
Direct Manipulation for Comprehensible, Predictable and Controllable User Interfaces Ben Direct manipulation user interfaces have proven their worth over two decades, but they are still in their youth. Dramatic opportunities exist to develop direct manipulation pro- gramming to create end
Combining Modeling and Gaming for Predictive Analytics
Riensche, Roderick M.; Whitney, Paul D.
2012-08-22T23:59:59.000Z
Many of our most significant challenges involve people. While human behavior has long been studied, there are recent advances in computational modeling of human behavior. With advances in computational capabilities come increases in the volume and complexity of data that humans must understand in order to make sense of and capitalize on these modeling advances. Ultimately, models represent an encapsulation of human knowledge. One inherent challenge in modeling is efficient and accurate transfer of knowledge from humans to models, and subsequent retrieval. The simulated real-world environment of games presents one avenue for these knowledge transfers. In this paper we describe our approach of combining modeling and gaming disciplines to develop predictive capabilities, using formal models to inform game development, and using games to provide data for modeling.
Young, R. Michael
Can Fault Prediction Models and Metrics be Used for Vulnerability Prediction? Yonghee Shin to prioritize security inspection and testing efforts may be better served by a prediction model that indicates commonalities that may allow development teams to use traditional fault prediction models and metrics
BEHAVIOR PREDICTION FOR DECISION AND CONTROL IN COGNITIVE AUTONOMOUS SYSTEMS
Ray, Asok
BEHAVIOR PREDICTION FOR DECISION AND CONTROL IN COGNITIVE AUTONOMOUS SYSTEMS ASOK RAY*, SHASHI for decision and control in cognitive autonomous systems. The objective is to coordinate human. 1. Introduction Modern human-engineered systems (e.g. power grid, communication, transportation
Using micro saint to predict performance in a nuclear power plant control room
Lawless, M.T.; Laughery, K.R. [Micro Analysis and Design, Inc., Boulder, CO (United States); Persenky, J.J. [Nuclear Regulatory Commission, Washington, DC (United States)
1995-09-01T23:59:59.000Z
The United States Nuclear Regulatory Commission (NRC) requires a technical basis for regulatory actions. In the area of human factors, one possible technical basis is human performance modeling technology including task network modeling. This study assessed the feasibility and validity of task network modeling to predict the performance of control room crews. Task network models were built that matched the experimental conditions of a study on computerized procedures that was conducted at North Carolina State University. The data from the {open_quotes}paper procedures{close_quotes} conditions were used to calibrate the task network models. Then, the models were manipulated to reflect expected changes when computerized procedures were used. These models` predictions were then compared to the experimental data from the {open_quotes}computerized conditions{close_quotes} of the North Carolina State University study. Analyses indicated that the models predicted some subsets of the data well, but not all. Implications for the use of task network modeling are discussed.
Solid Oxide Fuel Cell: Perspective of Dynamic Modeling and Control
Huang, Biao
Solid Oxide Fuel Cell: Perspective of Dynamic Modeling and Control Biao Huang Yutong Qi Monjur: This paper presents a review of state-of-the-art solid oxide fuel cells (SOFC), from perspective of dynamic. Keywords: Solid Oxide Fuel Cell, Control Relevant Model, Model Predictive Control 1. INTRODUCTION Today
Hybrid Modeling and Control of a Hydroelectric Power Plant
Ferrari-Trecate, Giancarlo
Hybrid Modeling and Control of a Hydroelectric Power Plant Giancarlo Ferrari-Trecate, Domenico,mignone,castagnoli,morari}@aut.ee.ethz.ch Abstract In this work we present the model of a hydroelectric power plant in the framework of Mixed Logic with a model predictive control scheme. 1 Introduction The outflow control for hydroelectric power plants
Risk prediction models for melanoma: A systematic review
Usher-Smith, Juliet A.; Emery, Jon; Kassianos, Angelos P.; Walter, Fiona M.
2014-06-03T23:59:59.000Z
of Cambridge, Cambridge, UK. 2 General Practice and Primary Care Academic Centre, University of Melbourne, Australia. 3 School of Primary, Aboriginal and Rural Health Care, University of Western Australia, Australia. Running title: Risk prediction models... :1000129. 35. English, DR, Armstrong, BK. Identifying people at high risk of cutaneous malignant melanoma: Results from a case-control study in Western Australia. Br. Med. J. (Clin. Res. Ed). 1988; 296: 1285–1288. 36. Amir, E, Freedman, OC, Seruga...
Disease Prediction Models and Operational Readiness
Corley, Courtney D.; Pullum, Laura L.; Hartley, David M.; Benedum, Corey M.; Noonan, Christine F.; Rabinowitz, Peter M.; Lancaster, Mary J.
2014-03-19T23:59:59.000Z
INTRODUCTION: The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. One of the primary goals of this research was to characterize the viability of biosurveillance models to provide operationally relevant information for decision makers to identify areas for future research. Two critical characteristics differentiate this work from other infectious disease modeling reviews. First, we reviewed models that attempted to predict the disease event, not merely its transmission dynamics. Second, we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011). Methods: We searched dozens of commercial and government databases and harvested Google search results for eligible models utilizing terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche-modeling, The publication date of search results returned are bound by the dates of coverage of each database and the date in which the search was performed, however all searching was completed by December 31, 2010. This returned 13,767 webpages and 12,152 citations. After de-duplication and removal of extraneous material, a core collection of 6,503 items was established and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. Next, PNNL’s IN-SPIRE visual analytics software was used to cross-correlate these publications with the definition for a biosurveillance model resulting in the selection of 54 documents that matched the criteria resulting Ten of these documents, However, dealt purely with disease spread models, inactivation of bacteria, or the modeling of human immune system responses to pathogens rather than predicting disease events. As a result, we systematically reviewed 44 papers and the results are presented in this analysis.
Prediction Intervals in Generalized Linear Mixed Models
Yang, Cheng-Hsueh
2013-01-01T23:59:59.000Z
3.1. BLP Based Prediction Intervals………………………………………..……3.2. BP Based Prediction Intervals………………..………………………..……4.1.1. BLP Based Prediction Interval………………………………………. 4.1.2.
Model Based Control Refrigeration Systems
Model Based Control of Refrigeration Systems Ph.D. Thesis Lars Finn Sloth Larsen Central R & D University, Denmark. The work has been carried out at the Central R&D - Refrigeration and Air Conditioning The subject for this Ph.D. thesis is model based control of refrigeration systems. Model based control covers
Gamma-Ray Pulsars: Models and Predictions
Alice K. Harding
2000-12-12T23:59:59.000Z
Pulsed emission from gamma-ray pulsars originates inside the magnetosphere, from radiation by charged particles accelerated near the magnetic poles or in the outer gaps. In polar cap models, the high energy spectrum is cut off by magnetic pair production above an energy that is dependent on the local magnetic field strength. While most young pulsars with surface fields in the range B = 10^{12} - 10^{13} G are expected to have high energy cutoffs around several GeV, the gamma-ray spectra of old pulsars having lower surface fields may extend to 50 GeV. Although the gamma-ray emission of older pulsars is weaker, detecting pulsed emission at high energies from nearby sources would be an important confirmation of polar cap models. Outer gap models predict more gradual high-energy turnovers at around 10 GeV, but also predict an inverse Compton component extending to TeV energies. Detection of pulsed TeV emission, which would not survive attenuation at the polar caps, is thus an important test of outer gap models. Next-generation gamma-ray telescopes sensitive to GeV-TeV emission will provide critical tests of pulsar acceleration and emission mechanisms.
MODELING AND CONTROL OF THERMOSTATICALLY CONTROLLED LOADS
Hiskens, Ian A.
controlled loads (TCLs) has demonstrated that such load following is feasible, but analyt- ical models) is well matched to the role of load following. Re- search into the behavior of TCLs began with the work was then employed in a minimum variance control law to demonstrate the load following capability of a population
Stimulation Prediction Models | Open Energy Information
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Predictive modelling of boiler fouling. Final report.
Chatwani, A
1990-12-31T23:59:59.000Z
A spectral element method embodying Large Eddy Simulation based on Re- Normalization Group theory for simulating Sub Grid Scale viscosity was chosen for this work. This method is embodied in a computer code called NEKTON. NEKTON solves the unsteady, 2D or 3D,incompressible Navier Stokes equations by a spectral element method. The code was later extended to include the variable density and multiple reactive species effects at low Mach numbers, and to compute transport of large particles governed by inertia. Transport of small particles is computed by treating them as trace species. Code computations were performed for a number of test conditions typical of flow past a deep tube bank in a boiler. Results indicate qualitatively correct behavior. Predictions of deposition rates and deposit shape evolution also show correct qualitative behavior. These simulations are the first attempts to compute flow field results at realistic flow Reynolds numbers of the order of 10{sup 4}. Code validation was not done; comparison with experiment also could not be made as many phenomenological model parameters, e.g., sticking or erosion probabilities and their dependence on experimental conditions were not known. The predictions however demonstrate the capability to predict fouling from first principles. Further work is needed: use of large or massively parallel machine; code validation; parametric studies, etc.
Predictable SCR co-benefits for mercury control
Pritchard, S. [Cormtech Inc. (USA)
2009-01-15T23:59:59.000Z
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.
Modeling and control of thermostatically controlled loads
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
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.
Zhang, YuMing
Control Engineering Practice 11 (2003) 1401Â1411 Modeling and control of quasi-keyhole arc welding to operate the keyhole arc welding process. Because the method's effectiveness depends on the amperage reserved. Keywords: Modeling; Predictive control; Manufacturing; Welding 1. Introduction Keyhole arc
A Simple HCCI Engine Model for Control
Killingsworth, N; Aceves, S; Flowers, D; Krstic, M
2006-06-29T23:59:59.000Z
The homogeneous charge compression ignition (HCCI) engine is an attractive technology because of its high efficiency and low emissions. However, HCCI lacks a direct combustion trigger making control of combustion timing challenging, especially during transients. To aid in HCCI engine control we present a simple model of the HCCI combustion process valid over a range of intake pressures, intake temperatures, equivalence ratios, and engine speeds. The model provides an estimate of the combustion timing on a cycle-by-cycle basis. An ignition threshold, which is a function of the in-cylinder motored temperature and pressure is used to predict start of combustion. This model allows the synthesis of nonlinear control laws, which can be utilized for control of an HCCI engine during transients.
A Predictive power control of Doubly Fed Induction Generator for Wave Energy Converter
Brest, Université de
A Predictive power control of Doubly Fed Induction Generator for Wave Energy Converter in Irregular there are several wave energy converters to harness this energy. Some of them, as in tidal applications, use based Wave Energy Converter under irregular wave climate which is modeled as time series elevation from
Developing Models for Predictive Climate Science
Drake, John B [ORNL; Jones, Philip W [Los Alamos National Laboratory (LANL)
2007-01-01T23:59:59.000Z
The Community Climate System Model results from a multi-agency collaboration designed to construct cutting-edge climate science simulation models for a broad research community. Predictive climate simulations are currently being prepared for the petascale computers of the near future. Modeling capabilities are continuously being improved in order to provide better answers to critical questions about Earth's climate. Climate change and its implications are front page news in today's world. Could global warming be responsible for the July 2006 heat waves in Europe and the United States? Should more resources be devoted to preparing for an increase in the frequency of strong tropical storms and hurricanes like Katrina? Will coastal cities be flooded due to a rise in sea level? The National Climatic Data Center (NCDC), which archives all weather data for the nation, reports that global surface temperatures have increased over the last century, and that the rate of increase is three times greater since 1976. Will temperatures continue to climb at this rate, will they decline again, or will the rate of increase become even steeper? To address such a flurry of questions, scientists must adopt a systematic approach and develop a predictive framework. With responsibility for advising on energy and technology strategies, the DOE is dedicated to advancing climate research in order to elucidate the causes of climate change, including the role of carbon loading from fossil fuel use. Thus, climate science--which by nature involves advanced computing technology and methods--has been the focus of a number of DOE's SciDAC research projects. Dr. John Drake (ORNL) and Dr. Philip Jones (LANL) served as principal investigators on the SciDAC project, 'Collaborative Design and Development of the Community Climate System Model for Terascale Computers.' The Community Climate System Model (CCSM) is a fully-coupled global system that provides state-of-the-art computer simulations of the Earth's past, present, and future climate states. The collaborative SciDAC team--including over a dozen researchers at institutions around the country--developed, validated, documented, and optimized the performance of CCSM using the latest software engineering approaches, computational technology, and scientific knowledge. Many of the factors that must be accounted for in a comprehensive model of the climate system are illustrated in figure 1.
Bayesian Models and Algorithms for Protein Beta-Sheet Prediction
Erdogan, Hakan
0 Bayesian Models and Algorithms for Protein Beta-Sheet Prediction Zafer Aydin, Student Member, IEEE, Yucel Altunbasak, Senior Member, IEEE, and Hakan Erdogan, Member, IEEE Abstract--Prediction of -sheet prediction defined as the prediction of -strand pairings, interaction types (parallel or anti
A case model for predictive maintenance
Li, Jiawei, M. Eng. Massachusetts Institute of Technology
2008-01-01T23:59:59.000Z
This project is to respond to a need by Varian Semiconductor Equipment Associates, Inc. (VSEA) to help predict failure of ion implanters. Predictive maintenance would help to reduce the unscheduled downtime of ion implanters, ...
Colliding cascades model for earthquake prediction
2000-10-12T23:59:59.000Z
3 International Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences, Moscow, Russia. 4 Department of Earth ...
Hybrid Model for Building Performance Diagnosis and Optimal Control
Wang, S.; Xu, X.
2003-01-01T23:59:59.000Z
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...
Model Predictability-Form Lorenz System to Operational Ocean and
Chu, Peter C.
Model Predictability- Form Lorenz System to Operational Ocean and Atmospheric Models Peter C Chu. Poberezhny, 2002: Power law decay in model predictability skill. Geophysical Research Letters, 29 (15), 10 Six Months Four-Times Daily Data From July 9, 1998 for Verification #12;Model Generated Velocity
Virtual Models for Prediction of Wind Turbine Parameters
Andrew Kusiak
Abstract—In this paper, a data-driven methodology for the development of virtual models of a wind turbine is presented. To demonstrate the proposed methodology, two parameters of the wind turbine have been selected for modeling, namely, power output and rotor speed. A virtual model for each of the two parameters is developed and tested with data collected at a wind farm. Both models consider controllable and noncontrollable parameters of the wind turbine, as well as the delay effect of wind speed and other parameters. To mitigate data bias of each virtual model and ensure its robustness, a training set is assembled from ten randomly selected turbines. The performance of a virtual model is largely determined by the input parameters selected and the data mining algorithms used to extract the model. Several data mining algorithms for parameter selection and model extraction are analyzed. The research presented in the paper is illustrated with computational results. Index Terms—Data mining, parameter selection, power prediction, virtual model, wind turbine. I.
Predictive control with Gaussian process models
Kocijan, J.; Murray-Smith, R.
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
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01T23:59:59.000Z
solution”. In: Energy and Buildings 52.0 (2012), pp. 39–49.with GenOpt”. In: Energy and Buildings 42.7 (2010), pp.lation Program”. In: Energy and Buildings 33.4 (2001), pp.
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01T23:59:59.000Z
chillers/cooling towers for energy conversion, an electricalconsuming energy are chillers, cooling towers, and pumps. Atconsuming energy are chillers, cooling towers, and pumps. It
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01T23:59:59.000Z
more sophisticated building automation systems and buildingthrough the building automation system “Automated Logic Websystem. ALC is a building automation system, offering a user
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01T23:59:59.000Z
Building thermal loadThe building thermal load predictor. . . . . . . .of Figures 1.1 Classification schematic for building MPC
Modeling And Control Of Articulated Vehicles
Chen, Chieh; Tomizuka, Masayoshi
1997-01-01T23:59:59.000Z
Modeling, Advanced Vehicle Control Systems, Lateral control, SteeringSteering and Braking Control of Heavy Duty Vehicles. Under this project, dynamic modeling
Schaltz, Erik
Predictive Direct Current Control in High Power PMSM Drive Systems M. Preindl1, 2 and E. Schaltz2 1. Power Magnet Synchronous Machine (PMSM), it contains an inner current i.e. torque control loop and an outer for Model Predictive Direct Current Control in High Power PMSM Drive Systems 555 Fig. 1 Block diagram
The myth of science-based predictive modeling.
Hemez, F. M. (François M.)
2004-01-01T23:59:59.000Z
A key aspect of science-based predictive modeling is the assessment of prediction credibility. This publication argues that the credibility of a family of models and their predictions must combine three components: (1) the fidelity of predictions to test data; (2) the robustness of predictions to variability, uncertainty, and lack-of-knowledge; and (3) the prediction accuracy of models in cases where measurements are not available. Unfortunately, these three objectives are antagonistic. A recently published Theorem that demonstrates the irrevocable trade-offs between fidelity-to-data, robustness-to-uncertainty, and confidence in prediction is summarized. High-fidelity models cannot be made increasingly robust to uncertainty and lack-of-knowledge. Similarly, robustness-to-uncertainty can only be improved at the cost of reducing the confidence in prediction. The concept of confidence in prediction relies on a metric for total uncertainty, capable of aggregating different representations of uncertainty (probabilistic or not). The discussion is illustrated with an engineering application where a family of models is developed to predict the acceleration levels obtained when impacts of varying levels propagate through layers of crushable hyper-foam material of varying thicknesses. Convex modeling is invoked to represent a severe lack-of-knowledge about the constitutive material behavior. The analysis produces intervals of performance metrics from which the total uncertainty and confidence levels are estimated. Finally, performance, robustness and confidence are extrapolated throughout the validation domain to assess the predictive power of the family of models away from tested configurations.
is proposed for the control of switching systems characterized by linear system dynamics with a time delay that will take the system closest to the desired future state. The resulting control action is sub-optimal by linear dynamics with a time-delayed input. A switching control system (as defined herein) is one
MODELING HORMONAL CONTROL MENSTRUAL CYCLE
MODELING HORMONAL CONTROL OF THE MENSTRUAL CYCLE James F. Selgrade Department of Mathematics of five hormones important for regulation and maintenance of the menstrual cycle. Models which correctly@math.ncsu.edu Abstract This study presents a strategy for developing a mathematical model describing the concentrations
Markovian Models for Electrical Load Prediction in Smart Buildings
California at Santa Barbara, University of
Markovian Models for Electrical Load Prediction in Smart Buildings Muhammad Kumail Haider, Asad,13100004,ihsan.qazi}@lums.edu.pk Abstract. Developing energy consumption models for smart buildings is important develop parsimo- nious Markovian models of smart buildings for different periods in a day for predicting
TROPICAL DEFORESTATION MODELLING: A COMPARATIVE ANALYSIS OF DIFFERENT PREDICTIVE APPROACHES.
Paris-Sud XI, UniversitĂ© de
TROPICAL DEFORESTATION MODELLING: A COMPARATIVE ANALYSIS OF DIFFERENT PREDICTIVE APPROACHES-time discretisation; Remote Sensing; Neural Networks; Markov Chains; MCE; Dinamica; Risk management; Deforestation
Hospital Readmission in General Medicine Patients: A Prediction Model
2010-01-01T23:59:59.000Z
to the department of medicine as a screening tool forquality of care problems. Medicine. 2008;87:294–300. 3.Readmission in General Medicine Patients: A Prediction Model
Martin, A; Venkatesan, Dr V Prasanna
2011-01-01T23:59:59.000Z
Today in every organization financial analysis provides the basis for understanding and evaluating the results of business operations and delivering how well a business is doing. This means that the organizations can control the operational activities primarily related to corporate finance. One way that doing this is by analysis of bankruptcy prediction. This paper develops an ontological model from financial information of an organization by analyzing the Semantics of the financial statement of a business. One of the best bankruptcy prediction models is Altman Z-score model. Altman Z-score method uses financial rations to predict bankruptcy. From the financial ontological model the relation between financial data is discovered by using data mining algorithm. By combining financial domain ontological model with association rule mining algorithm and Zscore model a new business intelligence model is developed to predict the bankruptcy.
Modeling and Control Interactive Networks
Amin, S. Massoud
Modeling and Control of Complex Interactive Networks By Massoud Amin E nergy, telecommunications complex networks, geographi- cally dispersed, nonlinear, and interacting both among themselves, distributed, highly interactive networks, nor does any such entity have the ability to evaluate, monitor
Tippett, Michael K. [Columbia University
2014-04-09T23:59:59.000Z
This report is a progress report of the accomplishments of the research grant “Collaborative Research: Separating Forced and Unforced Decadal Predictability in Models and Observa- tions” during the period 1 May 2011- 31 August 2013. This project is a collaborative one between Columbia University and George Mason University. George Mason University will submit a final technical report at the conclusion of their no-cost extension. The purpose of the proposed research is to identify unforced predictable components on decadal time scales, distinguish these components from forced predictable components, and to assess the reliability of model predictions of these components. Components of unforced decadal predictability will be isolated by maximizing the Average Predictability Time (APT) in long, multimodel control runs from state-of-the-art climate models. Components with decadal predictability have large APT, so maximizing APT ensures that components with decadal predictability will be detected. Optimal fingerprinting techniques, as used in detection and attribution analysis, will be used to separate variations due to natural and anthropogenic forcing from those due to unforced decadal predictability. This methodology will be applied to the decadal hindcasts generated by the CMIP5 project to assess the reliability of model projections. The question of whether anthropogenic forcing changes decadal predictability, or gives rise to new forms of decadal predictability, also will be investigated.
Predictive modeling of reactive wetting and metal joining.
van Swol, Frank B.
