HOMER® Micropower Optimization Model
Lilienthal, P.
2005-01-01
NREL has developed the HOMER micropower optimization model. The model can analyze all of the available small power technologies individually and in hybrid configurations to identify least-cost solutions to energy requirements. This capability is valuable to a diverse set of energy professionals and applications. NREL has actively supported its growing user base and developed training programs around the model. These activities are helping to grow the global market for solar technologies.
HOMER: The Micropower Optimization Model
Not Available
2004-03-01
HOMER, the micropower optimization model, helps users to design micropower systems for off-grid and grid-connected power applications. HOMER models micropower systems with one or more power sources including wind turbines, photovoltaics, biomass power, hydropower, cogeneration, diesel engines, cogeneration, batteries, fuel cells, and electrolyzers. Users can explore a range of design questions such as which technologies are most effective, what size should components be, how project economics are affected by changes in loads or costs, and is the renewable resource adequate.
Givler, T.; Lilienthal, P.
2005-05-01
This paper discusses using HOMER Software, NREL's Micropower Optimization Model, to explore the role of gen-sets in small solar power systems in Sri Lanka.
Micropower | Open Energy Information
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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION J APPENDIX E LIST OFAMERICA'SHeavyAgency (IRENA) JumpLiteratureMengdong Xiehe NewMichiganMicropower
Industrial Applications for Micropower: A Market Assessment,...
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More Documents & Publications Opportunities for Micropower and Fuel CellGas Turbine Hybrid Systems in Industrial Applications - Volume I, January 2000...
Opportunities for Micropower and Fuel Cell/Gas Turbine Hybrid...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
I, January 2000 Opportunities for Micropower and Fuel CellGas Turbine Hybrid Systems in Industrial Applications - Volume I, January 2000 In this January 2000 report, Arthur D....
Opportunities for Micropower and Fuel Cell/Gas Turbine Hybrid...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
I, January 2000 Industrial Applications for Micropower: A Market Assessment, November 1999 Assessment of Replicable Innovative Industrial Cogeneration Applications, June 2001...
Solar Thermoelectric Generator for Micropower Applications R. AMATYA1,2
Ram, Rajeev J.
Solar Thermoelectric Generator for Micropower Applications R. AMATYA1,2 and R.J. RAM1 1.--Research 02139, USA. 2.--e-mail: ramatya@mit.edu Solar thermoelectric generators (STG) using cheap parabolic concentrators with high-ZT modules can be a cost-effective alternative to solar photovoltaics for micropower
Stochastic Optimization Modeling
2014-07-04
Third, its theoretical properties were studied (convexity, separability and optimality con- .... in Section 3, have the structure of problems PEV and PS, respectively, and for this reason we review ... may produce poor optimization results as it is depicted in Figure 1 for the instance with ...... Second, it has been assessed that the.
Daraio, Chiara
is successfully demonstrated. The micro-power plant consists of micro-SOFCs, a micro-reactor and a gas carrierA thermally self-sustained micro-power plant with integrated micro-solid oxide fuel cells, micro l i g h t s g r a p h i c a l a b s t r a c t The assembly and operation of a micro-power plant
Phase coded, micro-power impulse radar motion sensor
McEwan, Thomas E. (Livermore, CA)
1996-01-01
A motion sensing, micro-power impulse radar MIR impresses on the transmitted signal, or the received pulse timing signal, one or more frequencies lower than the pulse repetition frequency, that become intermediate frequencies in a "IF homodyne" receiver. Thus, many advantages of classical RF receivers can be thereby be realized with ultra-wide band radar. The sensor includes a transmitter which transmits a sequence of electromagnetic pulses in response to a transmit timing signal at a nominal pulse repetition frequency. A receiver samples echoes of the sequence of electromagnetic pulses from objects within the field with controlled timing, in response to a receive timing signal, and generates a sample signal in response to the samples. A timing circuit supplies the transmit timing signal to the transmitter and supplies the receive timing signal to the receiver. The relative timing of the transmit timing signal and the receive timing signal is modulated between a first relative delay and a second relative delay at an intermediate frequency, causing the receiver to sample the echoes such that the time between transmissions of pulses in the sequence and samples by the receiver is modulated at the intermediate frequency. Modulation may be executed by modulating the pulse repetition frequency which drives the transmitter, by modulating the delay circuitry which controls the relative timing of the sample strobe, or by modulating amplitude of the transmitted pulses. The electromagnetic pulses will have a nominal center frequency related to pulse width, and the first relative delay and the second relative delay between which the timing signals are modulated, differ by less than the nominal pulse width, and preferably by about one-quarter wavelength at the nominal center frequency of the transmitted pulses.
Phase coded, micro-power impulse radar motion sensor
McEwan, T.E.
1996-05-21
A motion sensing, micro-power impulse radar MIR impresses on the transmitted signal, or the received pulse timing signal, one or more frequencies lower than the pulse repetition frequency, that become intermediate frequencies in a ``IF homodyne`` receiver. Thus, many advantages of classical RF receivers can be thereby be realized with ultra-wide band radar. The sensor includes a transmitter which transmits a sequence of electromagnetic pulses in response to a transmit timing signal at a nominal pulse repetition frequency. A receiver samples echoes of the sequence of electromagnetic pulses from objects within the field with controlled timing, in response to a receive timing signal, and generates a sample signal in response to the samples. A timing circuit supplies the transmit timing signal to the transmitter and supplies the receive timing signal to the receiver. The relative timing of the transmit timing signal and the receive timing signal is modulated between a first relative delay and a second relative delay at an intermediate frequency, causing the receiver to sample the echoes such that the time between transmissions of pulses in the sequence and samples by the receiver is modulated at the intermediate frequency. Modulation may be executed by modulating the pulse repetition frequency which drives the transmitter, by modulating the delay circuitry which controls the relative timing of the sample strobe, or by modulating amplitude of the transmitted pulses. The electromagnetic pulses will have a nominal center frequency related to pulse width, and the first relative delay and the second relative delay between which the timing signals are modulated, differ by less than the nominal pulse width, and preferably by about one-quarter wavelength at the nominal center frequency of the transmitted pulses. 5 figs.
Optimization Modeling Languages Emmanuel Fragni`ere
Gondzio, Jacek
Optimization Modeling Languages Emmanuel Fragni`ere HEC, Department of Management, University, 1999 1 #12;Abstract The access to advanced optimization software needs more and more sophisticated modeling tools. Optimization modeling languages are tools that facilitate the decision making process based
MODELING, SIMULATION AND OPTIMIZATION OF GROUND SOURCE
MODELING, SIMULATION AND OPTIMIZATION OF GROUND SOURCE HEAT PUMP SYSTEMS By MUHAMMAD HAIDER KHAN AND OPTIMIZATION OF GROUND SOURCE HEAT PUMP SYSTEMS Thesis Approved..................................................................................................................... 1 1.1 Overview of Ground Source Heat Pump Systems.............................................. 1 1
Modeling and optimization of permanent magnetic motors
Pinkham, Andrew P
2008-01-01
This thesis develops analytic models for the prediction and optimization of radial-flux permanent magnet motor torque and efficiency. It also facilitates the design optimization of electromagnetically-powered rotorcraft ...
Python Optimization Modeling Objects (Pyomo)
2009-12-29
Dec 29, 2009 ... Python Repository [10]. Coopr includes a flexible framework for applying optimizers ..... for transmission across a communications channel. This includes simple .... This example network has two major compute ..... a Lockheed Martin Company, for the United States Department of Energy's National. Nuclear ...
New Models Help Optimize Development of Bakken Shale Resources...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
New Models Help Optimize Development of Bakken Shale Resources New Models Help Optimize Development of Bakken Shale Resources February 7, 2012 - 12:00pm Addthis Washington, DC -...
Modeling and Optimization of Hybrid Solar Thermoelectric Systems...
Office of Scientific and Technical Information (OSTI)
Journal Article: Modeling and Optimization of Hybrid Solar Thermoelectric Systems with Thermosyphons Citation Details In-Document Search Title: Modeling and Optimization of Hybrid...
Reactor Modeling and Recipe Optimization of Polyether Polyol Processes
Grossmann, Ignacio E.
Reactor Modeling and Recipe Optimization of Polyether Polyol Processes Spring 2013 EWO Meeting Yisu.M. Wassick. Reactor Modeling and Recipe Optimization of Polyether Polyol Processes: Polypropylene Glycol
Applying the Battery Ownership Model in Pursuit of Optimal Battery...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Applying the Battery Ownership Model in Pursuit of Optimal Battery Use Strategies Applying the Battery Ownership Model in Pursuit of Optimal Battery Use Strategies 2012 DOE...
Optimization of neuron models using grid computing
Vella, Mike
2011-09-09
stream_source_info Mike_Vella.ppt.txt stream_content_type text/plain stream_size 2634 Content-Encoding UTF-8 stream_name Mike_Vella.ppt.txt Content-Type text/plain; charset=UTF-8 Optimization of neuron models using grid computing... channels Set of information to be included in a model is large Single neuron multi-compartment models Why optimize? Single neuron models provide a basis for understanding cell and local circuit function Maximal conductances, compartment capacitances...
Optimized delta expansion for relativistic nuclear models
G. Krein; R. S. Marques de Carvalho; D. P. Menezes; M. Nielsen; M. B. Pinto
1997-09-24
The optimized $\\delta$-expansion is a nonperturbative approach for field theoretic models which combines the techniques of perturbation theory and the variational principle. This technique is discussed in the $\\lambda \\phi^4$ model and then implemented in the Walecka model for the equation of state of nuclear matter. The results obtained with the $\\delta$ expansion are compared with those obtained with the traditional mean field, relativistic Hartree and Hartree-Fock approximations.
Model-Based Transient Calibration Optimization for Next Generation...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Based Transient Calibration Optimization for Next Generation Diesel Engines Model-Based Transient Calibration Optimization for Next Generation Diesel Engines 2005 Diesel Engine...
Optimal Model-Based Production Planning
Grossmann, Ignacio E.
Given Refinery configuration: Process units Feedstock & Final Product Objective Select crude oils Hydrotreatment Gasoline blending Distillate blending Gas oil blending Cat Crack CDU crude1 crude2 butane Fuel gas1 Optimal Model-Based Production Planning for Refinery Operation Abdulrahman Alattas Advisor
Optimal Model-Based Production Planning for
Grossmann, Ignacio E.
Motivation Refining Operation and crude cost variable cost of production Largest product price components Key to refinery profit and economics Refinery production planning models Operation optimization Crude selection Statement Cat Ref Hydrotreatment Gasoline blending Distillate blending Gas oil blending Cat Crack CDU crude1
Optimal Model-Based Production Planning
Grossmann, Ignacio E.
Given Refinery configuration: Process units Feedstock & Final Product Objective Select crude oils;2 Introduction Refinery production planning models Operation optimization Crude selection Maximizing profit Hydrotreatment Gasoline blending Distillate blending Gas oil blending Cat Crack CDU crude1 crude2 butane Fuel gas
MODEL-BASED OPTIMAL OPERATION OF SEEDED BATCH CRYSTALLISATION PROCESSES
Van den Hof, Paul
.mesbah@tudelft.nl Dynamic optimization is applied for optimal control of a semi-industrial batch crystallisation process of the open-loop optimal control due to plant-model mismatch, unmeasured process disturbances, irreproducibleMODEL-BASED OPTIMAL OPERATION OF SEEDED BATCH CRYSTALLISATION PROCESSES A. Mesbah1, 2 , J. Landlust
Bergman, Keren
Mathematical Modeling for CostMathematical Modeling for Cost Optimization of PV Recycling of plants Capital costs to open up a recycling center 4 #12;Time Horizon for PV Recycling Infrastructure 5 cost $189K System optimal cost $1079K 11 #12;PV Recycling Cost Optimization 1. Where is the optimized
MODELING, VERIFICATION AND OPTIMIZATION OF HYBRID GROUND SOURCE HEAT PUMP
MODELING, VERIFICATION AND OPTIMIZATION OF HYBRID GROUND SOURCE HEAT PUMP SYSTEMS IN ENERGYPLUS, VERIFICATION AND OPTIMIZATION OF HYBRID GROUND SOURCE HEAT PUMP SYSTEMS IN ENERGYPLUS Thesis Approved by: Dr.................................................................................................................... 16 MODELING OF HYBRID GROUND SOURCE HEAT PUMP SYSTEMS IN ENERGYPLUS
Optimization models in finance Ma 450 Darinka Dentcheva Fall 2014 darinka.dentcheva@stevens.edu
Dentcheva, Darinka
Optimization models in finance Ma 450 Darinka Dentcheva Fall 2014 darinka and dynamic optimization problems occurring in finance. We shall discuss linear and non-linear optimization models of finance, dynamic (sequential) optimization, optimization under uncertainty, mathematical models
Shi, Cong, Ph.D. Massachusetts Institute of Technology
2012-01-01
Many if not most of the core problems studied in operations management fall into the category of multi-stage stochastic optimization models, whereby one considers multiple, often correlated decisions to optimize a particular ...
optimal initial conditions for coupling ice sheet models to earth...
Office of Scientific and Technical Information (OSTI)
optimal initial conditions for coupling ice sheet models to earth system models Perego, Mauro Sandia National Laboratories Sandia National Laboratories; Price, Stephen F. Dr...
Finding Benefits by Modeling and Optimizing Steam and Power Systems
Jones, B.; Nelson, D.
2007-01-01
A site-wide steam modeling and optimization program (Visual MESA) was implemented at the INEOS Chocolate Bayou site. This program optimizes steam production, compressor turbine extraction, pump operation (turbine/motor) operation, as well...
15.094 Systems Optimization: Models and Computation, Spring 2002
Freund, Robert Michael
A computational and application-oriented introduction to the modeling of large-scale systems in a wide variety of decision-making domains and the optimization of such systems using state-of-the-art optimization software. ...
Grothey, Andreas
Optimization Modelling Example Design Implementation Conclusions A Structure-Conveying Modelling Languages for Mathematical Programming 3 An example problem from network design 4 Design of Structured, K. Woodsend Structure-Conveying Modelling Language #12;Optimization Modelling Example Design
Improved Crosstalk Modeling with Applications to Noise Constrained Interconnect Optimization
Pan, David Z.
Improved Crosstalk Modeling with Applications to Noise Constrained Interconnect Optimization This paper presents a highly accurate yet efficient crosstalk noise model, the 2-¢ model, and applies to be noise immune, ac- curate yet efficient noise models are needed to guide interconnect optimizations
Error Control Based Model Reduction for Parameter Optimization of Elliptic
of technical devices that rely on multiscale processes, such as fuel cells or batteries. As the solutionError Control Based Model Reduction for Parameter Optimization of Elliptic Homogenization Problems optimization of elliptic multiscale problems with macroscopic optimization functionals and microscopic material
Computational Modeling and Optimization of Proton Exchange Membrane Fuel Cells
Victoria, University of
Computational Modeling and Optimization of Proton Exchange Membrane Fuel Cells by Marc Secanell and Optimization of Proton Exchange Membrane Fuel Cells by Marc Secanell Gallart Bachelor in Engineering cells. In this thesis, a computational framework for fuel cell analysis and optimization is presented
Model Identification for Optimal Diesel Emissions Control
Stevens, Andrew J.; Sun, Yannan; Song, Xiaobo; Parker, Gordon
2013-06-20
In this paper we develop a model based con- troller for diesel emission reduction using system identification methods. Specifically, our method minimizes the downstream readings from a production NOx sensor while injecting a minimal amount of urea upstream. Based on the linear quadratic estimator we derive the closed form solution to a cost function that accounts for the case some of the system inputs are not controllable. Our cost function can also be tuned to trade-off between input usage and output optimization. Our approach performs better than a production controller in simulation. Our NOx conversion efficiency was 92.7% while the production controller achieved 92.4%. For NH3 conversion, our efficiency was 98.7% compared to 88.5% for the production controller.
Modeling and Multidimensional Optimization of a Tapered Free...
Office of Scientific and Technical Information (OSTI)
Electron Laser Citation Details In-Document Search Title: Modeling and Multidimensional Optimization of a Tapered Free Electron Laser Authors: Jiao, Y. ; SLAC Beijing, Inst....
Römisch, Werner
the model via uncertain electricity demand, heat demand, spot prices, and future prices. The objectiveMEAN-RISK OPTIMIZATION MODELS FOR ELECTRICITY PORTFOLIO MANAGEMENT 1 Mean-risk optimization models for electricity portfolio management Andreas Eichhorn and Werner R¨omisch Abstract-- The possibility
Sensitivity of Optimal Operation of an Activated Sludge Process Model
Skogestad, Sigurd
Sensitivity of Optimal Operation of an Activated Sludge Process Model Antonio Araujo, Simone sensitivity analysis of optimal operation conducted on an activated sludge process model based on the test.[7] applied a systematic procedure for control structure design of an activated sludge process
Local energy management through mathematical modeling and optimization
Craft David (David Loren), 1973-
2004-01-01
(cont.) Extensions to the core TOTEM model include a demand charge model, used for making daily optimal control decisions when the electric bill includes a charge based on the monthly maximum power draw. The problem of ...
Utility system integration and optimization models for nuclear power management
Deaton, Paul Ferris
1973-01-01
A nuclear power management model suitable for nuclear utility systems optimization has been developed for use in multi-reactor fuel management planning over periods of up to ten years. The overall utility planning model ...
MIP Models and BB Strategies in Brachytherapy Treatment Optimization
Meyer, Robert R.
MIP Models and BB Strategies in Brachytherapy Treatment Optimization Robert R. Meyer (rrmMadison Abstract. Brachytherapy (brachy being derived from a Greek word meaning short) is the treatment of cancer: brachytherapy, prostate cancer, branchandbound, optimization, inte ger programming, treatment planning
Modeling and Optimal Design of Di ractive Optical Structures
Dobson, David C.
Modeling and Optimal Design of Di ractive Optical Structures Gang Bao Department of Mathematics be designed to perform functions unattainable with traditionaloptical elements. For example, structures and for the determination of optimal" device designs. In contrast to the case of traditional optical structures, geometrical
Online Modeling in the Process Industry for Energy Optimization
Alexander, J.
1988-01-01
"This paper discusses how steady state models are being used in the process industry to perform online energy optimization of steam and electrical systems. It presents process demands commonly found in the processing industry in terms of steam...
An Optimization Model for Eco-Driving at Signalized Intersection
Chen, Zhi
2013-07-15
This research develops an optimization model for eco-driving at signalized intersection. In urban areas, signalized intersections are the “hot spots” of air emissions and have significant negative environmental and health impacts. Eco-driving is a...
Simulation Models to Optimize the Energy Consumption of Buildings
Burhenne, S.; Jacob, D.
2008-01-01
In practice, building operation systems are only adjusted during commissioning. This is done manually and leads to failure-free but often inefficient operation. This work deals with the development of simulation models to describe and optimize...
Contingency contractor optimization. phase 3, model description and formulation.
Gearhart, Jared Lee; Adair, Kristin Lynn; Jones, Katherine A.; Bandlow, Alisa; Detry, Richard Joseph; Durfee, Justin D.; Jones, Dean A.; Martin, Nathaniel; Nanco, Alan Stewart; Nozick, Linda Karen
2013-06-01
The goal of Phase 3 the OSD ATL Contingency Contractor Optimization (CCO) project is to create an engineering prototype of a tool for the contingency contractor element of total force planning during the Support for Strategic Analysis (SSA). An optimization model was developed to determine the optimal mix of military, Department of Defense (DoD) civilians, and contractors that accomplishes a set of user defined mission requirements at the lowest possible cost while honoring resource limitations and manpower use rules. An additional feature allows the model to understand the variability of the Total Force Mix when there is uncertainty in mission requirements.
Contingency contractor optimization. Phase 3, model description and formulation.
Gearhart, Jared Lee; Adair, Kristin Lynn; Jones, Katherine A.; Bandlow, Alisa; Durfee, Justin D.; Jones, Dean A.; Martin, Nathaniel; Detry, Richard Joseph; Nanco, Alan Stewart; Nozick, Linda Karen [Cornell University
2013-10-01
The goal of Phase 3 the OSD ATL Contingency Contractor Optimization (CCO) project is to create an engineering prototype of a tool for the contingency contractor element of total force planning during the Support for Strategic Analysis (SSA). An optimization model was developed to determine the optimal mix of military, Department of Defense (DoD) civilians, and contractors that accomplishes a set of user defined mission requirements at the lowest possible cost while honoring resource limitations and manpower use rules. An additional feature allows the model to understand the variability of the Total Force Mix when there is uncertainty in mission requirements.
Efficient Production Optimization Using Flow Network Models
Lerlertpakdee, Pongsathorn
2012-10-19
to predict the response of real reservoirs under proposed changes in the model inputs. To speed up reservoir response predictions without compromising accuracy, fast surrogate models have been proposed. These models are either derived by preserving...
Gas permeation carbon capture --- Process modeling and optimization
Morinelly, Juan; Miller, David
2011-01-01
A multi-staged gas permeation carbon capture process model was developed in Aspen Custom Modeler{reg_sign} (ACM) and optimized in the context of the retrofit of a 550 MW subcritical pulverized coal (PC) power plant. The gas permeation stages in the process are described by a custom multi-component, hollowfiber membrane model. Gas transport across the asymmetric membrane was modeled according to the solution-diffusion model for the selective skin layer and the assumption of negligible flux resistance by the porous support. Counter-current, one-dimensional plug flow was assumed with permeate pressure drop in the fiber lumen side due to capillary constrained flow. A modular optimization framework was used to minimize the levelized cost of electricity (LCOE) by optimizing a set of key process variables. The framework allows the external control of multiple simulation modules from different software packages from a common interface.
Modeling and Optimization of PEMFC Systems and its Application to Direct Hydrogen Fuel Cell Vehicles
Zhao, Hengbing; Burke, Andy
2008-01-01
In the original fuel cell optimization model [11], only theIn the original fuel cell optimization model, only the dryof the fuel cell system and optimization of the operating
Modeling and Optimizing Ergonomic Activities in Automobile Product Development
da Silva, Alberto Rodrigues
Modeling and Optimizing Ergonomic Activities in Automobile Product Development João Ferreira Anna.silva@acm.org Abstract We collect ergonomic rules and normative rules considerations for automobile business and modeled as use of past experience. Also we intend to define ergonomic associated templates, which reflect
OPTIMAL EXPERIMENTAL DESIGN FOR MODELING BATTERY DEGRADATION Joel C. Forman
Krstic, Miroslav
, battery health dependence on voltage, and a lack of power fade under the cy- cling conditions. The useOPTIMAL EXPERIMENTAL DESIGN FOR MODELING BATTERY DEGRADATION Joel C. Forman Mechanical Engineering.edu ABSTRACT Accurate battery health modeling allows one to make better design decisions, enables health
Reconciling the optimal and empirical approaches to modelling stomatal conductance
atmospheric CO2, and thus can be used to test for stomatal acclimation to elevated CO2. The reconciliation cost of carbon gain. The new model is fitted to a range of datasets ranging from tropical to boreal models, marginal water cost of carbon, stomatal conductance, stomatal optimization Received 24 May 2010
Nonlinear Hybrid Dynamical Systems: Modeling, Optimal Control, and Applications
Stryk, Oskar von
Nonlinear Hybrid Dynamical Systems: Modeling, Optimal Control, and Applications Martin Buss1¨unchen, Germany Abstract. Nonlinear hybrid dynamical systems are the main focus of this paper. A modeling Introduction The recent interest in nonlinear hybrid dynamical systems has forced the merger of two very
Optimal Model-Based Production Planning
Grossmann, Ignacio E.
Given Refinery configuration: Process units Feedstock & Final Product Objective Select crude oils Hydrotreatment Gasoline blending Distillate blending Gas oil blending Cat Crack CDU crude1 crude2 butane Fuel gas Refinery Planning Model Swing cut models: Improvement from the fixed-yield approach Crude oil cuts
Optimizing Symbolic Model Checking for Statecharts
Beame, Paul
model checking to a statecharts model, that of an electrical power distribution (EPD) system for Boeing checking based on binary decision diagrams is a powerful formal verification technique for reactive systems of a collision avoidance system and a fault- tolerant electrical power distribution (EPD) system, both used
Block-oriented modeling of superstructure optimization problems
Friedman, Z; Ingalls, J; Siirola, JD; Watson, JP
2013-10-15
We present a novel software framework for modeling large-scale engineered systems as mathematical optimization problems. A key motivating feature in such systems is their hierarchical, highly structured topology. Existing mathematical optimization modeling environments do not facilitate the natural expression and manipulation of hierarchically structured systems. Rather, the modeler is forced to "flatten" the system description, hiding structure that may be exploited by solvers, and obfuscating the system that the modeling environment is attempting to represent. To correct this deficiency, we propose a Python-based "block-oriented" modeling approach for representing the discrete components within the system. Our approach is an extension of the Pyomo library for specifying mathematical optimization problems. Through the use of a modeling components library, the block-oriented approach facilitates a clean separation of system superstructure from the details of individual components. This approach also naturally lends itself to expressing design and operational decisions as disjunctive expressions over the component blocks. By expressing a mathematical optimization problem in a block-oriented manner, inherent structure (e.g., multiple scenarios) is preserved for potential exploitation by solvers. In particular, we show that block-structured mathematical optimization problems can be straightforwardly manipulated by decomposition-based multi-scenario algorithmic strategies, specifically in the context of the PySP stochastic programming library. We illustrate our block-oriented modeling approach using a case study drawn from the electricity grid operations domain: unit commitment with transmission switching and N - 1 reliability constraints. Finally, we demonstrate that the overhead associated with block-oriented modeling only minimally increases model instantiation times, and need not adversely impact solver behavior. (C) 2013 Elsevier Ltd. All rights reserved.
Optimal Model-Based Production Planning
Grossmann, Ignacio E.
of column j) F1=Dj+Bk Successful model Example: 4 cascaded conventional columns, with 18- component feed: Ignacio Grossmann Chemical Engineering Department Carnegie Mellon University EWO Meeting March 2009 #12
Optimal Model-Based Production Planning
Grossmann, Ignacio E.
configuration Processing 2 crude oils & importing heavy naphtha Swing cut model Offers lower net cost (lighter) 142 0 Crude2 (heavier) 289 469 Other Feedstock Heavy Naphtha 13 9 Refinery Production Fuel Gas 13 Gasoline blending Distillate blending Gas oil blending Cat Crack CDU crude1 crude2 butane Fuel gas Premium
Optimal thermalization in a shell model of homogeneous turbulence
Thalabard, Simon
2015-01-01
We investigate the turbulence-induced dissipation of the large scales in a statistically homogeneous flow using an "optimal closure," which one of us (BT) has recently exposed in the context of Hamiltonian dynamics. This statistical closure employs a Gaussian model for the turbulent scales, with corresponding vanishing third cumulant, and yet it captures an intrinsic damping. The key to this apparent paradox lies in a clear distinction between true ensemble averages and their proxies, most easily grasped when one works directly with the Liouville equation rather than the cumulant hierarchy. We focus on a simple problem for which the optimal closure can be fully and exactly worked out: the relaxation arbitrarily far-from-equilibrium of a single energy shell towards Gibbs equilibrium in an inviscid shell model of 3D turbulence. The predictions of the optimal closure are validated against DNS and contrasted with those derived from EDQNM closure.
An Operational Model for Optimal NonDispatchable Demand Response
Grossmann, Ignacio E.
An Operational Model for Optimal NonDispatchable Demand Response for Continuous PowerintensiveFACTS, $ Demand Response Energy Storage HVDC Industrial Customer PEV Renewable Energy Source: U.S.-Canada Power: To balance supply and demand of a power system, one can manipulate both: supply and demand demand response
Modeling and Optimal Regulation of Erythropoiesis Subject to Benzene Intoxication
Modeling and Optimal Regulation of Erythropoiesis Subject to Benzene Intoxication H.T. Banks1.C. 27607-5298, email: ColeC@meredith.edu December 20, 2003 Abstract Benzene (C6H6) is a highly flammable, and industrial processes. Benzene increases the incidence of leukemia in humans when they are exposed to high
Modeling and Computational Strategies for Optimal Development Planning of Offshore
Grossmann, Ignacio E.
1 Modeling and Computational Strategies for Optimal Development Planning of Offshore Oilfields for offshore oil and gas fields as a basis to include the generic fiscal rules with ringfencing provisions-integer programming. 1 Introduction Offshore oil and gas field development planning has received significant attention
Optimal control of a dengue epidemic model with vaccination
Rodrigues, Helena Sofia; Torres, Delfim F M
2011-01-01
We present a SIR+ASI epidemic model to describe the interaction between human and dengue fever mosquito populations. A control strategy in the form of vaccination, to decrease the number of infected individuals, is used. An optimal control approach is applied in order to find the best way to fight the disease.
Silvya Dewi Rahmawati Integrated Field Modeling and Optimization
Foss, Bjarne A.
