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Aerospace system analysis and optimization in uncertainty

Spotlighting the field of Multidisciplinary Design Optimization (MDO), this book illustrates and implements state-of-the-art methodologies within the complex process of aerospace system design under uncertainties. The book provides approaches to integrating a multitude of components and constraints...

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Detalles Bibliográficos
Autores principales: Brevault, Loïc, Balesdent, Mathieu, Morio, Jérôme
Lenguaje:eng
Publicado: Springer 2020
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-030-39126-3
http://cds.cern.ch/record/2729506
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author Brevault, Loïc
Balesdent, Mathieu
Morio, Jérôme
author_facet Brevault, Loïc
Balesdent, Mathieu
Morio, Jérôme
author_sort Brevault, Loïc
collection CERN
description Spotlighting the field of Multidisciplinary Design Optimization (MDO), this book illustrates and implements state-of-the-art methodologies within the complex process of aerospace system design under uncertainties. The book provides approaches to integrating a multitude of components and constraints with the ultimate goal of reducing design cycles. Insights on a vast assortment of problems are provided, including discipline modeling, sensitivity analysis, uncertainty propagation, reliability analysis, and global multidisciplinary optimization. The extensive range of topics covered include areas of current open research. This Work is destined to become a fundamental reference for aerospace systems engineers, researchers, as well as for practitioners and engineers working in areas of optimization and uncertainty. Part I is largely comprised of fundamentals. Part II presents methodologies for single discipline problems with a review of existing uncertainty propagation, reliability analysis, and optimization techniques. Part III is dedicated to the uncertainty-based MDO and related issues. Part IV deals with three MDO related issues: the multifidelity, the multi-objective optimization and the mixed continuous/discrete optimization and Part V is devoted to test cases for aerospace vehicle design.
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spelling cern-27295062021-04-21T18:05:06Zdoi:10.1007/978-3-030-39126-3http://cds.cern.ch/record/2729506engBrevault, LoïcBalesdent, MathieuMorio, JérômeAerospace system analysis and optimization in uncertaintyMathematical Physics and MathematicsSpotlighting the field of Multidisciplinary Design Optimization (MDO), this book illustrates and implements state-of-the-art methodologies within the complex process of aerospace system design under uncertainties. The book provides approaches to integrating a multitude of components and constraints with the ultimate goal of reducing design cycles. Insights on a vast assortment of problems are provided, including discipline modeling, sensitivity analysis, uncertainty propagation, reliability analysis, and global multidisciplinary optimization. The extensive range of topics covered include areas of current open research. This Work is destined to become a fundamental reference for aerospace systems engineers, researchers, as well as for practitioners and engineers working in areas of optimization and uncertainty. Part I is largely comprised of fundamentals. Part II presents methodologies for single discipline problems with a review of existing uncertainty propagation, reliability analysis, and optimization techniques. Part III is dedicated to the uncertainty-based MDO and related issues. Part IV deals with three MDO related issues: the multifidelity, the multi-objective optimization and the mixed continuous/discrete optimization and Part V is devoted to test cases for aerospace vehicle design.Springeroai:cds.cern.ch:27295062020
spellingShingle Mathematical Physics and Mathematics
Brevault, Loïc
Balesdent, Mathieu
Morio, Jérôme
Aerospace system analysis and optimization in uncertainty
title Aerospace system analysis and optimization in uncertainty
title_full Aerospace system analysis and optimization in uncertainty
title_fullStr Aerospace system analysis and optimization in uncertainty
title_full_unstemmed Aerospace system analysis and optimization in uncertainty
title_short Aerospace system analysis and optimization in uncertainty
title_sort aerospace system analysis and optimization in uncertainty
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-030-39126-3
http://cds.cern.ch/record/2729506
work_keys_str_mv AT brevaultloic aerospacesystemanalysisandoptimizationinuncertainty
AT balesdentmathieu aerospacesystemanalysisandoptimizationinuncertainty
AT moriojerome aerospacesystemanalysisandoptimizationinuncertainty