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Assessment of Energy Storage Alternatives in the Puget Sound Energy System Volume 2: Energy Storage Evaluation Tool

Description: This volume presents the battery storage evaluation tool developed at Pacific Northwest National Laboratory (PNNL), which is used to evaluate benefits of battery storage for multiple grid applications, including energy arbitrage, balancing service, capacity value, distribution system equipment deferral, and outage mitigation. This tool is based on the optimal control strategies to capture multiple services from a single energy storage device. In this control strategy, at each hour, a look-ahead optimization is first formulated and solved to determine battery base operating point. The minute by minute simulation is then performed to simulate the actual battery operation. This volume provide background and manual for this evaluation tool.
Date: December 1, 2013
Creator: Wu, Di; Jin, Chunlian; Balducci, Patrick J. & Kintner-Meyer, Michael CW
Partner: UNT Libraries Government Documents Department

Generalized Monge-Kantorovich optimization for grid generation and adaptation in LP

Description: The Monge-Kantorovich grid generation and adaptation scheme of is generalized from a variational principle based on L{sub 2} to a variational principle based on L{sub p}. A generalized Monge-Ampere (MA) equation is derived and its properties are discussed. Results for p > 1 are obtained and compared in terms of the quality of the resulting grid. We conclude that for the grid generation application, the formulation based on L{sub p} for p close to unity leads to serious problems associated with the boundary. Results for 1.5 {approx}< p {approx}< 2.5 are quite good, but there is a fairly narrow range around p = 2 where the results are close to optimal with respect to grid distortion. Furthermore, the Newton-Krylov methods used to solve the generalized MA equation perform best for p = 2.
Date: January 1, 2009
Creator: Delzanno, G L & Finn, J M
Partner: UNT Libraries Government Documents Department

An Adaptive Linearization Method for a Constraint Satisfaction Problem in Semiconductor Device Design Optimization

Description: The device optimization is a very important element in semiconductor technology advancement. Its objective is to find a design point for a semiconductor device so that the optimized design goal meets all specified constraints. As in other engineering fields, a nonlinear optimizer is often used for design optimization. One major drawback of using a nonlinear optimizer is that it can only partially explore the design space and return a local optimal solution. This dissertation provides an adaptive optimization design methodology to allow the designer to explore the design space and obtain a globally optimal solution. One key element of our method is to quickly compute the set of all feasible solutions, also called the acceptability region. We described a polytope-based representation for the acceptability region and an adaptive linearization technique for device performance model approximation. These efficiency enhancements have enabled significant speed-up in estimating acceptability regions and allow acceptability regions to be estimated for a larger class of device design tasks. Our linearization technique also provides an efficient mechanism to guarantee the global accuracy of the computed acceptability region. To visualize the acceptability region, we study the orthogonal projection of high-dimensional convex polytopes and propose an output sensitive algorithm for projecting polytopes into two dimensions.
Date: May 1999
Creator: Chang, Chih-Hui, 1967-
Partner: UNT Libraries

Final Report---Next-Generation Solvers for Mixed-Integer Nonlinear Programs: Structure, Search, and Implementation

Description: The mathematical modeling of systems often requires the use of both nonlinear and discrete components. Problems involving both discrete and nonlinear components are known as mixed-integer nonlinear programs (MINLPs) and are among the most challenging computational optimization problems. This research project added to the understanding of this area by making a number of fundamental advances. First, the work demonstrated many novel, strong, tractable relaxations designed to deal with non-convexities arising in mathematical formulation. Second, the research implemented the ideas in software that is available to the public. Finally, the work demonstrated the importance of these ideas on practical applications and disseminated the work through scholarly journals, survey publications, and conference presentations.
Date: May 30, 2013
Creator: Linderoth, Jeff T. & Luedtke, James R.
Partner: UNT Libraries Government Documents Department

Adaptive Control Optimization of Cutting Parameters for High Quality Machining Operations based on Neural Networks and Search Algorithms

Description: This book chapter presents an Adaptive Control with Optimization (ACO) system for optimising a multi-objective function based on material removal rate, quality loss function related to surface roughness, and cutting-tool life subjected to surface roughness specifications constraint.
Date: October 1, 2008
Creator: Abellan, J. V.; Romero, F.; Siller, Héctor R.; Estruch, A. & Vila, C.
Partner: UNT College of Engineering