Technology, Mathematics and Electrical Engineering Department of Engineering Cybernetics #12;ii Summary Oil of philosophiae doctor Trondheim, March 2012 Norwegian University of Science and Technology Faculty of Information with optimization presents many technological challenges in terms efficient algorithms to couple models, as well
Optimization Models for Shale Gas Water Management Linlin Yang
Grossmann, Ignacio E.
Optimization Models for Shale Gas Water Management Linlin Yang , Jeremy Manno and Ignacio E With the advancement in directional drilling and hydraulic fracturing, shale gas is predicted to provide 46% of the United States natural gas supply by 20351 . The number of wells drilled in the Marcellus shale play has
Surrogate modeling based on statistical techniques for multi-fidelity optimization
Lam, Rémi
2014-01-01
Designing and optimizing complex systems generally requires the use of numerical models. However, it is often too expensive to evaluate these models at each step of an optimization problem. Instead surrogate models can be ...
Optimization of flagellar swimming by a model sperm
B. U. Felderhof
2015-05-05
The swimming of a bead-spring chain in a viscous incompressible fluid as a model of a sperm is studied in the framework of low Reynolds number hydrodynamics. The optimal mode in the class of planar flagellar strokes of small amplitude is determined on the basis of a generalized eigenvalue problem involving two matrices which can be evaluated from the mobility matrix of the set of spheres constituting the chain. For an elastic chain with a cargo constraint for its spherical head, the actuating forces yielding a nearly optimal stroke can be determined. These can be used in a Stokesian dynamics simulation of large amplitude swimming.
Traffic Optimization to Control Epidemic Outbreaks in Metapopulation Models
Preciado, Victor M
2013-01-01
We propose a novel framework to study viral spreading processes in metapopulation models. Large subpopulations (i.e., cities) are connected via metalinks (i.e., roads) according to a metagraph structure (i.e., the traffic infrastructure). The problem of containing the propagation of an epidemic outbreak in a metapopulation model by controlling the traffic between subpopulations is considered. Controlling the spread of an epidemic outbreak can be written as a spectral condition involving the eigenvalues of a matrix that depends on the network structure and the parameters of the model. Based on this spectral condition, we propose a convex optimization framework to find cost-optimal approaches to traffic control in epidemic outbreaks.
Optimal threshold policies in a workload model with a variable number of service phases per job
Brouns, Gido
and termination control, optimal threshold policies, Markov decision processes. 1 Introduction Workload models of performance optimization is the question of how to control some type of system in an optimal way within in literature so far. Stidham and Weber 4 present a comprehensive overview of models for the optimal control
Hybrid fuzzy and optimal modeling for water quality evaluation
Wang, Dong; Singh, Vijay P.; Zhu, Yuansheng
2007-05-08
modeling for water quality evaluation Dong Wang, 1 Vijay P. Singh, 2 and Yuansheng Zhu 3 Received 1 September 2006; revised 16 December 2006; accepted 19 January 2007; published 8 May 2007. [1] Water quality evaluation entails both randomness and fuzziness..., the proposed models are flexible and adaptable for diagnosing the eutrophic status. Citation: Wang, D., V. P. Singh, and Y. Zhu (2007), Hybrid fuzzy and optimal modeling for water quality evaluation, Water Resour. Res., 43, W05415, doi:10.1029/2006WR005490. 1...
Wally, Karl
2006-05-01
Although battery technology is relatively mature, power sources continue to impose serious limitations for small, portable, mobile, or remote applications. A potentially attractive alternative to batteries is chemical fuel-to-electric conversion. Chemical fuels have volumetric energy densities 4 to 10 times those of batteries. However, realizing this advantage requires efficient chemical fuel-to-electric conversion. Direct electrochemical conversion would be the ideal, but, for most fuels, is generally not within the state-of-the-science. Next best, chemical-to-thermal-to-electric conversion can be attractive if efficiencies can be kept high. This small investigative project was an exploration into the feasibility of a novel hybrid (i.e., thermal-electrochemical) micropower converter of high theoretical performance whose demonstration was thought to be within near-term reach. The system is comprised of a hydrogen concentration electrochemical cell with physically identical hydrogen electrodes as anode and cathode, with each electrode connected to physically identical hydride beds each containing the same low-enthalpy-of-formation metal hydride. In operation, electrical power is generated by a hydrogen concentration differential across the electrochemical cell. This differential is established via coordinated heating and passive cooling of the corresponding hydride source and sink. Heating is provided by the exothermic combustion (i.e., either flame combustion or catalytic combustion) of a chemical fuel. Upon hydride source depletion, the role of source and sink are reversed, heating and cooling reversed, electrodes commutatively reversed, cell operation reversed, while power delivery continues unchanged. This 'regenerative flip' of source and sink hydride beds can be cycled continuously until all available heating fuel is consumed. Electricity is efficiently generated electrochemically, but hydrogen is not consumed, rather the hydrogen is regeneratively cycled as an electrochemical 'working fluid'.
de Weck, Olivier L.
System Modeling, Analysis, and Optimization Methodology for Diesel Exhaust After;System Modeling, Analysis, and Optimization Methodology for Diesel Exhaust After-treatment Technologies Developing new aftertreatment technologies to meet emission regulations for diesel engines is a growing
Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production...
Optimal Model of Distributed Energy System by Using GAMS and Case Study
Yang, Yongwen; Gao, Weijun; Ruan, Yingjun; Xuan, Ji; Zhou, Nan; Marnay, Chris
2005-01-01
Optimal Model of Distributed Energy System by Using GAMS andEnergy Reliability, Distributed Energy Program of the U.S.Optimal Model of Distributed Energy System by Using GAMS and
MATH 4/5794 Mathematical Modeling Demonstrations % MATH 4/5794: Optimization Modeling
Lodwick, Weldon
:'; ************************************************************ ************************************************************ *********** Multiple Sclerosis Plaque Detection ************ ************************************************************ ************************************************************ % MATH 4/5794: Optimization Modeling % EXAMPLES: W. A. Lodwick - Example 1, Multiple Sclerosis Plaque Detection % Example 2, Multiple Sclerosis Plaque Detection % Example 3, Multiple Sclerosis Plaque Detection
Optimizing ZigBee Security using Stochastic Model Checking
Yüksel, Ender; Nielson, Flemming; Fruth, Matthias; Kwiatkowska, Marta
2012-01-01
ZigBee is a fairly new but promising wireless sensor network standard that offers the advantages of simple and low resource communication. Nevertheless, security is of great concern to ZigBee, and enhancements are prescribed in the latest ZigBee specication: ZigBee-2007. In this technical report, we identify an important gap in the specification on key updates, and present a methodology for determining optimal key update policies and security parameters. We exploit the stochastic model checking approach using the probabilistic model checker PRISM, and assess the security needs for realistic application scenarios.
Efficient Nonlinear Optimization with Rigorous Models for Large Scale Industrial Chemical Processes
Zhu, Yu
2011-08-08
of Department, Michael Pishko May 2011 Major Subject: Chemical Engineering iii ABSTRACT Efficient Nonlinear Optimization with Rigorous Models for Large Scale Industrial Chemical Processes. (May 2011) Yu Zhu, B.S., Zhejiang University; M.S., Zhejiang... . . . . . . . . . . . . . . . . . . . . . . . . . . 1 A. Nonlinear Optimization with Rigorous Large Scale Models 1 B. Chemical Applications of Nonlinear Optimization . . . . . 2 1. Design under Uncertainty . . . . . . . . . . . . . . . . 3 2. Optimal Operations with Steady State Models . . . . 4...
Lygeros, John
of High Performance Hybrid Race Cars Background The power unit of a high performance hybrid race carPrerequisites Control Systems, System Modeling, Optimal Control, Model Predictive Control, (Engine consists of an internal combustion engine (ICE) and a kinetic energy recovery system (KERS). The time
Data-Driven Optimization for Modeling in Computer Graphics and Vision
Yu, Lap Fai
2013-01-01
optimization problem, including: Explicit Control: Users can have explicit control over the modeling process,process while having close, interactive control. For example, in the Clutterbrush project, an optimization-
Implications of a Regime-Switching Model on Natural Gas Storage Valuation and Optimal Operation
Forsyth, Peter A.
Implications of a Regime-Switching Model on Natural Gas Storage Valuation and Optimal Operation-switching model for the risk adjusted natural gas spot price and study the implications of the model on the valuation and optimal operation of natural gas storage facilities. We calibrate the model parameters to both
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
2012-07-22
In an isolated power system (rural microgrid), Distributed Energy Resources (DERs) such as renewable energy resources (wind, solar), energy storage and demand response can be used to complement fossil fueled generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation. The problem is formulated as a multi-objective optimization problem with the goals of minimizing fuel costs and changes in power output of diesel generators, minimizing costs associated with low battery life of energy storage and maintaining system frequency at the nominal operating value. Two control modes are considered for controlling the energy storage to compensate either net load variability or wind variability. Model predictive control (MPC) is used to solve the aforementioned problem and the performance is compared to an open-loop look-ahead dispatch problem. Simulation studies using high and low wind profiles, as well as, different MPC prediction horizons demonstrate the efficacy of the closed-loop MPC in compensating for uncertainties in wind and demand.
Optimization of the structural Gabor functions in a homogeneous velocity model
Cerveny, Vlastislav
Optimization of the structural Gabor functions in a homogeneous velocity model for a zero-o#11;set functions should be optimized, and the Gabor functions should form a frame. We present a simple attempt functions and the space{wavenumber lattice of their central points are optimized analytically
20.18 Optimization Problems in Air Pollution Modeling Ivan Dimov, and Zahari Zlatev
Dimov, Ivan
20.18 Optimization Problems in Air Pollution Modeling Ivan Dimov, and Zahari Zlatev ABSTRACT. The appearance of optimization problems in the field of air pollution modeling and their importance arising in air pollution modeling will be considered. We shall present a review of some approaches
Application of stochastic parameter optimization to the Sacramento Soil Moisture Accounting model
Wagener, Thorsten
parameter set and underlying posterior distribution within a single optimization run. In particular, weApplication of stochastic parameter optimization to the Sacramento Soil Moisture Accounting model Moisture Accounting model (SAC-SMA) model using historical data from the Leaf River in Mississippi
Applying the Battery Ownership Model in Pursuit of Optimal Battery Use Strategies (Presentation)
Neubauer, J.; Ahmad, P.; Brooker, A.; Wood, E.; Smith, K.; Johnson, C.; Mendelsohn, M.
2012-05-01
This Annual Merit Review presentation describes the application of the Battery Ownership Model for strategies for optimal battery use in electric drive vehicles (PEVs, PHEVs, and BEVs).
Optimal rotary control of the cylinder wake using POD Reduced Order Model
Bergmann, Michel
Optimal rotary control of the cylinder wake using POD Reduced Order Model Michel Bergmann, Laurent frequently in engineering computations) obtained by spatial discretization of the governing equations need
Optimization and neural modelling of pulse combustors for drying applications
Zbicinski, I.; Smucerowicz, I.; Strumillo, C.; Kasznia, J.; Stawczyk, J.; Murlikiewicz, K. [Technical Univ. of Lodz (Poland). Faculty of Process and Environmental Engineering
1999-03-01
Results of investigations of a valved pulse combustor to choose optimal geometry, which covered measurements of the flow rates of air and fuel, pressure oscillations, including pressure amplitude and frequency and flue gas composition are presented in the paper. Experimental studies comparing the operation of the pulse combustor coupled with a drying chamber and working separately are described. It was found that coupling of the pulse combustor with a drying chamber had no significant effect on the pulse combustion process. Smoother runs of pressure oscillations in the combustion chamber, lower noise level and slightly higher NO{sub x} emission were observed. The velocity flow field inside the drying chamber was measured by LDA technique. Results confirmed a complex character of pulsating flow in the chamber. A large experimental data set obtained from measurements enabled developing a neural model of pulse combustion process. Artificial neural networks were trained to predict amplitudes and frequencies of pressure oscillations, temperatures in the combustion chamber and emission of toxic substances. An excellent mapping performance of the developed neural models was obtained. Due to complex character of the pulse combustion process, the application of artificial neural networks seems to be the best way to predict inlet parameters of drying agent produced by the pulse combustor.
Gas Network Optimization: A comparison of Piecewise Linear Models
2014-06-22
Gas network optimization manages the gas transport by minimizing operating costs and .... This problem represents the transportation process of natural gas. 79.
Tax policy can change the production path: A model of optimal oil extraction in Alaska
Lin, C.-Y. Cynthia
1 Tax policy can change the production path: A model of optimal oil extraction in Alaska Wayne@primal.ucdavis.edu * Corresponding author ABSTRACT We model the economically optimal dynamic oil production decisions for seven and an estimated inverse production function, which incorporates engineering aspects of oil production into our
Optimal consumption in a growth model with the Cobb-Douglas production function
Optimal consumption in a growth model with the Cobb-Douglas production function Hiroaki Morimoto Management, The Chinese University of Hong Kong, Shatin, Hong Kong Abstract An optimal consumption problem is studied in a growth model for the Cobb-Douglas production function in a finite horizon. The problem
Parameter optimization for the Gaussian model of protein foldingq Albert Erkipa
Seok, Chaok
of protein folding and ligand docking are large and complex. Few systematic methods have yet been developed apply this parameter optimization method to the recently developed Gaussian model of protein folding Science Ltd. All rights reserved. Keywords: Gaussian model; Protein folding; Parameter optimization 1
Mooring Line Modelling and Design Optimization of Floating Offshore Wind Turbines
Victoria, University of
Mooring Line Modelling and Design Optimization of Floating Offshore Wind Turbines by Matthew Thomas Mooring Line Modelling and Design Optimization of Floating Offshore Wind Turbines by Matthew Thomas Jair was coupled to the floating wind turbine simulator FAST. The results of the comparison study indicate the need
Finite Element Solution of Optimal Control Problems Arising in Semiconductor Modeling
Siefert, Chris
- timization problem, especially for highly heterogeneous materials with large jumps in material properties. 1Finite Element Solution of Optimal Control Problems Arising in Semiconductor Modeling Pavel Bochev, and inverse problems arising in the modeling of semiconductor devices lead to optimization problems
Optimal SCR Control Using Data-Driven Models
Stevens, Andrew J.; Sun, Yannan; Lian, Jianming; Devarakonda, Maruthi N.; Parker, Gordon
2013-04-16
We present an optimal control solution for the urea injection for a heavy-duty diesel (HDD) selective catalytic reduction (SCR). The approach taken here is useful beyond SCR and could be applied to any system where a control strategy is desired and input-output data is available. For example, the strategy could also be used for the diesel oxidation catalyst (DOC) system. In this paper, we identify and validate a one-step ahead Kalman state-space estimator for downstream NOx using the bench reactor data of an SCR core sample. The test data was acquired using a 2010 Cummins 6.7L ISB production engine with a 2010 Cummins production aftertreatment system. We used a surrogate HDD federal test procedure (FTP), developed at Michigan Technological University (MTU), which simulates the representative transients of the standard FTP cycle, but has less engine speed/load points. The identified state-space model is then used to develop a tunable cost function that simultaneously minimizes NOx emissions and urea usage. The cost function is quadratic and univariate, thus the minimum can be computed analytically. We show the performance of the closed-loop controller in using a reduced-order discrete SCR simulator developed at MTU. Our experiments with the surrogate HDD-FTP data show that the strategy developed in this paper can be used to identify performance bounds for urea dose controllers.
Finding Benefits by Modeling and Optimizing Steam and Power Systems
Harper, C.; Nelson, D. A.
2008-01-01
case studies which can be used to optimize production of these products on our industrial gas pipelines. The program is used for both day-to-day site optimization, outage forecasting, and long-term site planning. In this presentation, we will discuss...
Continuously Optimized Reliable Energy (CORE) Microgrid: Models & Tools (Fact Sheet)
Not Available
2013-07-01
This brochure describes Continuously Optimized Reliable Energy (CORE), a trademarked process NREL employs to produce conceptual microgrid designs. This systems-based process enables designs to be optimized for economic value, energy surety, and sustainability. Capabilities NREL offers in support of microgrid design are explained.
A micropower electrocardiogram amplifier
Sarpeshkar, Rahul
We introduce an electrocardiogram (EKG) preamplifier with a power consumption of 2.8 muW, 8.1 muV[subscript rms] input-referred noise, and a common-mode rejection ratio of 90 dB. Compared to previously reported work, this ...
Modeling and Optimization of a Bioethanol Production Facility
Gabriel, Kerron Jude
2011-10-21
The primary objective of this work is to identify the optimal bioethanol production plant capacity and configuration based on currently available technology for all the processing sections involved. To effect this study, a systematic method...
Kinetic modeling and automated optimization in microreactor systems
Moore, Jason Stuart
2013-01-01
The optimization, kinetic investigation, or scale-up of a reaction often requires significant time and materials. Silicon microreactor systems have been shown advantageous for studying chemical reactions due to their small ...
OPTIMAL METABOLIC REGULATION USING A CONSTRAINT-BASED MODEL
Segrè, Daniel
role in the maintenance of metabolic homeostasis, and in the capacity of living systems to undergo: metabolic regulation; flux balance analysis; enzyme kinetics; metabolism; optimality; logistic map; chaos 1
Modeling, Optimization and Economic Evaluation of Residual Biomass Gasification
Georgeson, Adam
2012-02-14
and product options are available for gasification along with combinations thereof. The objective of this work is to create a systematic method for optimizing the design of a residual biomass gasification unit. In detail, this work involves development...
Optimal reservoir management using adaptive reduced-order models
Alghareeb, Zeid M
2015-01-01
Reservoir management and decision-making is often cast as an optimization problem where we seek to maximize the field's potential recovery while minimizing associated operational costs. Two reservoir management aspects are ...
Oneida Tribe of Indians of Wisconsin Energy Optimization Model
Troge, Michael
2014-12-30
Oneida Nation is located in Northeast Wisconsin. The reservation is approximately 96 square miles (8 miles x 12 miles), or 65,000 acres. The greater Green Bay area is east and adjacent to the reservation. A county line roughly splits the reservation in half; the west half is in Outagamie County and the east half is in Brown County. Land use is predominantly agriculture on the west 2/3 and suburban on the east 1/3 of the reservation. Nearly 5,000 tribally enrolled members live in the reservation with a total population of about 21,000. Tribal ownership is scattered across the reservation and is about 23,000 acres. Currently, the Oneida Tribe of Indians of Wisconsin (OTIW) community members and facilities receive the vast majority of electrical and natural gas services from two of the largest investor-owned utilities in the state, WE Energies and Wisconsin Public Service. All urban and suburban buildings have access to natural gas. About 15% of the population and five Tribal facilities are in rural locations and therefore use propane as a primary heating fuel. Wood and oil are also used as primary or supplemental heat sources for a small percent of the population. Very few renewable energy systems, used to generate electricity and heat, have been installed on the Oneida Reservation. This project was an effort to develop a reasonable renewable energy portfolio that will help Oneida to provide a leadership role in developing a clean energy economy. The Energy Optimization Model (EOM) is an exploration of energy opportunities available to the Tribe and it is intended to provide a decision framework to allow the Tribe to make the wisest choices in energy investment with an organizational desire to establish a renewable portfolio standard (RPS).
High-throughput generation, optimization and analysis of genome-scale metabolic models.
Henry, C. S.; DeJongh, M.; Best, A. A.; Frybarger, P. M.; Linsay, B.; Stevens, R. L.
2010-09-01
Genome-scale metabolic models have proven to be valuable for predicting organism phenotypes from genotypes. Yet efforts to develop new models are failing to keep pace with genome sequencing. To address this problem, we introduce the Model SEED, a web-based resource for high-throughput generation, optimization and analysis of genome-scale metabolic models. The Model SEED integrates existing methods and introduces techniques to automate nearly every step of this process, taking {approx}48 h to reconstruct a metabolic model from an assembled genome sequence. We apply this resource to generate 130 genome-scale metabolic models representing a taxonomically diverse set of bacteria. Twenty-two of the models were validated against available gene essentiality and Biolog data, with the average model accuracy determined to be 66% before optimization and 87% after optimization.
Skogestad, Sigurd
Sensitivity Analysis of Optimal Operation of an Activated Sludge Process Model for Economic operation conducted on an activated sludge process model based on the test-bed benchmark simulation model no. 1 (BSM1) and the activated sludge model no. 1 (ASM1). The objective is to search for a control
Power system analysis project Modeling and Sizing optimization of Stand-alone
Lavaei, Javad
Power system analysis project Modeling and Sizing optimization of Stand-alone photovoltaic/wind to explore a new way to do the site matching of wind turbine by introducing the design parameters: cut-in, cut-out wind speed and rated power, into the optimization based on the real load of the site and write
Change Management in Enterprise IT Systems: Process Modeling and Capacity-optimal Scheduling
Sarkar, Saswati
Change Management in Enterprise IT Systems: Process Modeling and Capacity-optimal Scheduling of the optimal fluid scheduling policy, which is well suited for application to a real change management system management Â or handling of problem diagnosis and root cause analysis, and (ii) Change management Â or timely
A Network Modeling Approach Optimization of Internet-Based Advertising Strategies and Pricing
Nagurney, Anna
A Network Modeling Approach for the Optimization of Internet-Based Advertising Strategies and evaluation of optimal Internet mar- keting strategies when a firm is advertising on multiple websites examples are constructed that demonstrate two paradoxes: (1). that advertising on more websites may reduce
An Enterprise Decision Model for Optimal Vehicle Design and Technology Valuation
Papalambros, Panos
engineering simulation to provide a preliminary understanding of the technology's market and design potentialAn Enterprise Decision Model for Optimal Vehicle Design and Technology Valuation by Adam B. Cooper for Optimal Vehicle Design and Technology Valuation by Adam B. Cooper Chair: Panos Y. Papalambros Design
Global optimization by coupled local minimizers and its application to FE model updating
-3001 Heverlee, Belgium Received 2 August 2002; accepted 3 July 2003 Abstract Coupled local minimizersGlobal optimization by coupled local minimizers and its application to FE model updating Anne (CLM) is a new method applicable to global optimization of functions with multiple local minima. In CLM
Modeling Zero Energy Building: technical and economical optimization Maria Ferrara1-2
Paris-Sud XI, Université de
1 Modeling Zero Energy Building: technical and economical optimization Maria Ferrara1-2 , Joseph by the recast of Energy Performance of Buildings. The aim of this work is to provide a useful method to deal combines the use of TRNSYS, building energy simulation program, with GenOpt, Generic Optimization program
Brouns, Gido
models, admission and termination control, optimal threshold policies, Markov decision processes. 1 systems. The basic principle of performance optimization is the question of how to control some type of models for the optimal control of queueing systems. Emphasis is laid on models based on Markov decision
Using Evolution Strategy with Meta-models for Well Placement Optimization
Bouzarkouna, Zyed; Auger, Anne
2010-01-01
Optimum implementation of non-conventional wells allows us to increase considerably hydrocarbon recovery. By considering the high drilling cost and the potential improvement in well productivity, well placement decision is an important issue in field development. Considering complex reservoir geology and high reservoir heterogeneities, stochastic optimization methods are the most suitable approaches for optimum well placement. This paper proposes an optimization methodology to determine optimal well location and trajectory based upon the Covariance Matrix Adaptation - Evolution Strategy (CMA-ES) which is a variant of Evolution Strategies recognized as one of the most powerful derivative-free optimizers for continuous optimization. To improve the optimization procedure, two new techniques are investigated: (1). Adaptive penalization with rejection is developed to handle well placement constraints. (2). A meta-model, based on locally weighted regression, is incorporated into CMA-ES using an approximate ranking ...
An optimization model for strategic supply chain design under stochastic capacity disruptions
Luna Coronado, Jaime
2009-05-15
.6. Numerical Example ...................................................................................... 54 6. OPTIMIZATION PROCEDURE ....................................................................... 60 6.1. Sample Average Approximation (SAA... ................................................................................ 66 7. IMPLEMENTATION AND NUMERICAL EXAMPLES????? ???.. 70 7.1. Model Implementation ................................................................................. 71 7.2. Numerical Examples...
Soontrapa, Chaiyod
2005-01-01
Modifying material properties provides another approach to optimize coated particle fuel used in pebble bed reactors. In this study, the MIT fuel performance model (TIMCOAT) was applied after benchmarking against the ...
Sparse Models and Methods for Optimal Instruments with an Application to Eminent Domain
Belloni, Alexandre
2011-07-12
We develop results for the use of LASSO and Post-LASSO methods to form first-stage predictions and estimate optimal instruments in linear instrumental variables (IV) models with many instruments, p, that apply even when p ...
Lee, Yuan-Hsuan
2011-10-21
This dissertation focuses on issues related to fitting an optimal variance-covariance structure in multilevel linear modeling framework with two Monte Carlo simulation studies. In the first study, the author evaluated the ...
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
New methodologies for top-down statistical modeling and optimization of integrated circuits
Alexander, Daniel D.
1996-01-01
New methodologies intended to facilitate system level design and optimization are developed. Specifically, these methodologies allow: (1) development of system level models for the purpose of gathering statistical data on the performance of large...
Geometric modeling and optimization in 3D solar cells : implementation and algorithms
Wan, Jin Hao, M. Eng. Massachusetts Institute of Technology
2014-01-01
Conversion of solar energy in three-dimensional (3D) devices has been essentially untapped. In this thesis, I design and implement a C++ program that models and optimizes a 3D solar cell ensemble embedded in a given ...
Optimal Control for a System Modelling Tumor Anti-Angiogenesis
Ledzewicz, Urszula
inhibitors given. For both mod- els a full synthesis of optimal solutions is presented and the differences of chemotherapy in cancer treatments is drug resistance. Different from normal cells, cancer cells are geneti- cally highly unstable and thus quite diversified in their structure. As a consequence, some cancer cells
ADVANCES IN MATHEMATICAL PROGRAMMING MODELS FOR ENTERPRISE-WIDE OPTIMIZATION
Grossmann, Ignacio E.
The chemical industry is a major component of the US economy, converting raw materials such as oil, natural gas, the US chemical industry is responsible for 10 percent of US merchandise exports, totaling US$145 billion Pittsburgh, PA 15213 Abstract Enterprise-wide optimization (EWO) is an area that lies at the interface
Efficient mold Danscooling optimization by using model reduction
Mongeau, Marcel
.Chinesta@ec-nantes.fr ABSTRACT Optimization and inverse identification are two procedures usually encountered in many industrial the polymer melt into the mold. Its screw rotates and axially reciprocates to melt, mix, and pump the polymer to evacuate the heat since polymers are bad conductors as thermal conductivity #12;ranges form 0.1 W/mK to 1
Active and Accelerated Learning of Cost Models for Optimizing Scientific Applications
Chase, Jeffrey S.
Active and Accelerated Learning of Cost Models for Optimizing Scientific Applications Piyush Shivam of sciences including astrophysics, bioinformatics, systems biology, and climate modeling [15, 31]. This new University chase@cs.duke.edu ABSTRACT We present the NIMO system that automatically learns cost models
optimal initial conditions for coupling ice sheet models to earth...
Office of Scientific and Technical Information (OSTI)
for coupling ice sheet models to earth system models Authors: Perego, Mauro 1 ; Price, Stephen F. Dr 2 ; Stadler, Georg 3 + Show Author Affiliations Sandia National...
Optimal Initial Conditions for Coupling Ice Sheet Models to Earth...
Office of Scientific and Technical Information (OSTI)
Sheet Models to Earth System Models. Abstract not provided. Authors: Perego, Mauro ; Price, Stephen ; Stadler, Georg Publication Date: 2014-04-01 OSTI Identifier: 1142266 Report...
Turner, D P; Ritts, W D; Wharton, S; Thomas, C; Monson, R; Black, T A
2009-02-26
The combination of satellite remote sensing and carbon cycle models provides an opportunity for regional to global scale monitoring of terrestrial gross primary production, ecosystem respiration, and net ecosystem production. FPAR (the fraction of photosynthetically active radiation absorbed by the plant canopy) is a critical input to diagnostic models, however little is known about the relative effectiveness of FPAR products from different satellite sensors nor about the sensitivity of flux estimates to different parameterization approaches. In this study, we used multiyear observations of carbon flux at four eddy covariance flux tower sites within the conifer biome to evaluate these factors. FPAR products from the MODIS and SeaWiFS sensors, and the effects of single site vs. cross-site parameter optimization were tested with the CFLUX model. The SeaWiFs FPAR product showed greater dynamic range across sites and resulted in slightly reduced flux estimation errors relative to the MODIS product when using cross-site optimization. With site-specific parameter optimization, the flux model was effective in capturing seasonal and interannual variation in the carbon fluxes at these sites. The cross-site prediction errors were lower when using parameters from a cross-site optimization compared to parameter sets from optimization at single sites. These results support the practice of multisite optimization within a biome for parameterization of diagnostic carbon flux models.
