A Validation of Bayesian Finite Element Model Updating for Linear Dynamics

This work addresses the issue of statistical model updating and correlation. The updating procedure is formulated to improve the predictive quality of a structural model by minimizing out-of-balance modal forces. It is shown how measurement and modeling uncertainties can be taken into account to provide not only the correlated model but also the associated confidence levels. Hence, a Bayesian parameter estimation technique is derived and its numerical implementation is discussed. Two demonstration examples that involve test-analysis correlation with real test data are presented. First, the validation of an engine cradle model used in the automotive industry shows how the design's uncertainties can be reduced via model updating. The second example consists of employing test-analysis correlation for identifying the degree of nonlinearity of the LANL 8-DOF testbed.

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