Final Report of the Simulation Optimization Task Force

Description: This is the final report of the ATLAS Simulation Optimization Task Force, establishedin June of 2007. This note justifies the selected Geant4 version, physics list, and range cuts to be used by the default ATLAS simulation for initial data taking and beyond. The current status of several projects, including detector description, simulation validation, studies of additional Geant4 parameters, and cavern background, are reported.
Date: December 15, 2008
Creator: Collaboration, ATLAS; Rimoldi, A.; Carli, T.; Dell'Acqua, A.; Froidevaux, D.; Gianotti, F. et al.
Partner: UNT Libraries Government Documents Department

Stencil Computation Optimization and Auto-tuning on State-of-the-Art Multicore Architectures

Description: Understanding the most efficient design and utilization of emerging multicore systems is one of the most challenging questions faced by the mainstream and scientific computing industries in several decades. Our work explores multicore stencil (nearest-neighbor) computations -- a class of algorithms at the heart of many structured grid codes, including PDE solvers. We develop a number of effective optimization strategies, and build an auto-tuning environment that searches over our optimizations and their parameters to minimize runtime, while maximizing performance portability. To evaluate the effectiveness of these strategies we explore the broadest set of multicore architectures in the current HPC literature, including the Intel Clovertown, AMD Barcelona, Sun Victoria Falls, IBM QS22 PowerXCell 8i, and NVIDIA GTX280. Overall, our auto-tuning optimization methodology results in the fastest multicore stencil performance to date. Finally, we present several key insights into the architectural trade-offs of emerging multicore designs and their implications on scientific algorithm development.
Date: August 22, 2008
Creator: Datta, Kaushik; Murphy, Mark; Volkov, Vasily; Williams, Samuel; Carter, Jonathan; Oliker, Leonid et al.
Partner: UNT Libraries Government Documents Department

The Coupling of ESP-R and Genopt: A Simple Case Study

Description: This paper describes and demonstrates how to use the optimization program GenOpt with the building energy simulation program ESP-r. GenOpt, a generic optimization program, minimises an objective function that is evaluated by an external simulation program. It has been developed for optimization problems that are computationally expensive and that may have nonsmooth objective functions. ESP-r is a research oriented building simulation program that is well validated and has been used to conduct various building energy analysis studies. In this paper, the necessary file preparations are described and a simple optimization example is presented.
Date: July 1, 2010
Creator: Peeters, Leen; D'haeseleer, William; Ferguson, Alex & Wetter, Michael
Partner: UNT Libraries Government Documents Department

The Telecommunications Network Configuration Optimization Problem

Description: The purpose of telecommunication network configuration optimization is to find the best homing relationship between tandems and switches so as to minimize interswitch traffic, or equivalently to maximize intraswitch traffic. Note that, since minimal interswitch traffic implies minimal IMT utilization, communication costs will also be minimal.
Date: August 1995
Creator: Azizoglu, Mustafa C.
Partner: UNT Libraries

Steepest Descent

Description: The steepest descent method has a rich history and is one of the simplest and best known methods for minimizing a function. While the method is not commonly used in practice due to its slow convergence rate, understanding the convergence properties of this method can lead to a better understanding of many of the more sophisticated optimization methods. Here, we give a short introduction and discuss some of the advantages and disadvantages of this method. Some recent results on modified versions of the steepest descent method are also discussed.
Date: February 12, 2010
Creator: Meza, Juan C.
Partner: UNT Libraries Government Documents Department

Derivative-free optimization methods for surface structuredetermination of nanosystems

Description: Many properties of nanostructures depend on the atomicconfiguration at the surface. One common technique used for determiningthis surface structure is based on the low energy electron diffraction(LEED) method, which uses a high-fidelity physics model to compareexperimental results with spectra computed via a computer simulation.While this approach is highly effective, the computational cost of thesimulations can be prohibitive for large systems. In this work, wepropose the use of a direct search method in conjunction with an additivesurrogate. This surrogate is constructed from a combination of asimplified physics model and an interpolation that is based on thedifferences between the simplified physics model and the full fidelitymodel.
Date: October 18, 2007
Creator: Meza, Juan C.; Garcia-Lekue, Arantzazu; Abramson, Mark A. & Dennis, John E.
Partner: UNT Libraries Government Documents Department

