Multi-Resolution Markov-Chain-Monte-Carlo Approach for System Identification with an Application to Finite-Element Models
Description:
Estimating unknown system configurations/parameters by combining system knowledge gained from a computer simulation model on one hand and from observed data on the other hand is challenging. An example of such inverse problem is detecting and localizing potential flaws or changes in a structure by using a finite-element model and measured vibration/displacement data. We propose a probabilistic approach based on Bayesian methodology. This approach does not only yield a single best-guess solution…
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Date:
February 7, 2005
Creator:
Johannesson, G.; Glaser, R. E.; Lee, C. L.; Nitao, J. J. & Hanley, W. G.
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Partner:
UNT Libraries Government Documents Department