Solving Computationally Expensive Engineering Problems | Methods and Applications

Slawomir Koziel (u. a.)

ISBN 10: 3319349783 / ISBN 13: 9783319349787

Edité par Springer, 2016

A propos de cet article

Solving Computationally Expensive Engineering Problems | Methods and Applications | Slawomir Koziel (u. a.) | Taschenbuch | viii | Englisch | 2016 | Springer | EAN 9783319349787 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

N° de réf. du vendeur 111861454

Détails bibliographiques

• Titre: Solving Computationally Expensive Engineering Problems | Methods and Applications
• Éditeur: Springer
• Date de parution: 2016
• Langue: anglais
• ISBN à 10 chiffres: 3319349783
• ISBN à 13 chiffres: 9783319349787
• Reliure: Taschenbuch
• État de l'article: Neu
• Dimensions: 235 L x 155 H x 18 P (en millimètres) 235 millimètres de largeur par 155 millimètres de hauteur par 18 millimètres de profondeur
• Poids: 585 grammes
• Catalogues du vendeur:
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Synopsis

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.