Lu, Qingda; Gao, Xiaoyang; Krishnamoorthy, Sriram; Baumgartner, Gerald; Ramanujam, J.; Sadayappan, Ponnuswamy
2012-03-01
Empirical optimizers like ATLAS have been very effective in optimizing computational kernels in libraries. The best choice of parameters such as tile size and degree of loop unrolling is determined by executing different versions of the computation. In contrast, optimizing compilers use a model-driven approach to program transformation. While the model-driven approach of optimizing compilers is generally orders of magnitude faster than ATLAS-like library generators, its effectiveness can be limited by the accuracy of the performance models used. In this paper, we describe an approach where a class of computations is modeled in terms of constituent operations that are empirically measured, thereby allowing modeling of the overall execution time. The performance model with empirically determined cost components is used to perform data layout optimization together with the selection of library calls and layout transformations in the context of the Tensor Contraction Engine, a compiler for a high-level domain-specific language for expressing computational models in quantum chemistry. The effectiveness of the approach is demonstrated through experimental measurements on representative computations from quantum chemistry.
A system-level cost-of-energy wind farm layout optimization with landowner modeling
Chen, Le [Ames Laboratory; MacDonald, Erin [Ames Laboratory
2013-10-01
This work applies an enhanced levelized wind farm cost model, including landowner remittance fees, to determine optimal turbine placements under three landowner participation scenarios and two land-plot shapes. Instead of assuming a continuous piece of land is available for the wind farm construction, as in most layout optimizations, the problem formulation represents landowner participation scenarios as a binary string variable, along with the number of turbines. The cost parameters and model are a combination of models from the National Renewable Energy Laboratory (NREL), Lawrence Berkeley National Laboratory, and Windustiy. The system-level cost-of-energy (COE) optimization model is also tested under two land-plot shapes: equally-sized square land plots and unequal rectangle land plots. The optimal COEs results are compared to actual COE data and found to be realistic. The results show that landowner remittances account for approximately 10% of farm operating costs across all cases. Irregular land-plot shapes are easily handled by the model. We find that larger land plots do not necessarily receive higher remittance fees. The model can help site developers identify the most crucial land plots for project success and the optimal positions of turbines, with realistic estimates of costs and profitability. (C) 2013 Elsevier Ltd. All rights reserved.
Variable horizon model predictive control: robustness and optimality
Shekhar, Rohan Chandra
2012-07-03
. . . . . . . . . . . . . . . . . . . . . . . . . . . 106 6.3 Kinematic vectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 6.4 Mechanism model showing generalised coordinates . . . . . . . . . . . . . . . . 109 6.5 Static balance of material failure forces... .1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 6.1.1 Nomenclature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 6.2 Mechanism Model...
Model Order Reduction in Porous Media Flow Simulation and Optimization
Ghasemi, Mohammadreza
2015-05-06
Subsurface flow modeling and simulation is ubiquitous in many energy related processes, including oil and gas production. These models are usually large scale and simulating them can be very computationally demanding, particularly in work...
Pan, David Z.
Improved Crosstalk Modeling for Noise Constrained Interconnect Optimization Jason Cong, David This paper presents a much improved, highly accurate yet effi- cient crosstalk noise model, the 2-¢ model, and applies it to noise- constrained interconnect optimizations. Compared with previous crosstalk noise models
THE APPLICATION OF AN EVOLUTIONARY ALGORITHM TO THE OPTIMIZATION OF A MESOSCALE METEOROLOGICAL MODEL
Werth, D.; O'Steen, L.
2008-02-11
We show that a simple evolutionary algorithm can optimize a set of mesoscale atmospheric model parameters with respect to agreement between the mesoscale simulation and a limited set of synthetic observations. This is illustrated using the Regional Atmospheric Modeling System (RAMS). A set of 23 RAMS parameters is optimized by minimizing a cost function based on the root mean square (rms) error between the RAMS simulation and synthetic data (observations derived from a separate RAMS simulation). We find that the optimization can be efficient with relatively modest computer resources, thus operational implementation is possible. The optimization efficiency, however, is found to depend strongly on the procedure used to perturb the 'child' parameters relative to their 'parents' within the evolutionary algorithm. In addition, the meteorological variables included in the rms error and their weighting are found to be an important factor with respect to finding the global optimum.
An Optimization Model for Plug-In Hybrid Electric Vehicles
Malikopoulos, Andreas [ORNL] [ORNL; Smith, David E [ORNL] [ORNL
2011-01-01
The necessity for environmentally conscious vehicle designs in conjunction with increasing concerns regarding U.S. dependency on foreign oil and climate change have induced significant investment towards enhancing the propulsion portfolio with new technologies. More recently, plug-in hybrid electric vehicles (PHEVs) have held great intuitive appeal and have attracted considerable attention. PHEVs have the potential to reduce petroleum consumption and greenhouse gas (GHG) emissions in the commercial transportation sector. They are especially appealing in situations where daily commuting is within a small amount of miles with excessive stop-and-go driving. The research effort outlined in this paper aims to investigate the implications of motor/generator and battery size on fuel economy and GHG emissions in a medium-duty PHEV. An optimization framework is developed and applied to two different parallel powertrain configurations, e.g., pre-transmission and post-transmission, to derive the optimal design with respect to motor/generator and battery size. A comparison between the conventional and PHEV configurations with equivalent size and performance under the same driving conditions is conducted, thus allowing an assessment of the fuel economy and GHG emissions potential improvement. The post-transmission parallel configuration yields higher fuel economy and less GHG emissions compared to pre-transmission configuration partly attributable to the enhanced regenerative braking efficiency.
Hutter, Marcus
Optimization Difficulty Tansu Alpcan Introduction Definitions and Model Optimization Difficulty Bounds on Optimization Difficulty Conclusion Can we measure the difficulty of an optimization problem Science Australian National University ITW 2014, Hobart 1 / 22 #12;Optimization Difficulty Tansu Alpcan
Thermodynamic modeling and optimization of a screw compressor chiller and cooling tower system
Graves, Rhett David
2004-09-30
, absorption, thermoelectric, and thermoacoustic (Gordon and Ng 1995). Chiller models have been used to predict the performance of thermal storage 6 systems (Henze et al. 1997) and whole chiller plant systems (Lau et al. 1985). Chiller models have also been... used to aid in the development of control algorithms for chiller plants (Flake et al. 1997). There have been several attempts to generate an ?optimal? operating scheme using the Whillier cooling tower model, a chiller model, or a combination of both...
Handling risk of uncertainty in model-based production optimization: a
Van den Hof, Paul
.d.Jansen@tudelft.nl) Abstract: Model-based economic optimization of oil production suffers from high levels of uncertainty, the secondary objective is aimed at maximizing the speed of oil production to mitigate risk. This multi and production data about the true values of the model parameters. Furthermore, economic variables such as oil
A Mathematical Programming Model for Optimal Layout Considering Quantitative Risk Analysis
Grossmann, Ignacio E.
A Mathematical Programming Model for Optimal Layout Considering Quantitative Risk Analysis Nancy risk analysis; Plant layout *Corresponding author. Phone: +52-461-611-7575 Ext. 5577. E-mail: arturo of plant layout with safety considerations. The model considers a quantitative risk analysis to take safety
An optimizing reduced order FDS for the tropical Pacific Ocean reduced gravity model
Aluffi, Paolo
An optimizing reduced order FDS for the tropical Pacific Ocean reduced gravity model Zhendong Luoa) for the tropical Pacific Ocean reduced gravity model. Ensembles of data are compiled from transient solutions computed from the discrete equation system derived by FDS for the tropical Pacific Ocean reduced gravity
OLAF ---A General Modeling System to Evaluate and Optimize the Location of an Air
Fliege, Jörg
OLAF --- A General Modeling System to Evaluate and Optimize the Location of an Air Polluting.2 The Air Dispersion Model . . . . . . . . . . . . . . . . . . . . . 14 3 Ecology and Chemokinetics 17 3 . . . . . . . . . . . . . . . . . . . . . . . 48 6.1.3 Meteorological Data . . . . . . . . . . . . . . . . . . . . 48 6.1.4 Pollutant Data
Optimizing a Model for Siting Offshore Wind Farms using a Genetic Algorithm
Mountziaris, T. J.
Optimizing a Model for Siting Offshore Wind Farms using a Genetic Algorithm *Michael Ameckson Science Foundation. Generating electricity using offshore wind farms can assist coastal regions to meet growing electricity demands supported by a renewable source [4]. However modeling wind farm siting must
Modeling and Optimization Issues Concerning a Circular Piezoelectric Actuator Design \\Lambda
Modeling and Optimization Issues Concerning a Circular Piezoelectric Actuator Design \\Lambda Steven Raleigh, NC 27695 Abstract An electromechanical model for a circular piezoelectric actuator is developed and analyzed. A crit ical challenge in certain applications employing piezoceramic actuators is to maximize
Tentzeris, Manos
Modeling and Optimization of RF-MEMS Reconfigurable Tuners with Computationally Efficient Time of Technology, Atlanta, GA 30332 2 Raytheon Company, Tucson AZ, 85734 Abstract -- Modern RF-MEMS device design methods in which the FDTD technique can be used to model a reconfigurable RF-MEMS tuner. A new method
Optimization of large-scale heterogeneous system-of-systems models.
Parekh, Ojas; Watson, Jean-Paul; Phillips, Cynthia Ann; Siirola, John; Swiler, Laura Painton; Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Lee, Herbert K. H. (University of California, Santa Cruz, Santa Cruz, CA); Hart, William Eugene; Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Woodruff, David L. (University of California, Davis, Davis, CA)
2012-01-01
Decision makers increasingly rely on large-scale computational models to simulate and analyze complex man-made systems. For example, computational models of national infrastructures are being used to inform government policy, assess economic and national security risks, evaluate infrastructure interdependencies, and plan for the growth and evolution of infrastructure capabilities. A major challenge for decision makers is the analysis of national-scale models that are composed of interacting systems: effective integration of system models is difficult, there are many parameters to analyze in these systems, and fundamental modeling uncertainties complicate analysis. This project is developing optimization methods to effectively represent and analyze large-scale heterogeneous system of systems (HSoS) models, which have emerged as a promising approach for describing such complex man-made systems. These optimization methods enable decision makers to predict future system behavior, manage system risk, assess tradeoffs between system criteria, and identify critical modeling uncertainties.
Optimization of a Two-Fluid Hydrodynamic Model of Churn-Turbulent Flow
Donna Post Guillen
2009-07-01
A hydrodynamic model of two-phase, churn-turbulent flows is being developed using the computational multiphase fluid dynamics (CMFD) code, NPHASE-CMFD. The numerical solutions obtained by this model are compared with experimental data obtained at the TOPFLOW facility of the Institute of Safety Research at the Forschungszentrum Dresden-Rossendorf. The TOPFLOW data is a high quality experimental database of upward, co-current air-water flows in a vertical pipe suitable for validation of computational fluid dynamics (CFD) codes. A five-field CMFD model was developed for the continuous liquid phase and four bubble size groups using mechanistic closure models for the ensemble-averaged Navier-Stokes equations. Mechanistic models for the drag and non-drag interfacial forces are implemented to include the governing physics to describe the hydrodynamic forces controlling the gas distribution. The closure models provide the functional form of the interfacial forces, with user defined coefficients to adjust the force magnitude. An optimization strategy was devised for these coefficients using commercial design optimization software. This paper demonstrates an approach to optimizing CMFD model parameters using a design optimization approach. Computed radial void fraction profiles predicted by the NPHASE-CMFD code are compared to experimental data for four bubble size groups.
Constraining climate model properties using optimal fingerprint detection methods
Forest, Chris Eliot.; Allen, Myles R.; Sokolov, Andrei P.; Stone, Peter H.
We present a method for constraining key properties of the climate system that are important for climate prediction (climate sensitivity and rate of heat penetration into the deep ocean) by comparing a model's response to ...
Recent developments in DYNSUB: New models, code optimization and parallelization
Daeubler, M.; Trost, N.; Jimenez, J.; Sanchez, V. [Karlsruhe Institute of Technology, Institute for Neutron Physics and Reactor Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen (Germany)
2013-07-01
DYNSUB is a high-fidelity coupled code system consisting of the reactor simulator DYN3D and the sub-channel code SUBCHANFLOW. It describes nuclear reactor core behavior with pin-by-pin resolution for both steady-state and transient scenarios. In the course of the coupled code system's active development, super-homogenization (SPH) and generalized equivalence theory (GET) discontinuity factors may be computed with and employed in DYNSUB to compensate pin level homogenization errors. Because of the largely increased numerical problem size for pin-by-pin simulations, DYNSUB has bene fitted from HPC techniques to improve its numerical performance. DYNSUB's coupling scheme has been structurally revised. Computational bottlenecks have been identified and parallelized for shared memory systems using OpenMP. Comparing the elapsed time for simulating a PWR core with one-eighth symmetry under hot zero power conditions applying the original and the optimized DYNSUB using 8 cores, overall speed up factors greater than 10 have been observed. The corresponding reduction in execution time enables a routine application of DYNSUB to study pin level safety parameters for engineering sized cases in a scientific environment. (authors)
Ryan, Sarah M.
Process and Continuous Monitoring Index terms--Optimal replacement, proportional hazards model, semi1 Title: Optimal Replacement in the Proportional Hazards Model with semi-Markovian Covariate replacement problem for general deteriorating systems in the proportional hazards model with a semi
Subramanian, Venkat
Model-based simultaneous optimization of multiple design parameters for lithium-ion batteries Keywords: Lithium-ion batteries Model-based design Optimization Physics based reformulated model a b s t r for porous electrodes that are commonly used in advanced batteries such as lithium-ion systems. The approach
Modeling an optical magnetometer with electronic circuits Analysis and optimization
, and bandwidths of the sensors, as well as their different sizes, prices, and maintenance costs [1]. Currently 6 3.2 Model verification 7 3.3 Different detection scheme in self-oscillation mode 8 3.3.1 Pump-probe arrangement with balanced polarimeter 8 3.3.2 Pump-probe arrangement with nearly-crossed polarizer 9 3
Modeling and optimization of a chiller plant Xiupeng Wei*
Kusiak, Andrew
. The chillers have varying energy efficiency. Since the chiller plant model derived from data-driven approach of chillers, cooling towers, pumps and chilled water storage tanks. It is frequently used to air conditioning was found and controlled to reduce fluc- tuation in chiller efficiency in different operating conditions
Correlations, Competition, and Optimality: Modelling the Development of
Goodhill, Geoffrey J.
both qualitative and quantitative comparisons with the performance of an algorithm based on the self not satisfactorily address both of these phenomena simultaneously. In this thesis we discuss in detail several models was a great source of inspiration and encouragement to me throughout the thesis, and I am particularly
SUMMARY FOR POLICYMAKERS Modeling Optimal Transition Pathways to a Low
California at Davis, University of
of California Energy and Climate Policies 2 capture and sequestration or increased supplies of wind and solar and the social, environmental and economic aspects of major transformations. Energy models such as CA and sequestration (CCS). Elastic demand scenarios are also examined to reflect more realistic consumers' demand
Modeling and Optimization of Next Generation Feedstock Development for Chemical Process
Grossmann, Ignacio E.
1929, 2011 #12;Motivation Energy Consumption by Manufacturing Industry 20061Industry, 20061 Primary for CPI · Utilize sun-light energy as carbon- based molecules · Renewable · Reduced CO2 emissions, USA PanAmerican Advanced Studies Institute Process Modeling and Optimization for Energy
Boyer, Edmond
strategies based on anaerobic energy and variations of velocity J. Fr´ed´eric Bonnans Inria-Saclay and CMAP of running strategies hal-01024231,version1-15Jul2014 #12;Keller's model Variable energy recreation Bounding.F. Bonnans, Optimization of running strategies based on anaerobic energy and variations of velocity. SIAM J
A REAL OPTIONS OPTIMIZATION MODEL TO MEET AVAILABILITY REQUIREMENTS FOR OFFSHORE WIND TURBINES
Sandborn, Peter
1 A REAL OPTIONS OPTIMIZATION MODEL TO MEET AVAILABILITY REQUIREMENTS FOR OFFSHORE WIND TURBINES wind farm with prognostic capabilities. Alternative energy sources such as offshore wind turbines-based maintenance. This is especially important for offshore wind farms that require non- traditional resources
Journal of Power Sources 142 (2005) 184193 Modeling and optimization of catalytic partial oxidation
Daraio, Chiara
2005-01-01
of a micro-reformer for a fuel cell unit based on catalytic partial oxidation using a systematic numerical is around 80% is identified. © 2004 Elsevier B.V. All rights reserved. Keywords: Catalytic partial oxidationJournal of Power Sources 142 (2005) 184193 Modeling and optimization of catalytic partial
Modelling and Design Optimization of Low Speed Fuel Cell Hybrid Electric Vehicles
Victoria, University of
Modelling and Design Optimization of Low Speed Fuel Cell Hybrid Electric Vehicles by Matthew Blair of emissions to global climate change. Although electric cars and buses have been the focus of much of electric and utility purposes in many countries. In order to explore the viability of fuel cell - battery hybrid
Optimal Perturbations in the Eady Model: Resonance versus PV Unshielding H. DE VRIES
de Vries, Hylke
Optimal Perturbations in the Eady Model: Resonance versus PV Unshielding H. DE VRIES Institute August 2004) ABSTRACT Using a nonmodal decomposition technique based on the potential vorticity (PV, such that the initial surface potential temperature (PT) is zero. These nonmodal structures are used as PV building
Stochastic Modeling and Optimization for Robust Power Management in a Partially Observable System
Qiu, Qinru
-of-the- art system modules are capable of trading power for performance or being put into sleep or low powerStochastic Modeling and Optimization for Robust Power Management in a Partially Observable System As the hardware and software complexity grows, it is unlikely for the power management hardware/software to have
Economic Nonlinear Model Predictive Control for the Optimization of Gas Pipeline Networks
Grossmann, Ignacio E.
Compressor 4 Commercial Industry Power Plant LDC 3 Suppliers, 12 Demand nodes, 5 Compressors Sinusoidal Flowrates Industry: N6,12,13,19,21 Commercial: N30,32,34,35 Power Plant: N4,25 LDC: N23 Pcontract = 500 kEconomic Nonlinear Model Predictive Control for the Optimization of Gas Pipeline Networks EWO
Neural NetworkBased Modeling and Optimization for Effective Vehicle Emission Testing and
Huang, Yinlun
Introduction Automotive emission of hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx) has beenNeural NetworkBased Modeling and Optimization for Effective Vehicle Emission Testing and Engine emission testing and engine calibration are the key to achieving emission standards with satisfactory fuel
Fang-Yen, Christopher
EESOM: Electrical Energy Sourcing Optimization Model Department of Electrical and Systems Sobkiw Dr. John Keenan Project Overview The United States' electrical energy sector faces a set. Questions such as when and where electrical energy is needed and how the resources that fuel its generation
EXTENSIONS TO AN EFFICIENT OPTIMIZATION MODEL FOR LONG-TERM PRODUCTION PLANNING 1 Introduction
to the footwall. Once started, mining restrictions require continuous production of the blocks within a machine three raw ore products used to supply four ore post- processing plants, or mills. Phosphorus is the mainEXTENSIONS TO AN EFFICIENT OPTIMIZATION MODEL FOR LONG-TERM PRODUCTION PLANNING 1 Introduction LKAB
Baer, Ferdinand
Optimizing Computations in Weather and Climate Prediction Models* F. BAER, BANGLIN ZHANG, AND BING scenarios for many time scales, more computer power than is currently available will be needed. One and sometimes with a biosphere included, are very complex and require so much computing power on available
Wu, Xindong
Engines April 15, 2009 7 / 57 #12;Introduction - Section II - Outline Terms and Definitions Brief Search' or displayed back to the user in hypertextual format. mek (UVM) Search Engines April 15, 2009 9 / 57 #12;TermsModeling and Optimizing Hypertextual Search Engines Based on the Reasearch of Larry Page and Sergey
Hu, Jiang
Modeling, Optimization and Control of Rotary Traveling-Wave Oscillator Cheng Zhuo, Huafeng Zhang, Rupak Samanta1 , Jiang Hu2 , Kangsheng Chen Department of Information Science & Electronic Engineering, Zhejiang University, Hangzhou, 310027, China 1,2 Department of Electrical and Computer Engineering, Texas A
Hybrid Model for Building Performance Diagnosis and Optimal Control
Wang, S.; Xu, X.
2003-01-01
S. (1983). Raising the open U value by passive means. Proc. 8th Nat. Passive Solar Conf. Glorieta, NM, pp.839-842. Bahai H. and Esat I.I. (1994). A hybrid model for analysis of complex stress distribution in threaded connectors. Computers... Research Centre of Finland. Kalogirou SA, Neocleous CC and Schizas CN. (1997). Heating load estimation using artificial neural networks. In: Proc. CLIMA 2000 Conf., Brussels (Belgium). Klein S.A., Beckman W.A. et al. (1994). TRNSYS-A Transient System...
Energy Savings Opportunities through Combined Heat and Power Systems Optimization Model Case Studies
Owaidh, M.
2015-01-01
Use Energy Savings Opportunities Through CHP Optimization Models IETC, Jun 2-4 2015 © Copyright 2015, Saudi Aramco. All rights reserved. ESL-IE-15-06-07 Proceedings of the Thrity-Seventh Industrial Energy Technology Conference New Orleans, LA. June 2...-4, 2015 Saudi Aramco: Company General Use Outline: • Introduction – Overview of CHP models – Current Reality • Case Study – Correlations development – Analysis • Conclusion ESL-IE-15-06-07 Proceedings of the Thrity-Seventh Industrial Energy Technology...
MOGO: Model-Oriented Global Optimization of Petascale Applications
Malony, Allen D.; Shende, Sameer S.
2012-09-14
The MOGO project was initiated under in 2008 under the DOE Program Announcement for Software Development Tools for Improved Ease-of-Use on Petascale systems (LAB 08-19). The MOGO team consisted of Oak Ridge National Lab, Argonne National Lab, and the University of Oregon. The overall goal of MOGO was to attack petascale performance analysis by developing a general framework where empirical performance data could be efficiently and accurately compared with performance expectations at various levels of abstraction. This information could then be used to automatically identify and remediate performance problems. MOGO was be based on performance models derived from application knowledge, performance experiments, and symbolic analysis. MOGO was able to make reasonable impact on existing DOE applications and systems. New tools and techniques were developed, which, in turn, were used on important DOE applications on DOE LCF systems to show significant performance improvements.
Neumaier, Arnold
Efficient Global Optimization Under Conditions of Noise and Uncertainty A Multi-Model Multi. By understanding how noise, bias, and topographical inaccuracy in the objective function vary with model resolution into the calculation of the objective function in an optimization problem, producing noise, bias, and topo- graphical
Optimization of a Chilled Water Plant Using a Forward Plant Model
Zhang, Z.; Turner, W. D.; Chen, Q.; Xu, C.; Deng, S.
2010-01-01
of these controls originated from the supervisory control methodology developed by J. E. Braun (1988). Based on model-based ESL-IC-10-10-20 Proceedings of the Tenth International Conference for Enhanced Building Operations, Kuwait, October 26-28, 2010 simulation... for Enhanced Building Operations, Kuwait, October 26-28, 2010 programming (NLP) was more robust and could treat constraints on the state variables directly. Lu et al. (2005b) have presented the optimal set point control for the global optimization problem...
Model Predictive Control-based Optimal Coordination of Distributed Energy Resources
Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming; Elizondo, Marcelo A.
2013-01-07
Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive control (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.
Model Predictive Control-based Optimal Coordination of Distributed Energy Resources
Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming; Elizondo, Marcelo A.
2013-04-03
Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive control (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.
Observations on the Optimality Tolerance in the CAISO 33% RPS Model
Yao, Y; Meyers, C; Schmidt, A; Smith, S; Streitz, F
2011-09-22
In 2008 Governor Schwarzenegger of California issued an executive order requiring that 33 percent of all electricity in the state in the year 2020 should come from renewable resources such as wind, solar, geothermal, biomass, and small hydroelectric facilities. This 33% renewable portfolio standard (RPS) was further codified and signed into law by Governor Brown in 2011. To assess the market impacts of such a requirement, the California Public Utilities Commission (CPUC) initiated a study to quantify the cost, risk, and timing of achieving a 33% RPS by 2020. The California Independent System Operator (CAISO) was contracted to manage this study. The production simulation model used in this study was developed using the PLEXOS software package, which allows energy planners to optimize long-term system planning decisions under a wide variety of system constraints. In this note we describe our observations on varying the optimality tolerance in the CAISO 33% RPS model. In particular, we observe that changing the optimality tolerance from .05% to .5% leads to solutions over 5 times faster, on average, producing very similar solutions with a negligible difference in overall distance from optimality.
ARRAY OPTIMIZATION FOR TIDAL ENERGY EXTRACTION IN A TIDAL CHANNEL – A NUMERICAL MODELING ANALYSIS
Yang, Zhaoqing; Wang, Taiping; Copping, Andrea
2014-04-18
This paper presents an application of a hydrodynamic model to simulate tidal energy extraction in a tidal dominated estuary in the Pacific Northwest coast. A series of numerical experiments were carried out to simulate tidal energy extraction with different turbine array configurations, including location, spacing and array size. Preliminary model results suggest that array optimization for tidal energy extraction in a real-world site is a very complex process that requires consideration of multiple factors. Numerical models can be used effectively to assist turbine siting and array arrangement in a tidal turbine farm for tidal energy extraction.
Vrugt, Jasper A; Wohling, Thomas
2008-01-01
Most studies in vadose zone hydrology use a single conceptual model for predictive inference and analysis. Focusing on the outcome of a single model is prone to statistical bias and underestimation of uncertainty. In this study, we combine multi-objective optimization and Bayesian Model Averaging (BMA) to generate forecast ensembles of soil hydraulic models. To illustrate our method, we use observed tensiometric pressure head data at three different depths in a layered vadose zone of volcanic origin in New Zealand. A set of seven different soil hydraulic models is calibrated using a multi-objective formulation with three different objective functions that each measure the mismatch between observed and predicted soil water pressure head at one specific depth. The Pareto solution space corresponding to these three objectives is estimated with AMALGAM, and used to generate four different model ensembles. These ensembles are post-processed with BMA and used for predictive analysis and uncertainty estimation. Our most important conclusions for the vadose zone under consideration are: (1) the mean BMA forecast exhibits similar predictive capabilities as the best individual performing soil hydraulic model, (2) the size of the BMA uncertainty ranges increase with increasing depth and dryness in the soil profile, (3) the best performing ensemble corresponds to the compromise (or balanced) solution of the three-objective Pareto surface, and (4) the combined multi-objective optimization and BMA framework proposed in this paper is very useful to generate forecast ensembles of soil hydraulic models.
Parametric Studies and Optimization of Eddy Current Techniques through Computer Modeling
Todorov, E. I. [EWI, Engineering and NDE, 1250 Arthur E. Adams Dr., Columbus, OH 43221-3585 (United States)
2007-03-21
The paper demonstrates the use of computer models for parametric studies and optimization of surface and subsurface eddy current techniques. The study with high-frequency probe investigates the effect of eddy current frequency and probe shape on the detectability of flaws in the steel substrate. The low-frequency sliding probe study addresses the effect of conductivity between the fastener and the hole, frequency and coil separation distance on detectability of flaws in subsurface layers.
Optimizing Higher-Order Lagrangian Perturbation Theory for Standard CDM and BSI models
Arno G. Weiss; Stefan Gottloeber; Thomas Buchert
1995-05-24
We investigate the performance of Lagrangian perturbation theory up to the second order for two scenarios of cosmological large-scale structure formation, SCDM (standard cold dark matter) and BSI (broken scale invariance). The latter model we study as a representative of COBE-normalized CDM models which fit the small-scale power of galaxy surveys. In this context we optimize the performance of the Lagrangian perturbation schemes by smoothing the small-scale fluctuations in the initial data. The results of the so obtained Lagrangian mappings are computed for a set of COBE-normalized SCDM and BSI initial data of different sizes and at different times. We compare these results against those obtained with a numerical PM-code. We find an excellent performance of the optimized Lagrangian schemes down to scales close to the correlation length. This is explained by the counterintuitive fact that nonlinearities in the model can produce more small-scale power, if initially such power is removed. The optimization scheme can be expressed in a way which is independent of the type of fluctuation spectrum and of the size of the simulations.
Istrail, Sorin
Fast Protein Folding in the Hydrophobic-hydrophilic Model Within Three-eights of Optimal (Extended for the protein folding problem in the hydrophobic- hydrophilic model, Dill (1985). To our knowledge, our al for this model, Dill (1994). The hydrophobic-hydrophilic model abstracts the dominant force of protein folding
Abhayapala, Thushara D.