Computing Criticality of Lines in Power Systems

Description: We propose a computationally efficient method based onnonlinear optimization to identify critical lines, failure of which cancause severe blackouts. Our method computes criticality measure for alllines at a time, as opposed to detecting a single vulnerability,providing a global view of the system. This information on criticality oflines can be used to identify multiple contingencies by selectivelyexploring multiple combinations of broken lines. The effectiveness of ourmethod is demonstrated on the IEEE 30 and 118 bus systems, where we canvery quickly detect the most critical lines in the system and identifysevere multiple contingencies.
Date: October 13, 2006
Creator: Pinar, Ali; Reichert, Adam & Lesieutre, Bernard
Partner: UNT Libraries Government Documents Department

Multi-Robot, Multi-Target Particle Swarm Optimization Search in Noisy Wireless Environments

Description: Multiple small robots (swarms) can work together using Particle Swarm Optimization (PSO) to perform tasks that are difficult or impossible for a single robot to accomplish. The problem considered in this paper is exploration of an unknown environment with the goal of finding a target(s) at an unknown location(s) using multiple small mobile robots. This work demonstrates the use of a distributed PSO algorithm with a novel adaptive RSS weighting factor to guide robots for locating target(s) in high risk environments. The approach was developed and analyzed on multiple robot single and multiple target search. The approach was further enhanced by the multi-robot-multi-target search in noisy environments. The experimental results demonstrated how the availability of radio frequency signal can significantly affect robot search time to reach a target.
Date: May 1, 2009
Creator: Derr, Kurt & Manic, Milos
Partner: UNT Libraries Government Documents Department

APPSPACK 4.0 : asynchronous parallel pattern search for derivative-free optimization.

Description: APPSPACK is software for solving unconstrained and bound constrained optimization problems. It implements an asynchronous parallel pattern search method that has been specifically designed for problems characterized by expensive function evaluations. Using APPSPACK to solve optimization problems has several advantages: No derivative information is needed; the procedure for evaluating the objective function can be executed via a separate program or script; the code can be run in serial or parallel, regardless of whether or not the function evaluation itself is parallel; and the software is freely available. We describe the underlying algorithm, data structures, and features of APPSPACK version 4.0 as well as how to use and customize the software.
Date: December 1, 2004
Creator: Gray, Genetha Anne & Kolda, Tamara Gibson
Partner: UNT Libraries Government Documents Department

Flux Control in Networks of Diffusion Paths

Description: A class of optimization problems in networks of intersecting diffusion domains of a special form of thin paths has been considered. The system of equations describing stationary solutions is equivalent to an electrical circuit built of intersecting conductors. The solution of an optimization problem has been obtained and extended to the analogous electrical circuit. The interest in this network arises from, among other applications, an application to wave-particle diffusion through resonant interactions in plasma.
Date: July 8, 2009
Creator: Fisch, A. I. Zhmoginov and N. J.
Partner: UNT Libraries Government Documents Department

Thermodynamics for separation-process technology

Description: When contemplating or designing a separation process, every chemical engineer at once recognizes the thermodynamic boundary conditions that must be satisfied: when a mixture is continuously processed to yield at least partially purified products, energy and mass must be conserved and work must be done. In his daily tasks, a chemical engineer uses thermodynamic concepts as tacit, almost subconscious, knowledge. Thus, qualitative thermodynamics significantly informs process conception at its most fundamental level. However, quantitative design requires detailed knowledge of thermodynamic relations and physical chemistry. Most process engineers, concerned with flow sheets and economics, cannot easily command that detailed knowledge and therefore it is advantageous for them to maintain close contact with those specialists who do. Quantitative chemical thermodynamics provides an opportunity to evaluate possible separation processes not only because it may give support to the process engineer`s bold imagination but also because, when coupled with molecular models, it can significantly reduce the experimental effort required to determine an optimum choice of process alternatives. Six examples are presented to indicate the application of thermodynamics for conventional and possible future separation processes.
Date: October 1, 1995
Creator: Prausnitz, J.M.
Partner: UNT Libraries Government Documents Department

Designs Studies of Low-Aspect Ratio Quasi-Omnigenous Stellarators

Description: Significant progress has been made in the development of new modest-size compact stellarator devices that could test optimization principles for the design of a more attractive reactor. These are 3 and 4 field period low-aspect-ratio quasi-omnigenous (QO) stellarators based on an optimization method that targets improved confinement, stability, ease of coil design, low-aspect-ratio, and low bootstrap current.
Date: October 15, 1998
Creator: Batchelor, D.B.; Carreras, B.A.; Hirshman, S.P.; Lynch, V.E.; Sanchez, R.; Spong, D.A. et al.
Partner: UNT Libraries Government Documents Department

