Optimization Under Uncertainty with Applications to Aerospace Engineering
Editat de Massimiliano Vasileen Limba Engleză Paperback – 15 feb 2022
In an expanding world with limited resources, optimization and uncertainty quantification have become a necessity when handling complex systems and processes. This book provides the foundational material necessary for those who wish to embark on advanced research at the limits of computability, collecting together lecture material from leading experts across the topics of optimization, uncertainty quantification and aerospace engineering.
The aerospace sector in particular has stringent performance requirements on highly complex systems, for which solutions are expected to be optimal and reliable at the same time. The text covers a wide range of techniques and methods, from polynomial chaos expansions for uncertainty quantification to Bayesian and Imprecise Probability theories, and from Markov chains to surrogate models based on Gaussian processes. The book will serve as a valuable tool for practitioners, researchers and PhD students.
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Specificații
ISBN-13: 9783030601683
ISBN-10: 3030601684
Ilustrații: VI, 573 p. 155 illus., 108 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.8 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland
ISBN-10: 3030601684
Ilustrații: VI, 573 p. 155 illus., 108 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.8 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland
Cuprins
- Introduction to Spectral Methods for Uncertainty Quantification. - Introduction to Imprecise Probabilities. - Uncertainty Quantification in Lasso-Type Regularization Problems. - Reliability Theory. - An Introduction to Imprecise Markov Chains. - Fundamentals of Filtering. - Introduction to Optimisation. - An Introduction to Many-Objective Evolutionary Optimization. - Multilevel Optimisation. - Sequential Parameter Optimization for Mixed-Discrete Problems. - Parameter Control in Evolutionary Optimisation. - Response Surface Methodology. - Risk Measures in the Context of Robust and Reliability Based Optimization. - Best Practices for Surrogate Based Uncertainty Quantification in Aerodynamics and Application to Robust Shape Optimization. - In-flight Icing: Modeling, Prediction, and Uncertainty. - Uncertainty Treatment Applications: High-Enthalpy Flow Ground Testing. - Introduction to Evidence-Based Robust Optimisation.
Notă biografică
Massimiliano Vasile is a Professor of Space Systems Engineering and Director of the Aerospace Centre of Excellence in the Department of Mechanical & Aerospace Engineering at the University of Strathclyde. Previous to this, he was a Senior Lecturer in the Department of Aerospace Engineering and Head of Research for the Space Advanced Research Team at the University of Glasgow. Before starting his academic career in 2004, he was the first member of the European Space Agency (ESA) Advanced Concepts Team (ACT) and initiator of the ACT research stream on global trajectory optimization, mission analysis and biomimicry. His research interests include Computational Optimization, Robust Multi-Disciplinary Design and Optimization Under Uncertainty.
More recently, Professor Vasile has undertaken extensive research on techniques for asteroid manipulation as well as the sustainability of the space environment. His research has been funded by the European Space Agency, EPSRC, the Planetary Society and the European Commission. He was the Lead of the Stardust Marie Curie ITN on debris and asteroid manipulation and is now leading the UTOPIAE (Uncertainty Treatment and Optimization In Aerospace Engineering) Marie Curie ETN on optimization under uncertainty and uncertainty quantification in complex aerospace engineering systems.
Textul de pe ultima copertă
In an expanding world with limited resources, optimization and uncertainty quantification have become a necessity when handling complex systems and processes. This book provides the foundational material necessary for those who wish to embark on advanced research at the limits of computability, collecting together lecture material from leading experts across the topics of optimization, uncertainty quantification and aerospace engineering.
The aerospace sector in particular has stringent performance requirements on highly complex systems, for which solutions are expected to be optimal and reliable at the same time. The text covers a wide range of techniques and methods, from polynomial chaos expansions for uncertainty quantification to Bayesian and Imprecise Probability theories, and from Markov chains to surrogate models based on Gaussian processes. The book will serve as a valuable tool for practitioners, researchers and PhD students.
Caracteristici
Gathers lecture notes from leading experts in the field into one authoritative resource, providing readers with an essential starting point for cutting edge research
Provides the most modern techniques for optimization under uncertainty, many of which are outdated or not covered in existing texts on the subject
Includes never before published sections on optimization under uncertainty with imprecise probabilities, as well as new methods of uncertainty quantification based on imprecise probabilities and expert elicitation
Provides the most modern techniques for optimization under uncertainty, many of which are outdated or not covered in existing texts on the subject
Includes never before published sections on optimization under uncertainty with imprecise probabilities, as well as new methods of uncertainty quantification based on imprecise probabilities and expert elicitation