A stochastic simulation algorithm for Bayesian model updating of linear structural dynamic system with non-classical damping
Model updating using measured system dynamic response has a wide range of applications in structural health monitoring and control, response prediction, reliability and risk assessment. In this paper, we are interested in model updating of a linear structural dynamic system with non-classical damp...
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| Main Authors: | , |
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| Other Authors: | |
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/100590 http://hdl.handle.net/10220/24107 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Model updating using measured system dynamic response has a wide range of applications
in structural health monitoring and control, response prediction, reliability and risk assessment. In this paper,
we are interested in model updating of a linear structural dynamic system with non-classical damping based
on incomplete modal data including modal frequencies, damping ratios and partial complex mode shapes of
some of the dominant modes. To quantify the uncertainties and plausibility of the model parameters, a Bayesian
approach is considered in which the probability distribution of the model parameters needs to be updated.A new
stochastic simulation algorithm is proposed, which allows for an efficient update of the probability distribution
of the model parameters. The effectiveness and efficiency of the proposed method are illustrated by a numerical
example involving linear structural dynamic system with complex modes. |
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