210 IEEE SIGNAL PROCESSING LETTERS, VOL. 6, NO. 8, AUGUST 1999 Noise Modeling for Nearfield Array spherically isotropic noise model is introduced. The proposed noise model can be utilized effectively to apply. A simple array gain optimization is used to demonstrate the use of the new noise model. Index Terms
Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant
Kumar, Rajeeva; Kumar, Aditya; Dai, Dan; Seenumani, Gayathri; Down, John; Lopez, Rodrigo
2012-12-31
This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developed will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve these two formulations were developed and validated. For a given OSP problem the computation efficiency largely depends on the “size” of the problem. Initially a simplified 1-D gasifier model assuming axial and azimuthal symmetry was used to test out various OSP algorithms. Finally these algorithms were used to design the optimal sensor network for condition monitoring of IGCC gasifier refractory wear and RSC fouling. The sensors type and locations obtained as solution to the OSP problem were validated using model based sensing approach. The OSP algorithm has been developed in a modular form and has been packaged as a software tool for OSP design where a designer can explore various OSP design algorithm is a user friendly way. The OSP software tool is implemented in Matlab/Simulink© in-house. The tool also uses few optimization routines that are freely available on World Wide Web. In addition a modular Extended Kalman Filter (EKF) block has also been developed in Matlab/Simulink© which can be utilized for model based sensing of important process variables that are not directly measured through combining the online sensors with model based estimation once the hardware sensor and their locations has been finalized. The OSP algorithm details and the results of applying these algorithms to obtain optimal sensor location for condition monitoring of gasifier refractory wear and RSC fouling profile are summarized in this final report.
An MILP-MINLP decomposition method for the global optimization of a source based model of the
Grossmann, Ignacio E.
and regulatory specifications of products. For example, the economic and operability benefits from optimal crude-oilAn MILP-MINLP decomposition method for the global optimization of a source based model. In this work we present two major contributions for the global solution of the problem. The first one
Development of an entrained flow gasifier model for process optimization study
Biagini, E.; Bardi, A.; Pannocchia, G.; Tognotti, L. [Consorzio Pisa Ric, Pisa (Italy). Div Energia Ambiente
2009-10-15
Coal gasification is a versatile process to convert a solid fuel in syngas, which can be further converted and separated in hydrogen, which is a valuable and environmentally acceptable energy carrier. Different technologies (fixed beds, fluidized beds, entrained flow reactors) are used, operating under different conditions of temperature, pressure, and residence time. Process studies should be performed for defining the best plant configurations and operating conditions. Although 'gasification models' can be found in the literature simulating equilibrium reactors, a more detailed approach is required for process analysis and optimization procedures. In this work, a gasifier model is developed by using AspenPlus as a tool to be implemented in a comprehensive process model for the production of hydrogen via coal gasification. It is developed as a multizonal model by interconnecting each step of gasification (preheating, devolatilization, combustion, gasification, quench) according to the reactor configuration, that is in entrained flow reactor. The model removes the hypothesis of equilibrium by introducing the kinetics of all steps and solves the heat balance by relating the gasification temperature to the operating conditions. The model allows to predict the syngas composition as well as quantity the heat recovery (for calculating the plant efficiency), 'byproducts', and residual char. Finally, in view of future works, the development of a 'gasifier model' instead of a 'gasification model' will allow different reactor configurations to be compared.
Two terminal micropower radar sensor
McEwan, Thomas E. (Livermore, CA)
1995-01-01
A simple, low power ultra-wideband radar motion sensor/switch configuration connects a power source and load to ground. The switch is connected to and controlled by the signal output of a radar motion sensor. The power input of the motion sensor is connected to the load through a diode which conducts power to the motion sensor when the switch is open. A storage capacitor or rechargeable battery is connected to the power input of the motion sensor. The storage capacitor or battery is charged when the switch is open and powers the motion sensor when the switch is closed. The motion sensor and switch are connected between the same two terminals between the source/load and ground.
Micropower RF material proximity sensor
McEwan, Thomas E. (Livermore, CA)
1998-01-01
A level detector or proximity detector for materials capable of sensing through plastic container walls or encapsulating materials is of the sensor. Thus, it can be used in corrosive environments, as well as in a wide variety of applications. An antenna has a characteristic impedance which depends on the materials in proximity to the antenna. An RF oscillator, which includes the antenna and is based on a single transistor in a Colpitt's configuration, produces an oscillating signal. A detector is coupled to the oscillator which signals changes in the oscillating signal caused by changes in the materials in proximity to the antenna. The oscillator is turned on and off at a pulse repetition frequency with a low duty cycle to conserve power. The antenna consists of a straight monopole about one-quarter wavelength long at the nominal frequency of the oscillator. The antenna may be horizontally disposed on a container and very accurately detects the fill level within the container as the material inside the container reaches the level of the antenna.
Two terminal micropower radar sensor
McEwan, T.E.
1995-11-07
A simple, low power ultra-wideband radar motion sensor/switch configuration connects a power source and load to ground. The switch is connected to and controlled by the signal output of a radar motion sensor. The power input of the motion sensor is connected to the load through a diode which conducts power to the motion sensor when the switch is open. A storage capacitor or rechargeable battery is connected to the power input of the motion sensor. The storage capacitor or battery is charged when the switch is open and powers the motion sensor when the switch is closed. The motion sensor and switch are connected between the same two terminals between the source/load and ground. 3 figs.
A Mathematical Tumor Model with Immune Resistance and Drug Therapy: An Optimal Control Approach
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
De Pillis, L. G.; Radunskaya, A.
2001-01-01
We present a competition model of cancer tumor growth that includes both the immune system response and drug therapy. This is a four-population model that includes tumor cells, host cells, immune cells, and drug interaction. We analyze the stability of the drug-free equilibria with respect to the immune response in order to look for target basins of attraction. One of our goals was to simulate qualitatively the asynchronous tumor-drug interaction known as “Jeffs phenomenon.” The model we develop is successful in generating this asynchronous response behavior. Our other goal was to identify treatment protocols that could improve standard pulsed chemotherapymore »regimens. Using optimal control theory with constraints and numerical simulations, we obtain new therapy protocols that we then compare with traditional pulsed periodic treatment. The optimal control generated therapies produce larger oscillations in the tumor population over time. However, by the end of the treatment period, total tumor size is smaller than that achieved through traditional pulsed therapy, and the normal cell population suffers nearly no oscillations.« less
A Technical Review on Biomass Processing: Densification, Preprocessing, Modeling and Optimization
Jaya Shankar Tumuluru; Christopher T. Wright
2010-06-01
It is now a well-acclaimed fact that burning fossil fuels and deforestation are major contributors to climate change. Biomass from plants can serve as an alternative renewable and carbon-neutral raw material for the production of bioenergy. Low densities of 40–60 kg/m3 for lignocellulosic and 200–400 kg/m3 for woody biomass limits their application for energy purposes. Prior to use in energy applications these materials need to be densified. The densified biomass can have bulk densities over 10 times the raw material helping to significantly reduce technical limitations associated with storage, loading and transportation. Pelleting, briquetting, or extrusion processing are commonly used methods for densification. The aim of the present research is to develop a comprehensive review of biomass processing that includes densification, preprocessing, modeling and optimization. The specific objective include carrying out a technical review on (a) mechanisms of particle bonding during densification; (b) methods of densification including extrusion, briquetting, pelleting, and agglomeration; (c) effects of process and feedstock variables and biomass biochemical composition on the densification (d) effects of preprocessing such as grinding, preheating, steam explosion, and torrefaction on biomass quality and binding characteristics; (e) models for understanding the compression characteristics; and (f) procedures for response surface modeling and optimization.
Vandersall, Jennifer A.; Gardner, Shea N.; Clague, David S.
2010-05-04
A computational method and computer-based system of modeling DNA synthesis for the design and interpretation of PCR amplification, parallel DNA synthesis, and microarray chip analysis. The method and system include modules that address the bioinformatics, kinetics, and thermodynamics of DNA amplification and synthesis. Specifically, the steps of DNA selection, as well as the kinetics and thermodynamics of DNA hybridization and extensions, are addressed, which enable the optimization of the processing and the prediction of the products as a function of DNA sequence, mixing protocol, time, temperature and concentration of species.
Modeling and Optimization of PEMFC Systems and its Application to Direct Hydrogen Fuel Cell Vehicles
Zhao, Hengbing; Burke, Andy
2008-01-01
and Optimization of PEMFC Systems and its Application toand Optimization of PEMFC Systems and its Application onExchange Membrane fuel cell (PEMFC) technology for use in
Modeling and optimizing of the random atomic spin gyroscope drift based on the atomic spin gyroscope
Quan, Wei; Lv, Lin Liu, Baiqi
2014-11-15
In order to improve the atom spin gyroscope's operational accuracy and compensate the random error caused by the nonlinear and weak-stability characteristic of the random atomic spin gyroscope (ASG) drift, the hybrid random drift error model based on autoregressive (AR) and genetic programming (GP) + genetic algorithm (GA) technique is established. The time series of random ASG drift is taken as the study object. The time series of random ASG drift is acquired by analyzing and preprocessing the measured data of ASG. The linear section model is established based on AR technique. After that, the nonlinear section model is built based on GP technique and GA is used to optimize the coefficients of the mathematic expression acquired by GP in order to obtain a more accurate model. The simulation result indicates that this hybrid model can effectively reflect the characteristics of the ASG's random drift. The square error of the ASG's random drift is reduced by 92.40%. Comparing with the AR technique and the GP + GA technique, the random drift is reduced by 9.34% and 5.06%, respectively. The hybrid modeling method can effectively compensate the ASG's random drift and improve the stability of the system.
A Formal Model for Verifying the Impact of Stealthy Attacks on Optimal Power Flow in Power Grids
Wang, Yongge
- mal Power Flow; Formal Model 1. INTRODUCTION Power system control centers employ a numberA Formal Model for Verifying the Impact of Stealthy Attacks on Optimal Power Flow in Power Grids the integrity of OPF and undermine the economic and secure system operation. We present a formal verification
Optimization of relativistic mean field model for finite nuclei to neutron star matter
B. K. Agrawal; A. Sulaksono; P. -G. Reinhard
2012-04-12
We have optimized the parameters of extended relativistic mean-field model using a selected set of global observables which includes binding energies and charge radii for nuclei along several isotopic and isotonic chains and the iso-scalar giant monopole resonance energies for the $^{90}$Zr and $^{208}$Pb nuclei. The model parameters are further constrained by the available informations on the energy per neutron for the dilute neutron matter and bounds on the equations of state of the symmetric and asymmetric nuclear matter at supra-nuclear densities. Two new parameter sets BSP and IUFSU* are obtained, later one being the variant of recently proposed IUFSU parameter set. The BSP parametrization uses the contributions from the quartic order cross-coupling between $\\omega$ and $\\sigma$ mesons to model the high density behaviour of the equation of state instead of the $\\omega$ meson self-coupling as in the case of IUFSU* or IUFSU. Our parameter sets yield appreciable improvements in the binding energy systematics and the equation of state for the dilute neutron matter. The importance of the quartic order $\\omega-\\sigma$ cross coupling term of the extended RMF model, as often ignored, is realized.
Optimization Under Generalized Uncertainty
Lodwick, Weldon
11 Optimization Under Generalized Uncertainty Optimization Modeling Math 4794/5794: Spring 2013 Weldon A. Lodwick Weldon.Lodwick@ucdenver.edu 2/14/2013 Optimization Modeling - Spring 2013 #12 in the context of optimization problems. The theoretical frame-work for these notes is interval analysis. From
Modeling and Optimization of PEMFC Systems and its Application to Direct Hydrogen Fuel Cell Vehicles
Zhao, Hengbing; Burke, Andy
2008-01-01
01-0416) Appendix 1 Unit Conversion Correction of the Former44 Unit Conversion Correction of the Former Optimization
A Full Demand Response Model in Co-Optimized Energy and
Liu, Guodong; Tomsovic, Kevin
2014-01-01
It has been widely accepted that demand response will play an important role in reliable and economic operation of future power systems and electricity markets. Demand response can not only influence the prices in the energy market by demand shifting, but also participate in the reserve market. In this paper, we propose a full model of demand response in which demand flexibility is fully utilized by price responsive shiftable demand bids in energy market as well as spinning reserve bids in reserve market. A co-optimized day-ahead energy and spinning reserve market is proposed to minimize the expected net cost under all credible system states, i.e., expected total cost of operation minus total benefit of demand, and solved by mixed integer linear programming. Numerical simulation results on the IEEE Reliability Test System show effectiveness of this model. Compared to conventional demand shifting bids, the proposed full demand response model can further reduce committed capacity from generators, starting up and shutting down of units and the overall system operating costs.
Gianmarco Munaò; Francisco Gàmez; Dino Costa; Carlo Caccamo; Francesco Sciortino; Achille Giacometti
2015-05-26
We investigate thermodynamic properties of anisotropic colloidal dumbbells in the frameworks provided by the Reference Interaction Site Model (RISM) theory and an Optimized Perturbation Theory (OPT), this latter based on a fourth-order high-temperature perturbative expansion of the free energy, recently generalized to molecular fluids. Our model is constituted by two identical tangent hard spheres surrounded by square-well attractions with same widths and progressively different depths. Gas-liquid coexistence curves are obtained by predicting pressures, free energies, and chemical potentials. In comparison with previous simulation results, RISM and OPT agree in reproducing the progressive reduction of the gas-liquid phase separation as the anisotropy of the interaction potential becomes more pronounced; in particular, the RISM theory provides reasonable predictions for all coexistence curves, bar the strong anisotropy regime, whereas OPT performs generally less well. Both theories predict a linear dependence of the critical temperature on the interaction strength, reproducing in this way the mean-field behavior observed in simulations; the critical density~--~that drastically drops as the anisotropy increases~--~turns to be less accurate. Our results appear as a robust benchmark for further theoretical studies, in support to the simulation approach, of self-assembly in model colloidal systems.
Optimization of Depletion Modeling and Simulation for the High Flux Isotope Reactor
Betzler, Benjamin R; Ade, Brian J; Chandler, David; Ilas, Germina; Sunny, Eva E
2015-01-01
Monte Carlo based depletion tools used for the high-fidelity modeling and simulation of the High Flux Isotope Reactor (HFIR) come at a great computational cost; finding sufficient approximations is necessary to make the use of these tools feasible. The optimization of the neutronics and depletion model for the HFIR is based on two factors: (i) the explicit representation of the involute fuel plates with sets of polyhedra and (ii) the treatment of depletion mixtures and control element position during depletion calculations. A very fine representation (i.e., more polyhedra in the involute plate approximation) does not significantly improve simulation accuracy. The recommended representation closely represents the physical plates and ensures sufficient fidelity in regions with high flux gradients. Including the fissile targets in the central flux trap of the reactor as depletion mixtures has the greatest effect on the calculated cycle length, while localized effects (e.g., the burnup of specific isotopes or the power distribution evolution over the cycle) are more noticeable consequences of including a critical control element search or depleting burnable absorbers outside the fuel region.
Khovanskii, Askold
and the pro- duction of the objects of consumption-- in order to maximize the production of objectsASYMPTOTIC OPTIMIZATION OF CONSUMPTION IN A MODEL OF TWO-SECTOR ECONOMY L. V. Kantorovich, E. I and the capital resources between the two sectors of economy -- the production of the means of production
Subramanian, Venkat
Experimental analysis and model-based optimization of microalgae growth in photo-bioreactors using]. Besides physical and chemical methods for sequestration of CO2 from flue gas [2], microalgae culture holds great potential for converting flue gas to biomass. Microalgae can capture solar energy more efficiently
Vermont, University of
Local adaptation to biocontrol agents: A multi-objective data- driven optimization model & Environmental Engineering, 219 Votey Building, Burlington, VT 05405, USA 1. Introduction Biocontrol agents to biocontrol agents. In this paper, we examine the evolution of such resistance, along with correlated traits
Alam, Muhammad A.
of the morphology can double the efficiency of BH cells. 1. Introduction Polymer based organic solar cell remains/devices of organic cells to achievable efficiency. The cartoon of a BH solar cell in Fig. 1a illustrates four keyModeling and Optimization of Polymer based Bulk Heterojunction (BH) Solar cell * Biswajit Ray
Bjørnstad, Ottar Nordal
of a company under uncertainty is proposed in this study. Deterministic planning and scheduling models is optimal usage of future resources on the basis of available present information and future scenarios1 increase. As simple as uncertain lead time can affect the production plans which necessitates
Long, David G.
Wind Bias from Sub-optimal Estimation Due to Geophysical Modeling Error -Wind I Paul E. Johnson (which relates the wind to the normalized radar cross section, NRCS, of the ocean surface) is uncertainty in the NRCS for given wind conditions. When the estimated variability is in- cluded in the maximum likelihood
Zhou, Xuesong
1 Loading containers on double-stack cars: Multi-objective optimization models and solution-stack cars: Multi-objective optimization models and solution algorithms for improved safety and reduced maintenance cost Abstract To improve safety measures of loading containers on double-stack rail cars
Introduction Optimal Control Problem
Grigorieva, Ellina V.
and Computational Simulations Ellina Grigorieva and Evgenii Khailov Optimal control of a waste water cleaning plant Khailov Optimal control of a waste water cleaning plant #12;Introduction Model Optimal Control Problem applications will be discussed. Ellina Grigorieva and Evgenii Khailov Optimal control of a waste water cleaning
Optimal Airflow Control for Laboratory Air Handling Unit (LAHU) Systems
Cui, Y.; Liu, M.; Conger, K.
2002-01-01
the indoor air quality, This paper presents modeling, optimization procedures and optimal airflow control sequences....
Optimization of Fault Detection/Diagnosis Model for Thermal Storage System Using AIC
Pan, S.; Zheng, M.; Nakahara, N.
2006-01-01
of the event. In addition, human learning, recognition, and optimal judgment process of any event can be simulated by optimizing the most effective pa-rameters and their numbers for detection and diagnosis by the use of variable selection method. In previous...
Convex Optimization Convex Optimization
Masci, Frank
Convex Optimization #12;#12;Convex Optimization Stephen Boyd Department of Electrical Engineering Cataloguing-in-Publication data Boyd, Stephen P. Convex Optimization / Stephen Boyd & Lieven Vandenberghe p. cm. Includes bibliographical references and index. ISBN 0 521 83378 7 1. Mathematical optimization. 2
Tan, Sirui; Huang, Lianjie
2014-11-01
For modeling scalar-wave propagation in geophysical problems using finite-difference schemes, optimizing the coefficients of the finite-difference operators can reduce numerical dispersion. Most optimized finite-difference schemes for modeling seismic-wave propagation suppress only spatial but not temporal dispersion errors. We develop a novel optimized finite-difference scheme for numerical scalar-wave modeling to control dispersion errors not only in space but also in time. Our optimized scheme is based on a new stencil that contains a few more grid points than the standard stencil. We design an objective function for minimizing relative errors of phase velocities of waves propagating in all directions within a given range of wavenumbers. Dispersion analysis and numerical examples demonstrate that our optimized finite-difference scheme is computationally up to 2.5 times faster than the optimized schemes using the standard stencil to achieve the similar modeling accuracy for a given 2D or 3D problem. Compared with the high-order finite-difference scheme using the same new stencil, our optimized scheme reduces 50 percent of the computational cost to achieve the similar modeling accuracy. This new optimized finite-difference scheme is particularly useful for large-scale 3D scalar-wave modeling and inversion.
OLAF ---A General Modeling System to Evaluate and Optimize the Location of an Air
Fliege, Jörg
. . . . . . . . . . . . . . . . . . . . 17 3.1.2 Metabolism . . . . . . . . . . . . . . . . . . . . . . . . . 23 3.2 Ecosystems and Food Webs . . . . . . . . . . . . . . . . . . 40 5.1.3 The Gradient of the Objective Function . . . . . . . . . 40 5.2 Optimization
Optimal Mix of Penalties in a Principal-Agent Model under Different Institutional Arrangements
Earnhart, Dietrich H.
2000-03-13
This paper uses principal-agent theory to examine the optimal mix of monetary- and resource-based penalties in two institutional settings: a market economy and a centrally planned economy. In a centrally planned economy, an agent's wealth depends...
Individual-based Management of Meta-models for Evolutionary Optimization with
Jin, Yaochu
to Three-Dimensional Blade Optimization Lars Gr¨aning, Yaochu Jin, Bernhard Sendhoff Honda Research-250, Springer, 2007 #12;2 Gr¨aning, Jin, Sendhoff To reduce the number of fitness evaluations, one idea
Hydraulic Fracture Optimization with a Pseudo-3D Model in Multi-layered Lithology
Yang, Mei
2011-10-21
Hydraulic Fracturing is a technique to accelerate production and enhance ultimate recovery of oil and gas while fracture geometry is an important aspect in hydraulic fracturing design and optimization. Systematic design procedures are available...
Oak Ridge National Laboratory
#12;ABSTRACT A physically-based heat pump model was connected to an optimization program to form a computer code for use in the design of high-efficiency heat pumps. The method used allows efficiency of conventional heat pumps, ten variables were optimized while heating capacity was fixed
Hart, W.E.; Istrail, S. [Sandia National Labs., Albuquerque, NM (United States). Algorithms and Discrete Mathematics Dept.
1996-08-09
This paper considers the protein structure prediction problem for lattice and off-lattice protein folding models that explicitly represent side chains. Lattice models of proteins have proven extremely useful tools for reasoning about protein folding in unrestricted continuous space through analogy. This paper provides the first illustration of how rigorous algorithmic analyses of lattice models can lead to rigorous algorithmic analyses of off-lattice models. The authors consider two side chain models: a lattice model that generalizes the HP model (Dill 85) to explicitly represent side chains on the cubic lattice, and a new off-lattice model, the HP Tangent Spheres Side Chain model (HP-TSSC), that generalizes this model further by representing the backbone and side chains of proteins with tangent spheres. They describe algorithms for both of these models with mathematically guaranteed error bounds. In particular, the authors describe a linear time performance guaranteed approximation algorithm for the HP side chain model that constructs conformations whose energy is better than 865 of optimal in a face centered cubic lattice, and they demonstrate how this provides a 70% performance guarantee for the HP-TSSC model. This is the first algorithm in the literature for off-lattice protein structure prediction that has a rigorous performance guarantee. The analysis of the HP-TSSC model builds off of the work of Dancik and Hannenhalli who have developed a 16/30 approximation algorithm for the HP model on the hexagonal close packed lattice. Further, the analysis provides a mathematical methodology for transferring performance guarantees on lattices to off-lattice models. These results partially answer the open question of Karplus et al. concerning the complexity of protein folding models that include side chains.
A. E. Koshelev; I. A. Sadovskyy; C. L. Phillips; A. Glatz
2015-10-01
Introducing nanoparticles into superconducting materials has emerged as an efficient route to enhance their current-carrying capability. We address the problem of optimizing vortex pinning landscape for randomly distributed metallic spherical inclusions using large-scale numerical simulations of time-dependent Ginzburg-Landau equations. We found the size and density of particles for which the highest critical current is realized in a fixed magnetic field. For each particle size and magnetic field, the critical current reaches a maximum value at a certain particle density, which typically corresponds to 15-23% of the total volume being replaced by nonsuperconducting material. For fixed diameter, this optimal particle density increases with the magnetic field. Moreover, we found that the optimal particle diameter slowly decreases with the magnetic field from 4.5 to 2.5 coherence lengths at a given temperature. This result shows that pinning landscapes have to be designed for specific applications taking into account relevant magnetic field scales.
Sandborn, Peter
to Optimize Offshore Wind Farm Sustainment Peter Sandborn,1 Gilbert Haddad,2 Amir Kashani-Pour2 and Xin Lei2, representing 17-28% of the total levelized cost of offshore wind farms and more for farms that are more than 12 stakeholders. Understanding the life-cycle sustainment requirements of offshore wind farms is an area that has
The impact of uncertainty on shape optimization of idealized bypass graft models in unsteady flow
Marsden, Alison L.
in the upstream proximal angle. The impact of cost function choice on the optimal solution was explored construction of a graft over a blocked blood vessel. Depending on the location and the underlying disease of surgical geometry on flow fields and hence wall- shear stress WSS , oscillatory shear index OSI , wall
Michalski, Ryszard S.
specialized LEM-based systems for heat exchanger optimization. 1. Introduction Research on intelligent to conventional blind operators, such as mutation and recombination, LEM employs new types of innovation operators, LEM integrates both types of operators--new and conventional ones--in a way that seeks to maximize
Optimal Resource Allocation for Wireless Video Sensors with Power-Rate-Distortion Model of Imager
Heinzelman, Wendi
role in the resulting video quality as well as in the life-time of the system. The problem of power (WVSs), including the image sensor subsystem into the system analysis. By assigning a power quality under power and rate constraints. To demonstrate the optimization method, we further establish a P
Mohaghegh, Shahab
SPE 77659 Prudhoe Bay Oil Production Optimization: Using Virtual intelligence Techniques, Stage One, TX 75083-3836, U.S.A., fax 01-972-952-9435. Abstract Field data from the Prudhoe Bay oil field.998 respectively. This is the first phase in the development of a tool to maximize total field oil production
Stochastic Optimization of Electricity Portfolios: Scenario Tree Modeling and Risk Management
RÃ¶misch, Werner
of risk manage- ment into power production planning and trading based on stochastic programming. In energy and (physical) power trading. Moreover, risk management and stochastic optimization rest upon the same type of stochastic programming with regard to application in power management. In particular we discuss issues
Boyer, Edmond
and production planning and control has recently become an important research area. In this context, (O MAINTENANCE/PRODUCTION PLANNING FOR A MANUFACTURING SYSTEM UNDER THE MACHINE AVAILABILITY AND SUBCONTRACTING a subcontracting machine. In order to ensure a simultaneous economic production planning with an optimal
The Framework of an Optimization Model for the Thermal Design of Building Envelopes
Al-Homoud, M. S.; Degelman, L. O.; Boyer, L. L.
1994-01-01
to the decision making process of building design. In dealing with the building as a thermal system, the proper selection of its components and their relationships can be organized using a systems approach. This can be achieved by coupling an optimization...
Grizzle, Jessy W.
and sinks. Optimal solutions are easy to specify if the drive cycle is known a priori. It is very challenging to compute controllers that yield good fuel economy for a class of drive cycles representative simulation on large numbers of real-world drive cycles. I. INTRODUCTION Hybrid vehicles have become
Partial Optimality by Pruning for MAP-inference with General Graphical Models
Schnörr, Christoph
and for which dedicated and efficient algorithms exist. 1.1. Related Work We distinguish two classes of approaches to partial optimality. (i) Roof duality based approaches. The ear- liest paper dealing it for every solution of a certain re- laxation. This relaxation is the same, as used by the roof duality
Kwon, Eun Young; Primeau, Francois
2008-01-01
C08011 KWON AND PRIMEAU: OPTIMIZATION AND SENSITIVITY STUDYand F. Primeau (2006), Optimization and sensitivity study of10.1029/2007JC004520, 2008 Optimization and sensitivity of a
Bukhsh, Waqquas Ahmed
2014-07-01
Optimization plays a central role in the control and operation of electricity power networks. In this thesis we focus on two very important optimization problems in power systems. The first is the optimal power flow ...
Bradonjic, Milan [Los Alamos National Laboratory
2009-01-01
In this paper we study reputation mechanisms, and show how the notion of reputation can help us in building truthful online auction mechanisms. From the mechanism design prospective, we derive the conditions on and design a truthful online auction mechanism. Moreover, in the case when some agents may lay or cannot have the real knowledge about the other agents reputations, we derive the resolution of the auction, such that the mechanism is truthful. Consequently, we move forward to the optimal one-gambler/one-seller problem, and explain how that problem is refinement of the previously discussed online auction design in the presence of reputation mechanism. In the setting of the optimal one-gambler problem, we naturally rise and solve the specific question: What is an agent's optimal strategy, in order to maximize his revenue? We would like to stress that our analysis goes beyond the scope, which game theory usually discusses under the notion of reputation. We model one-player games, by introducing a new parameter (reputation), which helps us in predicting the agent's behavior, in real-world situations, such as, behavior of a gambler, real-estate dealer, etc.
From Physics Model to Results: An Optimizing Framework for Cross-Architecture Code Generation
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Blazewicz, Marek; Hinder, Ian; Koppelman, David M.; Brandt, Steven R.; Ciznicki, Milosz; Kierzynka, Michal; Löffler, Frank; Schnetter, Erik; Tao, Jian
2013-01-01
Starting from a high-level problem description in terms of partial differential equations using abstract tensor notation, theChemoraframework discretizes, optimizes, and generates complete high performance codes for a wide range of compute architectures. Chemora extends the capabilities of Cactus, facilitating the usage of large-scale CPU/GPU systems in an efficient manner for complex applications, without low-level code tuning. Chemora achieves parallelism through MPI and multi-threading, combining OpenMP and CUDA. Optimizations include high-level code transformations, efficient loop traversal strategies, dynamically selected data and instruction cache usage strategies, and JIT compilation of GPU code tailored to the problem characteristics. The discretization is based onmore »higher-order finite differences on multi-block domains. Chemora's capabilities are demonstrated by simulations of black hole collisions. This problem provides an acid test of the framework, as the Einstein equations contain hundreds of variables and thousands of terms.« less
From Physics Model to Results: An Optimizing Framework for Cross-Architecture Code Generation
Marek Blazewicz; Ian Hinder; David M. Koppelman; Steven R. Brandt; Milosz Ciznicki; Michal Kierzynka; Frank Löffler; Erik Schnetter; Jian Tao
2013-07-24
Starting from a high-level problem description in terms of partial differential equations using abstract tensor notation, the Chemora framework discretizes, optimizes, and generates complete high performance codes for a wide range of compute architectures. Chemora extends the capabilities of Cactus, facilitating the usage of large-scale CPU/GPU systems in an efficient manner for complex applications, without low-level code tuning. Chemora achieves parallelism through MPI and multi-threading, combining OpenMP and CUDA. Optimizations include high-level code transformations, efficient loop traversal strategies, dynamically selected data and instruction cache usage strategies, and JIT compilation of GPU code tailored to the problem characteristics. The discretization is based on higher-order finite differences on multi-block domains. Chemora's capabilities are demonstrated by simulations of black hole collisions. This problem provides an acid test of the framework, as the Einstein equations contain hundreds of variables and thousands of terms.
