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Aerospace system analysis and optimi...

Brevault, Loic.

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Aerospace system analysis and optimization in uncertainty

Record Type:	Electronic resources : Monograph/item
Title/Author:	Aerospace system analysis and optimization in uncertainty/ by Loic Brevault, Mathieu Balesdent, Jerome Morio.
Author:	Brevault, Loic.
other author:	Balesdent, Mathieu.
Published:	Cham :Springer International Publishing : : 2020.,
Description:	xxv, 477 p. :ill., digital ;24 cm.
[NT 15003449]:	Part I Aerospace system multidisciplinary modeling and uncertainty characterization -- 1 Multidisciplinary system modeling and optimization -- 2 Uncertainty characterization and modeling -- Part II Single discipline problem: uncertainty propagation, reliability analysis and optimization -- 3 Uncertainty propagation and sensitivity analysis -- 4 Reliability analysis -- 5 Problem formulations and optimization algorithms -- Part III Multidisciplinary Optimization under uncertainty -- 6 Uncertainty propagation for multidisciplinary problems -- 7 Uncertainty-based MDO -- Part IV MDO related issues: multi-fidelity, multi-objective and mixed continuous / discrete optimization -- 8 Multi-fidelity for MDO using Gaussian Processes -- 9 Multi-objective and mixed MDO -- Part V Case studies -- 10 Civil aircraft vehicle design -- 11 Blended Wing Body design -- 12 Expendable and reusable launch vehicle design -- Appendix: List of librairies used for the simulations.
Contained By:	Springer Nature eBook
Subject:	Aerospace engineering. -
Online resource:	https://doi.org/10.1007/978-3-030-39126-3
ISBN:	9783030391263

Aerospace system analysis and optimization in uncertainty
Brevault, Loic.

Aerospace system analysis and optimization in uncertainty[electronic resource] /by Loic Brevault, Mathieu Balesdent, Jerome Morio. - Cham :Springer International Publishing :2020. - xxv, 477 p. :ill., digital ;24 cm. - Springer optimization and its applications,v.1561931-6828 ;. - Springer optimization and its applications ;v.156..

Part I Aerospace system multidisciplinary modeling and uncertainty characterization -- 1 Multidisciplinary system modeling and optimization -- 2 Uncertainty characterization and modeling -- Part II Single discipline problem: uncertainty propagation, reliability analysis and optimization -- 3 Uncertainty propagation and sensitivity analysis -- 4 Reliability analysis -- 5 Problem formulations and optimization algorithms -- Part III Multidisciplinary Optimization under uncertainty -- 6 Uncertainty propagation for multidisciplinary problems -- 7 Uncertainty-based MDO -- Part IV MDO related issues: multi-fidelity, multi-objective and mixed continuous / discrete optimization -- 8 Multi-fidelity for MDO using Gaussian Processes -- 9 Multi-objective and mixed MDO -- Part V Case studies -- 10 Civil aircraft vehicle design -- 11 Blended Wing Body design -- 12 Expendable and reusable launch vehicle design -- Appendix: List of librairies used for the simulations.

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.

ISBN: 9783030391263

Standard No.: 10.1007/978-3-030-39126-3doiSubjects--Topical Terms:

1002622
Aerospace engineering.

LC Class. No.: TL545

Dewey Class. No.: 629.1

Aerospace system analysis and optimization in uncertainty
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100 1 $a Brevault, Loic. $3 3526033
245 1 0 $a Aerospace system analysis and optimization in uncertainty $h [electronic resource] / $c by Loic Brevault, Mathieu Balesdent, Jerome Morio.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xxv, 477 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer optimization and its applications, $x 1931-6828 ; $v v.156
505 0 $a Part I Aerospace system multidisciplinary modeling and uncertainty characterization -- 1 Multidisciplinary system modeling and optimization -- 2 Uncertainty characterization and modeling -- Part II Single discipline problem: uncertainty propagation, reliability analysis and optimization -- 3 Uncertainty propagation and sensitivity analysis -- 4 Reliability analysis -- 5 Problem formulations and optimization algorithms -- Part III Multidisciplinary Optimization under uncertainty -- 6 Uncertainty propagation for multidisciplinary problems -- 7 Uncertainty-based MDO -- Part IV MDO related issues: multi-fidelity, multi-objective and mixed continuous / discrete optimization -- 8 Multi-fidelity for MDO using Gaussian Processes -- 9 Multi-objective and mixed MDO -- Part V Case studies -- 10 Civil aircraft vehicle design -- 11 Blended Wing Body design -- 12 Expendable and reusable launch vehicle design -- Appendix: List of librairies used for the simulations.
520 $a 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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650 0 $a Systems engineering. $3 572511
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650 2 4 $a Algorithms. $3 536374
700 1 $a Balesdent, Mathieu. $3 3526034
700 1 $a Morio, Jerome. $3 3526035
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830 0 $a Springer optimization and its applications ; $v v.156. $3 3526036
856 4 0 $u https://doi.org/10.1007/978-3-030-39126-3
950 $a Mathematics and Statistics (SpringerNature-11649)