2013-09-01T23:59:59.000Z
The performance, reproducibility and reliability of metal joints are complex functions of the detailed history of physical processes involved in their creation. Prediction and control of these processes constitutes an intrinsically challenging multi-physics problem involving heating and melting a metal alloy and reactive wetting. Understanding this process requires coupling strong molecularscale chemistry at the interface with microscopic (diffusion) and macroscopic mass transport (flow) inside the liquid followed by subsequent cooling and solidification of the new metal mixture. The final joint displays compositional heterogeneity and its resulting microstructure largely determines the success or failure of the entire component. At present there exists no computational tool at Sandia that can predict the formation and success of a braze joint, as current capabilities lack the ability to capture surface/interface reactions and their effect on interface properties. This situation precludes us from implementing a proactive strategy to deal with joining problems. Here, we describe what is needed to arrive at a predictive modeling and simulation capability for multicomponent metals with complicated phase diagrams for melting and solidification, incorporating dissolutive and composition-dependent wetting.
Climate Prediction: The Limits of Ocean Models
Stone, Peter H.
We identify three major areas of ignorance which limit predictability in current ocean GCMs. One is the very crude representation of subgrid-scale mixing processes. These processes are parameterized with coefficients whose ...
Bootstrap Prediction for Returns and Volatilities in GARCH Models
Ortega, Esther Ruiz
Bootstrap Prediction for Returns and Volatilities in GARCH Models Lorenzo Pascuala , Juan Romob of GARCH processes is proposed. Financial market participants have shown an increasing interest Autoregressive Conditionally Heteroscedastic (GARCH) models, originally introduced by Bollerslev (1986), provide
Demonstrating the improvement of predictive maturity of a computational model
Hemez, Francois M [Los Alamos National Laboratory; Unal, Cetin [Los Alamos National Laboratory; Atamturktur, Huriye S [CLEMSON UNIV.
2010-01-01T23:59:59.000Z
We demonstrate an improvement of predictive capability brought to a non-linear material model using a combination of test data, sensitivity analysis, uncertainty quantification, and calibration. A model that captures increasingly complicated phenomena, such as plasticity, temperature and strain rate effects, is analyzed. Predictive maturity is defined, here, as the accuracy of the model to predict multiple Hopkinson bar experiments. A statistical discrepancy quantifies the systematic disagreement (bias) between measurements and predictions. Our hypothesis is that improving the predictive capability of a model should translate into better agreement between measurements and predictions. This agreement, in turn, should lead to a smaller discrepancy. We have recently proposed to use discrepancy and coverage, that is, the extent to which the physical experiments used for calibration populate the regime of applicability of the model, as basis to define a Predictive Maturity Index (PMI). It was shown that predictive maturity could be improved when additional physical tests are made available to increase coverage of the regime of applicability. This contribution illustrates how the PMI changes as 'better' physics are implemented in the model. The application is the non-linear Preston-Tonks-Wallace (PTW) strength model applied to Beryllium metal. We demonstrate that our framework tracks the evolution of maturity of the PTW model. Robustness of the PMI with respect to the selection of coefficients needed in its definition is also studied.
State Estimation for Force-Controlled Humanoid Balance using Simple Models in the Presence-based control frameworks, such as model predictive control (MPC), use the expected dynamics to generate that requires active balance control in the presence of modeling error. Primus humanoid shown in Figure 1
Summary & Implications Internal models adapt rapidly: Predictions
Kreiter, Andreas K.
Subjects Error-Bars: Standard Error * p motor control. · Heavytaileddistance distributions are con- sistent with removal of random trends to lower mean errors at the cost functionsmayinducediffer- ent control strategies and resulting dynam- ics 1-D Balancing with Highscore Distributions on Day
Fast prediction of transient stability margin in systems with SVC control and HVDC link
Tso, S.K. [City Univ. of Hong Kong (Hong Kong). Dept. of Manufacturing Engineering; Cheung, S.P. [ABB Transmission and Distribution Ltd., Hong Kong (Hong Kong). Dept. of Power Systems
1995-12-31T23:59:59.000Z
Recent developments in transient stability margin (TSM) prediction using the energy-based direct method have included excitation controllers, power system stabilizers (PSSs) and/or static VAr compensators (SVCs). These devices can be represented in their detailed dynamic models to desired degrees of complexity while the proposed extended equal-area criterion can still be effectively applied. This paper describes further development of this technique to incorporate an HVDC transmission into the test network for TSM prediction. The method is examined with a practical 17-machine power network representing the South China/Hong Kong system. An SVC control scheme is also installed in a weak bus of the test network for transient stability improvement. The results obtained show that there is no sacrifice in accuracy, speed or reliability of the TSM method with SVC and HVDC realistically incorporated into the study.
A probabilistic particle-control approximation of chance-constrained stochastic predictive control
Blackmore, Lars
Robotic systems need to be able to plan control actions that are robust to the inherent uncertainty in the real world. This uncertainty arises due to uncertain state estimation, disturbances, and modeling errors, as well ...
Estimation and prediction in spatial models with block composite likelihoods
Reich, Brian J.
Estimation and prediction in spatial models with block composite likelihoods Jo Eidsvik1 , Benjamin, IA 50011, U.S.A. (niemi@iastate.edu) 1 #12;Abstract A block composite likelihood is developed for estimation and prediction in large spatial datasets. The composite likelihood is constructed from the joint
Ensemble climate predictions using climate models and observational constraints
REVIEW Ensemble climate predictions using climate models and observational constraints BY PETER A. STOTT 1,* AND CHRIS E. FOREST 2 1 Hadley Centre for Climate Change (Reading Unit), Meteorology Building for constraining climate predictions based on observations of past climate change. The first uses large ensembles
Hierarchical Bayesian Models for Predicting The Spread of Ecological Processes
Hierarchical Bayesian Models for Predicting The Spread of Ecological Processes Christopher K. Wikle Department of Statistics, University of Missouri To appear: Ecology June 10, 2002 Key Words: Bayesian, Diffusion, Forecast, Hierarchical, House Finch, Invasive, Malthu- sian, State Space, Uncertainty Abstract
Predictive capacity planning modeling with tactical and strategic applications
Zeppieri, Michael A. (Michael Anthony), 1975-
2004-01-01T23:59:59.000Z
The focus of my internship was the development of a predictive capacity planning model to characterize the storage requirements and space utilization for Amazon's Campbellsville (SDF) Fulfillment Center (FC). Amazon currently ...
On the predictive capability and stability of rubber material models
Zheng, Haining
2008-01-01T23:59:59.000Z
Due to the high non-linearity and incompressibility constraint of rubber materials, the predictive capability and stability of rubber material models require specific attention for practical engineering analysis. In this ...
In silico modeling to predict drug-induced phospholipidosis
Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov; Sadrieh, Nakissa
2013-06-01T23:59:59.000Z
Drug-induced phospholipidosis (DIPL) is a preclinical finding during pharmaceutical drug development that has implications on the course of drug development and regulatory safety review. A principal characteristic of drugs inducing DIPL is known to be a cationic amphiphilic structure. This provides evidence for a structure-based explanation and opportunity to analyze properties and structures of drugs with the histopathologic findings for DIPL. In previous work from the FDA, in silico quantitative structure–activity relationship (QSAR) modeling using machine learning approaches has shown promise with a large dataset of drugs but included unconfirmed data as well. In this study, we report the construction and validation of a battery of complementary in silico QSAR models using the FDA's updated database on phospholipidosis, new algorithms and predictive technologies, and in particular, we address high performance with a high-confidence dataset. The results of our modeling for DIPL include rigorous external validation tests showing 80–81% concordance. Furthermore, the predictive performance characteristics include models with high sensitivity and specificity, in most cases above ? 80% leading to desired high negative and positive predictivity. These models are intended to be utilized for regulatory toxicology applied science needs in screening new drugs for DIPL. - Highlights: • New in silico models for predicting drug-induced phospholipidosis (DIPL) are described. • The training set data in the models is derived from the FDA's phospholipidosis database. • We find excellent predictivity values of the models based on external validation. • The models can support drug screening and regulatory decision-making on DIPL.
Predictive clothing insulation model based on outdoor air and indoor operative temperatures
Schiavon, Stefano; Lee, Kwang Ho
2012-01-01T23:59:59.000Z
2012) Predictive clothing insulation model based on outdoorPredictive clothing insulation model based on outdoor airpredictive models of clothing insulation have been developed
Settlement Prediction, Gas Modeling and Slope Stability Analysis
Politčcnica de Catalunya, Universitat
Settlement Prediction, Gas Modeling and Slope Stability Analysis in Coll Cardús Landfill Li Yu using mechanical models Simulation of gas generation, transport and extraction in MSW landfill 1 models Simulation of gas generation, transport and extraction in MSW landfill 1) Analytical solution
Conformal Higgs model: predicted dark energy density
R. K. Nesbet
2014-11-03T23:59:59.000Z
Postulated universal Weyl conformal scaling symmetry provides an alternative to the $\\Lambda$CDM paradigm for cosmology. Recent applications to galactic rotation velocities, Hubble expansion, and a model of dark galactic halos explain qualitative phenomena and fit observed data without invoking dark matter. Significant revision of theory relevant to galactic collisions and clusters is implied, but not yet tested. Dark energy is found to be a consequence of conformal symmetry for the Higgs scalar field of electroweak physics. The present paper tests this implication. The conformal Higgs model acquires a gravitational effect described by a modified Friedmann cosmic evolution equation, shown to fit cosmological data going back to the cosmic microwave background epoch. The tachyonic mass parameter of the Higgs model becomes dark energy in the Friedmann equation. A dynamical model of this parameter, analogous to the Higgs mechanism for gauge boson mass, is derived and tested here. An approximate calculation yields a result consistent with the empirical magnitude inferred from Hubble expansion.
Spatiotemporal discrimination model predicts temporal masking functions
CA 94035 a b Institute for Optical Research, Stockholm, Sweden W ABSTRACT e present a simplified dual, and masking based on local spatiotemporal contrast energy. The contras ensitivity filter parameters for the lack of spacetime l s separability in contrast detection, the model has separate sustained
Predictive microfluidic control of regulatory ligand trajectories in individual pluripotent cells
Zandstra, Peter W.
Predictive microfluidic control of regulatory ligand trajectories in individual pluripotent cells microfluidic perfusion culture demonstrated that STAT3 activation and consequently mESC fate were manipulable
A Scenario-based Predictive Control Approach to Building HVAC Management Systems
Johansson, Karl Henrik
A Scenario-based Predictive Control Approach to Building HVAC Management Systems Alessandra Parisio and Air Conditioning (HVAC) systems while minimizing the overall energy use. The strategy uses
Predictive modeling of pedestal structure in KSTAR using EPED model
Han, Hyunsun; Kim, J. Y. [National Fusion Research Institute, Daejeon 305-806 (Korea, Republic of)] [National Fusion Research Institute, Daejeon 305-806 (Korea, Republic of); Kwon, Ohjin [Department of Physics, Daegu University, Gyeongbuk 712-714 (Korea, Republic of)] [Department of Physics, Daegu University, Gyeongbuk 712-714 (Korea, Republic of)
2013-10-15T23:59:59.000Z
A predictive calculation is given for the structure of edge pedestal in the H-mode plasma of the KSTAR (Korea Superconducting Tokamak Advanced Research) device using the EPED model. Particularly, the dependence of pedestal width and height on various plasma parameters is studied in detail. The two codes, ELITE and HELENA, are utilized for the stability analysis of the peeling-ballooning and kinetic ballooning modes, respectively. Summarizing the main results, the pedestal slope and height have a strong dependence on plasma current, rapidly increasing with it, while the pedestal width is almost independent of it. The plasma density or collisionality gives initially a mild stabilization, increasing the pedestal slope and height, but above some threshold value its effect turns to a destabilization, reducing the pedestal width and height. Among several plasma shape parameters, the triangularity gives the most dominant effect, rapidly increasing the pedestal width and height, while the effect of elongation and squareness appears to be relatively weak. Implication of these edge results, particularly in relation to the global plasma performance, is discussed.
adaptive predictive control: Topics by E-print Network
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
applied to analyze the transient Antsaklis, Panos 44 ADAPTIVE ROBUST TRACKING CONTROL OF PRESSURE Engineering Websites Summary: 1---- 1 ADAPTIVE ROBUST TRACKING CONTROL OF...
Observer-Controllers for Output Regulation: the Internal Model Principle Revisited
Pao, Lucy Y.
Observer-Controllers for Output Regulation: the Internal Model Principle Revisited Jason H. Laks rejection;tracking;model predictive control;output feedback control 1 Introduction Output regulation, the design of an output regulating observer-controller is less clear. This latter approach is based
Towards Prediction-Based Prosthetic Control Pilarski PM1
Sutton, Richard S.
an approach to one of the principal open problems in multi-function myoelectric control--robust, ongoing-time machine learning, adaptive control, myoelectric control, prosthetics, assistive medical devices. Introduction Simultaneous myoelectric control of multiple joints remains a challenging unsolved problem [1
Predicting Vehicle Crashworthiness: Validation of Computer Models for
Berger, Jim
Predicting Vehicle Crashworthiness: Validation of Computer Models for Functional and Hierarchical. Cafeo, Chin-Hsu Lin, and Jian Tu Abstract The CRASH computer model simulates the effect of a vehicle colliding against different barrier types. If it accurately represents real vehicle crash- worthiness
New trends in vehicle dynamics: from modelling to control. Olivier SENAME
Paris-Sud XI, Université de
New trends in vehicle dynamics: from modelling to control. Olivier SENAME GIPSA-lab - Department approaches such as H approach for Linear Parameter Varying systems and Model predictive control have shown methods for modelling and control of subsystems and of the vehicle. The session will be organized
Hamiltonian control systems From modeling to analysis and control
Knobloch,Jürgen
Hamiltonian control systems From modeling to analysis and control Arjan van der Schaft Johann-based modeling 3 Definition of port-Hamiltonian systems 4 Scattering: from power variables to wave variables 5, University of Groningen, the Netherlands DiHamiltonian control systems Elgersburg School, March, 2012 1 / 108
A prediction based control scheme for networked systems with delays and packet dropouts
Knobloch,JĂĽrgen
A prediction based control scheme for networked systems with delays and packet dropouts Lars Gr based prediction and time-stamps in order to compensate for delays and packet dropouts to analyze the properties of our scheme, we introduce the notion of prediction consistency which enables us
Predictive Power Control of Doubly-Fed Induction Generator for Wave Energy Converters
Paris-Sud XI, Université de
Predictive Power Control of Doubly-Fed Induction Generator for Wave Energy Converters M.S. Lagoun1. There are several wave energy converters to harness this energy. Some of them, as in tidal applications, use of a DFIG-based Wave Energy Converter (WEC). In the proposed control approach, the predicted output power
A data-driven neuromuscular model of walking and its application to prosthesis control
Markowitz, Jared (Jared John)
2013-01-01T23:59:59.000Z
In this thesis we present a data-driven neuromuscular model of human walking and its application to prosthesis control. The model is novel in that it leverages tendon elasticity to more accurately predict the metabolic ...
Model based dependability evaluation for automotive control functions
Schlingloff, Holger
Model based dependability evaluation for automotive control functions Sasa Vulinovic 1 , Bernd@informatik.hu-berlin.de Abstract In this paper, we study the evaluation of reliability for embedded functions in automotive. In order to assess fault tolerant designs for automotive software it is essential to be able to predict
OPTIMAL CONTROL WITH ADAPTIVE INTERNAL DYNAMICS MODELS
Vijayakumar, Sethu
. The optimal feedback control law for systems with non-linear dynamics and non-quadratic costs can be foundOPTIMAL CONTROL WITH ADAPTIVE INTERNAL DYNAMICS MODELS Djordje Mitrovic, Stefan Klanke, and Sethu, optimal control, adaptive control, robot simulation Abstract: Optimal feedback control has been proposed
Lepton Flavor Violation in Predictive SUSY-GUT Models
Albright, Carl H.; /Northern Illinois U. /Fermilab; Chen, Mu-Chun; /UC, Irvine
2008-02-01T23:59:59.000Z
There have been many theoretical models constructed which aim to explain the neutrino masses and mixing patterns. While many of the models will be eliminated once more accurate determinations of the mixing parameters, especially sin{sup 2} 2{theta}{sub 13}, are obtained, charged lepton flavor violation (LFV) experiments are able to differentiate even further among the models. In this paper, they investigate various rare LFV processes, such as {ell}{sub i} {yields} {ell}{sub j} + {gamma} and {mu} - e conversion, in five predictive SUSY SO(10) models and their allowed soft SUSY breaking parameter space in the constrained minimal SUSY standard model (CMSSM). Utilizing the WMAP dark matter constraints, they obtain lower bounds on the branching ratios of these rare processes and find that at least three of the five models they consider give rise to predictions for {mu} {yields} e + {gamma} that will be tested by the MEG collaboration at PSI. in addition, the next generation {mu} - e conversion experiment has sensitivity to the predictions of all five models, making it an even more robust way to test these models. While generic studies have emphasized the dependence of the branching ratios of these rare processes on the reactor neutrino angle, {theta}{sub 13}, and the mass of the heaviest right-handed neutrino, M{sub 3}, they find very massive M{sub 3} is more significant than large {theta}{sub 13} in leading to branching ratios near to the present upper limits.
Predictive Validity of a Medication Adherence Measure for Hypertension Control
Morisky, Donald E
2008-01-01T23:59:59.000Z
and trained Community Hypertension Intervention Program (is available from the Hypertension Education Foundation P.O.treatment, and control of hypertension among United States
Model to predict the mechanical behaviour of oriented rigid PVC
Miroshnychenko, Dmitri
Model to predict the mechanical behaviour of oriented rigid PVC D. J. Hitt*1 and D. Miroshnychenko2 The mechanical properties of PVC sheets can be modified substantially by both uniaxial and biaxial stretching pattern in the relationship between tensile properties of oriented PVC products and imposed strains
Penetration rate prediction for percussive drilling via dry friction model
Krivtsov, Anton M.
Penetration rate prediction for percussive drilling via dry friction model Anton M. Krivtsov a of percussive drilling assuming a dry friction mechanism to explain the experimentally observed drop in pene as a frictional pair, and this can generate the pattern of the impact forces close to reality. Despite quite
Reference wind farm selection for regional wind power prediction models
Paris-Sud XI, Université de
1 Reference wind farm selection for regional wind power prediction models Nils Siebert George.siebert@ensmp.fr, georges.kariniotakis@ensmp.fr Abstract Short-term wind power forecasting is recognized today as a major requirement for a secure and economic integration of wind generation in power systems. This paper deals
The origins of computer weather prediction and climate modeling
Lynch, Peter [Meteorology and Climate Centre, School of Mathematical Sciences, University College Dublin, Belfield (Ireland)], E-mail: Peter.Lynch@ucd.ie
2008-03-20T23:59:59.000Z
Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.
Vehicle Trajectory Prediction based on Motion Model and Maneuver Recognition
Paris-Sud XI, Université de
Vehicle Trajectory Prediction based on Motion Model and Maneuver Recognition Adam Houenou, Philippe is a crucial task for an autonomous vehicle, in order to avoid collisions on its planned trajectory. It is also necessary for many Advanced Driver Assistance Systems, where the ego- vehicle's trajectory has
Predicting solar cycle 24 with a solar dynamo model
Arnab Rai Choudhuri; Piyali Chatterjee; Jie Jiang
2007-01-18T23:59:59.000Z
Whether the upcoming cycle 24 of solar activity will be strong or not is being hotly debated. The solar cycle is produced by a complex dynamo mechanism. We model the last few solar cycles by `feeding' observational data of the Sun's polar magnetic field into our solar dynamo model. Our results fit the observed sunspot numbers of cycles 21-23 extremely well and predict that cycle~24 will be about 35% weaker than cycle~23.
TRES predicts transcription control in embryonic stem cells.
Pooley, Christopher; Ruau, David; Lombard, Patrick; Gottgens, Berthold; Joshi, Anagha
2014-06-23T23:59:59.000Z
have developed a web tool called ‘Transcription Regulation in Embyonic Stem Cells’, or TRES for short, to link gene sets to likely upstream regulators in ES cells. *To whom correspondence should be addressed. 2 THE TRES PIPELINE Figure 1A... our understanding of normal development as well as disease. To facili- tate this, we have developed a novel web tool called ‘TRES’ that predicts the likely upstream regulators for a given gene list. This is achieved by integrating transcription...
A minimal and predictive $T_7$ lepton flavor 331 model
Hernández, A E Cárcamo
2015-01-01T23:59:59.000Z
We present a model based on the $SU(3)_{C}\\otimes SU(3)_{L}\\otimes U(1)_{X}$ gauge group having an extra $T_{7}\\otimes Z_{3}\\otimes Z_{14}$ flavor group, where the light active neutrino masses arise via double seesaw mechanism and the observed charged lepton mass hierarchy is a consequence of the $Z_{14}$ symmetry breaking at very high energy. In our minimal and predictive $T_7$ lepton flavor 331 model, the spectrum of neutrinos includes very light active neutrinos and heavy and very heavy sterile neutrinos. The obtained neutrino mixing parameters and neutrino mass squared splittings are compatible with the neutrino oscillation experimental data, for both normal and inverted hierarchies. The model predicts CP conservation in neutrino oscillations.
Model Predictability Depends on Model Fidelity: Challenges in...
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
and climate, and projections of climate change, show that current climate and Earth-system models continue to have stubborn irreducible errors. It is unlikely that the...
Prediction of Leptonic CP Phase in $A_4$ symmetric model
Sin Kyu Kang; Morimitsu Tanimoto
2015-01-29T23:59:59.000Z
We consider minimal modifications to tribimaximal (TBM) mixing matrix which accommodate non-zero mixing angle $\\theta_{13}$ and CP violation. We derive four possible forms for the minimal modifications to TBM mixing in a model with $A_4$ flavor symmetry by incorporating symmetry breaking terms appropriately. We show how possible values of the Dirac-type CP phase $\\delta_D$ can be predicted with regards to two neutrino mixing angles in the standard parametrization of the neutrino mixing matrix. Carrying out numerical analysis based on the recent updated experimental results for neutrino mixing angles, we predict the values of the CP phase for all possible cases. We also confront our predictions of the CP phase with the updated fit.