Small Sample Experimental Design Optimization and Repair

Description: The primary goal of using Design of Experiment (DOEx) methods is to extract the maximum amount of information concerning experimental factors and their interactions from as few observations as possible. DOEx methodology allows an experimenter to selectively and systematically adjust process settings to learn which factors have the greatest impact on process and product performance. Using information about these factors, process settings can be adjusted until optimum performance is obtained.
Date: April 1, 1999
Creator: Honson, A. J.; DeCarli, D. & Crowder, S. V.
Partner: UNT Libraries Government Documents Department

Role of twinning in the optimization of the grain boundary character distribution

Description: The grain boundary character distribution (GBCD) is a microstructural property that describes the proportions of �special� and �random� boundaries as defined by the coincident site lattice model. Recently, there has been increased attention on determination of the GBCD and manipulation of the relative fractions in the microstructure through thermomechanical processing in order to improve material� s properties like corrosion and creep resistance. Most of the �optimization� treatments reported in the literature have been performed on fee materials with relatively low stacking fault energies and have resulted in microstructures with high fractions of {Sigma}3, {Sigma}9, and {Sigma}27 boundaries. It could be interpreted that annealing twins are solely required to improve the GBCD. However, in order to optimize the properties, it appears imperative that the formation of annealing twins disrupt the connectivity of the random boundary network, thus implying that {Sigma}3{sup n} reactions and resultant triple lines are critical. Experiments to modify the GBCD of oxygen-free electronic Cu and Inconel 600 through thermomechanical processing are presented and discussed in light of observations of the deformed and recrystallized microstructures.
Date: January 8, 1999
Creator: King, W E; Kumar, M & Schwartz, A J
Partner: UNT Libraries Government Documents Department

Research on Oil Recovery Mechanisms in Heavy Oil Reservoirs

Description: The goal of this project is to increase recovery of heavy oils. Towards that goal studies are being conducted in how to assess the influence of temperature and pressure on the absolute and relative permeability to oil and water and on capillary pressure; to evaluate the effect of different reservoir parameters on the in site combustion process; to develop and understand mechanisms of surfactants on for the reduction of gravity override and channeling of steam; and to improve techniques of formation evaluation.
Date: March 31, 1998
Creator: Castanier, Louis M. & Brigham, William E.
Partner: UNT Libraries Government Documents Department

Reactive Separations via a Hydrothermally Stable Hydrogen Selective Membrane. Final Report

Description: In this SBIR Phase I program, we have successfully completed the fabrication of SiC-based hydrogen selective membranes suitable for use as a membrane reactor for steam-methane reforming applications. Hydrothermal stability was performed for selected membrane to demonstrate their stability for appx. 50 hours under the proposed reforming condition. In addition, several mechanistic study was conducted to elucidate the SiC membrane formation mechanism. This understanding will facilitate membrane optimization work to be proposed for the Phase II study. The reaction study was postponed to the Phase II study.
Date: October 29, 2002
Creator: Ciora, R. J. & Liu, P. KT.
Partner: UNT Libraries Government Documents Department

Optimizing Non-pharmaceutical Interventions Using Multi-coaffiliation Networks

Description: Computational modeling is of fundamental significance in mapping possible disease spread, and designing strategies for its mitigation. Conventional contact networks implement the simulation of interactions as random occurrences, presenting public health bodies with a difficult trade off between a realistic model granularity and robust design of intervention strategies. Recently, researchers have been investigating the use of agent-based models (ABMs) to embrace the complexity of real world interactions. At the same time, theoretical approaches provide epidemiologists with general optimization models in which demographics are intrinsically simplified. The emerging study of affiliation networks and co-affiliation networks provide an alternative to such trade off. Co-affiliation networks maintain the realism innate to ABMs while reducing the complexity of contact networks into distinctively smaller k-partite graphs, were each partition represent a dimension of the social model. This dissertation studies the optimization of intervention strategies for infectious diseases, mainly distributed in school systems. First, concepts of synthetic populations and affiliation networks are extended to propose a modified algorithm for the synthetic reconstruction of populations. Second, the definition of multi-coaffiliation networks is presented as the main social model in which risk is quantified and evaluated, thereby obtaining vulnerability indications for each school in the system. Finally, maximization of the mitigation coverage and minimization of the overall cost of intervention strategies are proposed and compared, based on centrality measures.
Date: May 2013
Creator: Loza, Olivia G.
Partner: UNT Libraries