Improving Response and Reliability Predictions Using Measured Data

Abstract

The concept of robust reliability is defined to take into account uncertainties from structural modeling in addition to the uncertain excitation a structure will experience during its lifetime. A Bayesian probabilistic methodology for system identification is integrated with probabilistic structural analysis tools for the purpose of updating the assessment of the robust reliability based on dynamic test data. Methods for updating the structural reliability for both identifiable and unidentifiable models are presented. Application of the methodology to a simple beam model of a single-span bridge with soil-structure interaction at the abutments, shows that the robust reliabilities computed before and after updating with "measured" dynamic data can differ significantly.

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