Kewlani, Gaurav
2009-01-01T23:59:59.000Z
The ability of autonomous or semi-autonomous unmanned ground vehicles (UGVs) to rapidly and accurately predict terrain negotiability, generate efficient paths online and have effective motion control is a critical requirement ...
Dynamical epidemic suppression using stochastic prediction and control Ira B. Schwartz
Billings, Lora
of stochastic dynamical sys- tems [13].) Other methods pulse the population without sam- pling for predictionDynamical epidemic suppression using stochastic prediction and control Ira B. Schwartz Plasma of stochastic processes with underlying deterministic structure. DOI: 10.1103/PhysRevE.70.046220 PACS number
Compiler And Runtime Support For Predictive Control Of Power And Cooling
Dietz, Henry G. "Hank"
1 Compiler And Runtime Support For Predictive Control Of Power And Cooling Henry G. Dietz William R clusters make significant demands on the power and cooling infrastructure. Minimizing the impact achieving the best system performance by predicting and avoiding power and cooling problems. Although
Predicting household occupancy for smart heating control: A comparative performance analysis of
, occupancy prediction, smart heating, energy management, smart home, energy efficiency Corresponding author.e. the household having too low a temperature when the residents come back home triggering the heatingPredicting household occupancy for smart heating control: A comparative performance analysis
AUTOMATIC GENERATION OF OPTIMAL CONTROLLERS THROUGH MODEL CHECKING TECHNIQUES
Tronci, Enrico
AUTOMATIC GENERATION OF OPTIMAL CONTROLLERS THROUGH MODEL CHECKING TECHNIQUES Giuseppe Della Penna Keywords: Controller Synthesis, Controller Optimization, Model Checking, Nonlinear Systems Abstract: We INTRODUCTION Control systems (or, shortly, controllers) are small hardware/software components that control
Stochastic Models Predict User Behavior in Social Media
Hogg, Tad; Smith, Laura M
2013-01-01T23:59:59.000Z
User response to contributed content in online social media depends on many factors. These include how the site lays out new content, how frequently the user visits the site, how many friends the user follows, how active these friends are, as well as how interesting or useful the content is to the user. We present a stochastic modeling framework that relates a user's behavior to details of the site's user interface and user activity and describe a procedure for estimating model parameters from available data. We apply the model to study discussions of controversial topics on Twitter, specifically, to predict how followers of an advocate for a topic respond to the advocate's posts. We show that a model of user behavior that explicitly accounts for a user transitioning through a series of states before responding to an advocate's post better predicts response than models that fail to take these states into account. We demonstrate other benefits of stochastic models, such as their ability to identify users who a...
A prediction of energy savings resulting from building infiltration control
McWatters, Kenneth Rob
1995-01-01T23:59:59.000Z
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...
Carbon-cycle models for better long-term predictions | EMSL
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
Carbon-cycle models for better long-term predictions Carbon-cycle models for better long-term predictions Released: November 04, 2014 Reduced variation among models should improve...
Clement, Prabhakar
modeling; Contaminant transport; Scaling; Numerical modeling 1. Introduction Management of groundwaterDevelopment of a scalable model for predicting arsenic transport coupled with oxidation is critical for predicting its transport dynamics in groundwater systems. We completed batch experiments
Prediction of interest rate using CKLS model with stochastic parameters
Ying, Khor Chia [Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor (Malaysia); Hin, Pooi Ah [Sunway University Business School, No. 5, Jalan Universiti, Bandar Sunway, 47500 Subang Jaya, Selangor (Malaysia)
2014-06-19T23:59:59.000Z
The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector ?{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j?-th time point where j?j??j+n. To model the variation of ?{sup (j)}, we assume that ?{sup (j)} depends on ?{sup (j?m)}, ?{sup (j?m+1)},…, ?{sup (j?1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d?2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.
Neutrino minimal standard model predictions for neutrinoless double beta decay
Bezrukov, F. [Institute for Nuclear Research of the Russian Academy of Sciences, 60th October Anniversary prospect 7a, Moscow 117312 (Russian Federation) and Institut de Theorie des Phenomenes Physiques, Ecole Polytechnique Federale de Lausanne, CH-1015 Lausanne (Switzerland)
2005-10-01T23:59:59.000Z
Prediction of the effective Majorana mass for neutrinoless double {beta} decay in a simple extension of the standard model ({nu}MSM) is given. The model adds three right-handed neutrinos with masses smaller than the electroweak scale and explains dark matter of the Universe. This leads to constraints 1.3
Fuel Conditioning Facility Electrorefiner Model Predictions versus Measurements
D Vaden
2007-10-01T23:59:59.000Z
Electrometallurgical treatment of spent nuclear fuel is performed in the Fuel Conditioning Facility (FCF) at the Idaho National Laboratory (INL) by electrochemically separating uranium from the fission products and structural materials in a vessel called an electrorefiner (ER). To continue processing without waiting for sample analyses to assess process conditions, an ER process model predicts the composition of the ER inventory and effluent streams via multicomponent, multi-phase chemical equilibrium for chemical reactions and a numerical solution to differential equations for electro-chemical transport. The results of the process model were compared to the electrorefiner measured data.
Modelling and Control of Activated Sludge Processes
Skogestad, Sigurd
Modelling and Control of Activated Sludge Processes Michela Mulas Dottorato di Ricerca of Activated Sludge Processes Michela Mulas Supervisors: Prof. Roberto Baratti Ing. Stefania Tronci Dottorato . . . . . . . . . . . . . . . . . . . . . . . . . 5 2 ASP Models and Simulations 7 2.1 The Activated Sludge Process
Predicting household occupancy for smart heating control: A comparative performance analysis of
, energy management, smart home, energy efficiency, thermostat strategy, heating setback Corresponding, a heating control system may require some time to heat a home to a comfortable temperature after itsPredicting household occupancy for smart heating control: A comparative performance analysis
Quantum Internal Model Principle: Decoherence Control
Narayan Ganesan; Tzyh-Jong Tarn
2010-12-10T23:59:59.000Z
In this article, we study the problem of designing a Decoherence Control for quantum systems with the help of a scalable ancillary quantum control and techniques from geometric control theory, in order to successfully and completely decouple an open quantum system from its environment. We re-formulate the problem of decoherence control as a disturbance rejection scheme which also leads us to the idea of Internal Model Principle for quantum control systems which is first of its kind in the literature. It is shown that decoupling a quantum disturbance from an open quantum system, is possible only with the help of a quantum controller which takes into account the model of the environmental interaction. This is demonstrated for a simple 2-qubit system wherein the effects of decoherence are completely eliminated. The theory provides conditions to be imposed on the controller to ensure perfect decoupling. Hence the problem of decoherence control naturally gives rise to the quantum internal model principle which relates the disturbance rejecting control to the model of the environmental interaction. Classical internal model principle and disturbance decoupling focus on different aspects viz. perfect output tracking and complete decoupling of output from external disturbances respectively. However for quantum systems, the two problems come together and merge in order to produce an effective platform for decoherence control. In this article we introduce a seminal connection between disturbance decoupling and the corresponding analog for internal model principle for quantum systems.
Modeling and Analysis ofModeling and Analysis of Hybrid Control SystemsHybrid Control Systems
Johansson, Karl Henrik
control systems, MOVEP, Bordeaux, 2006 Automatic gear boxAutomatic gear box #12;Karl H. Johansson, HybridModeling and Analysis ofModeling and Analysis of Hybrid Control SystemsHybrid Control Systems Karl.kth.se/~kallej MOVEP 2006, Bordeaux, France Karl H. Johansson, Hybrid control systems, MOVEP, Bordeaux
MODELING AND CONTROL OF A O2/CO2 GAS TURBINE CYCLE FOR CO2 CAPTURE
Foss, Bjarne A.
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
OFS model-based adaptive control for block-oriented non-linear Systems
Cambridge, University of
) and a heavy oil distillation column (Zhang et al., 2004b). Meanwhile, he has also made some theoretical processes such as distillation, pH neutralization control, hydro-control and chemical reactions linear model predictive control (MPC) based on a Laguerre series and successfully applied the scheme to p
Cardiovascular & Respiratory Modeling, Analysis & Control
Batzel, Jerry
Problem . . . . . . . . . . . . . 23 1.5 The Bicycle Ergometer Test eter identification problem . . . . . . . . . . . . . . 30 1.7 Numerical Results . . . . . . . . . . . . 47 2.1.2 The chemical control system for ventilation . . . . . 48 2.1.3 Structural features
Bürger, Raimund
Impact on sludge inventory and control strategies using the Benchmark Simulation Model No. 1 concentration predictions, plant sludge inventory and mixed liquor suspended solids based control actions-Diehl model allows for more realistic predictions of the underflow sludge concentration which is essential
An approach to model validation and model-based prediction -- polyurethane foam case study.
Dowding, Kevin J.; Rutherford, Brian Milne
2003-07-01T23:59:59.000Z
Enhanced software methodology and improved computing hardware have advanced the state of simulation technology to a point where large physics-based codes can be a major contributor in many systems analyses. This shift toward the use of computational methods has brought with it new research challenges in a number of areas including characterization of uncertainty, model validation, and the analysis of computer output. It is these challenges that have motivated the work described in this report. Approaches to and methods for model validation and (model-based) prediction have been developed recently in the engineering, mathematics and statistical literatures. In this report we have provided a fairly detailed account of one approach to model validation and prediction applied to an analysis investigating thermal decomposition of polyurethane foam. A model simulates the evolution of the foam in a high temperature environment as it transforms from a solid to a gas phase. The available modeling and experimental results serve as data for a case study focusing our model validation and prediction developmental efforts on this specific thermal application. We discuss several elements of the ''philosophy'' behind the validation and prediction approach: (1) We view the validation process as an activity applying to the use of a specific computational model for a specific application. We do acknowledge, however, that an important part of the overall development of a computational simulation initiative is the feedback provided to model developers and analysts associated with the application. (2) We utilize information obtained for the calibration of model parameters to estimate the parameters and quantify uncertainty in the estimates. We rely, however, on validation data (or data from similar analyses) to measure the variability that contributes to the uncertainty in predictions for specific systems or units (unit-to-unit variability). (3) We perform statistical analyses and hypothesis tests as a part of the validation step to provide feedback to analysts and modelers. Decisions on how to proceed in making model-based predictions are made based on these analyses together with the application requirements. Updating modifying and understanding the boundaries associated with the model are also assisted through this feedback. (4) We include a ''model supplement term'' when model problems are indicated. This term provides a (bias) correction to the model so that it will better match the experimental results and more accurately account for uncertainty. Presumably, as the models continue to develop and are used for future applications, the causes for these apparent biases will be identified and the need for this supplementary modeling will diminish. (5) We use a response-modeling approach for our predictions that allows for general types of prediction and for assessment of prediction uncertainty. This approach is demonstrated through a case study supporting the assessment of a weapons response when subjected to a hydrocarbon fuel fire. The foam decomposition model provides an important element of the response of a weapon system in this abnormal thermal environment. Rigid foam is used to encapsulate critical components in the weapon system providing the needed mechanical support as well as thermal isolation. Because the foam begins to decompose at temperatures above 250 C, modeling the decomposition is critical to assessing a weapons response. In the validation analysis it is indicated that the model tends to ''exaggerate'' the effect of temperature changes when compared to the experimental results. The data, however, are too few and to restricted in terms of experimental design to make confident statements regarding modeling problems. For illustration, we assume these indications are correct and compensate for this apparent bias by constructing a model supplement term for use in the model-based predictions. Several hypothetical prediction problems are created and addressed. Hypothetical problems are used because no guidance was provided concern
A Model to Predict Work-Related Fatigue Based on Hours of Work
A Model to Predict Work-Related Fatigue Based on Hours of Work Gregory D. Roach, Adam Fletcher, and Drew Dawson ROACH GD, FLETCHER A, DAWSON D. A model to predict work- related fatigue based on hours
Crucial stages of protein folding through a solvable model: Predicting target sites
Cecconi, Fabio
Crucial stages of protein folding through a solvable model: Predicting target sites for enzyme. Keywords: Protein-folding modeling; prediction of key folding sites; HIV-1 protease; drug resistance One
Development of a fourth generation predictive capability maturity model.
Hills, Richard Guy; Witkowski, Walter R.; Urbina, Angel; Rider, William J.; Trucano, Timothy Guy
2013-09-01T23:59:59.000Z
The Predictive Capability Maturity Model (PCMM) is an expert elicitation tool designed to characterize and communicate completeness of the approaches used for computational model definition, verification, validation, and uncertainty quantification associated for an intended application. The primary application of this tool at Sandia National Laboratories (SNL) has been for physics-based computational simulations in support of nuclear weapons applications. The two main goals of a PCMM evaluation are 1) the communication of computational simulation capability, accurately and transparently, and 2) the development of input for effective planning. As a result of the increasing importance of computational simulation to SNL's mission, the PCMM has evolved through multiple generations with the goal to provide more clarity, rigor, and completeness in its application. This report describes the approach used to develop the fourth generation of the PCMM.
Cardiovascular & Respiratory Modeling, Analysis & Control
Batzel, Jerry
of Grodins' system . . . . . 21 1.4 The Linear-quadratic Regulator Problem . . . . . . . . . . . . . 23 1-least-squares formulation of the param- eter identification problem . . . . . . . . . . . . . . 30 1.7 Numerical Results . . . . . . . . . . . . 47 2.1.2 The chemical control system for ventilation . . . . . 48 2.1.3 Structural features
Optimal Control of Building HVAC Systems in the Presence of Imperfect Predictions
Maasoumy, Mehdi; Sangiovanni-Vincentelli, Alberto
2014-01-01T23:59:59.000Z
minimization of building hvac systems using model predictivealgorithm design for hvac systems in energy efficient build-optimal control design for HVAC systems,” in Dynamic System
Rate controlling model for bioremediation of oil contaminated soil
Li, K.Y.; Annamali, S.N.; Hopper, J.R. (Lamar Univ., Beaumont, TX (United States))
1993-11-01T23:59:59.000Z
A mathematical model of bio-remediation of hydrocarbons in a soil matrix has been developed to predict the rate controlling step and the remediation rate during the bioremediation of a contaminated soil. The model is based on mass transfer of oxygen and oil into the aqueous solution in the soil matrix and the biodegradation of the hydrocarbons in the aqueous solution. Monod's equation was used to describe the biodegradation rate in aqueous solution while the mass transfer equations were used to describe the mass transfer rates of oxygen and oil in the soil matrix. Results from model calculations indicate that the bio-remediation rate increases and approaches a limiting value when one of the rates becomes controlling. When the parameters of the site soil samples are measured and the solubilities of oxygen and oil in aqueous solution are obtained, the bioremediation rate can be predicted by this model. The rate controlling step of the bioremediation site may be identified quickly and steps to improve the bioremediation rate can be recommended. 8 refs., 7 figs.
Modeling and control of genetic regulatory networks
Pal, Ranadip
2009-05-15T23:59:59.000Z
MODELING AND CONTROL OF GENETIC REGULATORY NETWORKS A Dissertation by RANADIP PAL Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY August 2007 Major... Subject: Electrical Engineering MODELING AND CONTROL OF GENETIC REGULATORY NETWORKS A Dissertation by RANADIP PAL Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of DOCTOR...
Modelling Monsoons: Understanding and Predicting Current and Future Behaviour
Turner, A; Sperber, K R; Slingo, J M; Meehl, G A; Mechoso, C R; Kimoto, M; Giannini, A
2008-09-16T23:59:59.000Z
The global monsoon system is so varied and complex that understanding and predicting its diverse behaviour remains a challenge that will occupy modellers for many years to come. Despite the difficult task ahead, an improved monsoon modelling capability has been realized through the inclusion of more detailed physics of the climate system and higher resolution in our numerical models. Perhaps the most crucial improvement to date has been the development of coupled ocean-atmosphere models. From subseasonal to interdecadal timescales, only through the inclusion of air-sea interaction can the proper phasing and teleconnections of convection be attained with respect to sea surface temperature variations. Even then, the response to slow variations in remote forcings (e.g., El Nino-Southern Oscillation) does not result in a robust solution, as there are a host of competing modes of variability that must be represented, including those that appear to be chaotic. Understanding the links between monsoons and land surface processes is not as mature as that explored regarding air-sea interactions. A land surface forcing signal appears to dominate the onset of wet season rainfall over the North American monsoon region, though the relative role of ocean versus land forcing remains a topic of investigation in all the monsoon systems. Also, improved forecasts have been made during periods in which additional sounding observations are available for data assimilation. Thus, there is untapped predictability that can only be attained through the development of a more comprehensive observing system for all monsoon regions. Additionally, improved parameterizations - for example, of convection, cloud, radiation, and boundary layer schemes as well as land surface processes - are essential to realize the full potential of monsoon predictability. Dynamical considerations require ever increased horizontal resolution (probably to 0.5 degree or higher) in order to resolve many monsoon features including, but not limited to, the Mei-Yu/Baiu sudden onset and withdrawal, low-level jet orientation and variability, and orographic forced rainfall. Under anthropogenic climate change many competing factors complicate making robust projections of monsoon changes. Without aerosol effects, increased land-sea temperature contrast suggests strengthened monsoon circulation due to climate change. However, increased aerosol emissions will reflect more solar radiation back to space, which may temper or even reduce the strength of monsoon circulations compared to the present day. A more comprehensive assessment is needed of the impact of black carbon aerosols, which may modulate that of other anthropogenic greenhouse gases. Precipitation may behave independently from the circulation under warming conditions in which an increased atmospheric moisture loading, based purely on thermodynamic considerations, could result in increased monsoon rainfall under climate change. The challenge to improve model parameterizations and include more complex processes and feedbacks pushes computing resources to their limit, thus requiring continuous upgrades of computational infrastructure to ensure progress in understanding and predicting the current and future behavior of monsoons.
RESIDUA UPGRADING EFFICIENCY IMPROVEMENT MODELS: COKE FORMATION PREDICTABILITY MAPS
John F. Schabron; A. Troy Pauli; Joseph F. Rovani Jr.
2002-05-01T23:59:59.000Z
The dispersed particle solution model of petroleum residua structure was used to develop predictors for pyrolytic coke formation. Coking Indexes were developed in prior years that measure how near a pyrolysis system is to coke formation during the coke formation induction period. These have been demonstrated to be universally applicable for residua regardless of the source of the material. Coking onset is coincidental with the destruction of the ordered structure and the formation of a multiphase system. The amount of coke initially formed appears to be a function of the free solvent volume of the original residua. In the current work, three-dimensional coke make predictability maps were developed at 400 C, 450 C, and 500 C (752 F, 842 F, and 932 F). These relate residence time and free solvent volume to the amount of coke formed at a particular pyrolysis temperature. Activation energies for two apparent types of zero-order coke formation reactions were estimated. The results provide a new tool for ranking residua, gauging proximity to coke formation, and predicting initial coke make tendencies.
Predictive control and thermal energy storage for optimizing a multi-energy district boiler
Paris-Sud XI, UniversitĂ© de
Predictive control and thermal energy storage for optimizing a multi- energy district boiler Julien energy storage. 1. Introduction Managing energy demand, promoting renewable energy and finding ways of the OptiEnR research project, the present paper deals with optimizing the multi-energy district boiler
Methods to Improve Process Safety Performance through Flange Connection Leak Prediction and Control
Nelson, Jeremy
2014-08-08T23:59:59.000Z
of their parent asset. This thesis focuses on methods to improve prediction and control of corrosion and leakage at flange connections in particular. Flange connection seal tightness can be monitored through vibration-based Non-Destruction Testing (NDT). The data...
Use of Linear Predictive Control for a Solar Electric Generating System
Wisconsin at Madison, University of
behavior can be used to design and operate plants. The solar power plant is characterized by significant1 Use of Linear Predictive Control for a Solar Electric Generating System Thorsten Stuetzle, Nathan Blair, William A. Beckman, John W. Mitchell Solar Energy Laboratory University of Wisconsin-Madison 1500
Modeling, Analysis, and Control of Demand Response Resources
Mathieu, Johanna L.
2013-01-01T23:59:59.000Z
Modeling and control of aggregated heterogeneous thermostatically controlled loads for ancillary services”. In: Proceedings of the Power SystemsModeling and control of thermostatically controlled loads”. In: Pro- ceedings of 17 th Power Systems
Modeling, Analysis, and Control of Demand Response Resources
Mathieu, Johanna L.
2012-01-01T23:59:59.000Z
Modeling and control of aggregated heterogeneous thermostatically controlled loads for ancillary services”. In: Proceedings of the Power SystemsModeling and control of thermostatically controlled loads”. In: Pro- ceedings of 17 th Power Systems
Prediction of Regulation Reserve Requirements in California ISO Control Area based on BAAL Standard
Etingov, Pavel V.; Makarov, Yuri V.; Samaan, Nader A.; Ma, Jian; Loutan, Clyde
2013-07-21T23:59:59.000Z
This paper presents new methodologies developed at Pacific Northwest National Laboratory (PNNL) to estimate regulation capacity requirements in the California ISO control area. Two approaches have been developed: (1) an approach based on statistical analysis of actual historical area control error (ACE) and regulation data, and (2) an approach based on balancing authority ACE limit control performance standard. The approaches predict regulation reserve requirements on a day-ahead basis including upward and downward requirements, for each operating hour of a day. California ISO data has been used to test the performance of the proposed algorithms. Results show that software tool allows saving up to 30% on the regulation procurements cost .
LIFETIME PREDICTION FOR MODEL 9975 O-RINGS IN KAMS
Hoffman, E.; Skidmore, E.
