Hu Design Optimization Under Uncertainty

Erscheinungsjahr 2023
ISBN: 978-3-031-49208-2
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 274 Seiten, eBook

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.

Zielgruppe

Upper undergraduate

Autoren/Hrsg.

Hu, Weifei

Inhaltsverzeichnis

Basic Concepts of Probability Theory .- Uncertainty Modeling .- Reliability Analysis Methods for Time-Independent Problems .- Surrogate Modeling for Reliability Analysis.- Model verification and validation (V&V).- Time-variant reliability analysis methods.- Reliability-based design optimization (RBDO).- Robust design optimization (RDO).- Other methods of design optimization under uncertainty.- Engineering applications.

Über Autor(innen)

Weifei Hu received the B.S. degree in 2008 from Zhejiang University, Hangzhou, China, the M.S. degree in 2010 from Hanyang University, Seoul, South Korea, and the Ph.D. degree in 2015 from the University of Iowa, Iowa city, Iowa, USA, all in mechanical engineering. From February 2016 to September 2018, Dr. Hu was a postdoctoral fellow at Cornell University, Ithaca, New York, USA. He is currently holding a ZJU100 Young Professor position at the School of Mechanical Engineering, Zhejiang University. His research interests include Design Optimization Under Uncertainty, Digital Twin, Artificial Intelligence, and Wind Energy. His work has been published in over 100 peer-reviewed journals and conference proceedings, e.g., Journal of Mechanical Design, Mechanical Systems and Signal Processing, Structural and Multidisciplinary Optimization, Journal of Intelligent Manufacturing, Journal of Manufacturing Systems, Renewable and Sustainable Energy Reviews, Applied Energy, Renewable Energy, Wind Energy, and many ASME and AIAA proceedings. He is now serving as an associate editor for the journal Wind Energy Science and an editorial board member for the journals Wind Energy and Journal of Intelligent Manufacturing and Special Equipment.