CaltechAUTHORS
  A Caltech Library Service

Probabilistic Damage Detection Using Markov Chain Simulation with Application to a Benchmark Problem

Beck, J. L. and Yuen, K. V. and Au, S. K. (2002) Probabilistic Damage Detection Using Markov Chain Simulation with Application to a Benchmark Problem. In: Proceedings of the 3rd World Conference on Structural Control. Wiley , Chichester, NY, pp. 1065-1070. ISBN 0471489808. https://resolver.caltech.edu/CaltechAUTHORS:20120925-141745375

Full text is not posted in this repository.

Use this Persistent URL to link to this item: https://resolver.caltech.edu/CaltechAUTHORS:20120925-141745375

Abstract

A Markov chain simulation method is presented to evaluate the integrals giving the probability of damage and updated reliability based on dynamic data in a Bayesian probabilistic approach to damage detection and assessment. The method is based on the Metropolis-Hastings algorithm and an adaptive procedure to gain information about the important regions of the updated probability distribution in an efficient manner. Statistical averaging over the Markov chain samples is used to estimate the damage probability for each substructure and the updated reliability. The method is illustrated by applying it to modal data from the ASCE four-story benchmark structure to perform damage detection and assessment by giving the likely locations of the damage, its severity and its impact on the interstory-drift reliability of the structure.


Item Type:Book Section
ORCID:
AuthorORCID
Yuen, K. V.0000-0002-1755-6668
Record Number:CaltechAUTHORS:20120925-141745375
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20120925-141745375
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:34360
Collection:CaltechAUTHORS
Deposited By: Kristin Buxton
Deposited On:14 Nov 2012 21:46
Last Modified:12 Aug 2021 22:44

Repository Staff Only: item control page