2009-11-24T23:59:59.000Z
The Savannah River Site (SRS) is currently storing plutonium materials in the K-Area Materials Storage (KAMS) facility. The materials are packaged per the DOE 3013 Standard and transported and stored in KAMS in Model 9975 shipping packages, which include double containment vessels sealed with dual O-rings made of Parker Seals compound V0835-75 (based on Viton{reg_sign} GLT). The outer O-ring of each containment vessel is credited for leaktight containment per ANSI N14.5. O-ring service life depends on many factors, including the failure criterion, environmental conditions, overall design, fabrication quality and assembly practices. A preliminary life prediction model has been developed for the V0835-75 O-rings in KAMS. The conservative model is based primarily on long-term compression stress relaxation (CSR) experiments and Arrhenius accelerated-aging methodology. For model development purposes, seal lifetime is defined as a 90% loss of measurable sealing force. Thus far, CSR experiments have only reached this target level of degradation at temperatures {ge} 300 F. At lower temperatures, relaxation values are more tolerable. Using time-temperature superposition principles, the conservative model predicts a service life of approximately 20-25 years at a constant seal temperature of 175 F. This represents a maximum payload package at a constant ambient temperature of 104 F, the highest recorded in KAMS to date. This is considered a highly conservative value as such ambient temperatures are only reached on occasion and for short durations. The presence of fiberboard in the package minimizes the impact of such temperature swings, with many hours to several days required for seal temperatures to respond proportionately. At 85 F ambient, a more realistic but still conservative value, bounding seal temperatures are reduced to {approx}158 F, with an estimated seal lifetime of {approx}35-45 years. The actual service life for O-rings in a maximum wattage package likely lies higher than the estimates due to the conservative assumptions used for the model. For lower heat loads at similar ambient temperatures, seal lifetime is further increased. The preliminary model is based on several assumptions that require validation with additional experiments and longer exposures at more realistic conditions. The assumption of constant exposure at peak temperature is believed to be conservative. Cumulative damage at more realistic conditions will likely be less severe but is more difficult to assess based on available data. Arrhenius aging behavior is expected, but non-Arrhenius behavior is possible. Validation of Arrhenius behavior is ideally determined from longer tests at temperatures closer to actual service conditions. CSR experiments will therefore continue at lower temperatures to validate the model. Ultrasensitive oxygen consumption analysis has been shown to be useful in identifying non-Arrhenius behavior within reasonable test periods. Therefore, additional experiments are recommended and planned to validate the model.
Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov [Science and Research Staff, Office of Pharmaceutical Science, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993–0002 (United States); Cross, Kevin P. [Leadscope, Inc., 1393 Dublin Road, Columbus, OH, 43215–1084 (United States)] [Leadscope, Inc., 1393 Dublin Road, Columbus, OH, 43215–1084 (United States)
2012-05-01T23:59:59.000Z
Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structure–activity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describe the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. -- Highlights: ? We characterize a new in silico model to predict mutagenicity of drug impurities. ? The model predicts Salmonella mutagenicity and will be useful for safety assessment. ? We examine toxicity fingerprints and toxicophores of this Ames assay model. ? We compare these attributes to those found in drug impurities known to FDA/CDER. ? We validate the model and find it has a desired predictive performance.
Prediction of Physico-Chemical Properties for REACH Based on QSPR Models
Paris-Sud XI, Université de
Prediction of Physico-Chemical Properties for REACH Based on QSPR Models Guillaume Fayeta models have been developed for the prediction of flash points of two families of organic compounds respected all OECD validation principles with excellent performances in predictivity, the one dedicated
Prediction of tree diameter growth using quantile regression and mixed-effects models
Cao, Quang V.
Prediction of tree diameter growth using quantile regression and mixed-effects models Som B. Bohora diameter predictions for the same tree in the future. Another approach considered in this study involved and mixed-effects models in predicting tree diameter growth. Tree diameter at the end of each growth period
Chaos control in traffic flow models
Elman Mohammed Shahverdiev; Shin-ichi Tadaki
1998-11-30T23:59:59.000Z
Chaos control in some of the one- and two-dimensional traffic flow dynamical models in the mean field theory is studied.One dimensional model is investigated taking into account the effect of random delay. Two dimensional model takes into account the effects of overpasses, symmetric distribution of cars and blockages of cars moving in the same direction. Chaos synchronization is performed within both replica and nonreplica approaches, and using parameter perturbation method.
Predictability and reduced order modeling in stochastic reaction networks.
Najm, Habib N.; Debusschere, Bert J.; Sargsyan, Khachik
2008-10-01T23:59:59.000Z
Many systems involving chemical reactions between small numbers of molecules exhibit inherent stochastic variability. Such stochastic reaction networks are at the heart of processes such as gene transcription, cell signaling or surface catalytic reactions, which are critical to bioenergy, biomedical, and electrical storage applications. The underlying molecular reactions are commonly modeled with chemical master equations (CMEs), representing jump Markov processes, or stochastic differential equations (SDEs), rather than ordinary differential equations (ODEs). As such reaction networks are often inferred from noisy experimental data, it is not uncommon to encounter large parametric uncertainties in these systems. Further, a wide range of time scales introduces the need for reduced order representations. Despite the availability of mature tools for uncertainty/sensitivity analysis and reduced order modeling in deterministic systems, there is a lack of robust algorithms for such analyses in stochastic systems. In this talk, we present advances in algorithms for predictability and reduced order representations for stochastic reaction networks and apply them to bistable systems of biochemical interest. To study the predictability of a stochastic reaction network in the presence of both parametric uncertainty and intrinsic variability, an algorithm was developed to represent the system state with a spectral polynomial chaos (PC) expansion in the stochastic space representing parametric uncertainty and intrinsic variability. Rather than relying on a non-intrusive collocation-based Galerkin projection [1], this PC expansion is obtained using Bayesian inference, which is ideally suited to handle noisy systems through its probabilistic formulation. To accommodate state variables with multimodal distributions, an adaptive multiresolution representation is used [2]. As the PC expansion directly relates the state variables to the uncertain parameters, the formulation lends itself readily to sensitivity analysis. Reduced order modeling in the time dimension is accomplished using a Karhunen-Loeve (KL) decomposition of the stochastic process in terms of the eigenmodes of its covariance matrix. Subsequently, a Rosenblatt transformation relates the random variables in the KL decomposition to a set of independent random variables, allowing the representation of the system state with a PC expansion in those independent random variables. An adaptive clustering method is used to handle multimodal distributions efficiently, and is well suited for high-dimensional spaces. The spectral representation of the stochastic reaction networks makes these systems more amenable to analysis, enabling a detailed understanding of their functionality, and robustness under experimental data uncertainty and inherent variability.
Schiavon, Stefano; Lee, Kwang Ho
2013-01-01T23:59:59.000Z
Predictive Clothing Insulation Models based on Outdoor AirPREDICTIVE CLOTHING INSULATION MODELS ON BUILDING ENERGYthat the clothing insulation is equal to a constant value of
Reference Model for Control and Automation Systems in Electrical...
Office of Environmental Management (EM)
Model for Control and Automation Systems in Electrical Power (October 2005) Reference Model for Control and Automation Systems in Electrical Power (October 2005) Modern...
Advanced LD Engine Systems and Emissions Control Modeling and...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
LD Engine Systems and Emissions Control Modeling and Analysis Advanced LD Engine Systems and Emissions Control Modeling and Analysis 2012 DOE Hydrogen and Fuel Cells Program and...
Demonstrating and Validating a Next Generation Model-Based Controller...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
and Validating a Next Generation Model-Based Controller for Fuel Efficient, Low Emissions Diesel Engines Demonstrating and Validating a Next Generation Model-Based Controller for...
Experimental Studies for DPF and SCR Model, Control System, and...
Broader source: Energy.gov (indexed) [DOE]
DPF and SCR Model, Control System, and OBD Development for Engines Using Diesel and Biodiesel Fuels Experimental Studies for DPF and SCR Model, Control System, and OBD...
Advanced PHEV Engine Systems and Emissions Control Modeling and...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
PHEV Engine Systems and Emissions Control Modeling and Analysis Advanced PHEV Engine Systems and Emissions Control Modeling and Analysis 2011 DOE Hydrogen and Fuel Cells Program,...
Advanced HD Engine Systems and Emissions Control Modeling and...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
HD Engine Systems and Emissions Control Modeling and Analysis Advanced HD Engine Systems and Emissions Control Modeling and Analysis 2012 DOE Hydrogen and Fuel Cells Program and...
Model based control of a coke battery
Stone, P.M.; Srour, J.M.; Zulli, P. [BHP Research, Mulgrave (Australia). Melbourne Labs.; Cunningham, R.; Hockings, K. [BHP Steel, Pt Kembla, New South Wales (Australia). Coal and Coke Technical Development Group
1997-12-31T23:59:59.000Z
This paper describes a model-based strategy for coke battery control at BHP Steel`s operations in Pt Kembla, Australia. The strategy uses several models describing the battery thermal and coking behavior. A prototype controller has been installed on the Pt Kembla No. 6 Battery (PK6CO). In trials, the new controller has been well accepted by operators and has resulted in a clear improvement in battery thermal stability, with a halving of the standard deviation of average battery temperature. Along with other improvements to that battery`s operations, this implementation has contributed to a 10% decrease in specific battery energy consumption. A number of enhancements to the low level control systems on that battery are currently being undertaken in order to realize further benefits.
A Forward Looking Version of the MIT Emissions Prediction and Policy Analysis (EPPA) Model
Babiker, Mustafa M.H.
This paper documents a forward looking multi-regional general equilibrium model developed from the latest version of the recursive-dynamic MIT Emissions Prediction and Policy Analysis (EPPA) model. The model represents ...
Babiker, Mustafa H.M.; Reilly, John M.; Mayer, Monika.; Eckaus, Richard S.; Sue Wing, Ian.; Hyman, Robert C.
The Emissions Prediction and Policy Analysis (EPPA) model is a component of the MIT Integrated Earth Systems Model (IGSM). Here, we provide an overview of the model accessible to a broad audience and present the detailed ...
The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4
Paltsev, Sergey.
The Emissions Prediction and Policy Analysis (EPPA) model is the part of the MIT Integrated Global Systems Model (IGSM) that represents the human systems. EPPA is a recursive-dynamic multi-regional general equilibrium model ...
Air Leakage of U.S. Homes: Model Prediction
Sherman, Max H.; McWilliams, Jennifer A.
2007-01-01T23:59:59.000Z
Air tightness is an important property of building envelopes. It is a key factor in determining infiltration and related wall-performance properties such as indoor air quality, maintainability and moisture balance. Air leakage in U.S. houses consumes roughly 1/3 of the HVAC energy but provides most of the ventilation used to control IAQ. The Lawrence Berkeley National Laboratory has been gathering residential air leakage data from many sources and now has a database of more than 100,000 raw measurements. This paper uses a model developed from that database in conjunction with US Census Bureau data for estimating air leakage as a function of location throughout the US.
Toward understanding predictability of climate: a linear stochastic modeling approach
Wang, Faming
2004-11-15T23:59:59.000Z
(E?) ? ; (2.29) which represents the predictable information(Schneider and Gri?es, 1999). In our case here, it is convenient to work with a derived quantity which we call predictive power loss (PPL) PPL(?) = e? 2nI(?x; x) = det ?E?C?1?1=n (2.30) after... the predictive power (PP) of Schneider and Gri?es (1999). Using the properties of positive de?nite matrix, one can show 0 6 PPL 6 1. It is consistent with ?(?) in the sense that PPL(0) = 0 and PPL(?1) = 1. The predictive power loss has some nice mathematical...
An Analytical Model for Predicting the Remaining Battery Capacity of Lithium-Ion Batteries
Pedram, Massoud
An Analytical Model for Predicting the Remaining Battery Capacity of Lithium-Ion Batteries Peng cycle-life tends to shrink significantly. The capacities of commercial lithium-ion batteries fade by 10 prediction model to estimate the remaining capacity of a Lithium-Ion battery. The proposed analytical model
Model for the prediction of 3D surface topography in 5-axis milling
Paris-Sud XI, Université de
1 Model for the prediction of 3D surface topography in 5-axis milling Sylvain Lavernhe LURPA - ENS surface topography obtained in 5-axis milling in function of the machining conditions. For this purpose to a feed rate prediction model. Thanks to the simulation model of 3D surface topography, the influence
Model predictive control for energy efficient cooling and dehumidification
Zakula, Tea
2013-01-01T23:59:59.000Z
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 ...
Model Predictive Control of Residential Energy Systems Using
Knobloch,Jürgen
generation technologies such as solar photovoltaics and wind turbines are leading to undesirable voltage network infrastructure and can lead to a degradation of power quality and even outages. In response, a local energy storage element, and solar photovoltaic panels. Each RES is connected to the wider
Model Predictive Control in Power Electronics: A Hybrid Systems Approach
Sontag, Eduardo
to transform electrical power from one usually unregulated form to another regulated one (consider e of semiconductor devices that operate as power switches, turning on and off with a high switching frequency. From of an underlying optimization problem. Given the high switching frequency used in power electronics app
Model Predictive Control of a Wind Aleksander Gosk
-3192 #12;Summary In the era of growing interest in limiting CO2 emission and our dependence on fossil fuels are aiming for maximizing the produced electric power for some range of wind speeds and keeping it constant
Economic and Distributed Model Predictive Control of Nonlinear Systems
Heidarinejad, Mohsen
2012-01-01T23:59:59.000Z
steady-state rate of heat supply to the reactor, V repre-denotes the rate of heat supply to the reactor, V represents
Modeling of boron control during power transients in a pressurized water reactor
Mathieu, P.; Distexhe, E.
1986-02-01T23:59:59.000Z
Accurate control instructions in a reactor control aid computer are included in order to realize the boron makeup throughput, which is required to obtain the boron concentration in the primary coolant loop, predicted by a neutronic code. A modeling of the transfer function between the makeup and the primary loop is proposed. The chemical and volumetric control system, the pressurizer, and the primary loop are modeled as instantaneous diffusion cells. The pipes are modeled as time lag lines. The model provides the unstationary boron distributions in the different elements of the setup. A numerical code is developed to calculate the time evolutions of the makeup throughput during power transients.
An invisible axion model with controlled FCNCs at tree level
Alejandro Celis; Javier Fuentes-Martin; Hugo Serodio
2015-01-04T23:59:59.000Z
We derive the necessary conditions to build a class of invisible axion models with Flavor Changing Neutral Currents at tree-level controlled by the fermion mixing matrices and present an explicit model implementation. A horizontal Peccei-Quinn symmetry provides a solution to the strong CP problem via the Peccei-Quinn mechanism and predicts a cold dark mater candidate, the invisible axion or familon. The smallness of active neutrino masses can be explained via a type I seesaw mechanism, providing a dynamical origin for the heavy seesaw scale. The possibility to avoid the domain wall problem stands as one of the most interesting features of the type of models considered. Experimental limits relying on the axion-photon coupling, astrophysical considerations and familon searches in rare kaon and muon decays are discussed.
Modeling Metal Fatigue As a Key Step in PV Module Life Time Prediction (Presentation)
Bosco, N.
2012-02-01T23:59:59.000Z
This presentation covers modeling metal fatigue as a key step in photovoltaic (PV) module lifetime predictions. Described are time-dependent and time-independent case studies.
Dynamic predictive clothing insulation models based on outdoor air and indoor operative temperatures
Schiavon, Stefano; Lee, Kwang Ho
2012-01-01T23:59:59.000Z
predictive clothing insulation models based on outdoor airrange of the clothing insulation calculated for eachbuilding). Figure 8 Clothing insulation versus dress code [
Influence of two dynamic predictive clothing insulation models on building energy performance
Lee, Kwang Ho; Schiavon, Stefano
2013-01-01T23:59:59.000Z
Predictive Clothing Insulation Models on Building Energyunnecessarily higher clothing insulation and lower heatingthat the constant clothing insulation assumption lead to the
Damage Modeling and Life Extending Control of a Boiler-Turbine System1
Marquez, Horacio J.
for the development of life-prediction systems. Many methods for estimating fatigue life were proposed on which lifeDamage Modeling and Life Extending Control of a Boiler-Turbine System1 Donglin Li Tongwen Chen2 of the system. For model I, we incorporate the improved rainflow cycle counting method and a continuous
Model Identification for Optimal Diesel Emissions Control
Stevens, Andrew J.; Sun, Yannan; Song, Xiaobo; Parker, Gordon
2013-06-20T23:59:59.000Z
In this paper we develop a model based con- troller for diesel emission reduction using system identification methods. Specifically, our method minimizes the downstream readings from a production NOx sensor while injecting a minimal amount of urea upstream. Based on the linear quadratic estimator we derive the closed form solution to a cost function that accounts for the case some of the system inputs are not controllable. Our cost function can also be tuned to trade-off between input usage and output optimization. Our approach performs better than a production controller in simulation. Our NOx conversion efficiency was 92.7% while the production controller achieved 92.4%. For NH3 conversion, our efficiency was 98.7% compared to 88.5% for the production controller.
, and it is on those time scales of interest to water managers that decadal climate prediction is being appliedThe rapidly evolving field of decadal climate prediction, using initialized climate models to produce time-evolving predictions of regional climate, is producing new results for predictions
Prediction of Channel State for Cognitive Radio Using Higher-Order Hidden Markov Model
Qiu, Robert Caiming
Prediction of Channel State for Cognitive Radio Using Higher-Order Hidden Markov Model Zhe Chen implementation. Prediction can be utilized to diminish the negative effect of such latency. In this paper, this latency is illustrated, and an approach for prediction of channel state using higher-order hidden Markov
Introduction to the model-free control of microgrids
Michel, Loďc
2011-01-01T23:59:59.000Z
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.
Edward H. Hellen; J. Keith Thomas
2010-01-14T23:59:59.000Z
Chaotic behavior can be produced from difference equations with unstable fixed points. Difference equations can be used for algorithms to control the chaotic behavior by perturbing a system parameter using feedback based on the first difference of the system value. This results in a system of nonlinear first order difference equations whose stable fixed point is the controlled chaotic behavior. Basing the feedback on the first difference produces distinctly different transient responses than when basing feedback on the error from the fixed point. Analog electronic circuits provide the experimental system for testing the chaos control algorithm. The circuits are low-cost, relatively easy to construct, and therefore provide a useful transition towards more specialized real-world applications. Here we present predictions and experimental results for the transient responses of a first difference based feedback control method applied to a chaotic finite difference 1-dimensional map. The experimental results are in good agreement with predictions, showing a variety of behaviors for the transient response, including erratic appearing non-steady convergence.
Burlatsky, S F; O'Neill, J; Atrazhev, V V; Varyukhin, A N; Dmitriev, D V; Erikhman, N S
2013-01-01T23:59:59.000Z
Under typical PEM fuel cell operating conditions, part of membrane electrode assembly is subjected to humidity cycling due to variation of inlet gas RH and/or flow rate. Cyclic membrane hydration/dehydration would cause cyclic swelling/shrinking of the unconstrained membrane. In a constrained membrane, it causes cyclic stress resulting in mechanical failure in the area adjacent to the gas inlet. A mathematical modeling framework for prediction of the lifetime of a PEM FC membrane subjected to hydration cycling is developed in this paper. The model predicts membrane lifetime as a function of RH cycling amplitude and membrane mechanical properties. The modeling framework consists of three model components: a fuel cell RH distribution model, a hydration/dehydration induced stress model that predicts stress distribution in the membrane, and a damage accrual model that predicts membrane life-time. Short descriptions of the model components along with overall framework are presented in the paper. The model was used...
USING PARAMETERIZED UML TO SPECIFY AND COMPOSE ACCESS CONTROL MODELS
Ray, Indrakshi
USING PARAMETERIZED UML TO SPECIFY AND COMPOSE ACCESS CONTROL MODELS Indrakshi Ray, Na Li, Dae is to model the access control frameworks, compose the models, and analyze the resulting model to identify problems. In this pa- per we outline a technique for modeling and composing access control policy
Locating Pleistocene refugia: Comparing phylogeographic and ecological niche model predictions
Waltari, Eric; Hijmans, Robert J.; Peterson, A. Townsend; Nyá ri, Á rpá d S.; Perkins, Susan L.; Guralnick, Robert P.
2007-07-11T23:59:59.000Z
, American Museum of Natural History, New York, New York, United States of America, 2 International Rice Research Institute, Los Banos, Laguna, Philippines, 3Natural History Museum & Biodiversity Research Center, University of Kansas, Lawrence, Kansas.... Refugia identified in phylogeographic studies are shown as black outlines. Areas predicted to be refugia are in green, areas not predicted are in gray, and hatching indicates approximate locations of ice sheets [68]. Gray lines indicate present day...
Hindi, Haitham; Prabhakar, Shyam; Fox, John D.; Linscott, Ivan; Teytelman, Dmitri; /SLAC
2011-08-31T23:59:59.000Z
We present a technique for the design and verification of efficient bunch-by-bunch controllers for damping longitudinal multibunch instabilities. The controllers attempt to optimize the use of available feedback amplifier power - one of the most expensive components of a feedback system - and define the limits of the closed loop system performance. Our design technique alternates between analytic computation of single bunch optimal controllers and verification on a multibunch numerical simulator. The simulator uses PEP-II parameters and identifies unstable coupled bunch modes, their growth rates and their damping rates with feedback. The results from the simulator are shown to be in reasonable agreement with analytical calculations based on the single bunch model. The technique is then used to evaluate the performance of a variety of controllers proposed for PEP-II.
A Benchmark of Computational Models of Saliency to Predict Human Fixations
Judd, Tilke
2012-01-13T23:59:59.000Z
Many computational models of visual attention have been created from a wide variety of different approaches to predict where people look in images. Each model is usually introduced by demonstrating performances on new ...
Predicting regeneration establishment with the prognosis model. Forest Service research paper
Ferguson, D.E.; Carlson, C.E.
1993-08-01T23:59:59.000Z
The conifer establishment following regeneration timber harvests is predicted by version 2 of the Regeneration Establishment Model, a submodel of the Prognosis Model. The regeneration model covers 10 species for forests in Montana, central Idaho, and northern Idaho. Most harvest and site preparation methods can be simulated so that alternative treatments can be evaluated. Also included in the model is the influence of western spruce budworm (Choristoneura occidentalis) on regeneration success. The model predicts the probability of stocking, seedling density, species composition, and seedling heights 2 to 20 years after harvest. The paper describes the study design, equation development, model formulation, and model behavior for the Regeneration Establishment Model.
