Aerospace System Analysis and Optimization in Uncertainty: Springer Optimization and Its Applications, cartea 156
Autor Loïc Brevault, Mathieu Balesdent, Jérôme Morioen Limba Engleză Paperback – 27 aug 2021
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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Specificații
ISBN-13: 9783030391287
ISBN-10: 3030391280
Pagini: 477
Ilustrații: XXV, 477 p. 348 illus., 319 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.77 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Springer Optimization and Its Applications
Locul publicării:Cham, Switzerland
ISBN-10: 3030391280
Pagini: 477
Ilustrații: XXV, 477 p. 348 illus., 319 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.77 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Springer Optimization and Its Applications
Locul publicării:Cham, Switzerland
Cuprins
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.
Textul de pe ultima copertă
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.
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.
Caracteristici
Examines the aerospace system design process and provides case studies Spotlights Multidisciplinary Design Optimization (MDO) within the complex process of aerospace design Features new techniques for uncertainty propagation, reliability and optimization Applies a global approach to realistic complex systems