國立高雄大學圖資館 |

Language: English

Back

Aerospace system analysis and optimi...

Balesdent, Mathieu.

Aerospace system analysis and optimization in uncertainty

Record Type:	Electronic resources : Monograph/item
Title/Author:	Aerospace system analysis and optimization in uncertaintyby 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.
Contained By:	Springer Nature eBook
Subject:	Aerospace engineering.
Online resource:	https://doi.org/10.1007/978-3-030-39126-3
ISBN:	9783030391263$q(electronic bk.)

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. 3..

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$q(electronic bk.)

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

324294
Aerospace engineering.

LC Class. No.: TL545

Dewey Class. No.: 629.1

Aerospace system analysis and optimization in uncertainty
LDR:03358nmm a2200337 a 4500 001 585403
003 DE-He213
005 20201228133529.0
006 m d
007 cr nn 008maaau
008 210311s2020 sz s 0 eng d
020 $a 9783030391263$q(electronic bk.)
020 $a 9783030391256$q(paper)
024 7 $a 10.1007/978-3-030-39126-3 $2 doi
035 $a 978-3-030-39126-3
040 $a GP $c GP
041 0 $a eng
050 4 $a TL545
072 7 $a PBU $2 bicssc
072 7 $a MAT003000 $2 bisacsh
072 7 $a PBU $2 thema
082 0 4 $a 629.1 $2 23
090 $a TL545 $b .B846 2020
100 1 $a Brevault, Loic. $3 876403
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.
650 0 $a Aerospace engineering. $3 324294
650 0 $a Systems engineering. $3 182491
650 1 4 $a Optimization. $3 274084
650 2 4 $a Aerospace Technology and Astronautics. $3 309707
650 2 4 $a Systems Theory, Control. $3 274654
650 2 4 $a Numerical Analysis. $3 275681
650 2 4 $a Algorithms. $3 184661
700 1 $a Balesdent, Mathieu. $3 876404
700 1 $a Morio, Jerome. $3 876405
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Springer optimization and its applications ; $v v. 3. $3 440366
856 4 0 $u https://doi.org/10.1007/978-3-030-39126-3
950 $a Mathematics and Statistics (SpringerNature-11649)