Introduction.- Probability Models.- Monte Carlo Simulation.- Structural Reliability Assessment.- Time-Dependendent Reliability Assessment.
Dr. Cao Wang is a Vice-Chancellor’s Postdoctoral Research Fellow from the School of Civil, Mining and Environmental Engineering, University of Wollongong, Australia. He obtained his Ph.D. degree from the School of Civil Engineering at the University of Sydney, Australia, in June 2019. His areas of expertise are mainly in structural reliability assessment, modelling of natural hazards, and reliability and resilience assessment of infrastructure systems. He has published more than 20 journal articles indexed in Web of Science and has performed over a hundred reviews for international journals. He is on the Early Career Editorial Board of the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, and serves as a Young Academic Editor for the Journal of Traffic and Transportation Engineering (English Edition).
This book provides structural reliability and design students with fundamental knowledge in structural reliability, as well as an overview of the latest developments in the field of reliability engineering. It addresses the mathematical formulation of analytical tools for structural reliability assessment.
This book offers an accessible introduction to structural reliability assessment and a solid foundation for problem-solving. It introduces the topic and background, before dealing with probability models for random variables. It then explores simulation techniques for single random variables, random vectors consisting of different variables, and stochastic processes. The book addresses analytical approaches for structural reliability assessment, including the reliability models for a single structure and those for multiple structures, as well as discussing the approaches for structural time-dependent reliability assessment in the presence of discrete and continuous load processes.
This book delivers a timely and pedagogical textbook, including over 170 worked-through examples, detailed solutions, and analytical tools, making it of interest to a wide range of graduate students, researchers, and practitioners in the field of reliability engineering.