Lively, Charles
2012-07-16
of Hybrid LU-MZ Application and Optimization (Class C) 171 39 Performance of Hybrid LU-MZ Application and Optimization (Class D) 172 40 Performance of Hybrid GTC Application and Optimization (50ppc) ....... 173 xvii Page 41 Performance... of Hybrid GTC Application and Optimization (100ppc) ..... 174 42 Performance of MPI GTC Application and Optimization (50ppc) ........... 176 43 Performance of MPI GTC Application and Optimization (100ppc) ......... 177 44 Performance...
Zhang, Xuesong
2009-05-15
&M University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY August 2008 Major Subject: Water Management and Hydrologic Sciences EVALUATING AND DEVELOPING PARAMETER OPTIMIZATION AND UNCERTAINTY ANALYSIS... OF PHILOSOPHY Approved by: Chair of Committee, Raghavan Srinivasan Committee Members, Faming Liang Patricia K. Smith Francisco Olivera Head of Department, Ronald Kaiser August 2008 Major Subject: Water Management and Hydrologic Sciences iii...
Richardson, Andrew D.
and earth system models, especially for long-term (multian- nual and greater) simulations. Data assimilation
Perez Roman, Eduardo
2011-08-08
(DEVS) simulation model for nuclear medicine patient service management that considers both patient and management perspectives. DEVS is a formal modeling and simulation framework based on dynamical systems theory and provides well de ned concepts...
Optimization Online Digest -- May 2015
Optimization Online Digest — May 2015. Applications — OR and Management Sciences Mathematical Models for Multi Container Loading Problems
First report on non-thermal plasma reactor scaling criteria and optimization models
Rosocha, L.A.; Korzekwa, R.A.
1998-01-13
The purpose of SERDP project CP-1038 is to evaluate and develop non-thermal plasma (NTP) reactor technology for Department of Defense (DoD) air emissions control applications. The primary focus is on oxides of nitrogen (NO{sub x}) and a secondary focus on hazardous air pollutants (HAPs), especially volatile organic compounds (VOCs). Example NO{sub x} sources are jet engine test cells (JETCs) and diesel engine powered electrical generators. Example VOCs are organic solvents used in painting, paint stripping, and parts cleaning. To design and build NTP reactors that are optimized for particular DoD applications, one must understand the basic decomposition chemistry of the target compound(s) and how the decomposition of a particular chemical species depends on the air emissions stream parameters and the reactor operating parameters. This report is intended to serve as an overview of the subject of reactor scaling and optimization and will discuss the basic decomposition chemistry of nitric oxide (NO) and two representative VOCs, trichloroethylene and carbon tetrachloride, and the connection between the basic plasma chemistry, the target species properties, and the reactor operating parameters (in particular, the operating plasma energy density). System architecture, that is how NTP reactors can be combined or ganged to achieve higher capacity, will also be briefly discussed.
Decomposition methods for semidefinite optimization
Sun, Yifan
2015-01-01
optimization . . . . . . . . . . . . . . . . . . . . . . . . . .Optimization over sparse matrixoptimization . . . . . . . . . . . . . . . . . . . . . . .
Optimizing future imaging survey of galaxies to confront dark energy and modified gravity models
Kazuhiro Yamamoto; David Parkinson; Takashi Hamana; Robert C. Nichol; Yasushi Suto
2007-07-22
We consider the extent to which future imaging surveys of galaxies can distinguish between dark energy and modified gravity models for the origin of the cosmic acceleration. Dynamical dark energy models may have similar expansion rates as models of modified gravity, yet predict different growth of structure histories. We parameterize the cosmic expansion by the two parameters, $w_0$ and $w_a$, and the linear growth rate of density fluctuations by Linder's $\\gamma$, independently. Dark energy models generically predict $\\gamma \\approx 0.55$, while the DGP model $\\gamma \\approx 0.68$. To determine if future imaging surveys can constrain $\\gamma$ within 20 percent (or $\\Delta\\gammafuture CMB observations.
Kusiak, Andrew
1 Abstract--A bi-objective optimization model of power and power changes generated by a wind the industrial data collected at a wind farm. The models and constraints derived from the data were integrated prediction, power ramp rate, data mining, wind turbine operation strategy, generator torque, blade pitch
Modeling and Optimization of PEMFC Systems and its Application to Direct Hydrogen Fuel Cell Vehicles
Zhao, Hengbing; Burke, Andy
2008-01-01
Polymer Electrolyte Fuel Cell Model, J. Electrochem. Soc. ,in Polymer Electrolyte Fuel Cells, J. Electrochem. Soc. ,Solid-Polymer- Electrolyte Fuel Cell, J. Electrochem. Soc. ,
Bond-Lamberty, Benjamin; Calvin, Katherine V.; Jones, Andrew D.; Mao, Jiafu; Patel, Pralit L.; Shi, Xiaoying; Thomson, Allison M.; Thornton, Peter E.; Zhou, Yuyu
2014-01-01
Human activities are significantly altering biogeochemical cycles at the global scale, posing a significant problem for earth system models (ESMs), which may incorporate static land-use change inputs but do not actively simulate policy or economic forces. One option to address this problem is a to couple an ESM with an economically oriented integrated assessment model. Here we have implemented and tested a coupling mechanism between the carbon cycles of an ESM (CLM) and an integrated assessment (GCAM) model, examining the best proxy variables to share between the models, and quantifying our ability to distinguish climate- and land-use-driven flux changes. CLM’s net primary production and heterotrophic respiration outputs were found to be the most robust proxy variables by which to manipulate GCAM’s assumptions of long-term ecosystem steady state carbon, with short-term forest production strongly correlated with long-term biomass changes in climate-change model runs. By leveraging the fact that carbon-cycle effects of anthropogenic land-use change are short-term and spatially limited relative to widely distributed climate effects, we were able to distinguish these effects successfully in the model coupling, passing only the latter to GCAM. By allowing climate effects from a full earth system model to dynamically modulate the economic and policy decisions of an integrated assessment model, this work provides a foundation for linking these models in a robust and flexible framework capable of examining two-way interactions between human and earth system processes.
Optimal model reduction for non-rational functions Mark R. Opmeer1
Opmeer, Mark
irrational functions. Irrational transfer functions arise for systems modeled by partial differential examples of irrational transfer functions: one arising from a heat equation and one arising from a beam equation. I. INTRODUCTION Model reduction has been a topic of considerable interest in control theory
accuracy. a r t i c l e i n f o Article history: Received 16 May 2014 Received in revised form 17 February. The National Renewable Energy Laboratory's BEopt/DOE-2.2 is used to evaluate an automated regression the calibration procedure. Substituting actual BEopt/DOE-2.2 model simulations with the statistical models reduces
Convex Optimization Course Welcome Pack
Hall, Julian
1 NATCOR Convex Optimization Course 23rd Â 27th June 2014 Welcome Pack This pack contains. ABSTRACT Convex optimization is the fundamental process of optimal decision-making. Although mathematically restrictive, many practical problems may be modelled directly as convex optimization problems. Convex
Optimization Online Links. Optimization related societies. Mathematical Optimization Society · SIAM · INFORMS. Optimization related journals. Mathematical ...
Suthar, B; Northrop, PWC; Braatz, RD; Subramanian, VR
2014-07-30
This paper illustrates the application of dynamic optimization in obtaining the optimal current profile for charging a lithium-ion battery by restricting the intercalation-induced stresses to a pre-determined limit estimated using a pseudo 2-dimensional (P2D). model. This paper focuses on the problem of maximizing the charge stored in a given time while restricting capacity fade due to intercalation-induced stresses. Conventional charging profiles for lithium-ion batteries (e.g., constant current followed by constant voltage or CC-CV) are not derived by considering capacity fade mechanisms, which are not only inefficient in terms of life-time usage of the batteries but are also slower by not taking into account the changing dynamics of the system. (C) The Author(s) 2014. Published by ECS. This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives 4.0 License (CC BY-NC-ND, http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is not changed in any way and is properly cited. For permission for commercial reuse, please email: oa@electrochem.org. All rights reserved.
Malik, Ejaz
2009-05-15
total manufacturing capacity. Data regarding the factory workers, machines, warehouse staff, and scheduling were not relevant and, therefore, were not considered in the creation of the linear programming model. All of the basic steps of generating a...
OLAF _ A General Modeling System to Evaluate and Optimize the Location of an Air
Fliege, Jörg
........................17 3.1.1The Standard Model ....................17 3.1.2Metabolism.1.2The Objective Function ..................40 5.1.3The Gradient of the Objective Function
Natti, Satish
2010-01-14
New maintenance techniques for circuit breakers are studied in this dissertation by proposing a probabilistic maintenance model and a new methodology to assess circuit breaker condition utilizing its control circuit data. ...
Grossmann, Ignacio E.
horizon, the model involves decisions related to FPSO (floating production, storage and offloading planning, FPSO * E-mail: vijaygup@andrew.cmu.edu To whom all correspondence should be addressed. E
California at Davis, University of
: · How would renewable/ alternative energy industry compete with conventional energy energy system planning University University of California, Davis PI Yueyue modeling framework for strategic renewable energy planning, where green technologies
Discrete optimization methods to fit piecewise-affine models to data ...
2015-03-09
(a) A piecewise affine model with k = 2, fitting the eight data points. A = {ai}i?I .... where: i) for every j ? J, each group Aj is completely contained into the subdo-.
Model-constrained optimization methods for reduction of parameterized large-scale systems
Bui-Thanh, Tan
2007-01-01
Most model reduction techniques employ a projection framework that utilizes a reduced-space basis. The basis is usually formed as the span of a set of solutions of the large-scale system, which are computed for selected ...
Model-Constrained Optimization Methods for Reduction of Parameterized Large-Scale Systems
Tan, Bui-Thanh
Most model reduction techniques employ a projection framework that utilizes a reduced-space basis. The basis is usually formed as the span of a set of solutions of the large-scale system, which are computed for selected ...
Modeling and Optimization of PEMFC Systems and its Application to Direct Hydrogen Fuel Cell Vehicles
Zhao, Hengbing; Burke, Andy
2008-01-01
H. Peng, Control of Fuel Cell Power Systems, Springer, 2004an arbitrary size (power) fuel cell. Finally, the model ison the rated fuel cell stack power. The rated stack power is
Optimal modeling of 1D azimuth correlations in the context of Bayesian inference
Michiel B. De Kock; Hans C. Eggers; Thomas A. Trainor
2015-02-16
Analysis and interpretation of spectrum and correlation data from high-energy nuclear collisions is currently controversial because two opposing physics narratives derive contradictory implications from the same data-one narrative claiming collision dynamics is dominated by dijet production and projectile-nucleon fragmentation, the other claiming collision dynamics is dominated by a dense, flowing QCD medium. Opposing interpretations seem to be supported by alternative data models, and current model-comparison schemes are unable to distinguish between them. There is clearly need for a convincing new methodology to break the deadlock. In this study we introduce Bayesian Inference (BI) methods applied to angular correlation data as a basis to evaluate competing data models. For simplicity the data considered are projections of 2D angular correlations onto 1D azimuth from three centrality classes of 200 GeV Au-Au collisions. We consider several data models typical of current model choices, including Fourier series (FS) and a Gaussian plus various combinations of individual cosine components. We evaluate model performance with BI methods and with power-spectrum (PS) analysis. We find that the FS-only model is rejected in all cases by Bayesian analysis which always prefers a Gaussian. A cylindrical quadrupole cos(2\\phi) is required in some cases but rejected for most-central Au-Au collisions. Given a Gaussian centered at the azimuth origin "higher harmonics" cos(m\\phi) for m > 2 are rejected. A model consisting of Gaussian + dipole cos(\\phi) + quadrupole cos(2\\phi) provides good 1D data descriptions in all cases.
Optimization Journals, Sites, Societies - Optimization Online
Optimization related societies. Mathematical Optimization Society · SIAM · INFORMS. Optimization related journals. Mathematical Programming and ...
Derivative-free optimization of rate parameters of capsid assembly models from bulk in vitro data
Xie, Lu; Schwartz, Russell
2015-01-01
The assembly of virus capsids from free coat proteins proceeds by a complicated cascade of association and dissociation steps, the great majority of which cannot be directly experimentally observed. This has made capsid assembly a rich field for computational models to attempt to fill the gaps in what is experimentally observable. Nonetheless, accurate simulation predictions depend on accurate models and there are substantial obstacles to model inference for such systems. Here, we describe progress in learning parameters for capsid assembly systems, particularly kinetic rate constants of coat-coat interactions, by computationally fitting simulations to experimental data. We previously developed an approach to learn rate parameters of coat-coat interactions by minimizing the deviation between real and simulated light scattering data monitoring bulk capsid assembly in vitro. This is a difficult data-fitting problem, however, because of the high computational cost of simulating assembly trajectories, the stochas...
A micropower DSP for sensor applications
Ickes, Nathan J. (Nathan Jeffrey), 1979-
2008-01-01
Ultra-low power systems, such as wireless microsensor networks or implanted medical devices, are driving the development of processors capable of performing increasingly complicated computations using mere microwatts of ...
Precision Micropower, Low Dropout Voltage References
Berns, Hans-Gerd
series references are specified over the extended industrial temperature range (-40°C to +85°C) with typical performance specifications over -40°C to +125°C for applications, such as automotive. All
Micropower generation using combustion: Issues and approaches
Fernandez-Pello, Carlos
2002-01-01
Int. Conf. on MicroElectroMechanical Systems, Interlaken,Pisano, A . , Microelectromechanical Systems (MEMS) Program,Beebe, D.J. , J. Microelectromechanical Systems, 9, 2, 190-
Micropower generation using combustion: Issues and approaches
Fernandez-Pello, Carlos
2002-01-01
Int. Conf. on MicroElectroMechanical Systems, Interlaken,1997. 8. Pisano, A . , Microelectromechanical Systems (MEMS)Beebe, D.J. , J. Microelectromechanical Systems, 9, 2, 190-
MicroPower Global | Open Energy Information
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 on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History ViewMayo, Maryland: Energy ResourcesDec 2005 WindPRO isMickey Hot Springs5) Jump
Pedram, Massoud
of the realistic electricity price function and the energy storage capacity limitation, the residential storage--Integrating residential photovoltaic (PV) power generation and energy storage systems into the Smart Grid is an effective a particularly interesting problem with the introduction of dynamic electricity energy pricing models since
Models for Optimization of Energy Consumption of Pumps in a Wastewater Processing Plant
Kusiak, Andrew
; Energy consumption; Data collection; Neural networks; Dynamic models; Statics; Water treatment plants in wastewater processing plants usually follow two strategies. One is to upgrade the current sewage sludge treatment process and produce higher quality efflu- ent. The other is to modify or redesign the sludge
Model-Driven Integration for a Service Placement Optimizer in a Sustainable Cloud of Clouds
Suzuki, Jun
--"Cloud of clouds" (or federated cloud) is an emerg- ing style of software deployment and execution to interoperate, federated clouds, model-driven system integration and sustainable clouds I. INTRODUCTION Cloud computing, cost effective (e.g., energy effi- cient) service/data placement and avoidance of "lock
Paris-Sud XI, Université de
manufacturers. While many models of hybrid cars have been devel- oped and put on the market in the last few Environment for Assessing Power Management Strategies in Hybrid Motorcycles Alessandro Beghi, Fabio Maran of transportation systems is a world wide priority. Hybrid propulsion vehicles have proved to have a strong
RESERVOIR MODEL OPTIMIZATION UNDER UNCERTAINTY Sasanka Are, Paul Dostert, Bree Ettinger
models for a simple oil reser- voir. Besides estimating NPV for certain high/low scenarios, we used and production strategy and need to come up with high/low scenarios for Net Present Value (NPV, the pressure drop P, and a hydraulic conductivity coefficient K which we call per- meability. The flow rate
Yu, Guo
2011-02-22
variations which serves as the baseline for robust analog circuit design. We propose statistical performance modeling methods for two popular types of complex analog/mixed-signal circuits including Sigma-Delta ADCs and charge-pump PLLs. A more general...
Optimization Models for Supply Chain and Operations Management OM 392, Spring 2012
Ghosh, Joydeep
Models for Supply Chain and Operations Management OM 392, Spring 2012 Unique Number: 03955 Professor Anant Balakrishnan Classroom: GSB 5.154 Office: CBA 6.486 Class time: W 2 to 5 p.m. e-mail: anantb Management involves planning and coordinating the value-adding activities and flow of materials
MODEL AND OPTIMIZATION OF ORGANIC PHOTOVOLTAIC CELLS Amelia McNamara
-layer photovoltaic system was reported in 1958 [9], the topic did not catch much attention until a conjugated polymer photovoltaic system is very different from the inorganic case. Unlike the three dimensional lattices cells may not be applied to organic photovoltaic system. Instead, some new approaches modeling
When the Model Hits the Runway: The DOZE Algorithm for optimal dispatching of
Morrow, James A.
the Bureau of Transportation Statistics to model flight delays. Utilizing estimates on different costs associated with escorting NAPs, we were able to prioritize and codify all the operations taking place during-Transit and Stationary . . . . . . . . . . . . . . . . . 12 4 Cost Analysis 13 4.1 Wheelchair Maintenance
A multiperiod optimization model to schedule large-scale petroleum development projects
Husni, Mohammed Hamza
2009-05-15
are to be selected subject to a number of resources constraints in several periods. The constraints may occur from limitations in various resources such as capital budgets, operating budgets, and drilling rigs. The model also accounts for a number of assumptions...
-mail: charles-alexis.asselineau@anu.edu.au 1. Introduction In concentrated solar power systems, receivers convert concentrated solar radiation into heat and, consequently, have a major impact on overall system modeling Charles-Alexis Asselineau1 , Jose Zapata1 and Dr John Pye1 1 Solar Thermal Group, College
Second-Order Signature: A Tool for Specifying Data Models, Query Processing, and Optimization
GÃ¼ting, Ralf Hartmut
-order signature (and algebra), a system of two coupled many-sorted signatures, where the top-level signature the types defined as terms of the top level. Hence the top level can be used to define a data or representation model and the bottom level to describe a query algebra or a query processing algebra. We show
Long Proteins with Unique Optimal Foldings in the H-P Model ?
state of proteins is a global energy minimum, and (2) in most cases proteins fold to a unique state model designed to answer qualitative questions about the protein folding process. In this paper we; 1 Introduction Protein folding [14,22,30] is a central problem in molecular and computational
Zhou, Zhi; de Bedout, Juan Manuel; Kern, John Michael; Biyik, Emrah; Chandra, Ramu Sharat
2013-01-22
A system for optimizing customer utility usage in a utility network of customer sites, each having one or more utility devices, where customer site is communicated between each of the customer sites and an optimization server having software for optimizing customer utility usage over one or more networks, including private and public networks. A customer site model for each of the customer sites is generated based upon the customer site information, and the customer utility usage is optimized based upon the customer site information and the customer site model. The optimization server can be hosted by an external source or within the customer site. In addition, the optimization processing can be partitioned between the customer site and an external source.
Ely, James H.; Siciliano, Edward R.; Swinhoe, Martyn T.; Lintereur, Azaree T.
2013-01-01
This report details the results of the modeling and simulation work accomplished for the ‘Neutron Detection without Helium-3’ project during the 2011 and 2012 fiscal years. The primary focus of the project is to investigate commercially available technologies that might be used in safeguards applications in the relatively near term. Other technologies that are being developed may be more applicable in the future, but are outside the scope of this study.
J. Vernon Cole; Abhra Roy; Ashok Damle; Hari Dahr; Sanjiv Kumar; Kunal Jain; Ned Djilai
2012-10-02
Water management in Proton Exchange Membrane, PEM, Fuel Cells is challenging because of the inherent conflicts between the requirements for efficient low and high power operation. Particularly at low powers, adequate water must be supplied to sufficiently humidify the membrane or protons will not move through it adequately and resistance losses will decrease the cell efficiency. At high power density operation, more water is produced at the cathode than is necessary for membrane hydration. This excess water must be removed effectively or it will accumulate in the Gas Diffusion Layers, GDLs, between the gas channels and catalysts, blocking diffusion paths for reactants to reach the catalysts and potentially flooding the electrode. As power density of the cells is increased, the challenges arising from water management are expected to become more difficult to overcome simply due to the increased rate of liquid water generation relative to fuel cell volume. Thus, effectively addressing water management based issues is a key challenge in successful application of PEMFC systems. In this project, CFDRC and our partners used a combination of experimental characterization, controlled experimental studies of important processes governing how water moves through the fuel cell materials, and detailed models and simulations to improve understanding of water management in operating hydrogen PEM fuel cells. The characterization studies provided key data that is used as inputs to all state-of-the-art models for commercially important GDL materials. Experimental studies and microscopic scale models of how water moves through the GDLs showed that the water follows preferential paths, not branching like a river, as it moves toward the surface of the material. Experimental studies and detailed models of water and airflow in fuel cells channels demonstrated that such models can be used as an effective design tool to reduce operating pressure drop in the channels and the associated costs and weight of blowers and pumps to force air and hydrogen gas through the fuel cell. Promising improvements to materials structure and surface treatments that can potentially aid in managing the distribution and removal of liquid water were developed; and improved steady-state and freeze-thaw performance was demonstrated for a fuel cell stack under the self-humidified operating conditions that are promising for stationary power generation with reduced operating costs.
DISSELKAMP RS
2011-01-06
Boehmite (e.g., aluminum oxyhydroxide) is a major non-radioactive component in Hanford and Savannah River nuclear tank waste sludge. Boehmite dissolution from sludge using caustic at elevated temperatures is being planned at Hanford to minimize the mass of material disposed of as high-level waste (HLW) during operation of the Waste Treatment Plant (WTP). To more thoroughly understand the chemistry of this dissolution process, we have developed an empirical kinetic model for aluminate production due to boehmite dissolution. Application of this model to Hanford tank wastes would allow predictability and optimization of the caustic leaching of aluminum solids, potentially yielding significant improvements to overall processing time, disposal cost, and schedule. This report presents an empirical kinetic model that can be used to estimate the aluminate production from the leaching of boehmite in Hanford waste as a function of the following parameters: (1) hydroxide concentration; (2) temperature; (3) specific surface area of boehmite; (4) initial soluble aluminate plus gibbsite present in waste; (5) concentration of boehmite in the waste; and (6) (pre-fit) Arrhenius kinetic parameters. The model was fit to laboratory, non-radioactive (e.g. 'simulant boehmite') leaching results, providing best-fit values of the Arrhenius A-factor, A, and apparent activation energy, E{sub A}, of A = 5.0 x 10{sup 12} hour{sup -1} and E{sub A} = 90 kJ/mole. These parameters were then used to predict boehmite leaching behavior observed in previously reported actual waste leaching studies. Acceptable aluminate versus leaching time profiles were predicted for waste leaching data from both Hanford and Savannah River site studies.
Automatic Calibration of a Building Energy Simulation Model Using a Global Optimization Program
Lee, S. U.; Claridge, D.
2002-01-01
, Proceedings of the ACEEE 1988 Summer Study on Energy Efficiency in Buildings, 10, 14-26. Balcomb, J.D., Burch, J.D., Subbarao, K., 1993. Short-term energy monitoring of residences, ASHRAE Transactions, 99 (2): 935-944. Balcomb, J.D., Burch, J.D...-259. Sorooshian, S., Gupta, V.K., 1983. Automatic calibration of conceptual rainfall-runoff models - the question of parameter observability and uniqueness, Water Resources Res., 19 (1): 260- 268. Subbarao, K., Burch, J., Hancock, C.E., Lekov, A., Balcomb, J.D...
An Optimization Model for Antenna Selection and Deployment in Single and Multi-cell RFID Systems
Zou, Sicheng; Crisp, Michael; Sabesan, Sithamparanathan; Kadri, Abdullah; Penty, Richard V.; White, Ian H.
2015-01-01
Sabesan*, Abdullah Kadri+, Richard V. Penty* and Ian H. White* *Electrical Division, Department of Engineering University of Cambridge, Cambridge, UK Email: zs271@cam.ac.uk Figure 2 3D model of antenna radiation pattern with half power... .-March 2006 [2]. D.W. Engels, S. E. Sanjay, “The Reader collision problem ," IEEE International Conference on Systems, Man and Cybernetics, vol.3, pp.6-9 Oct. 2002 [3]. D.-Y. Kim, H.-G. Yoon, B.-J. Jang, and J.-G. Yook, “Effects of reader interference...
Optimal Initial Conditions for Coupling Ice Sheet Models to Earth System
Office of Scientific and Technical Information (OSTI)
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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfateSciTech ConnectSpeeding access to science(Thesis/Dissertation)Models. (Journal Article) |
optimal initial conditions for coupling ice sheet models to earth system
Office of Scientific and Technical Information (OSTI)
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 Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefieldSulfateSciTechtail.Theory of rare Kaonfor DirectSciTechConnectXOP:(Journal Article)models
Optimization of the parameters of plasma liners with zero-dimensional models
Oreshkin, V. I.
2013-11-15
The efficiency of conversion of the energy stored in the capacitor bank of a high-current pulse generator into the kinetic energy of an imploding plasma liner is analyzed. The analysis is performed by using a model consisting of LC circuit equations and equations of motion of a cylindrical shell. It is shown that efficient energy conversion can be attained only with a low-inductance generator. The mode of an 'ideal' load is considered where the load current at the final stage of implosion is close to zero. The advantages of this mode are, first, high efficiency of energy conversion (80%) and, second, improved stability of the shell implosion. In addition, for inertial confinement fusion realized by the scheme of a Z pinch dynamic hohlraum, not one but several fusion targets can be placed in the cavity on the pinch axis due to the large length of the liner.
Optimized Fock space in the large N limit of quartic interactions in Matrix Models
Hynek, Mariusz
2015-01-01
We consider the problem of quantization of the bosonic membrane via the large $N$ limit of its matrix regularizations $H_N$ in Fock space. We prove that there exists a choice of the Fock space frequency such that $ H_N$ can be written as a sum of a non-interacting Hamiltonian $H_{0,N}$ and the original normal ordered quartic potential. Using this decomposition we obtain upper and lower bounds for the ground state energy, we study a perturbative expansion about the spectrum of $H_{0,N}$, and show that the spectral gap remains finite at $N=\\infty$ at least up to the second order. We also apply the method to a toy model, the $U(N)$-invariant anharmonic oscillator, and compare our bounds with the exact values.
