Bayesian Methods for Structural Dynamics and Civil Engineering

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John Wiley & Sons, Feb 22, 2010 - Mathematics - 320 pages
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Bayesian methods are a powerful tool in many areas of science andengineering, especially statistical physics, medical sciences,electrical engineering, and information sciences. They are alsoideal for civil engineering applications, given the numerous typesof modeling and parametric uncertainty in civil engineeringproblems. For example, earthquake ground motion cannot bepredetermined at the structural design stage. Complete windpressure profiles are difficult to measure under operatingconditions. Material properties can be difficult to determine to avery precise level – especially concrete, rock, and soil. Forair quality prediction, it is difficult to measure the hourly/dailypollutants generated by cars and factories within the area ofconcern. It is also difficult to obtain the updated air qualityinformation of the surrounding cities. Furthermore, themeteorological conditions of the day for prediction are alsouncertain. These are just some of the civil engineering examples towhich Bayesian probabilistic methods are applicable.

  • Familiarizes readers with the latest developments in thefield
  • Includes identification problems for both dynamic and staticsystems
  • Addresses challenging civil engineering problems such asmodal/model updating
  • Presents methods applicable to mechanical and aerospaceengineering
  • Gives engineers and engineering students a concrete sense ofimplementation
  • Covers real-world case studies in civil engineering and beyond,such as:
    • structural health monitoring
    • seismic attenuation
    • finite-element model updating
    • hydraulic jump
    • artificial neural network for damage detection
    • air quality prediction
  • Includes other insightful daily-life examples
  • Companion website with MATLAB code downloads for independentpractice
  • Written by a leading expert in the use of Bayesian methods forcivil engineering problems

This book is ideal for researchers and graduate students incivil and mechanical engineering or applied probability andstatistics. Practicing engineers interested in the application ofstatistical methods to solve engineering problems will also findthis to be a valuable text.

MATLAB code and lecture materials for instructors available atahref=""

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About the author (2010)

Ka-Veng Yuen is an Associate Professor of Civil and Environmental Engineering at the University of Macau. His research interests include random vibrations, system identification, structural health monitoring, modal/model identification, reliability analysis of engineering systems, structural control, model class selection, air quality prediction, non-destructive testing and probabilistic methods. He has been working on Bayesian statistical inference and its application since 1997. Yuen has published over sixty research papers in international conferences and top journals in the field. He is an editorial board member of the International Journal of Reliability and Safety, and is also a member of the ASCE Probabilistic Methods Committee, the Subcommittee on Computational Stochastic Mechanics, and the Subcommittee on System Identification and Structural Control of the International Association for Structural Safety and Reliability (IASSAR), as well as the Committee of Financial Analysis and Computation, Chinese Association of New Cross Technology in Mathematics, Mechanics and Physics. Yuen holds an M.S. from Hong Kong University of Science and Technology and a Ph.D. from Caltech, both in Civil Engineering.

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