A Markov-Chain Monte-Carlo Based Method for Flaw Detection in Beams
Description:
A Bayesian inference methodology using a Markov Chain Monte Carlo (MCMC) sampling procedure is presented for estimating the parameters of computational structural models. This methodology combines prior information, measured data, and forward models to produce a posterior distribution for the system parameters of structural models that is most consistent with all available data. The MCMC procedure is based upon a Metropolis-Hastings algorithm that is shown to function effectively with noisy dat…
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Date:
September 28, 2006
Creator:
Glaser, R. E.; Lee, C. L.; Nitao, J. J.; Hickling, T. L. & Hanley, W. G.
Partner:
UNT Libraries Government Documents Department