Modeling and Optimization of Direct Chill Casting to Reduce Ingot Cracking
Das, S.K.; Ningileri, S.; Long, Z.; Saito, K.; Khraisheh, M.; Hassan, M.H.; Kuwana, K.; Han, Q.; Viswanathan, S.; Sabau, A.S.; Clark, J.; Hyrn, J. (ANL)
2006-08-15
Approximately 68% of the aluminum produced in the United States is first cast into ingots prior to further processing into sheet, plate, extrusions, or foil. The direct chill (DC) semi-continuous casting process has been the mainstay of the aluminum industry for the production of ingots due largely to its robust nature and relative simplicity. Though the basic process of DC casting is in principle straightforward, the interaction of process parameters with heat extraction, microstructural evolution, and development of solidification stresses is too complex to analyze by intuition or practical experience. One issue in DC casting is the formation of stress cracks [1-15]. In particular, the move toward larger ingot cross-sections, the use of higher casting speeds, and an ever-increasing array of mold technologies have increased industry efficiencies but have made it more difficult to predict the occurrence of stress crack defects. The Aluminum Industry Technology Roadmap [16] has recognized the challenges inherent in the DC casting process and the control of stress cracks and selected the development of 'fundamental information on solidification of alloys to predict microstructure, surface properties, and stresses and strains' as a high-priority research need, and the 'lack of understanding of mechanisms of cracking as a function of alloy' and 'insufficient understanding of the aluminum solidification process', which is 'difficult to model', as technology barriers in aluminum casting processes. The goal of this Aluminum Industry of the Future (IOF) project was to assist the aluminum industry in reducing the incidence of stress cracks from the current level of 5% to 2%. Decreasing stress crack incidence is important for improving product quality and consistency as well as for saving resources and energy, since considerable amounts of cast metal could be saved by eliminating ingot cracking, by reducing the scalping thickness of the ingot before rolling, and by eliminating butt sawing. Full-scale industrial implementation of the results of the proposed research would lead to energy savings in excess of 6 trillion Btu by the year 2020. The research undertaken in this project aimed to achieve this objective by a collaboration of industry, university, and national laboratory personnel through Secat, Inc., a consortium of aluminum companies. During the four-year project, the industrial partners and the research team met in 16 quarterly meetings to discuss research results and research direction. The industrial partners provided guidance, facilities, and experience to the research team. The research team went to two industrial plants to measure temperature distributions in commercial 60,000-lb DC casting ingot production. The project focused on the development of a fundamental understanding of ingot cracking and detailed models of thermal conditions, solidification, microstructural evolution, and stress development during the initial transient in DC castings of the aluminum alloys 3004 and 5182. The microstructure of the DC casting ingots was systematically characterized. Carefully designed experiments were carried out at the national laboratory and university facilities as well as at the industrial locations using the industrial production facilities. The advanced computational capabilities of the national laboratories were used for thermodynamic and kinetic simulations of phase transformation, heat transfer and fluid flow, solidification, and stress-strain evolution during DC casting. The achievements of the project are the following: (1) Identified the nature of crack formation during DC casting; (2) Developed a novel method for determining the mechanical properties of an alloy at the nonequilibrium mushy zone of the alloy; (3) Measured heat transfer coefficients (HTCs) between the solidifying ingot and the cooling water jet; (4) Determined the material constitutive model at high temperatures; and (5) Developed computational capabilities for the simulation of cracking formation in DC casting ingot. The models and the database de
Nielsen, Finn Ã?rup
Canonical Ridge Analysis with Ridge Parameter Optimization F. Ã?. Nielsen, L. K. Hansen and S. C - PLS 1 = k 0 = k optimal k k = optimal k k Â£ Â£ 0 #12; Canonical Ridge Analysis with Ridge Parameter Optimization F. Ã?. Nielsen, L. K. Hansen and S. C. Strother The Human Brain Project, P20 MH57180 ``Spatial
Vlcek, Lukas [ORNL; Chialvo, Ariel A [ORNL; Cole, David [Ohio State University; Cole, David R [ORNL
2011-01-01
The unlike- pair interaction parameters for the SPC/E- EPM2 models have been optimized to reproduce the mutual solubility of water and carbon dioxide at the conditions of liquid- supercritical fluid phase equilibria. An efficient global optimization of the parameters is achieved through an implementation of the coupling parameter approach, adapted to phase equilibria calculations in the Gibbs ensemble, that explicitly corrects for the over- polarization of the SPC/E water molecule in the non- polar CO2 environments. The resulting H2O- CO2 force field reproduces accurately the available experimental solubilities at the two fluid phases in equilibria as well as the corresponding species tracer diffusion coefficients.
Brigantic, Robert T.; Papatyi, Anthony F.; Perkins, Casey J.
2010-09-30
This report summarizes a study and corresponding model development conducted in support of the United States Pacific Command (USPACOM) as part of the Federal Energy Management Program (FEMP) American Reinvestment and Recovery Act (ARRA). This research was aimed at developing a mathematical programming framework and accompanying optimization methodology in order to simultaneously evaluate energy efficiency (EE) and renewable energy (RE) opportunities. Once developed, this research then demonstrated this methodology at a USPACOM installation - Camp H.M. Smith, Hawaii. We believe this is the first time such an integrated, joint EE and RE optimization methodology has been constructed and demonstrated.
Optimization of Fuel Cell System Operating Conditions for Fuel Cell Vehicles
Zhao, Hengbing; Burke, Andy
2008-01-01
R.M. Moore, PEM Fuel Cell System Optimization, ProceedingsInterface of the fuel cell system optimization model Fig. 5hydrogen fuel cell vehicle; optimization model; simulation *
Control and optimization system
Xinsheng, Lou
2013-02-12
A system for optimizing a power plant includes a chemical loop having an input for receiving an input parameter (270) and an output for outputting an output parameter (280), a control system operably connected to the chemical loop and having a multiple controller part (230) comprising a model-free controller. The control system receives the output parameter (280), optimizes the input parameter (270) based on the received output parameter (280), and outputs an optimized input parameter (270) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.
Optimal smoothing length scale for actuator line models of lifting surfaces
Martinez-Tossas, Luis A
2015-01-01
The actuator line model (ALM) is a commonly used method to represent lifting surfaces such as wind turbine blades within Large-Eddy Simulations (LES). In ALM the lift and drag forces are replaced by an imposed body force which is typically smoothed over several grid points using a Gaussian kernel with some prescribed smoothing width $\\epsilon$. To date, the choice of $\\epsilon$ has most often been based on numerical considerations mostly related to the grid spacing used in LES. However, especially for finely resolved LES with grid spacings on the order or smaller than the chord-length of the blade, the best choice of $\\epsilon$ is not known. Focusing first on the lift force, here we find $\\epsilon$ and the force center location that minimize the square difference between the velocity fields obtained from solving 2D potential flow over Joukowski airfoils and solving the Euler equations including the imposed body force. The latter solution is found for the linearized problem, and is valid for small angles of at...
Wang, S L; Singer, M A
2009-07-13
The purpose of this report is to evaluate the hemodynamic effects of renal vein inflow and filter position on unoccluded and partially occluded IVC filters using three-dimensional computational fluid dynamics. Three-dimensional models of the TrapEase and Gunther Celect IVC filters, spherical thrombi, and an IVC with renal veins were constructed. Hemodynamics of steady-state flow was examined for unoccluded and partially occluded TrapEase and Gunther Celect IVC filters in varying proximity to the renal veins. Flow past the unoccluded filters demonstrated minimal disruption. Natural regions of stagnant/recirculating flow in the IVC are observed superior to the bilateral renal vein inflows, and high flow velocities and elevated shear stresses are observed in the vicinity of renal inflow. Spherical thrombi induce stagnant and/or recirculating flow downstream of the thrombus. Placement of the TrapEase filter in the suprarenal vein position resulted in a large area of low shear stress/stagnant flow within the filter just downstream of thrombus trapped in the upstream trapping position. Filter position with respect to renal vein inflow influences the hemodynamics of filter trapping. Placement of the TrapEase filter in a suprarenal location may be thrombogenic with redundant areas of stagnant/recirculating flow and low shear stress along the caval wall due to the upstream trapping position and the naturally occurring region of stagnant flow from the renal veins. Infrarenal vein placement of IVC filters in a near juxtarenal position with the downstream cone near the renal vein inflow likely confers increased levels of mechanical lysis of trapped thrombi due to increased shear stress from renal vein inflow.
Gonzalez-Horta, Francisco A; Ramirez-Cortes, Juan M; Martinez-Carballido, Jorge; Buenfil-Alpuche, Eldamira
2011-01-01
Performance curves of queueing systems can be analyzed by separating them into three regions: the flat region, the knee region, and the exponential region. Practical considerations, usually locate the knee region between 70-90% of the theoretical maximum utilization. However, there is not a clear agreement about where the boundaries between regions are, and where exactly the utilization knee is located. An open debate about knees in performance curves was undertaken at least 20 years ago. This historical debate is mainly divided between those who claim that a knee in the curve is not a well defined term in mathematics, or it is a subjective and not really meaningful concept, and those who define knees mathematically and consider their relevance and application. In this paper, we present a mathematical model and analysis for identifying the three mentioned regions on performance curves for M/M/1 systems; specifically, we found the knees, or optimal utilization percentiles, at the vertices of the hyperbolas tha...
Laura Sampson; Neil Cornish; Nicolas Yunes
2013-03-05
We study generic tests of strong-field General Relativity using gravitational waves emitted during the inspiral of compact binaries. Previous studies have considered simple extensions to the standard post-Newtonian waveforms that differ by a single term in the phase. Here we improve on these studies by (i) increasing the realism of injections and (ii) determining the optimal waveform families for detecting and characterizing such signals. We construct waveforms that deviate from those in General Relativity through a series of post-Newtonian terms, and find that these higher-order terms can affect our ability to test General Relativity, in some cases by making it easier to detect a deviation, and in some cases by making it more difficult. We find that simple single-phase post-Einsteinian waveforms are sufficient for detecting deviations from General Relativity, and there is little to be gained from using more complicated models with multiple phase terms. The results found here will help guide future attempts to test General Relativity with advanced ground-based detectors.
A Jackson Network Model and Threshold Policy for Joint Optimization of Energy and Delay in Multi-Hop
Shihada, Basem
of energy and delay in a multi- hop wireless network. The optimization variables are the transmission rates, transmit with the maximal rate (power); otherwise, no transmission. With these optimality properties of wireless networks since most of the mobile end users are powered by battery (Montemanni et al., 2008
Communication Optimization for Customizable Domain-Specific Computing
Xiao, Bingjun
2015-01-01
Optimization . . . . . . . . . . . . . . . . . . . . .Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . .176 Communication Optimization
Convex and Nonsmooth Optimization Submissions - 2012. January 2012. Nonsmooth Optimization Necessary optimality conditions in pessimistic bilevel ...
Optimization related societies. Mathematical Optimization Society · SIAM · INFORMS. Optimization related journals. Mathematical Programming and ...
Wang, Haoqing
2015-01-01
Optimization . . . . . . . . . . . . . . . . .annotation optimization . . . . . . . . . . . . . . . . .Opt. is the time after optimization. Anno- phos is the time
Ortiz Prada, Rubiel Paul
2012-02-14
Optimizing well spacing in unconventional gas reservoirs is difficult due to complex heterogeneity, large variability and uncertainty in reservoir properties, and lack of data that increase the production uncertainty. Previous methods are either...
Venkataramani, Arun
) of the system. What is the utility function corresponding to a max-min fair allocation? What is the utility function corresponding to a TCP-fair allocation? To understand this, we formalize the resource allocation with a model for the following resource allocation problem: Given a network and a set of users, (i.e., flows
March-Leuba, S.; Jansen, J.F.; Kress, R.L.; Babcock, S.M. ); Dubey, R.V. . Dept. of Mechanical and Aerospace Engineering)
1992-08-01
A new program package, Symbolic Manipulator Laboratory (SML), for the automatic generation of both kinematic and static manipulator models in symbolic form is presented. Critical design parameters may be identified and optimized using symbolic models as shown in the sample application presented for the Future Armor Rearm System (FARS) arm. The computer-aided development of the symbolic models yields equations with reduced numerical complexity. Important considerations have been placed on the closed form solutions simplification and on the user friendly operation. The main emphasis of this research is the development of a methodology which is implemented in a computer program capable of generating symbolic kinematic and static forces models of manipulators. The fact that the models are obtained trigonometrically reduced is among the most significant results of this work and the most difficult to implement. Mathematica, a commercial program that allows symbolic manipulation, is used to implement the program package. SML is written such that the user can change any of the subroutines or create new ones easily. To assist the user, an on-line help has been written to make of SML a user friendly package. Some sample applications are presented. The design and optimization of the 5-degrees-of-freedom (DOF) FARS manipulator using SML is discussed. Finally, the kinematic and static models of two different 7-DOF manipulators are calculated symbolically.
March-Leuba, S.; Jansen, J.F.; Kress, R.L.; Babcock, S.M.; Dubey, R.V.
1992-08-01
A new program package, Symbolic Manipulator Laboratory (SML), for the automatic generation of both kinematic and static manipulator models in symbolic form is presented. Critical design parameters may be identified and optimized using symbolic models as shown in the sample application presented for the Future Armor Rearm System (FARS) arm. The computer-aided development of the symbolic models yields equations with reduced numerical complexity. Important considerations have been placed on the closed form solutions simplification and on the user friendly operation. The main emphasis of this research is the development of a methodology which is implemented in a computer program capable of generating symbolic kinematic and static forces models of manipulators. The fact that the models are obtained trigonometrically reduced is among the most significant results of this work and the most difficult to implement. Mathematica, a commercial program that allows symbolic manipulation, is used to implement the program package. SML is written such that the user can change any of the subroutines or create new ones easily. To assist the user, an on-line help has been written to make of SML a user friendly package. Some sample applications are presented. The design and optimization of the 5-degrees-of-freedom (DOF) FARS manipulator using SML is discussed. Finally, the kinematic and static models of two different 7-DOF manipulators are calculated symbolically.
Supplementary Material Learning optimal adaptation strategies in unpredictable motor tasks
Supplementary Material Learning optimal adaptation strategies in unpredictable motor tasks D.A. Braun, A. Aertsen, D.M. Wolpert, C. Mehring Contents 1 Adaptive Optimal Control Methods 2 1-adaptive Optimal Control Models . . . . . . . . . . . . . . . . . 5 1.4 Arm Model
Interpolating Optimizing Process Control Bjarne A. Foss
Foss, Bjarne A.
Interpolating Optimizing Process Control Bjarne A. Foss Department of Engineering Cybernetics The University of Texas at Austin qin@che.utexas.edu August 9, 1996 Keywords: Model-based control, optimization a new model-based optimizing controller for a set of nonlinear systems is proposed. The nonlinear model
Optimization Online - Nonlinear Optimization Submissions - 2014
Nonlinear Optimization Submissions - 2014. January 2014. Constrained Nonlinear Optimization New active set identification for general constrained ...
Adilson E. Motter; Zoltan Toroczkai
2007-07-07
The recent surge in the network modeling of complex systems has set the stage for a new era in the study of fundamental and applied aspects of optimization in collective behavior. This Focus Issue presents an extended view of the state of the art in this field and includes articles from a large variety of domains where optimization manifests itself, including physical, biological, social, and technological networked systems.
Preisig, H. A.
1988-01-01
is the surface J(-) of which the optimum is sought. Experience teaches that the optimum of the unconstrained response surface lays often outside the permissible domain which puts the permissible optimal operating point on the boundary which is defined.... The optimizer can thus use the model to predict the steady state and decide on the next move before the process has reached the steady state. ? Identification Scheme Different identification schemes should be used depending on the signal/noise ra tio...
Optimal Real-time Dispatch for Integrated Energy Systems
Firestone, Ryan Michael
2007-01-01
Hybrid Optimization Model for Electric Renewables heating, ventilation, and air conditioning integrated energy system
Optimization of Heat Exchangers
Ivan Catton
2010-10-01
The objective of this research is to develop tools to design and optimize heat exchangers (HE) and compact heat exchangers (CHE) for intermediate loop heat transport systems found in the very high temperature reator (VHTR) and other Generation IV designs by addressing heat transfer surface augmentation and conjugate modeling. To optimize heat exchanger, a fast running model must be created that will allow for multiple designs to be compared quickly. To model a heat exchanger, volume averaging theory, VAT, is used. VAT allows for the conservation of mass, momentum and energy to be solved for point by point in a 3 dimensional computer model of a heat exchanger. The end product of this project is a computer code that can predict an optimal configuration for a heat exchanger given only a few constraints (input fluids, size, cost, etc.). As VAT computer code can be used to model characteristics )pumping power, temperatures, and cost) of heat exchangers more quickly than traditional CFD or experiment, optimization of every geometric parameter simultaneously can be made. Using design of experiment, DOE and genetric algorithms, GE, to optimize the results of the computer code will improve heat exchanger disign.
Optimal Demand Response and Power Flow
Willett, Rebecca
Optimal Demand Response and Power Flow Steven Low Computing + Math Sciences Electrical Engineering #12;Outline Optimal demand response n With L. Chen, L. Jiang, N. Li Optimal power flow n With S. Bose;Optimal demand response Model Results n Uncorrelated demand: distributed alg n Correlated demand
Ryan Babbush; Alejandro Perdomo-Ortiz; Bryan O'Gorman; William Macready; Alán Aspuru-Guzik
2013-06-11
Optimization problems associated with the interaction of linked particles are at the heart of polymer science, protein folding and other important problems in the physical sciences. In this review we explain how to recast these problems as constraint satisfaction problems such as linear programming, maximum satisfiability, and pseudo-boolean optimization. By encoding problems this way, one can leverage substantial insight and powerful solvers from the computer science community which studies constraint programming for diverse applications such as logistics, scheduling, artificial intelligence, and circuit design. We demonstrate how to constrain and embed lattice heteropolymer problems using several strategies. Each strikes a unique balance between number of constraints, complexity of constraints, and number of variables. Finally, we show how to reduce the locality of couplings in these energy functions so they can be realized as Hamiltonians on existing quantum annealing machines. We intend that this review be used as a case study for encoding related combinatorial optimization problems in a form suitable for adiabatic quantum optimization.
Armen E. Allahverdyan; Karen Hovhannisyan; Guenter Mahler
2010-07-25
We study a refrigerator model which consists of two $n$-level systems interacting via a pulsed external field. Each system couples to its own thermal bath at temperatures $T_h$ and $T_c$, respectively ($\\theta\\equiv T_c/T_hisolated interaction between the systems driven by the external field and isothermal relaxation back to equilibrium. There is a complementarity between the power of heat transfer from the cold bath and the efficiency: the latter nullifies when the former is maximized and {\\it vice versa}. A reasonable compromise is achieved by optimizing the product of the heat-power and efficiency over the Hamiltonian of the two system. The efficiency is then found to be bounded from below by $\\zeta_{\\rm CA}=\\frac{1}{\\sqrt{1-\\theta}}-1$ (an analogue of the Curzon-Ahlborn efficiency), besides being bound from above by the Carnot efficiency $\\zeta_{\\rm C} = \\frac{1}{1-\\theta}-1$. The lower bound is reached in the equilibrium limit $\\theta\\to 1$. The Carnot bound is reached (for a finite power and a finite amount of heat transferred per cycle) for $\\ln n\\gg 1$. If the above maximization is constrained by assuming homogeneous energy spectra for both systems, the efficiency is bounded from above by $\\zeta_{\\rm CA}$ and converges to it for $n\\gg 1$.
Brown, Matt
2013-01-01
Optimizations . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24 and 26. APPENDIX B Optimizations Included in thisappendix are the three optimization steps which together
Nuclear Energy Density Optimization
M. Kortelainen; T. Lesinski; J. Moré; W. Nazarewicz; J. Sarich; N. Schunck; M. V. Stoitsov; S. Wild
2010-05-27
We carry out state-of-the-art optimization of a nuclear energy density of Skyrme type in the framework of the Hartree-Fock-Bogoliubov (HFB) theory. The particle-hole and particle-particle channels are optimized simultaneously, and the experimental data set includes both spherical and deformed nuclei. The new model-based, derivative-free optimization algorithm used in this work has been found to be significantly better than standard optimization methods in terms of reliability, speed, accuracy, and precision. The resulting parameter set UNEDFpre results in good agreement with experimental masses, radii, and deformations and seems to be free of finite-size instabilities. An estimate of the reliability of the obtained parameterization is given, based on standard statistical methods. We discuss new physics insights offered by the advanced covariance analysis.
Preston, Jill C.; Barnett, Laryssa L.; Kost, Matthew A.; Oborny, Nathan J.; Hileman, Lena C.
2014-05-01
OPTIMIZATION OF VIRUS- Jill C. Preston,2 Laryssa L. Barnett,2,3 INDUCED GENE SILENCING TO Matthew A. Kost,2,4 Nathan J. Oborny,2,5 and Lena C. HilemanFACILITATE EVO-DEVO STUDIES 2,6 IN THE EMERGING MODEL SPECIES MIMULUS GUTTATUS (PHRYMACEAE)1... is evident in the young, but genetically diverse, Mimulus guttatus for evolutionary developmental species complex M. guttatus DC. (yellow monkey- genetic (‘‘evo-devo’’) studies requires transformation- flower) (Kelly & Willis, 1998; Sweigart & Willis, al...
AN INTERIOR-POINT METHOD FOR NONLINEAR OPTIMIZATION ...
2014-10-23
ear and nonsmooth optimization, Classification of optimization models, Gas network ...... The first part presents results on a small test library of low-
Optimizing Blast Furnace Operation to Increase Efficiency and...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Optimizing Blast Furnace Operation to Increase Efficiency and Lower Costs State-of-the-Art Computational Fluid Dynamics Model Optimizes Fuel Rate in Blast Furnaces The blast...
FEMP Completes 2000th Renewable Energy Optimization Screening...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Completes 2000th Renewable Energy Optimization Screening FEMP Completes 2000th Renewable Energy Optimization Screening July 23, 2015 - 12:03pm Addthis REopt models the complex...
Robust optimization based self scheduling of hydro-thermal Genco ...
Dec 29, 2013 ... Abstract: This paper proposes a robust optimization model for optimal self scheduling of a hydro-thermal generating company. The proposed ...
Fuel Efficiency and Emissions Optimization of Heavy-Duty Diesel...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
and Emissions Optimization of Heavy-Duty Diesel Engines using Model-Based Transient Calibration Fuel Efficiency and Emissions Optimization of Heavy-Duty Diesel Engines using...
Lunds Universitet
Alignments for the IBM-3 Translation Model Thomas Schoenemann Centre for Mathematical Sciences Lund University, Sweden Abstract Prior work on training the IBM-3 transla- tion model is based on suboptimal meth from a statistical viewpoint and introduced five probability models, known as IBM 1-5. Their models
dominic
2013-03-26
Lesson 30. Optimization (I). 1. A woman wants to build a rectangular garden next to a straight river. She will enclose the garden on 3 sides with fencing—the ...
Fuzzy logic controller optimization
Sepe, Jr., Raymond B; Miller, John Michael
2004-03-23
A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.
Liu, M.; Claridge, D. E.
1998-01-01
is the air flow rate, and cfr&, is the designed air flow rate. In the base cases, the cold deck temperature is 55°F regardless of the ambient temperature. The hot deck temperature varies from 1 10°F to 75°F when the ambient temperature increases from 40...°F to 75OF. When the ambient temperature is lower than 40°F, the hot deck temperature remains at 1 10°F. Figure 5: Cold and Hot Deck Temperature Versus the Ambient Temperature for Base Case or Normal VAV System The optimal cold and hot deck...
Optimization Online - Nonlinear Optimization Submissions - 2013
Nonlinear Optimization Submissions - 2013. January 2013. A Framework of Constraint Preserving Update Schemes for Optimization on Stiefel Manifold
Optimization Online - Nonlinear Optimization Submissions - 2012
Nonlinear Optimization Submissions - 2012. January 2012. Systems governed by Differential Equations Optimization Squeeze-and-Breathe Evolutionary Monte ...
Heat pump simulation model and optimal variable-speed control for a wide range of cooling conditions
Zakula, Tea
2010-01-01
The steady-state air-to-air heat pump model presented in this thesis was developed from the first principles. The main objective was to develop a heat pump model that can be used as a part of larger simulation models, and ...
Vanderbei, Robert J., E-mail: rvdb@princeton.edu [Princeton University, Department of Operations Research and Financial Engineering (United States); P Latin-Small-Letter-Dotless-I nar, Mustafa C., E-mail: mustafap@bilkent.edu.tr [Bilkent University, Department of Industrial Engineering (Turkey); Bozkaya, Efe B. [Sabanc Latin-Small-Letter-Dotless-I University, Faculty of Administrative Sciences (Turkey)] [Sabanc Latin-Small-Letter-Dotless-I University, Faculty of Administrative Sciences (Turkey)
2013-02-15
An American option (or, warrant) is the right, but not the obligation, to purchase or sell an underlying equity at any time up to a predetermined expiration date for a predetermined amount. A perpetual American option differs from a plain American option in that it does not expire. In this study, we solve the optimal stopping problem of a perpetual American option (both call and put) in discrete time using linear programming duality. Under the assumption that the underlying stock price follows a discrete time and discrete state Markov process, namely a geometric random walk, we formulate the pricing problem as an infinite dimensional linear programming (LP) problem using the excessive-majorant property of the value function. This formulation allows us to solve complementary slackness conditions in closed-form, revealing an optimal stopping strategy which highlights the set of stock-prices where the option should be exercised. The analysis for the call option reveals that such a critical value exists only in some cases, depending on a combination of state-transition probabilities and the economic discount factor (i.e., the prevailing interest rate) whereas it ceases to be an issue for the put.
Nelson, R.A. Jr.; Pimentel, D.A.; Jolly-Woodruff, S.; Spore, J.
1998-04-01
In this report, a phenomenological model of simultaneous bottom-up and top-down quenching is developed and discussed. The model was implemented in the TRAC-PF1/MOD2 computer code. Two sets of closure relationships were compared within the study, the Absolute set and the Conditional set. The Absolute set of correlations is frequently viewed as the pure set because the correlations is frequently viewed as the pure set because the correlations utilize their original coefficients as suggested by the developer. The Conditional set is a modified set of correlations with changes to the correlation coefficient only. Results for these two sets indicate quite similar results. This report also summarizes initial results of an effort to investigate nonlinear optimization techniques applied to the closure model development. Results suggest that such techniques can provide advantages for future model development work, but that extensive expertise is required to utilize such techniques (i.e., the model developer must fully understand both the physics of the process being represented and the computational techniques being employed). The computer may then be used to improve the correlation of computational results with experiments.
Convex and Nonsmooth Optimization Submissions - 2014. January 2014. Convex Optimization Generalized Gauss Inequalities via Semidefinite Programming
Carver Performance and Optimization
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
Optimization Performance and Optimization Performance Monitoring Last edited: 2012-01-09 12:31:03...
Deshpande, Vighnesh Prakash
2009-05-15
............................................................................. 10 2.1.1 Modeling Component Level Demand and Capacity ........... 10 2.1.1.1 Fatigue Cracking ................................................. 11 2.1.1.2 Rutting ................................................................ 11 2.1.1.3 Pavement... ............................................................................ 44 3.3.1 Pavement Response Model for Critical Tensile Strain ....... 46 3.3.2 Fragility Model for Fatigue Cracking Failure ..................... 47 3.3.2.1 Before Rehabilitation Actions (Three-layer System...
EU PVSEC, 4AV.3.8 A MODELING APPROACH TO THE OPTIMIZATION OF INTERCONNECTS FOR BACK CONTACT CELLS
down to -40°C. In a second step we add the interconnectors in a 2-dimensional geometry which the 3 soldered areas to depend significantly on the specific interconnector design. The model presented plain-stress modeling of the interconnector allows fast and easy modifications of the interconnector
Arefinia, Zahra [Research Institute for Applied Physics and Astronomy, University of Tabriz, Tabriz 51666-14766 (Iran, Islamic Republic of); Asgari, Asghar, E-mail: asgari@tabrizu.ac.ir [Research Institute for Applied Physics and Astronomy, University of Tabriz, Tabriz 51666-14766 (Iran, Islamic Republic of); School of Electrical, Electronic, and Computer Engineering, University of Western Australia, Crawley, WA 6009 (Australia)
2014-05-21
Based on the ability of In{sub x}Ga{sub 1?x}N materials to optimally span the solar spectrum and their superior radiation resistance, solar cells based on p-type In{sub x}Ga{sub 1?x}N with low indium contents and interfacing with graphene film (G/In{sub x}Ga{sub 1?x}N), is proposed to exploit the benefit of transparency and work function tunability of graphene. Then, their solar power conversion efficiency modeled and optimized using a new analytical approach taking into account all recombination processes and accurate carrier mobility. Furthermore, their performance was compared with graphene on silicon counterparts and G/p-In{sub x}Ga{sub 1?x}N showed relatively smaller short-circuits current (?7?mA/cm{sup 2}) and significantly higher open-circuit voltage (?4?V) and efficiency (?30%). The thickness, doping concentration, and indium contents of p-In{sub x}Ga{sub 1?x}N and graphene work function were found to substantially affect the performance of G/p-In{sub x}Ga{sub 1?x}N.
Optimizing Profits from Hydroelectricity Production
Leclercq, Remi
Optimizing Profits from Hydroelectricity Production Daniel De Ladurantaye Michel Gendreau Jean the profits obtained by the stochastic model. Keywords: Hydroelectricity, electricity market, prices, dams countries deregulate their electricity market, new challenges appear for hydroelectricity producers
Using Process Data for Finding Self-optimizing Controlled Variables
Skogestad, Sigurd
Using Process Data for Finding Self-optimizing Controlled Variables Johannes J¨aschke and Sigurd the process gain. It does not require a model which is optimized off-line to find the controlled variable. Keywords: Process Optimization, Control, Partial least squares, Empirical modelling, Self-optimizing
Miller, Travis Reed
2010-01-01
This work aimed to inform the design of ceramic pot filters to be manufactured by the organization Pure Home Water (PHW) in Northern Ghana, and to model the flow through an innovative paraboloid-shaped ceramic pot filter. ...
Krstic, Miroslav
stochastic behavior · Scaled for medium size office or apartment complex [1] California ISO: System Status Power Generation Automated Modeling Laboratory Slide 6 of 28 BATTERY COMPRESSOR H2 STORAGE TANK SUPPLY
Millstone, Rachel Diana
2010-01-01
a piece of heavy duty styrofoam. Everybody listen up. It’sone you are writing the Styrofoam pink. Second, write foam.surface (models). I wish the styrofoam was larger. It’s not.
