Overview
- 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
Part of the book series: Springer Optimization and Its Applications (SOIA, volume 156)
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Table of contents (12 chapters)
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Front Matter
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Aerospace System Multidisciplinary Modeling and Uncertainty Characterization
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Front Matter
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Single Discipline Problem: Uncertainty Propagation, Reliability Analysis and Optimization
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Front Matter
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Multidisciplinary Optimization Under Uncertainty
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Front Matter
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MDO Related Issues: Multi-Fidelity, Multi-Objective and Mixed Continuous/Discrete Optimization
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Front Matter
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Case Studies
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Front Matter
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Back Matter
Keywords
- Aerospace system design
- global multidisciplinary optimization
- Multidisciplinary Design Optimization
- complex system design
- uncertainty characterization
- reliability analysis
- Uncertainty propagation
- optimization problems
- optimization algorithms
- Evolutionary-based algorithms
- Sequential Optimization
- Qualitative analysis
- Quantitative heuristic approaches
- Variance-based methods
- MDO
About this book
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.
Authors and Affiliations
Bibliographic Information
Book Title: Aerospace System Analysis and Optimization in Uncertainty
Authors: Loïc Brevault, Mathieu Balesdent, Jérôme Morio
Series Title: Springer Optimization and Its Applications
DOI: https://doi.org/10.1007/978-3-030-39126-3
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-39125-6Published: 27 August 2020
Softcover ISBN: 978-3-030-39128-7Published: 27 August 2021
eBook ISBN: 978-3-030-39126-3Published: 26 August 2020
Series ISSN: 1931-6828
Series E-ISSN: 1931-6836
Edition Number: 1
Number of Pages: XXV, 477
Number of Illustrations: 29 b/w illustrations, 319 illustrations in colour
Topics: Optimization, Aerospace Technology and Astronautics, Systems Theory, Control, Numerical Analysis, Algorithms