A New Empirical Model for Predicting Single-Sided, Wind-Driven Natural Ventilation in Buildings
Chen, Qingyan "Yan"
A New Empirical Model for Predicting Single-Sided, Wind-Driven Natural Ventilation in Buildings-sided natural ventilation is difficult due to the bi-directional flow at the opening and the complex flow around buildings. A new empirical model was developed that can predict the mean ventilation rate and fluctuating
Statistical prediction of aircraft trajectory: regression methods vs point-mass model
Paris-Sud XI, Université de
the altitude of climbing aircraft. In addition to the standard linear regression model, two common non-linear, BADA, linear regression, neural networks, Loess. INTRODUCTION Predicting aircraft trajectoriesStatistical prediction of aircraft trajectory: regression methods vs point-mass model M. Ghasemi
A graphical model approach for predicting free energies of association for protein-protein
Langmead, Christopher James
A graphical model approach for predicting free energies of association for protein University, Pittsburgh, PA 1 Corresponding Author: cjl@cs.cmu.edu #12;Keywords: Graphical Models, Free Energy in free energy, and the ability to predict binding free energies provides both better understanding
Matchstick: A Room-to-Room Thermal Model for Predicting Indoor Temperature from Wireless Sensor Data
Hazas, Mike
that our model can predict future indoor temperature trends with a 90th percentile aggregate error between thermo- stat actuates the heating, ventilation, and air condition- ing (HVAC) infrastructure to bring and these energy approaches, a heating model could allow future temperature trends to be predicted using
Smith, Alice E.
A Predictive Model for Slip Resistance Using Artificial Neural Networks Janet M. Twomey, IIE Artificial Neural Networks Why This Paper is Important Slips and falls are a serious ergonomic problem a slip resistance testing device were used to develop an artificial neural network model which predicts
Genetic Algorithm for Predicting Protein Folding in the 2D HP Model
Emmerich, Michael
Genetic Algorithm for Predicting Protein Folding in the 2D HP Model A Parameter Tuning Case Study of a protein, predicting its tertiary structure is known as the protein folding problem. This problem has been. The protein folding problem in the HP model is to find a conformation (a folded sequence) with the lowest
Oxford, University of
A forward microphysical model to predict the size- distribution parameters of laboratory generated Interactions Â Condensational Growth and Coagulation, Submitted for Indian Aerosol Science and Technology Microphysical Model for the UTLS (FAMMUS) is applied to predict the size-distribution parameters of laboratory
Prediction Models for a Smart Home based Health Care System Vikramaditya R. Jakkula1
Cook, Diane J.
Prediction Models for a Smart Home based Health Care System Vikramaditya R. Jakkula1 , Diane J health care. Smart health care systems at home can be used to provide such solutions. A technology a prediction model in an intelligent smart home system can be used for identifying health trends over time
The US National Multi-Model Ensemble ISI Prediction System Ben Kirtman (University of Miami)
Miami, University of
The US National Multi-Model Ensemble ISI Prediction System Ben Kirtman (University of Miami) The newly emerging US National Multi-Model Ensemble (NMME) sub-seasonal to interannual (ISI) prediction includes experimental real-time ISI forecasting that leverages existing CTB partner activities. The NMME
MODELING AND VERIFICATION OF AN ATM PORT CONTROLLER IN VIS
Tahar, SofiĂ¨ne
MODELING AND VERIFICATION OF AN ATM PORT CONTROLLER IN VIS Jianping Lu and SofiĂ¨ne Tahar Dept port controller using model checking. The ATM port controller is part of the Cambridge Fairisle ATM on the model checking of the ATM port controller using the VIS tool from UC Berkeley. To this end, we
Paris-Sud XI, UniversitĂ© de
- net Synchronous Machines (PMSM) drives. The first control scheme predicts the future evolution a model of the PMSM in order to predict the stator voltages which allows to reach the desired currents frequency on the same test-bench (1.6kW PMSM drive). A simulation study is performed in order to compare
Modeling Combustion Control for High Power Diesel Mode Switching...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Combustion Control for High Power Diesel Mode Switching Modeling Combustion Control for High Power Diesel Mode Switching Poster presentation given at the 16th Directions in...
Paris-Sud XI, Université de
the second one on force [4][5]. In order to synthesize a controller for the manipulation force, a model is necessary. However, it is known that the model linking this manipulation force and the input controlRobust control for a class of interval model: application to the force control of piezoelectric
Uncertainty, Performance, and Model Dependency in Approximate Adaptive Nonlinear Control
Szepesvari, Csaba
Uncertainty, Performance, and Model Dependency in Approximate Adaptive Nonlinear Control M. French, and the performance of a class of approximate model based adaptive controllers is studied. An upper performance bound uncertainty model; control effort bounds require both L 2 and L 1 uncertainty models), and various structural
On Model Based Synthesis of Embedded Control Software Vadim Alimguzhin
Tronci, Enrico
Model Based Design approaches for control software. Given the formal model of a plant as a Discrete Time addresses model based synthesis of control software by trading system level non-functional requirementsOn Model Based Synthesis of Embedded Control Software Vadim Alimguzhin Federico Mari Igor Melatti
Watney, W.L.
1992-01-01T23:59:59.000Z
Interdisciplinary studies of the Upper Pennsylvanian Lansing and Kansas City groups have been undertaken in order to improve the geologic characterization of petroleum reservoirs and to develop a quantitative understanding of the processes responsible for formation of associated depositional sequences. To this end, concepts and methods of sequence stratigraphy are being used to define and interpret the three-dimensional depositional framework of the Kansas City Group. The investigation includes characterization of reservoir rocks in oil fields in western Kansas, description of analog equivalents in near-surface and surface sites in southeastern Kansas, and construction of regional structural and stratigraphic framework to link the site specific studies. Geologic inverse and simulation models are being developed to integrate quantitative estimates of controls on sedimentation to produce reconstructions of reservoir-bearing strata in an attempt to enhance our ability to predict reservoir characteristics.
Overview of Neutrino Mixing Models and Their Mixing Angle Predictions
Albright, Carl H.
2009-11-01T23:59:59.000Z
An overview of neutrino-mixing models is presented with emphasis on the types of horizontal flavor and vertical family symmetries that have been invoked. Distributions for the mixing angles of many models are displayed. Ways to differentiate among the models and to narrow the list of viable models are discussed.
Numerical and analytical modeling of sanding onset prediction
Yi, Xianjie
2004-09-30T23:59:59.000Z
results vary with the selection of one or another rock strength criterion. In this work, we present four commonly used rock strength criteria in sanding onset prediction and wellbore stability studies: Mohr-Coulomb, Hoek-Brown, Drucker-Prager, and Modified...
Predictive Linear Regression Model for Microinverter Internal Temperature
Rollins, Andrew M.
, photovoltaic (PV) module temperature, irradiance and AC power data. Time-series environmental, temperature prediction, reliabil- ity, photovoltaic systems. I. INTRODUCTION PV modules equipped with microinverters have system. Reliability of microinverters in harsh and extreme real- world outdoor operating conditions has
MOLECULAR MODELING OF PROTEINS AND MATHEMATICAL PREDICTION OF PROTEIN STRUCTURE
Neumaier, Arnold
called protein folding problem. The static aspect is concerned with how to predict the folded (native, tertiary at solutions to the protein folding problem. Key words. protein folding, molecular mechanics, transition states. This socalled protein folding problem is one of the most challenging problems in current bio chemistry
MOLECULAR MODELING OF PROTEINS AND MATHEMATICAL PREDICTION OF PROTEIN STRUCTURE
Neumaier, Arnold
-called protein folding problem. The static aspect is concerned with how to predict the folded (native, tertiary at solutions to the protein folding problem. Key words. protein folding, molecular mechanics, transition states. This so-called protein folding problem is one of the most challenging problems in current bio- chemistry
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
Predictive Simulation of Bidirectional Glenn Shunt Using a Hybrid Blood Vessel Model
Leow, Wee Kheng
Predictive Simulation of Bidirectional Glenn Shunt Using a Hybrid Blood Vessel Model Hao Li1 to model the deformation of blood vessels. The hybrid blood vessel model consists of a reference Cosserat rod and a surface mesh. The reference Cosserat rod models the blood vessel's global bending
Human walking model predicts joint mechanics, electromyography and mechanical economy
Endo, Ken
In this paper, we present an under-actuated model of human walking, comprising only a soleus muscle and flexion/extension monoarticular hip muscles. The remaining muscle groups of the human leg are modeled using quasi-passive, ...
On the Predictive Uncertainty of a Distributed Hydrologic Model
Cho, Huidae
2009-05-15T23:59:59.000Z
.2.2. Sampling strategy for high diversity . . . . . . . . . . 34 3.2.3. Isolated speciation . . . . . . . . . . . . . . . . . . . 36 3.2.4. Fitness assimilation . . . . . . . . . . . . . . . . . . . 39 3.2.5. Nesting criteria for global and local optima... unique optimal solution Beven (2006a). There may exist even mathematically inferior solutions, often referred to as local optima, that provide more realistic predictions. However, it is not straight- forward to find local optima using global optimization...
Nguyen, Ba Nghiep; Kunc, Vlastimil; Jin, Xiaoshi; Tucker III, Charles L.; Costa, Franco
2013-12-18T23:59:59.000Z
This article illustrates the predictive capabilities for long-fiber thermoplastic (LFT) composites that first simulate the injection molding of LFT structures by Autodesk® Simulation Moldflow® Insight (ASMI) to accurately predict fiber orientation and length distributions in these structures. After validating fiber orientation and length predictions against the experimental data, the predicted results are used by ASMI to compute distributions of elastic properties in the molded structures. In addition, local stress-strain responses and damage accumulation under tensile loading are predicted by an elastic-plastic damage model of EMTA-NLA, a nonlinear analysis tool implemented in ABAQUS® via user-subroutines using an incremental Eshelby-Mori-Tanaka approach. Predicted stress-strain responses up to failure and damage accumulations are compared to the experimental results to validate the model.
The Operating Regime Approach to Nonlinear Modelling and Control
Johansen, T.A.; Murray-Smith, R.
Johansen,T.A. Murray-Smith,R. Multiple Model Approaches to Modelling and Control pp 3-72 Taylor and Francis
Sleep Dynamics and Seizure Control in a Mesoscale Cortical Model
Lopour, Beth Ann
2009-01-01T23:59:59.000Z
Contributions . . . . . . . . . 2 Mesoscale Cortical Modelstates in h e from the mesoscale cortical model, here- afterand Seizure Control in a Mesoscale Cortical Model by Beth
Predicting hurricane regional landfall rates: comparing local and basin-wide track model approaches
Hall, T; Hall, Tim; Jewson, Stephen
2006-01-01T23:59:59.000Z
We compare two methods for making predictions of the climatological distribution of the number of hurricanes making landfall along short sections of the North American coastline. The first method uses local data, and the second method uses a basin-wide track model. Using cross-validation we show that the basin-wide track model gives better predictions for almost all parts of the coastline. This is the first time such a comparison has been made, and is the first rigourous justification for the use of basin-wide track models for predicting hurricane landfall rates and hurricane risk.
Using Model Checking for Analyzing Distributed Power Control Problems
Paris-Sud XI, Université de
1 Using Model Checking for Analyzing Distributed Power Control Problems Thomas Brihaye, Marc. Realizing that the distributed power control (PC) problem can be modeled by a timed game between a given Distributed power control, game theory, interference channel, model checking, timed games, verification
Analyzing and Developing Role-Based Access Control Models
Sheldon, Nathan D.
Analyzing and Developing Role-Based Access Control Models by Liang Chen A thesis submitted-based access control (RBAC) has become today's dominant access control model, and many of its theoretical and practical aspects are well understood. However, certain aspects of more advanced RBAC models
Preprint submitted to SAE Optimal Control Based Modeling of
Stryk, Oskar von
Preprint submitted to SAE Optimal Control Based Modeling of Vehicle Driver Properties Torsten Butz. On the stabilization level, a nonlinear position controller guides the full vehicle dynamics model along the prescribed operation and at the driving limits. In the following, we investigate an optimal control based model
A Provenance-based Access Control Model Jaehong Park
Sandhu, Ravi
A Provenance-based Access Control Model Jaehong Park Institute for Cyber Security University of protecting provenance data. In this paper, we propose a novel provenance-based access control model additional capabilities beyond those available in traditional access control models. We utilize a notion
Modeling and Analysis of Multi-Hop Control Networks
Alur, Rajeev
Modeling and Analysis of Multi-Hop Control Networks Rajeev Alur1 , Alessandro D'Innocenzo1,2 , Karl on control performance is needed. In this paper, we propose a formal model for analyzing the joint dynamics of the system, we define a switched system that models the dynamics of the composed multi-hop control network
A Hybrid Model and MIMO Control for Intelligent Buildings Temperature
Boyer, Edmond
A Hybrid Model and MIMO Control for Intelligent Buildings Temperature Regulation over WSN Emmanuel is to propose a model-based feedback control strategy for indoor temperature regulation in buildings equipped. In order to set a model-based Fig. 1. UFAD ventilation control approach, we first investigate
Automatic Model Complexity Control Using Marginalized Discriminative Growth Functions
Hain, Thomas
Automatic model complexity control . Most LVCSR systems are trained on large amounts of data. . ManyAutomatic Model Complexity Control Using Marginalized Discriminative Growth Functions X. Liu & M. J. J. F. Gales: Automatic Model Complexity Control Using Marginalized Discriminative Growth Functions
Development of Chemical Model to Predict the Interactions between...
Broader source: Energy.gov (indexed) [DOE]
large domain size and multiple realizations. * Model calibration and verification (End of project) - We will collect data from literature, extrapolate existing data and conduct...
Gray, Jeffrey G.
Model Comparison: A Key Challenge for Transformation Testing and Version Control in Model Driven practices associated with model transformation testing and version control of models. 1. Introduction target model). #12;Â· Version Control Tools do not Match the Structural Nature of Models An essential
Prediction of Solid Polycyclic Aromatic Hydrocarbons Solubility in Water with the NRTL-PR Model
Paris-Sud XI, Université de
Prediction of Solid Polycyclic Aromatic Hydrocarbons Solubility in Water with the NRTL-PR Model of solid polycyclic aromatic hydrocarbons in water. For this purpose, we first validate our methodology for fluid phase equilibria predictions of aromatic hydrocarbons and gas (CO2, C2H6) mixtures. Finally, we
Predicting the net carbon exchanges of crop rotations in Europe with an agro-ecosystem model
Boyer, Edmond
Predicting the net carbon exchanges of crop rotations in Europe with an agro-ecosystem model S.Lehuger@art.admin.ch. Fax: (+41) 44 377 72 01. Phone: (+41) 44 377 75 13. hal-00414342,version2-1Sep2010 #12;Abstract Carbon and measuring land-atmosphere carbon exchanges from arable lands are important tasks to predict the influence
Ventilation performance prediction for buildings: Model Assessment Qingyan Chena,b,*
Chen, Qingyan "Yan"
1 Ventilation performance prediction for buildings: Model Assessment Qingyan Chena,b,* , Kisup Leeb ventilation systems for buildings requires a suitable tool to assess the system performance-scale experimental, multizone network, zonal, and CFD) for predicting ventilation performance in buildings, which can
Cerpa, Alberto E.
A Occupancy Modeling and Prediction for Building Energy Management Varick L. Erickson, University.Cerpa, University of California, Merced Heating, cooling and ventilation accounts for 35% energy usage in the United and Prediction for Building Energy Management and Auditing. ACM Trans. Sensor Netw. V, N, Article A (August 2012
Paris-Sud XI, Université de
Non-asymptotic Adaptive Prediction in Functional Linear Models ´Elodie Brunel, Andr´e Mas, and Angelina Roche I3M, Universit´e Montpellier II Abstract Functional linear regression has recently attracted. Functional linear regression, functional principal components analysis, mean squared prediction error
Towards Accurate and Practical Predictive Models of Active-Vision-Based Visual Search
Hornof, Anthony
which permit increasingly realistic and accurate predictions for visual human-computer interaction tasks not practical. For as long as human-computer interaction has been studied, researchers have been working@cs.uoregon.edu ABSTRACT Being able to predict the performance of interface designs using models of human cognition
USING LEARNING MACHINES TO CREATE SOLAR RADIATION MAPS FROM NUMERICAL WEATHER PREDICTION MODELS,
Paris-Sud XI, UniversitĂ© de
USING LEARNING MACHINES TO CREATE SOLAR RADIATION MAPS FROM NUMERICAL WEATHER PREDICTION MODELS to develop a methodology to generate solar radiation maps using information from different sources. First with conclusions and next works in the last section. Keywords: Solar Radiation maps, Numerical Weather Predictions
`TVLSI-00029-2003.R1 An Analytical Model for Predicting the Remaining Battery
Pedram, Massoud
. Reference [7] studied the battery discharge efficiency under different loading conditions and approximated`TVLSI-00029-2003.R1 1 An Analytical Model for Predicting the Remaining Battery Capacity of Lithium-Ion Batteries Peng Rong, Student Member, IEEE and Massoud Pedram, Fellow, IEEE Abstract -- Predicting
Discrepancies in the Prediction of Solar Wind using Potential Field Source Surface Model: An
Zhao, Xuepu
Discrepancies in the Prediction of Solar Wind using Potential Field Source Surface Model. This inverse relation has been made use of in the prediction of solar wind speed at 1 AU using a potential between the magnetic flux tube expansion factor (FTE) at the source surface and the solar wind speed
Model Formulation and Predictions for a Pyrotechnically Actuated Pin Puller*
) actuated pin puller. The conservation principles are written as a set of ordinary differential equations-stirred reactor is simulated. These assumptions generally restrict the validity of the model to regimes near a formulation of the model in terms of the mass, momentum, and energy principles supplemented by appropriate
Dontsova, K.; Steefel, C.I.; Desilets, S.; Thompson, A.; Chorover, J.
2009-07-15T23:59:59.000Z
A reactive transport geochemical modeling study was conducted to help predict the mineral transformations occurring over a ten year time-scale that are expected to impact soil hydraulic properties in the Biosphere 2 (B2) synthetic hillslope experiment. The modeling sought to predict the rate and extent of weathering of a granular basalt (selected for hillslope construction) as a function of climatic drivers, and to assess the feedback effects of such weathering processes on the hydraulic properties of the hillslope. Flow vectors were imported from HYDRUS into a reactive transport code, CrunchFlow2007, which was then used to model mineral weathering coupled to reactive solute transport. Associated particle size evolution was translated into changes in saturated hydraulic conductivity using Rosetta software. We found that flow characteristics, including velocity and saturation, strongly influenced the predicted extent of incongruent mineral weathering and neo-phase precipitation on the hillslope. Results were also highly sensitive to specific surface areas of the soil media, consistent with surface reaction controls on dissolution. Effects of fluid flow on weathering resulted in significant differences in the prediction of soil particle size distributions, which should feedback to alter hillslope hydraulic conductivities.
Gosavi, Abhijit
Pollution Control in a Manufacturing System Stochastic Models for Analysis and Control of Air Pollution in a Manufacturing System Jan, 1, 2005 Technical Report SOPTL-05-01 Missouri University of Science models that can be used for controlling pollution in a manufacturing system. The models are developed
Evaluation of short-term climate change prediction in multi-model CMIP5 decadal hindcasts
Webster, Peter J.
events such as trop- ical cyclone activity. On decadal timescales, some aspects of internal climate skill of individual models have been analyzed separately for multi-year prediction horizons over
Application of the cumulative risk model in predicting school readiness in Head Start children
Rodriguez-Escobar, Olga Lydia
2009-05-15T23:59:59.000Z
outcomes. This study built on this literature by investigating how child, parent, and family risk factors predicted school readiness in Head Start children using two statistical models. Specific aims of this study included identifying 1) to what degree...
McDonald, Jennifer Nicole
2012-07-16T23:59:59.000Z
The present study investigated the extent to which importance ratings (i.e., a measure of perceived importance for driving-related concepts) are a viable alternative to traditional mental model assessment methods in predicting driving performance...
Image Segmentation for the Application of the Neugebauer Colour Prediction Model on Inkjet Printed
Figueiredo, Mário A. T.
are reported in Section 5. The paper is concluded in Section 6. 2 The Neugebauer Color Prediction Model overlaps (CM, CY, MY, CK, MK, YK); all ternary overlaps (CMY, CMK, CYK, MYK), the single full overlap (CMYK
Tang, William C
, atomic MEMS, compact thermal model. INTRODUCTION We present a two-step process for predicting and the VCSEL, active heating and cooling was included in the presented prototype through an external heater
Huang, C.; Song, Y.; Luo, X.
2006-01-01T23:59:59.000Z
Based on the Block model for predicting vertical temperature distribution in a large space, this paper describes an improved Gebhart-Block model for predicting vertical temperature distribution of a large space with natural ventilation...
S. F. Burlatsky; M. Gummalla; J. O'Neill; V. V. Atrazhev; A. N. Varyukhin; D. V. Dmitriev; N. S. Erikhman
2013-06-19T23:59:59.000Z
Under typical PEM fuel cell operating conditions, part of membrane electrode assembly is subjected to humidity cycling due to variation of inlet gas RH and/or flow rate. Cyclic membrane hydration/dehydration would cause cyclic swelling/shrinking of the unconstrained membrane. In a constrained membrane, it causes cyclic stress resulting in mechanical failure in the area adjacent to the gas inlet. A mathematical modeling framework for prediction of the lifetime of a PEM FC membrane subjected to hydration cycling is developed in this paper. The model predicts membrane lifetime as a function of RH cycling amplitude and membrane mechanical properties. The modeling framework consists of three model components: a fuel cell RH distribution model, a hydration/dehydration induced stress model that predicts stress distribution in the membrane, and a damage accrual model that predicts membrane life-time. Short descriptions of the model components along with overall framework are presented in the paper. The model was used for lifetime prediction of a GORE-SELECT membrane.
