Optimization Under Uncertainty With Applications To Aerospace Engineering
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| Author | : Massimiliano Vasile |
| Publisher | : Springer Nature |
| Total Pages | : 573 |
| Release | : 2021-02-15 |
| Genre | : Science |
| ISBN | : 3030601668 |
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.
| Author | : Massimiliano Vasile |
| Publisher | : Springer Nature |
| Total Pages | : 448 |
| Release | : 2022-01-27 |
| Genre | : Technology & Engineering |
| ISBN | : 3030805425 |
The 2020 International Conference on Uncertainty Quantification & Optimization gathered together internationally renowned researchers in the fields of optimization and uncertainty quantification. The resulting proceedings cover all related aspects of computational uncertainty management and optimization, with particular emphasis on aerospace engineering problems. The book contributions are organized under four major themes: Applications of Uncertainty in Aerospace & Engineering Imprecise Probability, Theory and Applications Robust and Reliability-Based Design Optimisation in Aerospace Engineering Uncertainty Quantification, Identification and Calibration in Aerospace Models This proceedings volume is useful across disciplines, as it brings the expertise of theoretical and application researchers together in a unified framework.
| Author | : Loïc Brevault |
| Publisher | : Springer Nature |
| Total Pages | : 477 |
| Release | : 2020-08-26 |
| Genre | : Mathematics |
| ISBN | : 3030391264 |
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.
| Author | : Louis J. M. Aslett |
| Publisher | : Springer Nature |
| Total Pages | : 148 |
| Release | : 2022 |
| Genre | : |
| ISBN | : 3030836401 |
This open access book provides an introduction to uncertainty quantification in engineering. Starting with preliminaries on Bayesian statistics and Monte Carlo methods, followed by material on imprecise probabilities, it then focuses on reliability theory and simulation methods for complex systems. The final two chapters discuss various aspects of aerospace engineering, considering stochastic model updating from an imprecise Bayesian perspective, and uncertainty quantification for aerospace flight modelling. Written by experts in the subject, and based on lectures given at the Second Training School of the European Research and Training Network UTOPIAE (Uncertainty Treatment and Optimization in Aerospace Engineering), which took place at Durham University (United Kingdom) from 2 to 6 July 2018, the book offers an essential resource for students as well as scientists and practitioners.
| Author | : Weifei Hu |
| Publisher | : Springer Nature |
| Total Pages | : 282 |
| Release | : 2023-12-22 |
| Genre | : Mathematics |
| ISBN | : 3031492080 |
This book introduces the fundamentals of probability, statistical, and reliability concepts, the classical methods of uncertainty quantification and analytical reliability analysis, and the state-of-the-art approaches of design optimization under uncertainty (e.g., reliability-based design optimization and robust design optimization). The topics include basic concepts of probability and distributions, uncertainty quantification using probabilistic methods, classical reliability analysis methods, time-variant reliability analysis methods, fundamentals of deterministic design optimization, reliability-based design optimization, robust design optimization, other methods of design optimization under uncertainty, and engineering applications of design optimization under uncertainty.
| Author | : Charles Hirsch |
| Publisher | : Springer |
| Total Pages | : 799 |
| Release | : 2018-07-21 |
| Genre | : Technology & Engineering |
| ISBN | : 331977767X |
This book covers cutting-edge findings related to uncertainty quantification and optimization under uncertainties (i.e. robust and reliable optimization), with a special emphasis on aeronautics and turbomachinery, although not limited to these fields. It describes new methods for uncertainty quantification, such as non-intrusive polynomial chaos, collocation methods, perturbation methods, as well as adjoint based and multi-level Monte Carlo methods. It includes methods for characterization of most influential uncertainties, as well as formulations for robust and reliable design optimization. A distinctive element of the book is the unique collection of test cases with prescribed uncertainties, which are representative of the current engineering practice of the industrial consortium partners involved in UMRIDA, a level 1 collaborative project within the European Commission's Seventh Framework Programme (FP7). All developed methods are benchmarked against these industrial challenges. Moreover, the book includes a section dedicated to Best Practice Guidelines for uncertainty quantification and robust design optimization, summarizing the findings obtained by the consortium members within the UMRIDA project. All in all, the book offers a authoritative guide to cutting-edge methodologies for uncertainty management in engineering design, covers a wide range of applications and discusses new ideas for future research and interdisciplinary collaborations.
| Author | : Laurence William Cook |
| Publisher | : |
| Total Pages | : |
| Release | : 2018 |
| Genre | : |
| ISBN | : |
| Author | : Debiao Meng |
| Publisher | : CRC Press |
| Total Pages | : 349 |
| Release | : 2024-09-02 |
| Genre | : Technology & Engineering |
| ISBN | : 1040113516 |
In the realm of engineering structures design, the inevitability of uncertainties poses a significant challenge. Uncertainty-Based Multidisciplinary Design and Optimization (UBMDO) stands out for its dual ability to precisely quantify the impact of uncertain variables and harness the potential of multidisciplinary design and optimization, thereby attracting considerable attention. From basic theory to advanced applications, this book helps readers achieve more efficient and reliable design optimization in complex systems through rich case studies and practical technical guidance. The book systematically expounds the fundamental theories and methods of UBMDO, encompassing crucial techniques such as uncertainty modeling, sensitivity analysis, approximate modeling, and uncertainty-based optimization. It also introduces various uncertainty analysis methods, such as stochastic, non-probabilistic, and hybrid approaches, aiding readers in comprehending and managing uncertainty within systems. Through diverse practical engineering cases in fields like machinery, aerospace, and energy, it illustrates the specific application and implementation process of the UBMDO method. Rich graphics, algorithms, and simulation results augment the practicality and applicability of the theoretical knowledge. Furthermore, it explores in depth the future development trends and challenges of UBMDO, sparking innovative thinking and research interests among readers in this field. Multidisciplinary Design Optimization of Complex Structures Under Uncertainty caters to a diverse audience: Engineers specializing in multidisciplinary design optimization are given the tools to master uncertainty management, and researchers in related fields will gain important theoretical insights and practical guidance in uncertainty analysis. Additionally, scholars and educators can utilize the book as a comprehensive resource for advanced courses, enabling students to grasp the latest UBMDO applications. Decision makers and managers handling complex systems can extract methods from the book, facilitating improved risk assessment, and strategic development through uncertainty-based optimization.
| Author | : Manish C. Tayal |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2003 |
| Genre | : |
| ISBN | : |
| Author | : |
| Publisher | : |
| Total Pages | : 64 |
| Release | : 2002 |
| Genre | : Space vehicles |
| ISBN | : |
