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.

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.

The book exposes three alternative and competing approaches to uncertainty analysis in engineering. It is composed of some essays on various sub-topics like random vibrations, probabilistic reliability, fuzzy-sets-based analysis, unknown-but-bounded variables, stochastic linearization, possible difficulties with stochastic analysis of structures.

In the current, increasingly aggressive business environment, crucial decisions about product design often involve significant uncertainty. Highlighting the competitive advantage available from using risk-based reliability design, Engineering Design Reliability Applications: For the Aerospace, Automotive, and Ship Industries provides an overview of

The solutions to technical challenges posed by flight and space exploration tend to be multidimensional, multifunctional, and increasingly focused on the interaction of systems and their environment. The growing discipline of biomimicry focuses on what humanity can learn from the natural world. Biomimicry for Aerospace: Technologies and Applications features the latest advances of bioinspired materials–properties relationships for aerospace applications. Readers will get a deep dive into the utility of biomimetics to solve a number of technical challenges in aeronautics and space exploration. Part I: Biomimicry in Aerospace: Education, Design, and Inspiration provides an educational background to biomimicry applied for aerospace applications. Part II: Biomimetic Design: Aerospace and Other Practical Applications discusses applications and practical aspects of biomimetic design for aerospace and terrestrial applications and its cross-disciplinary nature. Part III: Biomimicry and Foundational Aerospace Disciplines covers snake-inspired robots, biomimetic advances in photovoltaics, electric aircraft cooling by bioinspired exergy management, and surrogate model-driven bioinspired optimization algorithms for large-scale and complex problems. Finally, Part IV: Bio-Inspired Materials, Manufacturing, and Structures reviews nature-inspired materials and processes for space exploration, gecko-inspired adhesives, bioinspired automated integrated circuit manufacturing on the Moon and Mars, and smart deployable space structures inspired by nature. - Introduces educational aspects of bio-inspired design for novel and practical technologies - Presents a series of bio-inspired technologies applicable to the field of aerospace engineering - Provides an introduction to nature-inspired design and engineering and its relevance to planning and developing the next generation of robotic and human space missions

Zusammenfassung: This conference attracts GN&C specialists from across the globe. The 2022 Conference was the 44th Annual GN&C conference with more than 230 attendees from six different countries with 44 companies and 28 universities represented. The conference presented more than 100 presentations and 16 posters across 18 topics. This year, the planning committee wanted to continue a focus on networking and collaboration hoping to inspire innovation through the intersection of diverse ideas. These proceedings present the relevant topics of the day while keeping our more popular and well-attended sessions as cornerstones from year to year. Several new topics including "Autonomous Control of Multiple Vehicles" and "Results and Experiences from OSIRIS-REx" were directly influenced by advancements in our industry. In the end, the 44th Annual GN&C conference became a timely reflection of the current state of the GN&C ins the space industry. The annual American Astronautical Society Rocky Mountain Guidance, Navigation and Control (GN&C) Conference began 1977 as an informal exchange of ideas and reports of achievements among guidance and control specialists local to the Colorado area. Bud Gates, Don Parsons, and Bob Culp organized the first conference, and began the annual series of meetings the following winter. In March 1978, the First Annual Rocky Mountain Guidance and Control Conference met at Keystone, Colorado. It met there for eighteen years, moving to Breckenridge in 1996 where it has been for over 25 years

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.