Wake models are used to improve predictions of Annual Energy Production (AEP) of wind farms.
Daraio, Chiara
·Wake models are used to improve predictions of Annual Energy Production (AEP) of wind farms. ·Wake measurements in the ETHZ facility compare well with measurements at the Horns Rev offshore wind farm models take account of the effects of wakes on downstream wind turbines. ·Wake models used in the wind
Detection and Prediction of Errors in EPCs of the SAP Reference Model
van der Aalst, Wil
as a blueprint for roll-out projects of SAP's ERP system. It reflects Version18 4.6 of SAP R/3 which was marketedDetection and Prediction of Errors in EPCs of the SAP Reference Model J. Mendling a, H.M.W. Verbeek provide empirical evidence for these questions based on the SAP reference model. This model collection
Sunshine-Factor Model with Treshold GARCH for Predicting Temperature of Weather Contracts
Paris-Sud XI, Université de
Sunshine-Factor Model with Treshold GARCH for Predicting Temperature of Weather Contracts Hélčne of the shocks on the volatility by estimating a structural model with a periodic threshold GARCH. We show model, Markov chain, threshold GARCH, Monte- Carlo simulations, pricing, Value-at-Risk. JEL
Power law decay in model predictability skill Peter C. Chu,1
Chu, Peter C.
Power law decay in model predictability skill Peter C. Chu,1 Leonid M. Ivanov,1,2 Lakshmi H. Kantha a Gulf of Mexico nowcast/forecast model. Power law scaling is found in the mean square error of displacement between drifting buoy and model trajectories (both at 50 m depth). The probability density
1 Artificial Neural Networks and Hidden Markov Models for Predicting the Protein Structures advice on the development of this project #12;2 Artificial Neural Networks and Hidden Markov Models learning methods: artificial neural networks (ANN) and hidden Markov models (HMM) (Rost 2002; Karplus et al
Modeling, Analysis, Predictions, and Projections Email: oar.cpo.mapp@noaa.gov
Earth system models to better simulate the climate system? Can we improve intraseasonal to seasonal mission, MAPP supports the development of advanced Earth system models that can predict climate variations, and the external research community. MAPP Objectives · Improve Earth system models · Achieve an integrated Earth
An Advanced Induction Machine Model for Predicting Inverter-Machine Interaction
Chapman, Patrick
An Advanced Induction Machine Model for Predicting Inverter-Machine Interaction [31 [41 [51 [6] [7 saturntion d d d d d d d d d d d d d d d d d d d d d d d Leakage inductance saturation as a function of flux- tion machine model specifically designed for use with inverter models to study machin
Evaluation of SWAT model - subdaily runoff prediction in Texas watersheds
Palanisamy, Bakkiyalakshmi
2007-09-17T23:59:59.000Z
Spatial variability of rainfall is a significant factor in hydrologic and water quality modeling. In recent years, characterizing and analyzing the effect of spatial variability of rainfall in hydrologic applications has become vital with the advent...
Predictive models for power dissipation in optical transceivers
Butler, Katherine, 1981-
2004-01-01T23:59:59.000Z
Power dissipation in optical networks is a significant problem for the telecommunications industry. The optical transceiver was selected as a representative device of the network, and a component based power model is ...
How predictable : modeling rates of change in individuals and populations
Krumme, Katherine
2013-01-01T23:59:59.000Z
This thesis develops methodologies to measure rates of change in individual human behavior, and to capture statistical regularities in change at the population level, in three pieces: i) a model of individual rate of change ...
Dispersion modeling for prediction of emission factors for cattle feedyards
Parnell, Sarah Elizabeth
1994-01-01T23:59:59.000Z
of state air pollution regulatory agencies will require accurate EPA AP-42 emission factors. A protocol was developed so that accurate emission factors can be determined using both source sampling data and dispersion modeling. In this study, an emission...
Wenzel, Mike
2013-10-14T23:59:59.000Z
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.
Evaluation of a mathematical model in predicting intake of growing and finishing cattle
Bourg, Brandi Marie
2009-05-15T23:59:59.000Z
EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment... of the requirements for the degree of MASTER OF SCIENCE December 2007 Major Subject: Animal Science EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG Submitted...
Evaluation of a mathematical model in predicting intake of growing and finishing cattle
Bourg, Brandi Marie
2008-10-10T23:59:59.000Z
EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment... of the requirements for the degree of MASTER OF SCIENCE December 2007 Major Subject: Animal Science EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG Submitted...
A quantitative model to predict the cost of quality nonconformance in the construction industry
Opara, Ethelbert Okechukwu
1993-01-01T23:59:59.000Z
A QUANTITATIVE MODEL TO PREDICT THE COST OF QUALITY NONCONFORMANCE IN THE CONSTRUCTION INDUSTRY A Thesis by ETHELBERT OKECHUKWU OPARA Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of requirements... for the degree of MASTER OF SCIENCE August 1993 Major Subject: Construction Management A QUANTITATIVE MODEL TO PREDICT THE COST OF QUALITY NONCONFORMANCE IN THE CONSTRUCTION INDUSTRY A Thesis by ETHELBERT OKECHUKWU OPARA Submitted to Texas A&M University...
Development of a new model for predicting sucker-rod pumping system performance
Garcia, Julian Perez
1988-01-01T23:59:59.000Z
DEVELOPMENT OF A NEW MODEL FOR PREDICTING SUCKER-ROD PUMPING SYSTEM PERFORMANCE A Thesis by JULIAN PEREZ GARCIA, JR. Submitted to the Graduate College of Texas A&M University in partial fulfillment of the requirements for the degree... of MASTER OF SCIENCE August 1988 Major Subject: Petroleum Engineering DEVELOPMENT OF A NEW MODEL FOR PREDICTING SUCKER-ROD PUMPING SYSTEM PERFORMANCE A Thesis by JULIAN PEREZ GARCIA, JR. Approved as to style and content by: J. . Jen in s (Cha...
Rothe, Jeanne Marie
1983-01-01T23:59:59.000Z
A COMPUTER SIMULATION MODEL FOR THE PREDICTION OF . EMPERATURE DISTRIBUTIONS IN RADIOFREQUENCY HYPERTHERMIA TREATMENT A Thesis by JEANNE MARIE ROTHE Submitted to the Graduate College of Texas ASM University in Partial fulfillment... of the requirement for the degree of MASTER OF SCIENCE DECEMBER 1983 Major Subject: Bioengineering A COMPUTER SIMULATION MODEL FOR THE PREDICTION OF TEMPERATURE DISTRIBUTIONS IN RADIOFREQUENCY HYPERTHERMIA TREATMENT A Thesis by JEANNE MARIE ROTHE Approved...
A new, efficient computational model for the prediction of fluid seal flowfields
Hibbs, Robert Irwin
1988-01-01T23:59:59.000Z
A NEW) EFFICIENT COMPUTATIONAL MODEL FOR THE PREDICTION OF FLUID SEAL FLOWFIELDS A Thesis by ROBERT IRWIN HIBBS, JR. Submitted to the Office of Graduate Studies of Texas ASM University in partial fulfillment of the requirement for the degree... of MASTER OF SCIENCE December 1988 Major Subject: Mechanical Engineering A NEW, EFFICIENT COMPUTATIONAL MODEL FOR THE PREDICTION OF FLUID SEAL FLOWFIELDS A Thesis by ROBERT IRWIN HIBBS, JR. Approved as to style and content by: David L. Rhode...
CONTROL-ORIENTED PLANAR MOTION MODELING OF UNMANNED SURFACE VEHICLES
Virginia Tech
CONTROL-ORIENTED PLANAR MOTION MODELING OF UNMANNED SURFACE VEHICLES C. Sonnenburg, A. Gadre, D effective model-based control design, (2) sufficiently simple to allow straight forward parameter. A first order steering model relates steering angle to turn rate. A second order steering model relates
On modeling and controlling intelligent systems
Dress, W.B.
1993-11-01T23:59:59.000Z
The aim of this paper is to show how certain diverse and advanced techniques of information processing and system theory might be integrated into a model of an intelligent, complex entity capable of materially enhancing an advanced information management system. To this end, we first examine the notion of intelligence and ask whether a semblance thereof can arise in a system consisting of ensembles of finite-state automata. Our goal is to find a functional model of intelligence in an information-management setting that can be used as a tool. The purpose of this tool is to allow us to create systems of increasing complexity and utility, eventually reaching the goal of an intelligent information management system that provides and anticipates needed data and information. We base our attempt on the ideas of general system theory where the four topics of system identification, modeling, optimization, and control provide the theoretical framework for constructing a complex system that will be capable of interacting with complex systems in the real world. These four key topics are discussed within the purview of cellular automata, neural networks, and evolutionary programming. This is a report of ongoing work, and not yet a success story of a synthetic intelligent system.
449 Model Refinement Needs A model developed by Peters and Marmorek (2003) will be used to generate primarily an energy sink or primarily a source of food? More information is needed as to interactions predictions for comparison with observed variations in kokanee production. As with most models
Property Verification for Access Control Models via Model Checking1 Vincent C. Hu1
Young, R. Michael
Property Verification for Access Control Models via Model Checking1 Vincent C. Hu1 , D. Richard. In this paper, we propose a new general approach for property verification for access control models via model checking. The approach defines a standardized structure for access control models, providing for both
3D Rigid Body Impact Burial Prediction Model
Chu, Peter C.
-fixed coordinate (E-coordinate) · cylinder's main-axis following coordinate (M-coordinate) · hydrodynamic force-Coordiante Hydrodynamic forces (drag and lift) are easily calculated. #12;Moment of Momentum Equations #12;Interfacial;Experiment · Hydrodynamic Model Development · Behavior of Falling Cylinder in Water Column (Chaotic
Prediction under uncertainty in reservoir modeling S. Subbeya,*, M. Christiea
Sambridge, Malcolm
a Institute of Petroleum Engineering, Heriot-Watt University, Edinburgh EH14 4AS, UK b Research School to production data, is obtained. The model is then used to forecast future production profiles. Because the history match is non-unique, the forecast production profiles are therefore uncertain, although
Crowdtuning: systematizing auto-tuning using predictive modeling and
Paris-Sud XI, Université de
in a public repository to initiate systematic, reproducible and collaborative R&D with a new publication model, reliability and cost. We present our novel long-term holistic and practical solution to this problem basedTuning.org for collaborative explanation, top-down complexity reduction, incremental problem decomposition and detection
A NEW MODEL FOR PERFORMANCE PREDICTION OF HARD ROCK TBMS.
TBMs. The model uses information on the rock properties and cutting geometry to calculate TBM rate on data collected in the field and is merely a regression between machine parameters, rock properties is introduced to provide an estimate of disc cutting forces as a function of rock properties and the cutting
Motor Modeling and Position Control Lab Week 3: Closed Loop Control
Krovi, Venkat
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
Goal-Directed Biped Stepping and Push Recovery with Momentum Control
Wu, Chun-Chih
2011-01-01T23:59:59.000Z
model-predictive control. Computer Graphics Forum, 27(2),neuro- motor control models. Pacific Graphics, 2003. [96]biped walking control. ACM Transactions on Graphics, 29(3),
Title of dissertation: MODELING, SIMULATING, AND CONTROLLING THE FLUID DYNAMICS
Shapiro, Benjamin
ABSTRACT Title of dissertation: MODELING, SIMULATING, AND CONTROLLING THE FLUID DYNAMICS OF ELECTRO an algorithm to steer indi- vidual particles inside the EWOD system by control of actuators already present number of actuators available in the EWOD system. #12;MODELING, SIMULATING, AND CONTROLLING THE FLUID
Modeling of TCR and VSI Based FACTS Controllers
Cańizares, Claudio A.
and Voltage Sourced In- verter VSI based Flexible AC Transmission System FACTS Controllers. The models to many applications of these controllers to improve the stability of power networks 1, 2 . Thus, many concentrates on presenting transient stability and power ow models of Thyristor Controlled Reactor TCR
Subsidence prediction for the forthcoming TONO UCG project. [Rubble model and block model
Sutherland, H.R.; Hommert, P.J.; Taylor, L.M.; Benzley, S.E.
1983-01-01T23:59:59.000Z
The motion of the strata that overlie the TONO UCG Project partial-seam test is calculated using the analyses that have been developed for the prediction of subsidence above coal mines. This purely mechanical analysis of the overburden response to the formation of a void in the underlying coal seam is based on the analysis of two codes. The first is a finite-element code that uses a nonlinear rubble model to describe both the kinematics of roof fall and the continuum behavior of broken and unbroken strata. The second is a block code that treats the overburden as an assemblage of blocks. The equations of motion are solved for each block using an explicit integration operator. As both of these calculations are two-dimensional in nature, they are used to calibrate the semi-empirical, complementary influence function model. This model permits the extension of the two-dimensional analyses to three dimensions by using computationally efficient algorithms. These techniques are calibrated to UCG projects by analyzing the Hoe Creek 3 burn. Their application to the TONO project required the estimation of the lateral extent of the cavity for the partial-seam test. The estimates utilized the projected tons of coal to be removed and two scenarios for the burn sequence. The subsidence analytical techniques were combined with the expected patterns of coal removal to place an upper bound on the surface subsidence that can be anticipated at the TONO UCG site. 9 figures.
In-situ prediction on sensor networks using distributed multiple linear regression models
Basha, Elizabeth (Elizabeth Ann)
2010-01-01T23:59:59.000Z
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 ...
A soil moisture availability model for crop stress prediction
Gay, Roger Franklin
1983-01-01T23:59:59.000Z
wet so11 profile [Ritch1e et al. , 1972] . . . . . . . . . . . . . . 12 Relationships between the ratio of actual evaporation (Ea) to pan evaporat1on (E an) as a function of the available soil water in Rule and Bragg soybean [Burch et al. , 1978...] F1gure Interact1ons between soil-moisture status and other components of a general crop yield model . . . . . . . . . . . . . . . 16 Figure Root densit1es for ra1nfed Ruse and Bragg soybean, 98 days after planting [Burch et al. , 1978...
Gamma-ray Burst Models: General Requirements and Predictions
P. Meszaros
1995-02-21T23:59:59.000Z
Whatever the ultimate energy source of gamma-ray bursts turns out to be, the resulting sequence of physical events is likely to lead to a fairly generic, almost unavoidable scenario: a relativistic fireball that dissipates its energy after it has become optically thin. This is expected both for cosmological and halo distances. Here we explore the observational motivation of this scenario, and the consequences of the resulting models for the photon production in different wavebands, the energetics and the time structure of classical gamma-ray bursters.
Development and Validation of an Advanced Stimulation Prediction Model for
AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOE Facility DatabaseMichigan: EnergyKansas:DetroitOpen Energy1987)
Development of Chemical Model to Predict the Interactions between
AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOE Facility DatabaseMichigan: EnergyKansas:DetroitOpen
Autothermal reforming of gasoline for fuel cell applications : a control-oriented dynamic model.
Hu, Y.; Chmielewski, D. J.; Papadias, D.; Chemical Sciences and Engineering Division; Illinois Inst. of Tech.
2008-11-05T23:59:59.000Z
In this work, we develop a control-oriented, reduced order dynamic model of an autothermal reforming (ATR) reactor. The targeted application is within the on-board fuel-processing unit of a fuel cell vehicle. A previous effort has illustrated that a predictive-type controller may be required to achieve desired performance within this application. The objective of the current effort is to determine the existence of a reduced order model with enough speed and accuracy to meet the online computational demands of a predictive controller. Central to the model development is an approximation of reaction rates that achieve reasonable accuracy near the inlet while preserving the overall energy balance. The resulting scheme converts a partial differential equation model into a set of ordinary differential/algebraic equations and achieves nearly a 4 orders of magnitude improvement in computational speed while preserving most of the nonlinear characteristics of the original system. Such results give clear indication that the hurdle of computational viability can be overcome and opens the door for further development of a predictive controller for the ATR application.
Gravdahl, Jan Tommy
with the required background. Reprinted, with permission, from IEEE Control Systems Mag- azine, Vol. 24, No. 5, 2004 Norwegian Society of Automatic Controldoi:10.4173/mic.2007.2.2 #12;Modeling, Identification and Control Year in Industrial Systems 3rd Linear System Theory, Modeling and Simulation, Optimization and Control, Real
Scarrott, Carl
Spatial Spectral Estimation forSpatial Spectral Estimation for Reactor Modeling and ControlReactor in Magnox nuclear reactors l Establish safe operating limits l Issues: Â Subset of measurements Â Control Modeling and Control Carl Scarrott Granville Tunnicliffe-Wilson Lancaster University, UK c
Model Transformation with Hierarchical Discrete-Event Control
Model Transformation with Hierarchical Discrete- Event Control Thomas Huining Feng Electrical permission. #12;Model Transformation with Hierarchical Discrete-Event Control by Huining Feng B.S. (Nanjing Date Date University of California, Berkeley Spring 2009 #12;Model Transformation with Hierarchical
Prediction of oxy-coal flame stand-off using high-fidelity thermochemical models
Prediction of oxy-coal flame stand-off using high-fidelity thermochemical models and the one Abstract An Eulerian one-dimensional turbulence (ODT) model is applied to simulate oxy-coal combustion temperature and mixing rate on oxy-coal flame is simulated and discussed where flame stand-off is used
An Efficient Genetic Algorithm for Predicting Protein Tertiary Structures in the 2D HP Model
Istrail, Sorin
, predicting its tertiary structure is known as the protein folding problem. This problem has been widely genetic algo- rithm for the protein folding problem under the HP model in the two-dimensional square Genetic Algorithm, Protein Folding Problem, 2D HP Model 1. INTRODUCTION Amino acids are the building
User-click Modeling for Understanding and Predicting Search-behavior
Yang, Qiang
. Categories and Subject Descriptors H.3.3 [Information Search and Retrieval]: General Terms AlgorithmsUser-click Modeling for Understanding and Predicting Search-behavior Yuchen Zhang1 , Weizhu Chen1 advances in search users' click modeling consider both users' search queries and click/skip behavior
Paris-Sud XI, UniversitĂ© de
1 Development of a new model to predict indoor daylighting : integration in CODYRUN software in the scientific literature for determining indoor daylighting values. They are classified in three categories. The originality of our paper relies on the coupling of several simplified models of indoor daylighting
Predicting Response to Political Blog Posts with Topic Models Language Technologies Institute
Cohen, William W.
- tent Dirichlet Allocation, introduced by Blei et al. (2003), in various ways to capture different char a blog site. The model is an extension of Latent Dirichlet Allocation (LDA) introduced by Blei et al for learning and/or prediction (Blei et al., 2003). Different models can be compared to explore
PAVEMENT PREDICTION PERFORMANCE MODELS AND RELATION WITH TRAFFIC FATALITIES AND INJURIES
Boyer, Edmond
PAVEMENT PREDICTION PERFORMANCE MODELS AND RELATION WITH TRAFFIC FATALITIES AND INJURIES V. CEREZO.gothie@developpement-durable.gouv.fr ABSTRACT This paper presents some results of a study, which aimed at modelling pavement evolution, pavement characteristics and age. In a second part, non-linear regressions were used in view of obtaining
Predictive Modeling of Transient Storage and Nutrient Uptake: Implications for Stream Restoration
Predictive Modeling of Transient Storage and Nutrient Uptake: Implications for Stream Restoration of reactive transport modeling for stream restoration purposes: the accuracy of the nutrient spiraling geomorphology and hydraulics influence nu- trient uptake is vital for stream restoration projects that modify
carrying capacity. Keywords Visitation model Ă Recreation management Ă Water quality Ă River visitation ĂA Model for Predicting Daily Peak Visitation and Implications for Recreation Management and Water Quality: Evidence from Two Rivers in Puerto Rico Luis E. Santiago Ă? Armando Gonzalez-Caban Ă? John Loomis
Chaubey, Indrajeet
considerable interest in developing methods for uncertainty analysis of artificial neural network (ANN) models and parametric uncertainty in artificial neural network hydrologic models, Water Resour. Res., 43, W10407, doi:10A simplified approach to quantifying predictive and parametric uncertainty in artificial neural
Broader source: Energy.gov [DOE]
NREL, under the Physics of Reliability: Evaluating Design Insights for Component Technologies in Solar (PREDICTS) Program will be developing a physics-based computational degradation model to assess the kinetic oxidation rates; realistic model light attenuation and transport; and multi-layer treatment with variable properties Simulation based experimental design.
Bayesian calibration of a k -turbulence model for predictive jet-in-crossflow simulations
Ray, Jaideep
Bayesian calibration of a k - turbulence model for predictive jet-in-crossflow simulations Jaideep skill in jet-in-crossflow simulations. The method is based on the hypotheses that (1) informative features of jet-in-crossflow interactions and (2) one can construct surrogates of RANS models
Weston, Ken
Atomistic Modeling of Macromolecular Crowding Predicts Modest Increases in Protein Folding that macromolecular crowding can increase protein folding stability, but depending on details of the models (e.g., how on the effects of macro- molecular crowding on protein folding and binding stability has been reached. Crowders
The 1D Iterative Model for Predicting Thermal Radiation from a Jet Fire
Paris-Sud XI, Université de
manuscript, published in "6. International Seminar on Fire and Explosion Hazards (FEH), Leeds : UnitedThe 1D Iterative Model for Predicting Thermal Radiation from a Jet Fire Leroy, G.* and Duplantier of the current jet fire models used in the accidental fire risks department are semi- empirical. They depend
Maasoumy, Mehdi
2012-01-01T23:59:59.000Z
optimal control design for HVAC systems,” in Dynamic Systemalgorithm design for hvac systems in energy efficient build-OPTIMAL CONTROL OF BUILDING HVAC SYSTEMS IN THE PRESENCE OF
Langton, C.; Kosson, D.