, TEXAS COUNTY, OKLAHOMA by Tiffany Dawn Jobe #12;#12;ABSTRACT Reservoir characterization, modeling Field is a mature oil and gas field in Texas County, Oklahoma which produces from Pennsylvanian valley
Kanta, Lufthansa Rahman
2011-02-22
) minimizing the cost of mitigation. Third, a stochastic modeling approach is developed to assess urban fire risk for the coupled water distribution and fire response systems that includes probabilistic expressions for building ignition, WDS failure, and wind...
ONLINE OPTIMIZATION AND SELECTION OF MEASUREMENTS
Skogestad, Sigurd
117 Chapter 7 ONLINE OPTIMIZATION AND SELECTION OF MEASUREMENTS This is the last of three chapters that discuss optimal operation of a general heat exchanger network. A method that combines the use of steady state optimization and decentralized feedback control is proposed. A general steady state model
CASCADE OPTIMIZATION AND CONTROL OF BATCH REACTORS
Jutan, Arthur
CASCADE OPTIMIZATION AND CONTROL OF BATCH REACTORS Xiangming Hua, Sohrab Rohani and Arthur Jutan ajutan@uwo.ca Abstract: In this study, a cascade closed-loop optimization and control strategy for batch reactor. Using model reduction a cascade system is developed, which can effectively combine optimization
Interconnection networks synthesis and optimization
Zhu, Yi
2008-01-01
Synthesis and Optimization . . . . . . . . . . .1.Wire Style Optimization . . . . . . . . . . . . . B. PowerSynthesis and Optimization . 1. Overview . . . . . . . . . .
Michael Harold; Vemuri Balakotaiah
2010-05-31
In this project a combined experimental and theoretical approach was taken to advance our understanding of lean NOx trap (LNT) technology. Fundamental kinetics studies were carried out of model LNT catalysts containing variable loadings of precious metals (Pt, Rh), and storage components (BaO, CeO{sub 2}). The Temporal Analysis of Products (TAP) reactor provided transient data under well-characterized conditions for both powder and monolith catalysts, enabling the identification of key reaction pathways and estimation of the corresponding kinetic parameters. The performance of model NOx storage and reduction (NSR) monolith catalysts were evaluated in a bench scale NOx trap using synthetic exhaust, with attention placed on the effect of the pulse timing and composition on the instantaneous and cycle-averaged product distributions. From these experiments we formulated a global model that predicts the main spatio-temporal features of the LNT and a mechanistic-based microkinetic models that incorporates a detailed understanding of the chemistry and predicts more detailed selectivity features of the LNT. The NOx trap models were used to determine its ability to simulate bench-scale data and ultimately to evaluate alternative LNT designs and operating strategies. The four-year project led to the training of several doctoral students and the dissemination of the findings as 47 presentations in conferences, catalysis societies, and academic departments as well 23 manuscripts in peer-reviewed journals. A condensed review of NOx storage and reduction was published in an encyclopedia of technology.
Kohut, Sviataslau V.; Staroverov, Viktor N.; Ryabinkin, Ilya G.
2014-05-14
We describe a method for constructing a hierarchy of model potentials approximating the functional derivative of a given orbital-dependent exchange-correlation functional with respect to electron density. Each model is derived by assuming a particular relationship between the self-consistent solutions of Kohn–Sham (KS) and generalized Kohn–Sham (GKS) equations for the same functional. In the KS scheme, the functional is differentiated with respect to density, in the GKS scheme—with respect to orbitals. The lowest-level approximation is the orbital-averaged effective potential (OAEP) built with the GKS orbitals. The second-level approximation, termed the orbital-consistent effective potential (OCEP), is based on the assumption that the KS and GKS orbitals are the same. It has the form of the OAEP plus a correction term. The highest-level approximation is the density-consistent effective potential (DCEP), derived under the assumption that the KS and GKS electron densities are equal. The analytic expression for a DCEP is the OCEP formula augmented with kinetic-energy-density-dependent terms. In the case of exact-exchange functional, the OAEP is the Slater potential, the OCEP is roughly equivalent to the localized Hartree–Fock approximation and related models, and the DCEP is practically indistinguishable from the true optimized effective potential for exact exchange. All three levels of the proposed hierarchy require solutions of the GKS equations as input and have the same affordable computational cost.
Authors, Various
2012-01-01
3 1st Edition FTN4 OPTIMIZATION TECHNIQUES November 1979O. INTRODUCTION 1. COt1PILER OPTIMIZATIONS 2. SOURCE CODEcode. Most of these optimizations decrease central processor
Optimization Online - All Areas Submissions - November 2013
Variational analysis in psychological modeling T.Q. Bao ... Derivative-free Robust Optimization for Circuit Design ... Linear, Cone and Semidefinite Programming
Chandy, K. Mani
time periods. The model is motivated by the intensifying trend to deploy renewable energy such as wind and Huan Xu Abstract-- The integration of renewable energy, such as wind power, into the electric grid from wind projects in the Tehachapi area in California [9]. Not only is renewable energy more
deYoung, Brad
modelling, catchability, fish eggs, sampling, survey design, uncertainty, vertical distribution. Received 28 an absolute measure of abundance, because gear avoidance is non-existent and the reten- tion efficiency of plankton nets can be estimated precisely (Lo, 1985). However, survey design and precision represent key
Paris-Sud XI, Université de
technologies emerged. The manufacturing by layers keeps a common characteristic and the additive manufacturing approach applied to additive manufacturing and a specific machine. We suggest to use the numerical model manufactured by rapid prototyping A. SCHNEIDER a , J. GARDAN b , N. GARDAN c a. URCA/IFTS NUM3D
On the Single-Zone Modeling for Optimal Climate Control of a Real-Sized Livestock Stable System
Yang, Zhenyu
. As a typical modern and large-sized stable system, the considered stable uses hybrid ventilation and low described. The models for air inlets, outlets and their driving systems as well as the heating systems, one climate control systems. A typical modern stable system is usually equipped with a hybrid ventilation [3
Istrail, Sorin
Lattice and Off-Lattice Side Chain Models of Protein Folding: Linear Time Structure Prediction This paper considers the protein structure prediction problem for lattice and off-lattice protein folding tools for reasoning about protein folding in unrestricted continuous space through anal- ogy. This paper
Moro, Erik A.
2012-06-07
Optical fiber sensors offer advantages over traditional electromechanical sensors, making them particularly well-suited for certain measurement applications. Generally speaking, optical fiber sensors respond to a desired measurand through modulation of an optical signal's intensity, phase, or wavelength. Practically, non-contacting fiber optic displacement sensors are limited to intensity-modulated and interferometric (or phase-modulated) methodologies. Intensity-modulated fiber optic displacement sensors relate target displacement to a power measurement. The simplest intensity-modulated sensor architectures are not robust to environmental and hardware fluctuations, since such variability may cause changes in the measured power level that falsely indicate target displacement. Differential intensity-modulated sensors have been implemented, offering robustness to such intensity fluctuations, and the speed of these sensors is limited only by the combined speed of the photodetection hardware and the data acquisition system (kHz-MHz). The primary disadvantages of intensity-modulated sensing are the relatively low accuracy (?m-mm for low-power sensors) and the lack of robustness, which consequently must be designed, often with great difficulty, into the sensor's architecture. White light interferometric displacement sensors, on the other hand, offer increased accuracy and robustness. Unlike their monochromatic-interferometer counterparts, white light interferometric sensors offer absolute, unambiguous displacement measurements over large displacement ranges (cm for low-power, 5 mW, sources), necessitating no initial calibration, and requiring no environmental or feedback control. The primary disadvantage of white light interferometric displacement sensors is that their utility in dynamic testing scenarios is limited, both by hardware bandwidth and by their inherent high-sensitivity to Doppler-effects. The decision of whether to use either an intensity-modulated interferometric sensor depends on an appropriate performance function (e.g., desired displacement range, accuracy, robustness, etc.). In this dissertation, the performance limitations of a bundled differential intensity-modulated displacement sensor are analyzed, where the bundling configuration has been designed to optimize performance. The performance limitations of a white light Fabry-Perot displacement sensor are also analyzed. Both these sensors are non-contacting, but they have access to different regions of the performance-space. Further, both these sensors have different degrees of sensitivity to experimental uncertainty. Made in conjunction with careful analysis, the decision of which sensor to deploy need not be an uninformed one.
Optimization Online - Nonlinear Optimization Submissions - 2015
Nonlinear Optimization Submissions - 2015. January 2015. On iteratively reweighted Algorithms for Non-smooth Non-convex Optimization in Computer Vision
Advanced Review Geometry optimization
Schlegel, H. Bernhard
Advanced Review Geometry optimization H. Bernhard Schlegel Geometry optimization is an important part of most quantum chemical calcu- lations. This article surveys methods for optimizing equilibrium geometries, lo- cating transition structures, and following reaction paths. The emphasis is on optimizations
Jodice, Patrick
Optimization Jason Courter Foundations of Ecology #12;What is optimization? Maximization Minimization Optimization Natural Selection 1. Variation 2. Heritable Variation 3. Differential Reproduction #12;On Optimal use of a Patchy Environment · Robert MacArthur · Eric Pianka http
[SIAM conference on optimization
Not Available
1992-05-10
Abstracts are presented of 63 papers on the following topics: large-scale optimization, interior-point methods, algorithms for optimization, problems in control, network optimization methods, and parallel algorithms for optimization problems.
Optimization Online - Coordinators
Optimization Online Coordinators. Optimization Online submissions are electronically handled by a team of volunteer coordinators: Principal Coordinators.
Convex and Nonsmooth Optimization Submissions - 2001. January 2001. Convex Optimization Two properties of condition numbers for convex programs via ...
Authors, Various
2012-01-01
OPTIMIZATION When OPT=2 is specified on the FTN control statement, the compiler optimizes the user code in the process
Lovley, Derek R
2012-12-28
The goal of this research was to provide computational tools to predictively model the behavior of two microbial communities of direct relevance to Department of Energy interests: 1) the microbial community responsible for in situ bioremediation of uranium in contaminated subsurface environments; and 2) the microbial community capable of harvesting electricity from waste organic matter and renewable biomass. During this project the concept of microbial electrosynthesis, a novel form of artificial photosynthesis for the direct production of fuels and other organic commodities from carbon dioxide and water was also developed and research was expanded into this area as well.
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Matlab-based Optimization: Optimization Toolbox
Crawford, T. Daniel
Matlab-based Optimization: the Optimization Toolbox Gene Cliff (AOE/ICAM - ecliff@vt.edu ) 3:00pm Engineering ICAM: Interdisciplinary Center for Applied Mathematics 1 / 37 #12;Matlab's Optimization Toolbox Classifying Optimization Problems A Soup Can Example Intermezzo A Trajectory Example 2nd Trajectory Example
Optimal segmentation and packaging process
Kostelnik, Kevin M. (Idaho Falls, ID); Meservey, Richard H. (Idaho Falls, ID); Landon, Mark D. (Idaho Falls, ID)
1999-01-01
A process for improving packaging efficiency uses three dimensional, computer simulated models with various optimization algorithms to determine the optimal segmentation process and packaging configurations based on constraints including container limitations. The present invention is applied to a process for decontaminating, decommissioning (D&D), and remediating a nuclear facility involving the segmentation and packaging of contaminated items in waste containers in order to minimize the number of cuts, maximize packaging density, and reduce worker radiation exposure. A three-dimensional, computer simulated, facility model of the contaminated items are created. The contaminated items are differentiated. The optimal location, orientation and sequence of the segmentation and packaging of the contaminated items is determined using the simulated model, the algorithms, and various constraints including container limitations. The cut locations and orientations are transposed to the simulated model. The contaminated items are actually segmented and packaged. The segmentation and packaging may be simulated beforehand. In addition, the contaminated items may be cataloged and recorded.
Thomas, Dennis G.; Jaramillo Riveri, Sebastian I.; Baxter, Douglas J.; Cannon, William R.
2014-12-15
We have applied a new stochastic simulation approach to predict the metabolite levels, energy flow, and material flux in the different oxidative TCA cycles found in E. coli and Synechococcus sp. PCC 7002, and in the reductive TCA cycle typical of chemolithoautotrophs and phototrophic green sulfur bacteria such as Chlorobaculum tepidum. The simulation approach is based on equations of state and employs an assumption similar to that used in transition state theory. The ability to evaluate the thermodynamics of metabolic pathways allows one to understand the relationship between coupling of energy and material gradients in the environment and the selforganization of stable biological systems, and it is shown that each cycle operates in the direction expected due to its environmental niche. The simulations predict changes in metabolite levels and flux in response to changes in cofactor concentrations that would be hard to predict without an elaborate model based on the law of mass action. In fact, we show that a thermodynamically unfavorable reaction can still have flux in the forward direction when it is part of a reaction network. The ability to predict metabolite levels, energy flow and material flux should be significant for understanding the dynamics of natural systems and for understanding principles for engineering organisms for production of specialty chemicals, such as biofuels.
Online optimization and choice of optimization variables for control of heat exchanger networks
Skogestad, Sigurd
Online optimization and choice of optimization variables for control of heat exchanger networks B operation of a general heat exchanger network with given structure, heat exchanger areas and stream data to any heat exchanger network. Using this model periodically for optimization, the operating conditions
On-line optimization and choice of optimization variables for control of heat exchanger networks
Skogestad, Sigurd
On-line optimization and choice of optimization variables for control of heat exchanger networks B operation of a general heat exchanger network with given structure, heat exchanger areas and stream data to any heat exchanger network. Using this model periodically for optimization, the operating conditions
Sootblowing optimization for improved boiler performance
James, John Robert; McDermott, John; Piche, Stephen; Pickard, Fred; Parikh, Neel J
2013-07-30
A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.
Sootblowing optimization for improved boiler performance
James, John Robert; McDermott, John; Piche, Stephen; Pickard, Fred; Parikh, Neel J.
2012-12-25
A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.
Event-driven multithreaded dynamic optimization
Zhang, Weifeng
2006-01-01
Speci?c Optimizations . . . . . . . . . . . . . F.3. Trace Optimization Overhead . . . . . . . . . . . . . . .Dynamic Optimization . . . . . . .B. Optimizations with the
The optimization problem Genetic Algorithm
Giménez, Domingo
The optimization problem Genetic Algorithm Particle Swarm Optimization Experimental results for time-power optimization META, October 27-31, 2014 1 / 25 #12;The optimization problem Genetic Algorithm Particle Swarm Optimization Experimental results Conclusions Time and energy optimization Traditionally
Optimization and geophysical inverse problems
Barhen, J.
2008-01-01
for Unconstrained Optimization and Nonlinear Equations,equality constrained optimization, SIAM J. Optim. , 7, 28.R. , Practical Methods of Optimization, Wiley, New York, 436
Compiler Optimization Jordan Bradshaw
Valtorta, Marco
Compiler Optimization Jordan Bradshaw #12;Outline Overview Goals and Considerations Scope. 346- 352. Print. "Compiler Optimization." Wikipedia. Wikimedia Foundation, 25 04 2010. Web. 25 Apr 2010. #12;Compiler Optimization Goals: Speed
Pessimistic Bilevel Optimization
Wiesemann, Wolfram
We study a variant of the pessimistic bilevel optimization problem, which comprises constraints that must be satisfied for any optimal solution of a subordinate (lower-level) optimization problem. We present conditions ...
Reis, Catarina (Catarina Luis Monteiro dos)
2007-01-01
This thesis studies the optimal income tax scheme in four different settings. Chapter 1 focuses on the implications of lack of commitment for the optimal labor and capital income tax rates. It finds that it is optimal to ...
Jilla, Cyrus D., 1974-
2002-01-01
A multiobjective, multidisciplinary design optimization methodology for mathematically modeling the distributed satellite system (DSS) conceptual design problem as an optimization problem has been developed to advance the ...
Optimization Online - Combinatorial Optimization Submissions - 2015
Combinatorial Optimization Submissions - 2015. January 2015. Polyhedra Steiner Trees with Degree Constraints: Structural Results and an Exact Solution ...
Optimization Online - Robust Optimization Submissions - 2015
Robust Optimization Submissions - 2015. January 2015. A Composite Risk Measure Framework for Decision Making under Uncertainty Pengyu Qian, Zizhuo ...
Optimization Online - Robust Optimization Submissions - 2013
Robust Optimization Submissions - 2013. January 2013. Robust Least Square Semidefinite Programming with Applications to Correlation Stress Testing
Optimization Online - Combinatorial Optimization Submissions - 2014
Combinatorial Optimization Submissions - 2014. January 2014. Approximation Algorithms Worst-Case Performance Analysis of Some Approximation Algorithms ...
Energy Systems Optimization, Modeling, Simulation,
Qu, Zhihua
such as solar or wind energy, fuel cells or even small diesel generators. To in- crease the harness price to the micro grid, minimizes its cost and se- cures the power supply that the microgrid
Modeling & Optimization An ABB Speciality
and portfolio Ultrahigh, high and medium voltage products (eg, switchgear, capacitors); distribution automation- starters, DIN rail equipment, LV breakers, LV switchgear Control systems, instrumentation and application
Air Transport Optimization Model | NISAC
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Industrial Applications for Micropower: A Market Assessment, November 1999
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
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Optimal Deployment of Emissions Reduction Technologies for Construction Equipment
Quadrifoglio, Luca
Optimal Deployment of Emissions Reduction Technologies for Construction Equipment Muhammad Ehsanul The objective of this research was to develop a multiob- jective optimization model to deploy emissions reduction technologies for nonroad construction equipment to re- duce emissions in a cost
Optimal Sequencing of Central Refrigeration Equipment in an Industrial Plant
Fiorino, D. P.; Priest, J. W.
1986-01-01
A model was developed to find a viable solution to the problem of selecting the optimal sequence of refrigeration equipment (chillers, cooling towers, pumps) to operate in a Central Utility Plant. The optimal equipment sequence is that sequence...
An Approximate Inference Approach to Temporal Optimization in Optimal Control
Vijayakumar, Sethu
Motivation · Stochastic Optimal feedback control (SOFC) is a plausible move- ment generation strategy in goal with non-linear dynamics and non-quadratic costs SOFC law can only be found locally and iteratively, e SOFC Model Random variables we use here: xt state of a plant (joint angles q and velocities q) ut
Branch and Bound for Boolean Optimization and the Generation of Optimality Certificates
Larrosa, Javier
optimization problems of the form (S, cost), where S is a clause set over Boolean variables x1 . . . xn, with an arbi- trary cost function cost : Bn R, and the aim is to find a model A of S such that cost algorithm that can model optimization concepts such as cost-based propagation and cost-based backjumping
Design of a building structural skin using multi-objective optimization techniques
Merello, Riccardo
2006-01-01
Multi-disciplinary System Design Optimization was used to design the geometry and to select the materials for the structural facade of a building. A multi-objective optimization model was developed, capable of optimizing ...
Wind Electrolysis: Hydrogen Cost Optimization
Saur, G.; Ramsden, T.
2011-05-01
This report describes a hydrogen production cost analysis of a collection of optimized central wind based water electrolysis production facilities. The basic modeled wind electrolysis facility includes a number of low temperature electrolyzers and a co-located wind farm encompassing a number of 3MW wind turbines that provide electricity for the electrolyzer units.
Multivariable Optimization: Quantum Annealing & Computation
Sudip Mukherjee; Bikas K. Chakrabarti
2014-08-21
Recent developments in quantum annealing techniques have been indicating potential advantage of quantum annealing for solving NP-hard optimization problems. In this article we briefly indicate and discuss the beneficial features of quantum annealing techniques and compare them with those of simulated annealing techniques. We then briefly discuss the quantum annealing studies of some model spin glass and kinetically constrained systems.
Smyth, Gordon K.
Optimization Gordon K. Smyth Volume 3, pp 14811487 in Encyclopedia of Environmetrics (ISBN 0471 #12;Optimization Optimization is the process by which one finds that value of a vector x, say, that maximizes or minimizes a given function f x . The idea of optimization goes to the heart of statistical
Optimal Power Dispatch via Multistage Stochastic Programming
RÃ¶misch, Werner
Mathematical models for cost-optimal power scheduling in hydro-thermal systems often combine several di culties for the dis- patch of electric power in a hydro-thermal generation system over a certain time horizonOptimal Power Dispatch via Multistage Stochastic Programming M.P. Nowak1 and W. Romisch1 Abstract
February 15, 2006 Dynamic Optimization for
Grossmann, Ignacio E.
with A+ models · Dow/MDC/Emerson - RTO of system of 4 cogeneration plants, optimization run every 30 min,000 variables and equations) 1986 - Shell Opera package for ethylene plants 1988 - First DMO application, Sunoco://www.arcweb.com/research/ent/rpo.asp for industry assessment 6 #12;Some Recent RTO Studies · Agrium - optimization of integrated NH3 plant, 1
Modal test optimization using VETO (Virtual Environment for Test Optimization)
Klenke, S.E.; Reese, G.M.; Schoof, L.A.; Shierling, C.
1996-01-01
We present a software environment integrating analysis and test-based models to support optimal modal test design through a Virtual Environment for Test Optimization (VETO). A goal in developing this software tool is to provide test and analysis organizations with a capability of mathematically simulating the complete test environment in software. Derived models of test equipment, instrumentation and hardware can be combined within the VETO to provide the user with a unique analysis and visualization capability to evaluate new and existing test methods. The VETO assists analysis and test engineers in maximizing the value of each modal test. It is particularly advantageous for structural dynamics model reconciliation applications. The VETO enables an engineer to interact with a finite element model of a test object to optimally place sensors and exciters and to investigate the selection of data acquisition parameters needed to conduct a complete modal survey. Additionally, the user can evaluate the use of different types of instrumentation such as filters, amplifiers and transducers for which models are available in the VETO. The dynamic response of most of the virtual instruments (including the device under test) is modeled in the state space domain. Design of modal excitation levels and appropriate test instrumentation are facilitated by the VETO`s ability to simulate such features as unmeasured external inputs, A/D quantization effects, and electronic noise. Measures of the quality of the experimental design, including the Modal Assurance Criterion, and the Normal Mode Indicator Function are available.
Impact of Turbulence Closures and Numerical Errors for the Optimization of Flow Control Devices
Paris-Sud XI, Université de
Impact of Turbulence Closures and Numerical Errors for the Optimization of Flow Control Devices J the use of a Kriging-based global optimization method to determine optimal control parameters conduct an optimization process and measure the impact of numerical and modeling errors on the optimal
Optimization Online - Robust Dual Response Optimization
Aug 8, 2015 ... Abstract: This article presents a robust optimization reformulation of the dual response problem developed in response surface methodology.
Optimization Online - Solving nonsmooth convex optimization with ...
May 8, 2015 ... Solving nonsmooth convex optimization with complexity $O(\\eps^{-1/2})$. Masoud Ahookhosh (masoud.ahookhosh ***at*** univie.ac.at)
Optimization Online - Probabilistic optimization via approximate p ...
W. van vAckooij
2015-05-27
May 27, 2015 ... Probabilistic optimization via approximate p-efficient points and bundle methods. W. van vAckooij(wim.van-ackooij ***at*** edf.fr )
Theory and Applications of Robust Optimization
Bertsimas, Dimitris J.
In this paper we survey the primary research, both theoretical and applied, in the area of robust optimization (RO). Our focus is on the computational attractiveness of RO approaches, as well as the modeling power and broad ...
Signal Timing Optimization to Improve Air Quality
Lv, Jinpeng 1983-
2012-12-11
the gap that the research on signal optimization at intersections lags behind the development of emissions models. The methodology development includes four levels: the vehicle level, the movement level, the intersection level, and the arterial level...
Optimal Control of Quantum Measurement
Daniel J. Egger; Frank K. Wilhelm
2014-08-26
Pulses to steer the time evolution of quantum systems can be designed with optimal control theory. In most cases it is the coherent processes that can be controlled and one optimizes the time evolution towards a target unitary process, sometimes also in the presence of non-controllable incoherent processes. Here we show how to extend the GRAPE algorithm in the case where the incoherent processes are controllable and the target time evolution is a non-unitary quantum channel. We perform a gradient search on a fidelity measure based on Choi matrices. We illustrate our algorithm by optimizing a phase qubit measurement pulse. We show how this technique can lead to large measurement contrast close to 99%. We also show, within the validity of our model, that this algorithm can produce short 1.4 ns pulses with 98.2% contrast.
PGO: a Parallel Computing Platform for Global Optimization Based on Genetic
Kurien, Susan
scientific modeling and simulation processes. Along with a core optimization kernel built on a Genetic. Optimization refers to the pro- cess of identifying values for unknown model parameters or control variables so for the optimization process. For example, PEST (Doherty, 2004) uses a nonlinear optimization technique known
Global Optimization of Chemical Reactors and Kinetic Optimization
ALHUSSEINI, ZAYNA ISHAQ
2013-01-01
and M. Sheintuch. "OPTIMIZATION OF AN AUTOTHERMAL MONOLITHICIdentification Via Global Optimization Techniques. AIChE1: 91-103. Chapter 3 Optimization of a 3-D Monolith Reactor
E85 Optimized Engine through Boosting, Spray Optimized DIG, VCR...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
E85 Optimized Engine through Boosting, Spray Optimized GDi, VCR and Variable Valvetrain E85 Optimized Engine Enhanced Ethanol Engine And Vehicle Efficiency (Agreement 13425)...
HOMOTOPY OPTIMIZATION METHODS FOR GLOBAL OPTIMIZATION
O'Leary, Dianne P.
HOMOTOPY OPTIMIZATION METHODS FOR GLOBAL OPTIMIZATION DANIEL M. DUNLAVY AND DIANNE P. O'LEARY under Grants CCR 02-04084 and CCF 05-14213. 1 #12;2 D.M. DUNLAVY AND D.P. O'LEARY point is generated
Design of an Electron Gun using Computer Optimization
Design of an Electron Gun using Computer Optimization B. M. Lewis H. T. Tran Department geometry of the system. This optimization framework, to be considered in the context of electron guns the methods of shape optimization to design the cathode of an electron gun. The dynamical equations modeling
Global Optimization of Chemical Processes using Stochastic Algorithms
Neumaier, Arnold
Global Optimization of Chemical Processes using Stochastic Algorithms JULIO R. BANGA 1 and WARREN D engineering are difficult to optimize using gradientÂbased algorithms. These include process models with multimodalobjective functions and discontinuities. Herein, a stochastic algorithm is applied for the optimal design
MURTHY, MURTY AND RAGHUPATHY Designing Earth Dams Optimally
Murty, Katta G.
[ 91 ] MURTHY, MURTY AND RAGHUPATHY Designing Earth Dams Optimally G S R Murthy1 , Katta G Murty2, it aims at formulating the problem of designing earth dams as an optimization problem. The problem provides mathematical modeling for optimizing earth dam designs and for computing the factor of safety
ENERGY AND WATER OPTIMIZATION IN BIOFUEL PLANTS Ignacio E. Grossmann*
Grossmann, Ignacio E.
1 ENERGY AND WATER OPTIMIZATION IN BIOFUEL PLANTS Ignacio E. Grossmann* , Mariano Martín Center, PA 15213, USA Abstract In this paper we address the topic of energy and water optimization, we propose a strategy based on mathematical programming techniques to model and optimize
Real-time Dynamic Optimization of Batch Crystallization Processes
Van den Hof, Paul
process. The seeded fed-batch crystallizer is represented by a nonlinear moment model. An optimal controlReal-time Dynamic Optimization of Batch Crystallization Processes Ali Mesbah, , Alex N. Kalbasenka-time implementations of the proposed strategy reveal the effectiveness of closed-loop optimal control
Optimization and learning based video coding
An, Cheolhong
2008-01-01
2 Rate-Distortion Optimization . . . . . . . . . . . .Distortion Optimization . . . . . . . . . . . . . . . . . .Rate-Distortion Optimization . . . . . . . . . . . .
Optimized nanoporous materials.
Braun, Paul V.; Langham, Mary Elizabeth; Jacobs, Benjamin W.; Ong, Markus D.; Narayan, Roger J.; Pierson, Bonnie E.; Gittard, Shaun D.; Robinson, David B.; Ham, Sung-Kyoung; Chae, Weon-Sik; Gough, Dara V.; Wu, Chung-An Max; Ha, Cindy M.; Tran, Kim L.
2009-09-01
Nanoporous materials have maximum practical surface areas for electrical charge storage; every point in an electrode is within a few atoms of an interface at which charge can be stored. Metal-electrolyte interfaces make best use of surface area in porous materials. However, ion transport through long, narrow pores is slow. We seek to understand and optimize the tradeoff between capacity and transport. Modeling and measurements of nanoporous gold electrodes has allowed us to determine design principles, including the fact that these materials can deplete salt from the electrolyte, increasing resistance. We have developed fabrication techniques to demonstrate architectures inspired by these principles that may overcome identified obstacles. A key concept is that electrodes should be as close together as possible; this is likely to involve an interpenetrating pore structure. However, this may prove extremely challenging to fabricate at the finest scales; a hierarchically porous structure can be a worthy compromise.
