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Solving computationally expensive engineering problems

Computational complexity is a serious bottleneck for the design process in virtually any engineering area. While migration from prototyping and experimental-based design validation to verification using computer simulation models is inevitable and has a number of advantages, high computational costs...

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Detalles Bibliográficos
Autores principales: Koziel, Slawomir, Leifsson, Leifur, Yang, Xin-She
Lenguaje:eng
Publicado: Springer 2014
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-08985-0
http://cds.cern.ch/record/1968837
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author Koziel, Slawomir
Leifsson, Leifur
Yang, Xin-She
author_facet Koziel, Slawomir
Leifsson, Leifur
Yang, Xin-She
author_sort Koziel, Slawomir
collection CERN
description Computational complexity is a serious bottleneck for the design process in virtually any engineering area. While migration from prototyping and experimental-based design validation to verification using computer simulation models is inevitable and has a number of advantages, high computational costs of accurate, high-fidelity simulations can be a major issue that slows down the development of computer-aided design methodologies, particularly those exploiting automated design improvement procedures, e.g., numerical optimization. The continuous increase of available computational resources does not always translate into shortening of the design cycle because of the growing demand for higher accuracy and necessity to simulate larger and more complex systems. Accurate simulation of a single design of a given system may be as long as several hours, days or even weeks, which often makes design automation using conventional methods impractical or even prohibitive. Additional problems include numerical noise often present in the simulation data, possible presence of multiple locally optimum designs, as well as multiple conflicting objectives. In this edited book, various techniques that can alleviate solving computationally expensive engineering design problems are presented. One of the most promising approaches is the use of fast replacement models, so-called surrogates, that reliably represent the expensive, simulation-based model of the system/device of interest but they are much cheaper and analytically tractable. Here, a group of international experts summarize recent developments in the area and demonstrate applications in various disciplines of engineering and science. The main purpose of the work is to provide the basic concepts and formulations of the surrogate-based modeling and optimization paradigm, as well as discuss relevant modeling techniques, optimization algorithms and design procedures. Therefore, this book should be useful to researchers and engineers from any discipline where computationally heavy simulations are used on daily basis in the design process.
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spelling cern-19688372021-04-22T07:00:31Zdoi:10.1007/978-3-319-08985-0http://cds.cern.ch/record/1968837engKoziel, SlawomirLeifsson, LeifurYang, Xin-SheSolving computationally expensive engineering problemsMathematical Physics and MathematicsComputational complexity is a serious bottleneck for the design process in virtually any engineering area. While migration from prototyping and experimental-based design validation to verification using computer simulation models is inevitable and has a number of advantages, high computational costs of accurate, high-fidelity simulations can be a major issue that slows down the development of computer-aided design methodologies, particularly those exploiting automated design improvement procedures, e.g., numerical optimization. The continuous increase of available computational resources does not always translate into shortening of the design cycle because of the growing demand for higher accuracy and necessity to simulate larger and more complex systems. Accurate simulation of a single design of a given system may be as long as several hours, days or even weeks, which often makes design automation using conventional methods impractical or even prohibitive. Additional problems include numerical noise often present in the simulation data, possible presence of multiple locally optimum designs, as well as multiple conflicting objectives. In this edited book, various techniques that can alleviate solving computationally expensive engineering design problems are presented. One of the most promising approaches is the use of fast replacement models, so-called surrogates, that reliably represent the expensive, simulation-based model of the system/device of interest but they are much cheaper and analytically tractable. Here, a group of international experts summarize recent developments in the area and demonstrate applications in various disciplines of engineering and science. The main purpose of the work is to provide the basic concepts and formulations of the surrogate-based modeling and optimization paradigm, as well as discuss relevant modeling techniques, optimization algorithms and design procedures. Therefore, this book should be useful to researchers and engineers from any discipline where computationally heavy simulations are used on daily basis in the design process.Springeroai:cds.cern.ch:19688372014
spellingShingle Mathematical Physics and Mathematics
Koziel, Slawomir
Leifsson, Leifur
Yang, Xin-She
Solving computationally expensive engineering problems
title Solving computationally expensive engineering problems
title_full Solving computationally expensive engineering problems
title_fullStr Solving computationally expensive engineering problems
title_full_unstemmed Solving computationally expensive engineering problems
title_short Solving computationally expensive engineering problems
title_sort solving computationally expensive engineering problems
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-319-08985-0
http://cds.cern.ch/record/1968837
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