2009-11-30T23:59:59.000Z
Cementitious barriers for nuclear applications are one of the primary controls for preventing or limiting radionuclide release into the environment. At the present time, performance and risk assessments do not fully incorporate the effectiveness of engineered barriers because the processes that influence performance are coupled and complicated. Better understanding the behavior of cementitious barriers is necessary to evaluate and improve the design of materials and structures used for radioactive waste containment, life extension of current nuclear facilities, and design of future nuclear facilities, including those needed for nuclear fuel storage and processing, nuclear power production and waste management. The focus of the Cementitious Barriers Partnership (CBP) literature review is to document the current level of knowledge with respect to: (1) mechanisms and processes that directly influence the performance of cementitious materials (2) methodologies for modeling the performance of these mechanisms and processes and (3) approaches to addressing and quantifying uncertainties associated with performance predictions. This will serve as an important reference document for the professional community responsible for the design and performance assessment of cementitious materials in nuclear applications. This review also provides a multi-disciplinary foundation for identification, research, development and demonstration of improvements in conceptual understanding, measurements and performance modeling that would be lead to significant reductions in the uncertainties and improved confidence in the estimating the long-term performance of cementitious materials in nuclear applications. This report identifies: (1) technology gaps that may be filled by the CBP project and also (2) information and computational methods that are in currently being applied in related fields but have not yet been incorporated into performance assessments of cementitious barriers. The various chapters contain both a description of the mechanism or and a discussion of the current approaches to modeling the phenomena.
Optimal control with adaptive internal dynamics models
Mitrovic, Djordje; Klanke, Stefan; Vijayakumar, Sethu
2008-01-01T23:59:59.000Z
Optimal feedback control has been proposed as an attractive movement generation strategy in goal reaching tasks for anthropomorphic manipulator systems. The optimal feedback control law for systems with non-linear dynamics ...
On Dynamic Models of Robot Force Control
Eppinger, Steven D.
1986-07-01T23:59:59.000Z
For precise robot control, endpoint compliance strategies utilize feedback from a force sensor located near the tool/workpiece interface. Such endpoint force control systems have been observed in the laboratory to be ...
A Nonlinear Continuous Time Optimal Control Model of Dynamic Pricing and Inventory Control with no
Adida, Elodie
time optimal control model for studying a dynamic pricing and inventory control problem for a make-to-stock of not introducing any approximation to the real setting: it provides the exact solution of the system. When taking
Nadim Chowdhury; Imtiaz Ahmed; Zubair Al Azim; Md. Hasibul Alam; Iftikhar Ahmad Niaz; Quazi D. M. Khosru
2014-04-14T23:59:59.000Z
We propose a physically based analytical compact model to calculate Eigen energies and Wave functions which incorporates penetration effect. The model is applicable for a quantum well structure that frequently appears in modern nano-scale devices. This model is equally applicable for both silicon and III-V devices. Unlike other models already available in the literature, our model can accurately predict all the eigen energies without the inclusion of any fitting parameters. The validity of our model has been checked with numerical simulations and the results show significantly better agreement compared to the available methods.
Modeling and Control of Advanced Technology Engines
Stefanopoulou, Anna
in powertrain control systems, largely driven by government regulations aimed at improving fuel economy, and apply classical and modern control techniques to improve engine performance. Moreover, we study control systems. #12;c Anna Stefanopoulou 1996 All Rights Reserved #12;Dedicated to George, Kaite
Reference Model for Control and Automation Systems in Electrical...
Broader source: Energy.gov (indexed) [DOE]
Reference Model for Control and Automation Systems in Electrical Power Version 1.2 October 12, 2005 Prepared by: Sandia National Laboratories' Center for SCADA Security Jason...
Machine Learning for Humanoid Robot Modeling and Control /
Wu, Tingfan
2013-01-01T23:59:59.000Z
of robot dynamics parameters: Theory and application. [36]in [12] for applications to model free robot control. ThisApplication to Robotics For Newtonian problems, including articulated robots,
Asset-Liability Management Modelling with Risk Control by ...
Xi Yang
2009-01-15T23:59:59.000Z
Jan 15, 2009 ... Asset-Liability Management Modelling with Risk Control by Stochastic Dominance. Xi Yang (X.Yang ***at*** ed.ac.uk) Jacek Gondzio ...
Advanced PHEV Engine Systems and Emissions Control Modeling and...
Broader source: Energy.gov (indexed) [DOE]
PHEV Engine Systems and Emissions Control Modeling and Analysis Stuart Daw (PI), Zhiming Gao, Kalyan Chakravarthy Oak Ridge National Laboratory 2011 U.S. DOE Hydrogen and Vehicle...
On the modeling and control of delamination processes
Michal Kocvara
2004-01-20T23:59:59.000Z
Jan 20, 2004 ... On the modeling and control of delamination processes. Michal Kocvara (kocvara ***at*** utia.cas.cz) Jiri V. Outrata (outrata ***at*** utia.cas.cz).
Modeling Combustion Control for High Power Diesel Mode Switching
Broader source: Energy.gov (indexed) [DOE]
Directions in Engine-Efficiency and Emissions Research Conference 2010 Modeling Combustion Control for High Power Diesel Mode Switching Siddhartha Banerjee, Christopher J. Rutland...
Ritchie, L.T.; Brown, W.D.; Wayland, J.R.
1980-05-01T23:59:59.000Z
A general temperate latitude cyclonic rainstorm model is presented which describes the effects of washout and runoff on consequences of atmospheric releases of radioactive material from potential nuclear reactor accidents. The model treats the temporal and spatial variability of precipitation processes. Predicted air and ground concentrations of radioactive material and resultant health consequences for the new model are compared to those of the original WASH-1400 model under invariant meteorological conditions and for realistic weather events using observed meteorological sequences. For a specific accident under a particular set of meteorological conditions, the new model can give significantly different results from those predicted by the WASH-1400 model, but the aggregate consequences produced for a large number of meteorological conditions are similar.
Aditya Kumar
2010-12-30T23:59:59.000Z
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.
Goldsby, Michael E.; Mayo, Jackson R.; Bhattacharyya, Arnab (Massachusetts Institute of Technology, Cambridge, MA); Armstrong, Robert C.; Vanderveen, Keith
2008-09-01T23:59:59.000Z
The goal of this research was to examine foundational methods, both computational and theoretical, that can improve the veracity of entity-based complex system models and increase confidence in their predictions for emergent behavior. The strategy was to seek insight and guidance from simplified yet realistic models, such as cellular automata and Boolean networks, whose properties can be generalized to production entity-based simulations. We have explored the usefulness of renormalization-group methods for finding reduced models of such idealized complex systems. We have prototyped representative models that are both tractable and relevant to Sandia mission applications, and quantified the effect of computational renormalization on the predictive accuracy of these models, finding good predictivity from renormalized versions of cellular automata and Boolean networks. Furthermore, we have theoretically analyzed the robustness properties of certain Boolean networks, relevant for characterizing organic behavior, and obtained precise mathematical constraints on systems that are robust to failures. In combination, our results provide important guidance for more rigorous construction of entity-based models, which currently are often devised in an ad-hoc manner. Our results can also help in designing complex systems with the goal of predictable behavior, e.g., for cybersecurity.
Modeling control room crews for accident sequence analysis
Huang, Y. (Yuhao)
1991-01-01T23:59:59.000Z
This report describes a systems-based operating crew model designed to simulate the behavior of an nuclear power plant control room crew during an accident scenario. This model can lead to an improved treatment of potential ...
Nonlinear adaptive internal model control using neural networks
Gandhi, Amit Krushnavadan
2001-01-01T23:59:59.000Z
(NIMC) strategy based on neural network models is presented for SISO processes. The nonlinearities of the dynamical system are modelled by neural network architectures. Recurrent neural networks can be used for both the identification and control of nonlinear...
Park, Joo-Yang
1994-01-01T23:59:59.000Z
. . . . . . . . . . . . . . . . . ?. .. , . . . . . . . . . . . . 55 10 Prediction of porewater pH . 11 Effects of pH on predictions of various species . . . 12 Prediction of Al concentration 13 Prediction of Fe concentration 14 Prediction of SO4 concentration . 15 Prediction of Ca concentration . 16...A hydration (16). However, Reardon (9) indicated that equilibrium models using current K, ?values of these minerals tend to predict the thermodynamic stability of ettringite over monosulfate. Because the hydration of C4AF is analogous to that of CsA, C4AF...
Flow control techniques for real-time media applications in best-effort networks using fluid models
Konstantinou, Apostolos
2004-11-15T23:59:59.000Z
at the application layer. An end-to-end ?uid model is used, including the source bu?er, the network and the destination bu?er. Traditional con- trol techniques, along with more advanced adaptive predictive control methods, are considered in order to provide... OF THE END-TO-END FLOW TRANSPORT SYSTEM : : : : : : : : : : : : : : : : : : : : : : 25 A. Source Bu?er Model . . . . . . . . . . . . . . . . . . . . . 25 B. Network Dynamic Model . . . . . . . . . . . . . . . . . . . 27 1. Time-Varying Time Delay Model...
Hybrid Control Models of Next Generation Air Traffic Management ?
Pappas, George J.
Hybrid Control Models of Next Generation Air Traffic Management ? C. Tomlin, G. Pappas, J. Lygeros of California at Berkeley Berkeley, CA 94720 Abstract. The study of hierarchical, hybrid control systems by today's Air Traffic Control (ATC), a groundbased system which routes aircraft along predefined jet ways
Generic Average Modeling and Simulation of Discrete Controllers
modeling of discrete controllers for PWM power conversion systems. The method applies a section be advantageous to have the capability of running AC analysis of digitally controlled power systems on a general the simulation of digitally controlled power conversion systems on general-purpose circuit simulators
Transformer Thermal Modeling: Improving Reliability Using Data Quality Control
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
Controlling Social Dynamics with a Parametrized Model of Floor Regulation
Das, Suman
Controlling Social Dynamics with a Parametrized Model of Floor Regulation Crystal Chao, Andrea L is to build autonomous robot controllers for successfully engaging in human-like turn-taking interactions. Towards this end, we present CADENCE, a novel computational model and architecture that explicitly reasons
NEWS AND VIEWS Modeling gene expression control using Omes Law
Nguyen, Dat H.
NEWS AND VIEWS Modeling gene expression control using Omes Law Harmen J Bussemaker Department class of methods that fit simple mathematical models of transcription regulation to DNA microarray data factors (TFs) to specific sites in the genome is a crucial step in the molecular process controlling gene
A NONLINEAR MODELING FRAMEWORK FOR AUTONOMOUS CRUISE CONTROL Gabor Orosz
Daly, Samantha
.) and allows optimization in the entire torque and engine speed range (e.g., for energy consumption). NONLINEARA NONLINEAR MODELING FRAMEWORK FOR AUTONOMOUS CRUISE CONTROL GÂ´abor Orosz Department of Mechanical A nonlinear modeling framework is presented for au- tonomous cruise control (ACC) equipped vehicles which
Model-Free Control of Shape Memory Alloys Antagonistic Actuators
Paris-Sud XI, Université de
Model-Free Control of Shape Memory Alloys Antagonistic Actuators Pierre-Antoine G´edouin , C with a first application of the new framework of model-free control to the promising technology of shape memory alloys actuators. In particular antagonistic shape memory alloys actuator. These devices are known
Identification and Control Problems in Petroleum and Groundwater Modeling \\Lambda
Ewing, Richard E.
Identification and Control Problems in Petroleum and Groundwater Modeling \\Lambda R.E. Ewing, y , M in groundwater remediation. 1 Introduction The outline of this survey talk is as follows: A general introduction differential equation models for multiÂphase fluid flow through porous media, but the use of control
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
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 vs >7 (median), although the findings suggested a trend toward improved LRFS: 96% for SUVmax {<=}7 vs 79% 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.
Lovley, Derek R.
2012-10-31T23:59:59.000Z
This project successfully accomplished its goal of coupling genome-scale metabolic models with hydrological and geochemical models to predict the activity of subsurface microorganisms during uranium bioremediation. Furthermore, it was demonstrated how this modeling approach can be used to develop new strategies to optimize bioremediation. The approach of coupling genome-scale metabolic models with reactive transport modeling is now well enough established that it has been adopted by other DOE investigators studying uranium bioremediation. Furthermore, the basic principles developed during our studies will be applicable to much broader investigations of microbial activities, not only for other types of bioremediation, but microbial metabolism in diversity of environments. This approach has the potential to make an important contribution to predicting the impact of environmental perturbations on the cycling of carbon and other biogeochemical cycles.
Building environment modeling and minimum-energy control
Godfrey, James Bradford
1980-01-01T23:59:59.000Z
be expanded to study energy loss due to vapor condensation. The mathematical model of the building environment is simplified so that optimal temperature control can be studied. Simulations of the building environment heating system using feed- back.... Heating System Simulation. . OPTIMAL TEMPERATURE CONTROL. . . A. Def i ni ti ons 8, Model for the Dynamic Programming Algorithm C. The Dynamic Programming Algorithm. . D. Stochastic External Forcing Terms. . E. Optimal Stochastic Heating Control...
Subtask 2.4 - Integration and Synthesis in Climate Change Predictive Modeling
Jaroslav Solc
2009-06-01T23:59:59.000Z
The Energy & Environmental Research Center (EERC) completed a brief evaluation of the existing status of predictive modeling to assess options for integration of our previous paleohydrologic reconstructions and their synthesis with current global climate scenarios. Results of our research indicate that short-term data series available from modern instrumental records are not sufficient to reconstruct past hydrologic events or predict future ones. On the contrary, reconstruction of paleoclimate phenomena provided credible information on past climate cycles and confirmed their integration in the context of regional climate history is possible. Similarly to ice cores and other paleo proxies, acquired data represent an objective, credible tool for model calibration and validation of currently observed trends. It remains a subject of future research whether further refinement of our results and synthesis with regional and global climate observations could contribute to improvement and credibility of climate predictions on a regional and global scale.
Unified Modeling of Complex Real-Time Control Systems
Hai, He; Chi-Lan, Cai
2011-01-01T23:59:59.000Z
Complex real-time control system is a software dense and algorithms dense system, which needs modern software engineering techniques to design. UML is an object-oriented industrial standard modeling language, used more and more in real-time domain. This paper first analyses the advantages and problems of using UML for real-time control systems design. Then, it proposes an extension of UML-RT to support time-continuous subsystems modeling. So we can unify modeling of complex real-time control systems on UML-RT platform, from requirement analysis, model design, simulation, until generation code.
Dynamics of Cell Shape and Forces on Micropatterned Substrates Predicted by a Cellular Potts Model
Philipp J. Albert; Ulrich S. Schwarz
2014-05-19T23:59:59.000Z
Micropatterned substrates are often used to standardize cell experiments and to quantitatively study the relation between cell shape and function. Moreover, they are increasingly used in combination with traction force microscopy on soft elastic substrates. To predict the dynamics and steady states of cell shape and forces without any a priori knowledge of how the cell will spread on a given micropattern, here we extend earlier formulations of the two-dimensional cellular Potts model. The third dimension is treated as an area reservoir for spreading. To account for local contour reinforcement by peripheral bundles, we augment the cellular Potts model by elements of the tension-elasticity model. We first parameterize our model and show that it accounts for momentum conservation. We then demonstrate that it is in good agreement with experimental data for shape, spreading dynamics, and traction force patterns of cells on micropatterned substrates. We finally predict shapes and forces for micropatterns that have not yet been experimentally studied.
Chen, Long-Qing
Predicting effective magnetoelectric response in magnetic-ferroelectric composites via phase Articles you may be interested in Stress magnetization model for magnetostriction in multiferroic composite circular fibrous multiferroic composites J. Appl. Phys. 109, 104901 (2011); 10.1063/1.3583580 Effect
Paul Smolen; Douglas A. Baxter; John H. Byrne
2012-08-03T23:59:59.000Z
Protein synthesis-dependent, late long-term potentiation (LTP) and depression (LTD) at glutamatergic hippocampal synapses are well characterized examples of long-term synaptic plasticity. Persistent increased activity of the enzyme protein kinase M (PKM) is thought essential for maintaining LTP. Additional spatial and temporal features that govern LTP and LTD induction are embodied in the synaptic tagging and capture (STC) and cross capture hypotheses. Only synapses that have been "tagged" by an stimulus sufficient for LTP and learning can "capture" PKM. A model was developed to simulate the dynamics of key molecules required for LTP and LTD. The model concisely represents relationships between tagging, capture, LTD, and LTP maintenance. The model successfully simulated LTP maintained by persistent synaptic PKM, STC, LTD, and cross capture, and makes testable predictions concerning the dynamics of PKM. The maintenance of LTP, and consequently of at least some forms of long-term memory, is predicted to require continual positive feedback in which PKM enhances its own synthesis only at potentiated synapses. This feedback underlies bistability in the activity of PKM. Second, cross capture requires the induction of LTD to induce dendritic PKM synthesis, although this may require tagging of a nearby synapse for LTP. The model also simulates the effects of PKM inhibition, and makes additional predictions for the dynamics of CaM kinases. Experiments testing the above predictions would significantly advance the understanding of memory maintenance.
Stryk, Oskar von
. INTRODUCTION The major fields of machining applications for industrial robots are automated pre- machining an industrial robot for milling applications inaccuracies of the serial robot kinematic, the low structuralPrediction of the tool displacement for robot milling applications using coupled models
Three-Dimensional Hydrodynamic Model for Prediction of Falling Cylinder Through Water Column
Chu, Peter C.
1 1 Three-Dimensional Hydrodynamic Model for Prediction of Falling Cylinder Through Water Column-coordinate), cylinder's main-axis following coordinate (M-coordinate), and hydrodynamic force following coordinate (F-coordinate system. The hydrodynamic forces (such as the drag and lift forces) and their moments are easily computed
A comparison of various models in predicting ignition delay in single-particle coal combustion
A comparison of various models in predicting ignition delay in single-particle coal combustion November 2013 Accepted 7 January 2014 Available online xxxx Keywords: Coal Devolatilization Ignition delay a b s t r a c t In this paper, individual coal particle combustion under laminar conditions
Predicting Protein Folds with Structural Repeats Using a Chain Graph Model
Xing, Eric P.
Predicting Protein Folds with Structural Repeats Using a Chain Graph Model Yan Liu yanliu, Carnegie Mellon University, Pittsburgh, PA 15213 USA Abstract Protein fold recognition is a key step to to accurately identify protein folds aris- ing from typical spatial arrangements of well-defined secondary
Giurgiutiu, Victor
Structural health monitoring with piezoelectric wafer active sensors predictive modeling of the state of the art in structural health monitoring with piezoelectric wafer active sensors and follows with conclusions and suggestions for further work Key Words: structural health monitoring, SHM, nondestructive
Towards a Generalized Regression Model for On-body Energy Prediction from Treadmill Walking
Sukhatme, Gaurav S.
Towards a Generalized Regression Model for On-body Energy Prediction from Treadmill Walking sensor data to energy expenditure is the ques- tion of normalizating across physiological parameters. Common approaches such as weight scaling require validation for each new population. An alternative
A Prediction Model for Adiabatic and Diabatic Capillary Tubes with Alternative Refrigerants
Zhang, Yupeng
2014-12-05T23:59:59.000Z
line) that exits the evaporator, which creates the so called capillary tube/suction line heat exchanger. Models to predict the mass flow in both adiabatic capillary tubes and capillary tube/suction line heat exchangers are developed in this thesis...
Model-predicted distribution of wind-induced internal wave energy in the world's oceans
Miami, University of
Model-predicted distribution of wind-induced internal wave energy in the world's oceans Naoki 9 July 2008; published 30 September 2008. [1] The distribution of wind-induced internal wave energy-induced internal wave energy in the world's oceans, J. Geophys. Res., 113, C09034, doi:10.1029/2008JC004768. 1
Virtual Electrodes Mechanisms Predictions with a Current-Lifted Monodomain Model
Boyer, Edmond
Virtual Electrodes Mechanisms Predictions with a Current-Lifted Monodomain Model Yves Coudi`ere1 cost. The source term is derived from a lifting principle ap- plied to the resolution, and an excitation part, that remains unchanged. Equivalently, we make a lifting of the stimula- tion functions
Predictive Modeling for Glass-Side Laser Scribing of Thin Film Photovoltaic Cells
Yao, Y. Lawrence
with reduced thermal effect. Film side laser scribing is governed by heating, melting and vaporizing of selective films. Glass side laser scribing is a thermal-mechanical process which involves stress inducedPredictive Modeling for Glass-Side Laser Scribing of Thin Film Photovoltaic Cells Hongliang Wang
Prediction Intervals for NAR Model Structures Using a Bootstrap De Brabanter J.,
Prediction Intervals for NAR Model Structures Using a Bootstrap Method De Brabanter J structure. Our approach relies on the external bootstrap procedure [1]. This method is contrasted. In this paper, an external bootstrap method will be proposed for this purpose. The bootstrap is a computer
Predicting pesticide fate in the hive (part 2): development of a dynamic hive model
.g. bees, wax and honey). The proposed model is validated using empirical data on -fluvalinate residues in bees, wax and honey. It predicts with good approximation both the trends over time to measured data. A honeybee hive is a micro-ecosystem com- posed of several components (e.g. bees, wax, honey
Qiu, Qinru
Binghamton University, State University of New York Binghamton, New York, USA {jlu5, sliu5, qwu, qqiuAccurate Modeling and Prediction of Energy Availability in Energy Harvesting Real-Time Embedded}@binghamton.edu Abstract -- Energy availability is the primary subject that drives the research innovations in energy
Mitnitski, Arnold B.