Birnir, Bjorn; Rowlett, Julie
2010-01-01
383 pp. EROSION AND OPTIMAL TRANSPORT [23] I. Ekeland and T.and D. Simons, Sediment transport capacity of overland ?ow,measure spaces via optimal transport, Ann. of Math. (2),
Matson, J.
1985-01-01
A cooling water system can be optimized by operation at the highest possible cycles of concentration without risking sealing and fouling on heat exchanger surfaces. The way to optimize will be shown, with a number of examples of new systems....
Nanoscale SRAM Variability and Optimization
Toh, Seng Oon
2011-01-01
Dynamic Read Stability 5 Stochastic Optimization of SRAM 5.15.2 Bitcell Optimization . . . . . . . . .5.2.1 GlobalTechnology . . Optimization . . . . . . Read and Write
Integrated Energy System Dispatch Optimization
Firestone, Ryan; Stadler, Michael; Marnay, Chris
2006-01-01
Energy System Dispatch Optimization Ryan Firestone, MichaelEnergy System Dispatch Optimization Ryan Firestone - Studentthe real-time dispatch optimization problem for a generic
Power network analysis and optimization
Zhang, Wanping
2009-01-01
chip power supply network optimization using multigrid-basedchip decoupling capacitor optimization for high- performanceSapatnekar, “Analysis and optimization of structured power/
Positive and Negative Electrodes: Novel and Optimized Materials...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Investigation of critical parameters in Li-ion battery electrodes Novel and Optimized Materials Phases for High Energy Density Batteries Atomistic Modeling of Electrode Materials...
The watershed-scale optimized and rearranged landscape design...
Office of Scientific and Technical Information (OSTI)
The watershed-scale optimized and rearranged landscape design (WORLD) model and local biomass processing depots for sustainable biofuel production: Integrated life cycle...
Linear, Cone and Semidefinite Programming Submissions - 2014. January 2014. Linear Programming A strongly polynomial algorithm for linear optimization ...
Convex and Nonsmooth Optimization Submissions - 2013. January 2013. Second-Order Variational Analysis in Conic Programming with Applications to ...
Magnetic Resonance Tissue Density Estimation using Optimal SSFP Pulse- Sequence Design Christopher Anand ... Gun Srijuntongsiri, Stephen Vavasis.
Optimal segmentation and packaging process
Kostelnik, K.M.; Meservey, R.H.; Landon, M.D.
1999-08-10
A process for improving packaging efficiency uses three dimensional, computer simulated models with various optimization algorithms to determine the optimal segmentation process and packaging configurations based on constraints including container limitations. The present invention is applied to a process for decontaminating, decommissioning (D and D), and remediating a nuclear facility involving the segmentation and packaging of contaminated items in waste containers in order to minimize the number of cuts, maximize packaging density, and reduce worker radiation exposure. A three-dimensional, computer simulated, facility model of the contaminated items are created. The contaminated items are differentiated. The optimal location, orientation and sequence of the segmentation and packaging of the contaminated items is determined using the simulated model, the algorithms, and various constraints including container limitations. The cut locations and orientations are transposed to the simulated model. The contaminated items are actually segmented and packaged. The segmentation and packaging may be simulated beforehand. In addition, the contaminated items may be cataloged and recorded. 3 figs.
Cold Climates Heat Pump Design Optimization
Abdelaziz, Omar [ORNL] [ORNL; Shen, Bo [ORNL] [ORNL
2012-01-01
Heat pumps provide an efficient heating method; however they suffer from sever capacity and performance degradation at low ambient conditions. This has deterred market penetration in cold climates. There is a continuing effort to find an efficient air source cold climate heat pump that maintains acceptable capacity and performance at low ambient conditions. Systematic optimization techniques provide a reliable approach for the design of such systems. This paper presents a step-by-step approach for the design optimization of cold climate heat pumps. We first start by describing the optimization problem: objective function, constraints, and design space. Then we illustrate how to perform this design optimization using an open source publically available optimization toolbox. The response of the heat pump design was evaluated using a validated component based vapor compression model. This model was treated as a black box model within the optimization framework. Optimum designs for different system configurations are presented. These optimum results were further analyzed to understand the performance tradeoff and selection criteria. The paper ends with a discussion on the use of systematic optimization for the cold climate heat pump design.
POET: Parameterized Optimization for Empirical Tuning
Yi, Q; Seymour, K; You, H; Vuduc, R; Quinlan, D
2007-01-29
The excessive complexity of both machine architectures and applications have made it difficult for compilers to statically model and predict application behavior. This observation motivates the recent interest in performance tuning using empirical techniques. We present a new embedded scripting language, POET (Parameterized Optimization for Empirical Tuning), for parameterizing complex code transformations so that they can be empirically tuned. The POET language aims to significantly improve the generality, flexibility, and efficiency of existing empirical tuning systems. We have used the language to parameterize and to empirically tune three loop optimizations-interchange, blocking, and unrolling-for two linear algebra kernels. We show experimentally that the time required to tune these optimizations using POET, which does not require any program analysis, is significantly shorter than that when using a full compiler-based source-code optimizer which performs sophisticated program analysis and optimizations.
Price, R; Veltchev, I; Cherian, G; Ma, C [Chase Cancer Center, Philadelphia, PA (United States)
2014-06-01
Purpose: Multiple publications exist concerning fixed-jaw utilization to avoid linac carriage shifts and reduce intensity modulated radiotherapy (IMRT) treatment times. The purpose of this work is to demonstrate delivery QA discrepancies and illustrate the need for improved treatment planning system (TPS) commissioning for non-routine use. Methods: A 6cm diameter spherical target was delineated on a virtual phantom containing the Iba Matrixx linear array within the Varian Eclipse TPS. Optimization was performed for target coverage for the following 3 scenarios: a single open, zero degree field where the X and Y jaws completely cover the target; the same field using an asymmetric, fixed-jaw technique where the upper Y jaw does not cover the superior 2cm of the target; and both of the aforementioned directed at the target at 315 and 45 degree gantry angles, respectively. This final orientation was also irradiated on a linac for delivery analysis. A sarcoma patient case was also analyzed where the fixed jaw technique was utilized for kidney sparing. Results: The open beam results were as predicted but the fixed-jaw results demonstrate a pronounced fluence increase along the asymmetric, upper jaw. Analysis of the delivery of the combined beam plan Resultin 83% of pixels evaluated passing gamma criteria of 3%, 3mm DTA. Analysis for the sarcoma patient, in the plane of the shielded kidney, indicated 93% passing although the maximum dose discrepancies in this region were approximately 23%. Conclusion: Optimization within the target is routinely performed using MLC leaf-end characteristics. The fixed-jaw technique forces optimization of target coverage to utilize the penumbra profiles of the associated beamdefining jaw. If the profiles were collected using a common 0.125cc ionization chamber, the resolution may be insufficient resulting in a planvs.-delivery mismatch. It is recommended that high-resolution beam characteristics be considered when non-routine planning methods are utilized.
Optimization Online Digest -- October 2015
Optimization Online Digest — October 2015. Applications — OR and Management Sciences Polynomial SDP Cuts for Optimal Power Flow Hassan Hijazi ...
Optimization Online Digest -- March 2015
Optimization Online Digest — March 2015. Applications — OR and Management Sciences Stochastic versus Robust Optimization for a Transportation Problem
Optimization Online Digest -- September 2014
Optimization Online Digest — September 2014. Applications — OR and Management Sciences Multistage Adaptive Robust Optimization for the Unit ...
Optimization Online Digest -- March 2014
Topology Optimization for Magnetic Circuits dedicated to Electric Propulsion Satafa Sanogo, Frederic Messine, Carole Henaux, Raphael Vilamot Inverse optimal ...
Optimized Triple-Junction Solar Cells Using Inverted Metamorphic Approach (Presentation)
Geisz, J. F.
2008-11-01
Record efficiencies with triple-junction inverted metamorphic designs, modeling useful to optimize, and consider operating conditions before choosing design.
Real-Time Utility System Optimization
Fernandez-Polanco, D.; Eastwood, A.; Knight, N.
2004-01-01
be defined for each process unit and then combined using the production plan to calculate predicted steam, power and fuel demands. The optimizer model can then determine in advance how the site should react. This can be especially useful for planning... OPTIMIZATION Diego Fernández-Polanco Linnhoff March, a division of KBC Process Technology Ltd. Northwich, UK Alan Eastwood Linnhoff March, a division of KBC Process Technology Ltd. Northwich, UK Nicola Knight KBC Advanced Technologies Inc...
-International Doctorate Program -Identification, Optimization and Control
Dettweiler, Michael
PDAE Molten Carbonate Fuel Cell Model February 7, 2008 Preprint IOC-12 #12;#12;Optimal Control of a Large PDAE Molten Carbonate Fuel Cell Model Armin Rund , Kati Sternberg, Hans Josef Pesch, and Kurt carbonate fuel cells are well suited for stationary power production and heat supply. In order to enhance
SIMULATION AND OPTIMAL CONTROL OF HYBRID GROUND SOURCE HEAT
SIMULATION AND OPTIMAL CONTROL OF HYBRID GROUND SOURCE HEAT PUMP SYSTEMS By XIAOWEI XU Bachelor #12;ii SIMULATION AND OPTIMAL CONTROL OF HYBRID GROUND SOURCE HEAT PUMP SYSTEMS Dissertation Approved Loop Heat Exchanger Model....................................................... 11 2.1.1.1 Modeling
OPTIMIZATION OF AUTOMOTIVE VALVE TRAIN COMPONENTS WITH IMPLICT , O. J. ELSINGER
OPTIMIZATION OF AUTOMOTIVE VALVE TRAIN COMPONENTS WITH IMPLICT FILTERING T. D. CHOI ¡ , O. J and optimization in automotive valve train design. We extend our previous work by using a more refined model to obtain optimal profiles for camshaft lobes. Key words. Noisy Optimization, Implicit Filtering, Mechanical
Convex and Nonsmooth Optimization Submissions - 2015. December 2015. Solving ill-posed bilevel programs. Alain B. Zemkoho. January 2015. A remark on ...
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Applications — OR and Management Sciences Submissions - 2013. January 2013. A two-step optimization approach for job shop scheduling problem using a ...
Classification Scheme - Optimization Online
Submissions are organized according to the following top areas and sub areas: Applications - OR and Management Sciences. Airline Optimization; Finance and ...
Hopper Performance and Optimization
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
Performance and Optimization Compiler Comparisons Comparison of different compilers with different options on several benchmarks. Read More Using OpenMP Effectively...
Graben, Peter beim; Fröhlich, Flavio
2015-01-01
We optimally estimate the recurrence structure of a multivariate time series by Markov chains obtained from recurrence grammars. The goodness of fit is assessed with a utility function derived from the stochastic Markov transition matrix. It assumes a local maximum for the distance threshold of the optimal recurrence grammar. We validate our approach by means of the nonlinear Lorenz system and its linearized stochastic surrogates. Finally we apply our optimization procedure to the segmentation of neurophysiological time series obtained from anesthetized animals. We propose the number of optimal recurrence domains as a statistic for classifying an animals' state of consciousness.
Euler's fluid equations: Optimal Control vs Optimization
Darryl D. Holm
2009-09-28
An optimization method used in image-processing (metamorphosis) is found to imply Euler's equations for incompressible flow of an inviscid fluid, without requiring that the Lagrangian particle labels exactly follow the flow lines of the Eulerian velocity vector field. Thus, an optimal control problem and an optimization problem for incompressible ideal fluid flow both yield the \\emph {same} Euler fluid equations, although their Lagrangian parcel dynamics are \\emph{different}. This is a result of the \\emph{gauge freedom} in the definition of the fluid pressure for an incompressible flow, in combination with the symmetry of fluid dynamics under relabeling of their Lagrangian coordinates. Similar ideas are also illustrated for SO(N) rigid body motion.
results about bonds in the H-P model. 1 Introduction Protein folding is a central problem such as drug de- sign. One of the most popular models of protein folding is the hydrophilic-hydrophobic (H of protein folding such as the tendency for the hydrophobic components to fold to the center of a globular
Run-time optimization of adaptive irregular applications
Yu, Hao
2004-11-15
deployed an off-line, systematic experiment process to generate prediction models. These models, in turn, match the parameters to the best optimization transformations for a given machine. The technique has been evaluated thoroughly in terms of applications...
Homotopy optimization methods for global optimization.
Dunlavy, Daniel M.; O'Leary, Dianne P. (University of Maryland, College Park, MD)
2005-12-01
We define a new method for global optimization, the Homotopy Optimization Method (HOM). This method differs from previous homotopy and continuation methods in that its aim is to find a minimizer for each of a set of values of the homotopy parameter, rather than to follow a path of minimizers. We define a second method, called HOPE, by allowing HOM to follow an ensemble of points obtained by perturbation of previous ones. We relate this new method to standard methods such as simulated annealing and show under what circumstances it is superior. We present results of extensive numerical experiments demonstrating performance of HOM and HOPE.
Tabone, Michaelangelo D; Callaway, Duncan S
2015-01-01
require- ments in unit commitment optimal dispatch modelsLaboratory (NREL) uses a unit commitment optimal dispatch
Synthesis of optimal adsorptive carbon capture processes.
chang, Y.; Cozad, A.; Kim, H.; Lee, A.; Vouzis, P.; Konda, M.; Simon, A.; Sahinidis, N.; Miller, D.
2011-01-01
Solid sorbent carbon capture systems have the potential to require significantly lower regeneration energy compared to aqueous monoethanol amine (MEA) systems. To date, the majority of work on solid sorbents has focused on developing the sorbent materials themselves. In order to advance these technologies, it is necessary to design systems that can exploit the full potential and unique characteristics of these materials. The Department of Energy (DOE) recently initiated the Carbon Capture Simulation Initiative (CCSI) to develop computational tools to accelerate the commercialization of carbon capture technology. Solid sorbents is the first Industry Challenge Problem considered under this initiative. An early goal of the initiative is to demonstrate a superstructure-based framework to synthesize an optimal solid sorbent carbon capture process. For a given solid sorbent, there are a number of potential reactors and reactor configurations consisting of various fluidized bed reactors, moving bed reactors, and fixed bed reactors. Detailed process models for these reactors have been modeled using Aspen Custom Modeler; however, such models are computationally intractable for large optimization-based process synthesis. Thus, in order to facilitate the use of these models for process synthesis, we have developed an approach for generating simple algebraic surrogate models that can be used in an optimization formulation. This presentation will describe the superstructure formulation which uses these surrogate models to choose among various process alternatives and will describe the resulting optimal process configuration.
Hybrid Design Optimization of High Voltage Pulse Transformers for Klystron Modulators
Sylvain, Candolfi; Davide, Aguglia; Jerome, Cros
2015-01-01
This paper presents a hybrid optimization methodology for the design of high voltage pulse transformers used in klystron modulators. The optimization process is using simplified 2D FEA design models of the 3D transformer structure. Each intermediate optimal solution is evaluated by 3D FEA and correction coefficients of the 2D FEA models are derived. A new optimization process using 2D FEA models is then performed. The convergence of this hybrid optimal design methodology is obtained with a limited number of time consuming 3D FEA simulations. The method is applied to the optimal design of a monolithic high voltage pulse transformer for the CLIC klystron modulator.
Powers, Tom [JLAB
2013-09-01
This work describes preliminary results of a new software tool that allows one to vary parameters and understand the effects on the optimized costs of construction plus 10 year operations of an SRF linac, the associated cryogenic facility, and controls, where operations includes the cost of the electrical utilities but not the labor or other costs. It derives from collaborative work done with staff from Accelerator Science and Technology Centre, Daresbury, UK several years ago while they were in the process of developing a conceptual design for the New Light Source project.[1] The initial goal was to convert a spread sheet format to a graphical interface to allow the ability to sweep different parameter sets. The tools also allow one to compare the cost of the different facets of the machine design and operations so as to better understand the tradeoffs. The work was first published in an ICFA Beam Dynamics News Letter.[2] More recent additions to the software include the ability to save and restore input parameters as well as to adjust the Qo versus E parameters in order to explore the potential costs savings associated with doing so. Additionally, program changes now allow one to model the costs associated with a linac that makes use of energy recovery mode of operation.
Davis, Michael A.
2011-10-21
Single Duct Variable Air Volume (SDVAV) systems use series and parallel Fan Powered Terminal Units to control the air flow in conditioned spaces. This research developed a laboratory verified model of SDVAV systems that ...
Industrial Optimization Compact Course
Kirches, Christian
Industrial Optimization Compact Course and Challenge Workshop Optimization plays a crucial role in designing and conducting industrial processes. The potential gains range from saving valuable resources over makers from industry and academia to initiate new projects and to foster new structured collaborations
Optimization and Control of Electric Power Systems
Lesieutre, Bernard C.; Molzahn, Daniel K.
2014-10-17
The analysis and optimization needs for planning and operation of the electric power system are challenging due to the scale and the form of model representations. The connected network spans the continent and the mathematical models are inherently nonlinear. Traditionally, computational limits have necessitated the use of very simplified models for grid analysis, and this has resulted in either less secure operation, or less efficient operation, or both. The research conducted in this project advances techniques for power system optimization problems that will enhance reliable and efficient operation. The results of this work appear in numerous publications and address different application problems include optimal power flow (OPF), unit commitment, demand response, reliability margins, planning, transmission expansion, as well as general tools and algorithms.
Optimal Uncertainty Quantification
Owhadi, Houman; Sullivan, Timothy John; McKerns, Mike; Ortiz, Michael
2010-01-01
We propose a rigorous framework for Uncertainty Quantification (UQ) in which the UQ objectives and the assumptions/information set are brought to the forefront. This framework, which we call \\emph{Optimal Uncertainty Quantification} (OUQ), is based on the observation that, given a set of assumptions and information about the problem, there exist optimal bounds on uncertainties: these are obtained as extreme values of well-defined optimization problems corresponding to extremizing probabilities of failure, or of deviations, subject to the constraints imposed by the scenarios compatible with the assumptions and information. In particular, this framework does not implicitly impose inappropriate assumptions, nor does it repudiate relevant information. Although OUQ optimization problems are extremely large, we show that under general conditions, they have finite-dimensional reductions. As an application, we develop \\emph{Optimal Concentration Inequalities} (OCI) of Hoeffding and McDiarmid type. Surprisingly, contr...
Computational Differentiation in Global Optimization
Neumaier, Arnold
Computational Differentiation in Global Optimization Software This talk will present: 1. The general problem framework in optimization software. 2. An example of effectiveness of computational differentiation in optimization packages. 3. Particular importance of computational differentiation verified
Query Optimization Techniques Class Hierarchies
Mannheim, Universität
Query Optimization Techniques Exploiting Class Hierarchies Sophie Cluet 1 Guido Moerkotte 2 1 INRIA Since the introduction of object base management systems (OBMS), many query optimization techniques tailored for object query languages have been proposed. They adapt known optimization techniques
J. E. Avron; A. Elgart; G. M. Graf; L. Sadun
2001-07-12
We study adiabatic quantum pumps on time scales that are short relative to the cycle of the pump. In this regime the pump is characterized by the matrix of energy shift which we introduce as the dual to Wigner's time delay. The energy shift determines the charge transport, the dissipation, the noise and the entropy production. We prove a general lower bound on dissipation in a quantum channel and define optimal pumps as those that saturate the bound. We give a geometric characterization of optimal pumps and show that they are noiseless and transport integral charge in a cycle. Finally we discuss an example of an optimal pump related to the Hall effect.
Optimal Demand Response Libin Jiang
Optimal Demand Response Libin Jiang Steven Low Computing + Math Sciences Electrical Engineering Caltech Oct 2011 #12;Outline Caltech smart grid research Optimal demand response #12;Global trends 1
Optimization Online Digest -- July 2014
Analysis of mixed integer programming formulations for single machine scheduling problems with sequence dependent setup ... Linear conic optimization for nonlinear optimal control ... Circuit and bond polytopes on series-
Optimized Algorithms Boost Combustion Research
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
Optimized Algorithms Boost Combustion Research Optimized Algorithms Boost Combustion Research Methane Flame Simulations Run 6x Faster on NERSC's Hopper Supercomputer November 25,...
Cognitive Energy Value Chain: Leveraging Big Data to Optimize Energy
Birg, G.; Reitmeier, T.
2014-01-01
-if’ Scenarios Predicting The Future Variance Analyses Performance Management System Wide Trade Offs ESL-IE-14-05-44 Proceedings of the Thrity-Sixth Industrial Energy Technology Conference New Orleans, LA. May 20-23, 2014 - 6 -CEO Cognitive Energy Optimization... Optimization Confidential Predictive vs. Prescriptive Analytics Predictive analytics solutions allow organizations to discover, evaluate, optimize, and deploy predictive models by analyzing data sources to improve business outcomes where: – Evidence...
Crowe, B.; Yucel, V.; Rawlinson, S.; Black, P.; Carilli, J.; DiSanza, F.
2002-02-25
The U.S. Department of Energy (DOE), National Nuclear Security Administration of the Nevada Operations Office (NNSA/NV) operates and maintains two active facilities on the Nevada Test Site (NTS) that dispose defense-generated low-level radioactive waste (LLW), mixed radioactive waste, and ''classified waste'' in shallow trenches and pits. The operation and maintenance of the LLW disposal sites are self-regulated by the DOE under DOE Order 435.1. This Order requires formal review of a performance assessment (PA) and composite analysis (CA; assessment of all interacting radiological sources) for each LLW disposal system followed by an active maintenance program that extends through and beyond the site closure program. The Nevada disposal facilities continue to receive NTS-generated LLW and defense-generated LLW from across the DOE complex. The PA/CAs for the sites have been conditionally approved and the facilities are now under a formal maintenance program that requires testing of conceptual models, quantifying and attempting to reduce uncertainty, and implementing confirmatory and long-term background monitoring, all leading to eventual closure of the disposal sites. To streamline and reduce the cost of the maintenance program, the NNSA/NV is converting the deterministic PA/CAs to probabilistic models using GoldSim, a probabilistic simulation computer code. The output of probabilistic models will provide expanded information supporting long-term decision objectives of the NTS disposal sites.
Optimization of tensegrity structures
Marzari, Quentin
2014-01-01
This thesis presents a new approach to solve the optimization of articulated structures and especially looks into the performance of tensegrity systems compared to regular trusses. Volume is the objective to minimize and ...
Multi-period portfolio optimization with alpha decay ... Transmission and Generation Investment in Electricity Markets: The Effects of Market Splitting and ... Improving Large Scale Day-ahead Security Constrained Unit Commitment Performance
Xiong, Ying, S.M. Massachusetts Institute of Technology
2010-01-01
Although most racers are good at controlling their cars, world champions are always talented at choosing the right racing line while others mostly fail to do that. Optimal racing line selection is a critical problem in car ...
Polyethylene fiber drawing optimization
Chiloyan, Vazrik
2011-01-01
Polymer fiber drawing creates fibers with enhanced thermal conductivity and strength compared to bulk polymer because drawing aligns the molecular chains. I optimize the polymer fiber drawing method in order to achieve ...
Communicating optimization results
Bailey, Drake (William Drake)
2013-01-01
With global supply chains becoming increasingly complex, leading companies are embracing optimization software tools to help them structure and coordinate their supply chains. With an array of choices available, many ...
Kim, Wonjung, Ph. D. Massachusetts Institute of Technology
2013-01-01
It is generally presupposed that the shapes and mechanisms encountered in nature have evolved in such a way as to maximize the robustness of a species. However, most such optimization problems arising in biology are ...
de Souza, J.; Holden, D.
2004-01-01
Energy Optimization is one of the key issues facing the chemical process industries today. The drivers are both economic and environmental. Utilities are among the top operating expenses for manufacturers, reflecting elevated energy prices...
Brown, David Benjamin, Ph. D. Massachusetts Institute of Technology
2006-01-01
This thesis develops and explores the connections between risk theory and robust optimization. Specifically, we show that there is a one-to-one correspondence between a class of risk measures known as coherent risk measures ...
Wang, Haoqing
2015-01-01
optimization with the new Java 8 feature: type annotation.12] is an extension of Java type system and can be used withon State Of the Art in Java Program Analysis, SOAP ’13,
Service based logistics optimization
Price, Gregory D., Jr
2014-01-01
This thesis explores the use of a service based logistics optimization (SBLO) methodology for an inbound reverse logistics network. Currently, Quest Diagnostics solves the vehicle routing problem with time windows (VRPTW) ...
Optimization of Multi-Stack Exhaust Systems - New System Design Application
Wang, G.; Cui, Y.; Yuill, D.; Liu, M.
2002-01-01
airflow. The theoretical analysis indicates that the optimized design uses as little as 50% of the design fan power annually. This paper presents the system models, the optimization methods, and describes appropriate applications....
Optimal Newton-type algorithms for nonconvex smooth optimization
Sidorov, Nikita
Optimal Newton-type algorithms for nonconvex smooth optimization Coralia Cartis Mathematical-HPC Workshop on New Directions in Nonlinear Optimization University of Manchester, School of Mathematics, March 19, 2014 New Directions in Nonlinear Optimization: Manchester, 2014 Â p. 1/33 #12;Unconstrained
Next Generation Calibration Models with Dimensional Modeling...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Decision Tree Based Control Model-Based Transient Calibration Optimization for Next Generation Diesel Engines An Accelerated Aging Method for Diesel Exhaust Aftertreatment Systems...
Engineering adiabaticity at an avoided crossing with optimal control
T. Chasseur; L. S. Theis; Y. R. Sanders; D. J. Egger; F. K. Wilhelm
2015-02-24
We investigate ways to optimize adiabaticity and diabaticity in the Landau-Zener model with non-uniform sweeps. We show how diabaticity can be engineered with a pulse consisting of a linear sweep augmented by an oscillating term. We show that the oscillation leads to jumps in populations whose value can be accurately modeled using a model of multiple, photon-assisted Landau-Zener transitions, which generalizes work by Wubs et al. [New J. Phys. 7, 218 (2005)]. We extend the study on diabaticity using methods derived from optimal control. We also show how to preserve adiabaticity with optimal pulses at limited time, finding a non-uniform quantum speed limit.
Groundwater Remediation Strategy Using Global Optimization Algorithms
Neumaier, Arnold
Groundwater Remediation Strategy Using Global Optimization Algorithms Shreedhar Maskey1 ; Andreja Jonoski2 ; and Dimitri P. Solomatine3 Abstract: The remediation of groundwater contamination by pumping as decision variables. Groundwater flow and particle-tracking models MODFLOW and MODPATH and a GO tool GLOBE
OptFuels: Fuel Treatment Optimization
OptFuels: Fuel Treatment Optimization Scientists a Rocky Mountain Research Station Missoula, MT, scientists at the University of Montana, are developing a tool to help forest managers prioritize forest fuel reduction treatments. Although several computer models analyz stand-level effects of fuel treatments
Optimization Online Digest -- June 2014
Optimization Online Digest — June 2014. Applications — OR and Management Sciences Robust newsvendor problem with autoregressive demand
Contexts/Motivation Online optimization
Jaillet, Patrick
with recourse, Markov decision process, stochastic optimal control, etc.) No probabilistic assumptionsContexts/Motivation Online optimization In-depth Cases Online Optimization Patrick Jaillet1 Michael funded by NSF, ONR, AFOSR, and Singapore Online Optimization, Jaillet & Wagner INFORMS, November 8, 2010
DISTRIBUTED OPTIMIZATION AND CONTROL OF OFFSHORE OIL PRODUCTION: THE INTELLIGENT
Foss, Bjarne A.
DISTRIBUTED OPTIMIZATION AND CONTROL OF OFFSHORE OIL PRODUCTION: THE INTELLIGENT PLATFORM Michael R to distributed optimization and control of offshore oil production systems. The model incorporates a complex pipeline network. Oil and gas production systems are represented as a network of connected hierarchical
DHV water pumping optimization Simon van Mourik1
Rottschäfer, Vivi
Chapter 6 DHV water pumping optimization Simon van Mourik1 Joris Bierkens2 Hans Stigter1 Martijn for optimizing a drinking water network over a horizon of 48 hours, given variable water demands, energy prices and constraints on the pumping strategy and water levels in the reservoirs. Both the dynamic model and goal
Optimal Current Waveforms for Brushless Permanent Magnet Motors
14, 2014 Abstract In this paper we give energy-optimal excitation current waveforms for a permanent work by including a general back-EMF waveform, voltage and cur- rent limits, an arbitrary phase winding. Another advantage of on-line optimization is the ability to adapt in real time to changes in the model
Multiobjective Optimization and Multiple Constraint Handling with Evolutionary
Coello, Carlos A. Coello
The gas turbine engine model 1 3 The design problem 3 3.1 Design objectives] is applied to the optimization of the lowpressure spool speed governor of a Pegasus gas turbine engine] is applied to the optimization of the lowpressure spool speed governor of a Pegasus gas turbine engine