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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.
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.
14th International Conference on Turbochargers and Turbocharging addresses current and novel turbocharging system choices and components with a renewed emphasis to address the challenges posed by emission regulations and market trends. The contributions focus on the development of air management solutions and waste heat recovery ideas to support thermal propulsion systems leading to high thermal efficiency and low exhaust emissions. These can be in the form of internal combustion engines or other propulsion technologies (eg. Fuel cell) in both direct drive and hybridised configuration. 14th International Conference on Turbochargers and Turbocharging also provides a particular focus on turbochargers, superchargers, waste heat recovery turbines and related air managements components in both electrical and mechanical forms.
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.
Zusammenfassung: This book develops robust design and assessment of product and production from viewpoint of system theory, which is quantized with the introduction of brand new concept of preferable probability and its assessment. It aims to provide a new idea and novel way to robust design and assessment of product and production and relevant problems. Robust design and assessment of product and production is attractive to both customer and producer since the stability and insensitivity of a product's quality to uncontrollable factors reflect its value. Taguchi method has been used to conduct robust design and assessment of product and production for half a century, but its rationality is criticized by statisticians due to its casting of both mean value of a response and its dispersion into one index, which doesn't characterize the issue of simultaneous robust design of above two independent responses sufficiently, so an appropriate approach is needed. The preference or role of a response in the evaluation is indicated by using preferable probability as the unique index. Thus, the rational approach for robust design and assessment of product and production is formulated by means of probabilistic multi-objective optimization, which reveals the simultaneous robust designs of both mean value of a response and its dispersion in manner of joint probability. Besides, defuzzification and fuzzification measurements are involved as preliminary approaches for robust assessment, the latter provides miraculous treatment for the 'target the best' case flexibly
This volume presents up-to-date material on the state of the art in evolutionary and deterministic methods for design, optimization and control with applications to industrial and societal problems from Europe, Asia, and America. EUROGEN 2015 was the 11th of a series of International Conferences devoted to bringing together specialists from universities, research institutions and industries developing or applying evolutionary and deterministic methods in design optimization, with emphasis on solving industrial and societal problems. The conference was organised around a number of parallel symposia, regular sessions, and keynote lectures focused on surrogate-based optimization in aerodynamic design, adjoint methods for steady & unsteady optimization, multi-disciplinary design optimization, holistic optimization in marine design, game strategies combined with evolutionary computation, optimization under uncertainty, topology optimization, optimal planning, shape optimization, and production scheduling.
This book discusses the recent advances in aircraft design methodologies. It provides an overview of topics such as shape optimization, robust design and aeroelasticity, focusing on fluid-structure numerical methodologies to address static and dynamic aeroelastic problems. It demonstrates that the capability to evaluate the interaction between aerodynamics, inertia and elastic forces is important to avoid drag penalties, control system efficiency loss and generation of potentially dangerous phenomena, such as divergence, control reversal and flutter. The book particularly highlights the advances in “high fidelity” CFD-CSM coupling, describing the latest experimental research to validate the numerical fluid-structure interaction analysis methodologies resulting from the EU-funded RBF4AERO and RIBES projects.
AI Assurance: Towards Trustworthy, Explainable, Safe, and Ethical AI provides readers with solutions and a foundational understanding of the methods that can be applied to test AI systems and provide assurance. Anyone developing software systems with intelligence, building learning algorithms, or deploying AI to a domain-specific problem (such as allocating cyber breaches, analyzing causation at a smart farm, reducing readmissions at a hospital, ensuring soldiers' safety in the battlefield, or predicting exports of one country to another) will benefit from the methods presented in this book. As AI assurance is now a major piece in AI and engineering research, this book will serve as a guide for researchers, scientists and students in their studies and experimentation. Moreover, as AI is being increasingly discussed and utilized at government and policymaking venues, the assurance of AI systems—as presented in this book—is at the nexus of such debates. - Provides readers with an in-depth understanding of how to develop and apply Artificial Intelligence in a valid, explainable, fair and ethical manner - Includes various AI methods, including Deep Learning, Machine Learning, Reinforcement Learning, Computer Vision, Agent-Based Systems, Natural Language Processing, Text Mining, Predictive Analytics, Prescriptive Analytics, Knowledge-Based Systems, and Evolutionary Algorithms - Presents techniques for efficient and secure development of intelligent systems in a variety of domains, such as healthcare, cybersecurity, government, energy, education, and more - Covers complete example datasets that are associated with the methods and algorithms developed in the book
This handbook analyzes and develops methods and models to optimize solutions for energy access (for industry and the general world population alike) in terms of reliability and sustainability. With a focus on improving the performance of energy systems, it brings together state-of-the-art research on reliability enhancement, intelligent development, simulation and optimization, as well as sustainable development of energy systems. It helps energy stakeholders and professionals learn the methodologies needed to improve the reliability of energy supply-and-demand systems, achieve more efficient long-term operations, deal with uncertainties in energy systems, and reduce energy emissions. Highlighting novel models and their applications from leading experts in this important area, this book will appeal to researchers, students, and engineers in the various domains of smart energy systems and encourage them to pursue research and development in this exciting and highly relevant field.
This book presents improved and extended versions of selected papers from EUROGEN 2019, a conference with interest on developing or applying evolutionary and deterministic methods in optimization of design and emphasizing on industrial and societal applications.