,5]. The aim of our report is to compare the performance of sev- eral well known machine learning techniquesComparison of Machine Learning Techniques with Classical Statistical Models in Predicting Health Faculty of Computer Science, Dalhousie University, Canada Abstract Several machine learning techniques
Nonparametric Variable Selection for Predictive Models and Subpopulations in Clinical Trials
Xie, Jun
Introduction In most clinical trials, there is much heterogeneity among individual outcomes and the treat- mentNonparametric Variable Selection for Predictive Models and Subpopulations in Clinical Trials Jingyi, IN 47907 Abstract Most clinical trials have heterogeneous treatment effect among patient individuals
function within the homologous proteins, despite the lack of a direct connection between sequenceA Graphical Model for Predicting Protein Molecular Function Barbara E. Engelhardt bee function evolves within a phylogenetic tree based on the proteins' sequence. Inputs are a phylogeny
A graphical model for predicting protein molecular function Barbara E Engelhardt bee@cs.berkeley.edu
Stephens, Matthew
function within the homologous proteins, despite the lack of a direct connection between sequenceA graphical model for predicting protein molecular function Barbara E Engelhardt bee function evolves within a phylogenetic tree based on the proteins' sequence. Inputs are a phylogeny
Blood Glucose Level Prediction using Physiological Models and Support Vector Regression
Bunescu, Razvan C.
Blood Glucose Level Prediction using Physiological Models and Support Vector Regression Razvan continually monitor their blood glucose levels and adjust insulin doses, striving to keep blood glucose levels as close to normal as possible. Blood glucose levels that deviate from the normal range can lead to serious
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
A LIFETIME PREDICTION MODEL FOR SINGLE CRYSTAL SUPERALLOYS SUBJECTED TO THERMOMECHANICAL
Paris-Sud XI, Université de
materials tensile, creep and LCF test data at different temperatures. Some parameters, independentA LIFETIME PREDICTION MODEL FOR SINGLE CRYSTAL SUPERALLOYS SUBJECTED TO THERMOMECHANICAL CREEP for Single Crystal Superalloys operated at high temperatures and subjected to creep, fatigue and oxidation
Exploiting Two Intelligent Models to Predict Water Level: A field study of Urmia lake, Iran
Fernandez, Thomas
Exploiting Two Intelligent Models to Predict Water Level: A field study of Urmia lake, Iran Shahab. The measurements from a single tide gauge at Urmia Lake, Northwest Iran, were used to train and validate the GP of Tabriz, Tabriz, Iran. Tel: 0098-411-3392786 Fax: 0098-411-3345332, (e-mail: sha- hab kvk66@yahoo
Pedram, Massoud
Trace-Based Analysis and Prediction of Cloud Computing User Behavior Using the Fractal Modeling and technology. In this paper, we investigate the characteristics of the cloud computing requests received the alpha- stable distribution. Keywords- cloud computing; alpha-stable distribution; fractional order
Stochastic optimal control with learned dynamics models
Mitrovic, Djordje
2011-01-01T23:59:59.000Z
The motor control of anthropomorphic robotic systems is a challenging computational task mainly because of the high levels of redundancies such systems exhibit. Optimality principles provide a general strategy to resolve ...
Modelling and Dynamic Simulation for Process Control
Skogestad, Sigurd
principles for model development are outlined, and these principles are applied to a simple ash tank (which. In this paper we consider dynamic process models obtained using fundamental principles (eg. based reactor, a simple trend analysis using temperature measurements may be suĆcient. Dynamic models
Reliability analysis and prediction of mixed mode load using Markov Chain Model
Nikabdullah, N. [Department of Mechanical and Materials Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia and Institute of Space Science (ANGKASA), Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (Malaysia); Singh, S. S. K.; Alebrahim, R.; Azizi, M. A. [Department of Mechanical and Materials Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (Malaysia); K, Elwaleed A. [Institute of Space Science (ANGKASA), Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (Malaysia); Noorani, M. S. M. [School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia (Malaysia)
2014-06-19T23:59:59.000Z
The aim of this paper is to present the reliability analysis and prediction of mixed mode loading by using a simple two state Markov Chain Model for an automotive crankshaft. The reliability analysis and prediction for any automotive component or structure is important for analyzing and measuring the failure to increase the design life, eliminate or reduce the likelihood of failures and safety risk. The mechanical failures of the crankshaft are due of high bending and torsion stress concentration from high cycle and low rotating bending and torsional stress. The Markov Chain was used to model the two states based on the probability of failure due to bending and torsion stress. In most investigations it revealed that bending stress is much serve than torsional stress, therefore the probability criteria for the bending state would be higher compared to the torsion state. A statistical comparison between the developed Markov Chain Model and field data was done to observe the percentage of error. The reliability analysis and prediction was derived and illustrated from the Markov Chain Model were shown in the Weibull probability and cumulative distribution function, hazard rate and reliability curve and the bathtub curve. It can be concluded that Markov Chain Model has the ability to generate near similar data with minimal percentage of error and for a practical application; the proposed model provides a good accuracy in determining the reliability for the crankshaft under mixed mode loading.
Probe measurements and numerical model predictions of evolving size distributions in premixed flames
De Filippo, A.; Sgro, L.A.; Lanzuolo, G.; D'Alessio, A. [Dipartimento di Ingegneria Chimica, Universita degli Studi di Napoli Federico II, Piazzale Tecchio 80, 80125 Napoli (Italy)
2009-09-15T23:59:59.000Z
Particle size distributions (PSDs), measured with a dilution probe and a Differential Mobility Analyzer (DMA), and numerical predictions of these PSDs, based on a model that includes only coagulation or alternatively inception and coagulation, are compared to investigate particle growth processes and possible sampling artifacts in the post-flame region of a C/O = 0.65 premixed laminar ethylene-air flame. Inputs to the numerical model are the PSD measured early in the flame (the initial condition for the aerosol population) and the temperature profile measured along the flame's axial centerline. The measured PSDs are initially unimodal, with a modal mobility diameter of 2.2 nm, and become bimodal later in the post-flame region. The smaller mode is best predicted with a size-dependent coagulation model, which allows some fraction of the smallest particles to escape collisions without resulting in coalescence or coagulation through the size-dependent coagulation efficiency ({gamma}{sub SD}). Instead, when {gamma} = 1 and the coagulation rate is equal to the collision rate for all particles regardless of their size, the coagulation model significantly under predicts the number concentration of both modes and over predicts the size of the largest particles in the distribution compared to the measured size distributions at various heights above the burner. The coagulation ({gamma}{sub SD}) model alone is unable to reproduce well the larger particle mode (mode II). Combining persistent nucleation with size-dependent coagulation brings the predicted PSDs to within experimental error of the measurements, which seems to suggest that surface growth processes are relatively insignificant in these flames. Shifting measured PSDs a few mm closer to the burner surface, generally adopted to correct for probe perturbations, does not produce a better matching between the experimental and the numerical results. (author)
Model-Inspired Research. TES research uses modeling, prediction, and synthesis to identify
in Earth system models (ESMs). TES supports research to advance fundamental understanding of terrestrial-process models, ecosystem models, and the Community Earth System Model). This emphasis on the capture of advanced in Earth system models to increase the quality of climate model projections and to provide the scientific
Predictions and measurements of isothermal airflow in a model once-through steam generator
Carter, H R; Promey, G J; Rush, G C
1982-11-01T23:59:59.000Z
Once-Through Steam Generators (OTSGs) are used in the Nuclear Steam Supply Systems marketed by The Babcock and Wilcox Company (B and W). To analytically predict the three-dimensional, steady-state thermohydraulic conditions in the OTSG, B and W has developed a proprietary code THEDA-1 and is working in cooperation with EPRI to develop an improved version, THEDA-2. Confident application of THEDA requires experimental verification to demonstrate that the code can accurately describe the thermohydraulic conditions in geometries characteristic of the OTSG. The first step in the THEDA verification process is the subject of this report. A full-scale, partial-section model of two OTSG spans was constructed and tested using isothermal air as the working fluid. Model local velocities and pressure profiles were measured and compared to THEDA prediction for five model configurations. Over 3000 velocity measurements were taken and the results were compared to THEDA predictions. Agreement between measured and predicted velocity data was generally better than +-12.5%.
Van Blackwood; Travis Koenig; Saleem Drera; Brajenda Mishra; Davis Olson; Doug Porter; Robert Mariani
2012-03-01T23:59:59.000Z
Traditional alloy theory models, specifically Darken-Gurry and Miedema’s analyses, that characterize solutes in solid solvents relative to physical properties of the elements have been used to assist in predicting alloy behavior. These models will be applied relative to the three solid phases of uranium: alpha (orthorhombic), beta (tetragonal), and gamma (bcc). These phases have different solubilities for specific alloy additions as a function of temperature. The Darken-Gurry and Miedema models, with modifications based on concepts of Waber, Gschneider, and Brewer will be used to predict the behavior of four types of solutes: 1) Transition metals that are used for various purposes associated with the containment as alloy additions in the uranium fuel 2) Transuranic elements in the uranium 3) Rare earth fission products (lanthanides) 4) Transition metals and other fission products Using these solute map criteria, elemental behavior will be predicted as highly soluble, marginally soluble, or immiscible (compound formers) and will be used to compare solute effects during uranium phase transformations. The overlapping of these solute maps are convenient first approximation tools for predicting alloy behavior.
Predicting Land-Ice Retreat and Sea-Level Rise with the Community Earth System Model
Lipscomb, William [Los Alamos National Laboratory
2012-06-19T23:59:59.000Z
Coastal stakeholders need defensible predictions of 21st century sea-level rise (SLR). IPCC assessments suggest 21st century SLR of {approx}0.5 m under aggressive emission scenarios. Semi-empirical models project SLR of {approx}1 m or more by 2100. Although some sea-level contributions are fairly well constrained by models, others are highly uncertain. Recent studies suggest a potential large contribution ({approx}0.5 m/century) from the marine-based West Antarctic Ice Sheet, linked to changes in Southern Ocean wind stress. To assess the likelihood of fast retreat of marine ice sheets, we need coupled ice-sheet/ocean models that do not yet exist (but are well under way). CESM is uniquely positioned to provide integrated, physics based sea-level predictions.
M. K. Parida; Sudhanwa Patra
2013-01-14T23:59:59.000Z
In TeV scale left-right symmetric models, new dominant predictions to neutrinoless double beta decay and light neutrino masses are in mutual contradiction because of large contribution to the latter through popular seesaw mechanisms. We show that in a class of left-right models with high-scale parity restoration, these results coexist without any contravention with neutrino oscillation data and the relevant formula for light neutrino masses is obtained via gauged inverse seesaw mechanism. The most dominant contribution to the double beta decay is shown to be via $W^-_L- W^-_R$ mediation involving both light and heavy neutrino exchanges, and the model predictions are found to discriminate whether the Dirac neutrino mass is of quark-lepton symmetric origin or without it. We also discuss associated lepton flavor violating decays.
Papalambros, Panos
in increased use of battery storage, this does not necessarily pro- duce significant decreases in fuel usage
Smart Structures: Model Development and Control Applications
for smart structure which utilize piezoelectric, electrostrictive, magnetostrictive or shape memory alloys are dictated by the design requirements for the system. For aeronautic and aerospace systems, control which, in certain aerospace structures, may require the scavenging of power from other components
A model for predicting the costs of research and development in the Post Office Department
Watts, David Eli
1970-01-01T23:59:59.000Z
coefficients relating Y and 4. e is an n x 1 vector of the random errors c which are 2 normally distributed with mean 0 and variance a The least squares solution to this model is I ] I B ~ (K X) X Y Linear Cost Models The general philosophy behind linear... of Committee) ~ g QAr4 (Member) (Head of Department) ( er) January 1970 ABSTRACT A Model for Predicting the Costs of Research and Development in the Post Office Department. (January 1970) David E. Vatts, B. S. , Texas A&M University; Directed by: Dr...
Interim Models Developed to Predict Key Hanford Waste Glass Properties Using Composition
Vienna, John D.; Kim, Dong-Sang; Hrma, Pavel R.
2003-08-08T23:59:59.000Z
Over the past several years the amount of waste glass property data available in the open literature has increased markedly. We have compiled the data from over 2000 glass compositions, evaluated the data for consistency, and fit glass property models to portions of this database.[1] The properties modeled include normalized releases of boron (rB), sodium (rNa), and lithium (rLi) from glass exposed to the product consistency test (PCT), liquidus temperature (TL) of glasses in the spinel and zircon primary phase field, viscosity (?) at 1150°C (?1150) and as a function of temperature (?T), and molar volume (V). These models were compared to some of the previously available models and were found to predict the properties of glasses not used in model fitting better and covered broader glass composition regions than the previous ones. This paper summarizes the data collected and the models that resulted from this effort.
Blackman, Jonathan; Galley, Chad R; Szilagyi, Bela; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A
2015-01-01T23:59:59.000Z
Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. In this paper, we construct an accurate and fast-to-evaluate surrogate model for numerical relativity (NR) waveforms from non-spinning binary black hole coalescences with mass ratios from $1$ to $10$ and durations corresponding to about $15$ orbits before merger. Our surrogate, which is built using reduced order modeling techniques, is distinct from traditional modeling efforts. We find that the full multi-mode surrogate model agrees with waveforms generated by NR to within the numerical error of the NR code. In particular, we show that our modeling strategy produces surrogates which can correctly predict NR waveforms that were {\\em not} used for the surrogate's training. For all practical purposes, then, the surrogate waveform model is equivalent to the high-accuracy, large-scale simulation waveform but can be evaluated in a millisecond to a second dependin...
Earthquake prediction: Simple methods for complex phenomena
Luen, Bradley
2010-01-01T23:59:59.000Z
and predictions . . . . . . . . . . . . . . . . . . . . .6.1 Assessing models and predictions . . . . . . .What are earthquake predictions and forecasts? . . . . . .
Neural Modeling and Control of Diesel Engine with Pollution Constraints
Ouladsine, Mustapha; Dovifaaz, Xavier; 10.1007/s10846-005-3806-y
2009-01-01T23:59:59.000Z
The paper describes a neural approach for modelling and control of a turbocharged Diesel engine. A neural model, whose structure is mainly based on some physical equations describing the engine behaviour, is built for the rotation speed and the exhaust gas opacity. The model is composed of three interconnected neural submodels, each of them constituting a nonlinear multi-input single-output error model. The structural identi?cation and the parameter estimation from data gathered on a real engine are described. The neural direct model is then used to determine a neural controller of the engine, in a specialized training scheme minimising a multivariable criterion. Simulations show the effect of the pollution constraint weighting on a trajectory tracking of the engine speed. Neural networks, which are ?exible and parsimonious nonlinear black-box models, with universal approximation capabilities, can accurately describe or control complex nonlinear systems, with little a priori theoretical knowledge. The present...
Merson, Alexander I; Abdalla, Filipe B; Gonzalez-Perez, Violeta; Lagos, Claudia del P; Mei, Simona
2015-01-01T23:59:59.000Z
High redshift galaxy clusters allow us to examine galaxy formation in extreme environments. Here we compile data for $z>1$ galaxy clusters to test the predictions from one of the latest semi-analytical models of galaxy formation. The model gives a good match to the slope and zero-point of the cluster red sequence. The model is able to match the cluster galaxy luminosity function at faint and bright magnitudes, but under-estimates the number of galaxies around the break in the luminosity function. We find that simply assuming a weaker dust attenuation improves the model predictions for the cluster galaxy luminosity function, but worsens the predictions for the red sequence at bright magnitudes. Examination of the properties of the bright cluster galaxies suggests that the default dust attenuation is very large due to these galaxies having large reservoirs of cold gas as well as small radii. We find that matching the luminosity function and colours of high redshift cluster galaxies, whilst remaining consistent ...
Model Based Control of Refrigeration Systems
Lars Finn; Sloth Larsen; Central R
2005-01-01T23:59:59.000Z
Thybo has supervised the work. I would especially like to express my gratitude to my good friend, dive mate, college and supervisor Claus Thybo, for his invaluable help, support and inspiration. His guidance and support has truly been ideal. Without his presence this project would not have been at all and it wouldn’t have been so enjoyable. I would like to thank Jakob Stoustrup for sharing of his profound knowledge within control theory, that has improved the acad-emic level of this thesis. Moreover I would like to thank Henrik Rasmussen, who has more than a lifetimes experience within application of control theory. His sincere and eager interest in my work has truly been a source of inspiration. I would like to thank Professor Manfred Morari for giving me the opportunity to stay at the Automatic Control Laboratory, ETH Zürich and for giving me valuable guidance while I was there. I was amazed by the unique scientific milieu and the high academic level there. I would especially like to thank Tobias Geyer, who contributed with many ideas and a lot of help, while I was at the ETH. I would furthermore like to thank him for taking of his valuable time at the ending of his Ph.D.-study to come and visit Danfoss
Lubliner, Howard
2011-12-31T23:59:59.000Z
for states other than those the model was developed for. To address this gap the Kansas Department of Transportation (KDOT) commissioned this study to analyze both the accuracy and the practicality of using these crash prediction models on Kansas highways...
Wang, Chien.; Prinn, Ronald G.
The possible trends for atmospheric carbon monoxide in the next 100 yr have been illustrated using a coupled atmospheric chemistry and climate model driven by emissions predicted by a global economic development model. ...
Model Specification for Networked Outdoor Lighting Control Systems
Broader source: Energy.gov [DOE]
The DOE Municipal Solid-State Street Lighting Consortium's Model Specification for Networked Outdoor Lighting Control Systems is a tool designed to help cities, utilities, and other local agencies...
UNCORRECTED 2 Stochastic adaptive control model for traffic signal systems
Detwiler, Russell
UNCORRECTED PROOF 1 2 Stochastic adaptive control model for traffic signal systems 3 X.-H. Yu a,1 , W.W. Recker b,* 4 a Department of Electrical Engineering, California Polytechnic State University
2.003 Modeling Dynamics and Control I, Spring 2002
Trumper, David L.
First of two-term sequence on modeling, analysis and control of dynamic systems. Mechanical translation, uniaxial rotation, electrical circuits and their coupling via levers, gears and electro-mechanical devices. Analytical ...
Advanced LD Engine Systems and Emissions Control Modeling and...
Broader source: Energy.gov (indexed) [DOE]
Light-Duty Engine Systems and Emissions Control Modeling and Analysis Zhiming Gao (PI) C. Stuart Daw (Co-PI, Presenter) Oak Ridge National Laboratory This presentation does not...
Experimental Studies for DPF and SCR Model, Control System, and...
Broader source: Energy.gov (indexed) [DOE]
CPF and SCR Model, Control System, and OBD Development for Engines Using Diesel and Biodiesel Fuels John H. Johnson, P.I. Gordon G. Parker, Co-P.I. & Presenter Jeffrey D. Naber,...
Experimental Studies for DPF and SCR Model, Control System, and...
Broader source: Energy.gov (indexed) [DOE]
DPF and SCR Model, Control System, and OBD Development for Engines Using Diesel and Biodiesel Fuels John H. Johnson, P.I. Gordon G. Parker, Co-P.I. & Presenter Michigan...
Experimental Studies for DPF and SCR Model, Control System, and...
Broader source: Energy.gov (indexed) [DOE]
CPF and SCR Model, Control System, and OBD Development for Engines Using Diesel and Biodiesel Fuels John H. Johnson, P.I. Gordon G. Parker, Co-P.I. & Presenter Michigan...
Integrated modeling of the electric grid, communications, and control
Nutaro, James J [ORNL; Miller, Laurie E [ORNL; Shankar, Mallikarjun [ORNL; Kuruganti, Phani Teja [ORNL
2006-01-01T23:59:59.000Z
We present a central concern in modeling and simulating electric grids and the information infrastructure that monitors and controls them: hybrid modeling and simulation. We argue that imminent modernizations and new technologies will require a joint (hybrid) modeling of the continuous world of power systems and the discrete world of events sparked by external contingencies, and by communication, computation, and control operations. The power systems community requires methods to model and simulate hybrid scenarios for systems as large and complex as the electric grid. We discuss an approach based on DEVS and present a scenario in which the integrated information and electric grid infrastructures address a frequency maintenance problem.
MODELING AND CONTROL OF A CONTINUOUS BIOREACTOR WITH CROSSFLOW FILTRATION
Skogestad, Sigurd
MODELING AND CONTROL OF A CONTINUOUS BIOREACTOR WITH CROSSÂFLOW FILTRATION Ying Zhao and Sigurd on an industrial application of a continuous bioreactor with crossÂflow filtration. In this paper the general study the possibility of partial control of this bioreactor. keywords: Continuous bioreactor
MODELING AND CONTROL OF A DIESEL HCCI ENGINE
Paris-Sud XI, Université de
MODELING AND CONTROL OF A DIESEL HCCI ENGINE J. Chauvin A. Albrecht G. Corde N. Petit Institut Abstract: This article focuses on the control of a Diesel engine airpath. We propose a detailed description of the airpath of a Diesel HCCI engine supported by experimental results. Moreover, we propose a simple, yet
A Fault Model and Mutation Testing of Access Control Policies
Xie, Tao
A Fault Model and Mutation Testing of Access Control Policies Evan Martin and Tao Xie Dept (responses) against expected ones. Unfortunately, manual testing is tedious and few tools exist for automated in web applications. It controls which principals such as users or processes have access to which re
Development of model reference adaptive control theory for electric power plant control applications
Mabius, L.E.
1982-09-15T23:59:59.000Z
The scope of this effort includes the theoretical development of a multi-input, multi-output (MIMO) Model Reference Control (MRC) algorithm, (i.e., model following control law), Model Reference Adaptive Control (MRAC) algorithm and the formulation of a nonlinear model of a typical electric power plant. Previous single-input, single-output MRAC algorithm designs have been generalized to MIMO MRAC designs using the MIMO MRC algorithm. This MRC algorithm, which has been developed using Command Generator Tracker methodologies, represents the steady state behavior (in the adaptive sense) of the MRAC algorithm. The MRC algorithm is a fundamental component in the MRAC design and stability analysis. An enhanced MRC algorithm, which has been developed for systems with more controls than regulated outputs, alleviates the MRC stability constraint of stable plant transmission zeroes. The nonlinear power plant model is based on the Cromby model with the addition of a governor valve management algorithm, turbine dynamics and turbine interactions with extraction flows. An application of the MRC algorithm to a linearization of this model demonstrates its applicability to power plant systems. In particular, the generated power changes at 7% per minute while throttle pressure and temperature, reheat temperature and drum level are held constant with a reasonable level of control. The enhanced algorithm reduces significantly control fluctuations without modifying the output response.