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Damage Identification for Masonry Materials Based on Bayesian Inference
Abstract:
The basic frequency of masonry specimens can be obtained by dynamic tests with ambient or artificial excitation. The elastic modulus of masonry structures, as well as the damage factors, can then be determined by training their finite element models and make the calculated frequencies agree with the measured ones. Using 530 groups of dynamic test data, the damage factors of four masonry specimens were identified. The Bayesian inferences of the highly diverse measured results were conducted through a Markov Chain Monte Carlo (MCMC) sampling method, and the location of the damage was identified. The methodology was applicable, and can be used in the damage identification for other materials or structures.
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2498-2502
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September 2013
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© 2013 Trans Tech Publications Ltd. All Rights Reserved
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