Bayesian seismic strong-motion response and damage estimation with application to a full-scale seven story shear wall structure

Abstract In this paper a Bayesian framework is employed to estimate the seismic strong-motion response and the state of structural integrity of a full-scale structure. The approach is applied in the context of a full-scale section of a seven-story shear wall building designed for southern California and tested at the George E. Brown Jr. Network for Earthquake Engineering Simulation shake table site at the University of California San Diego. The test structure was subjected to earthquake records of increasing amplitude until severe damage was observed, and the dynamic response was measured during the experimental program using an array of sensors. The proposed approach provides an estimate of the nonlinear dynamic response at unmeasured degrees of freedom by combining a potentially inaccurate structural model with sparse acceleration measurements using an unscented Kalman filter. Although the method also provides an optimal estimate of the parameters that define the mathematical models, joint state-parameter estimation is not the main purpose of this study. To assess the modeling robustness of the approach two model classes are considered: a linear time-varying cantilever beam model that accounts only for flexural deformations, and a coupled nonlinear chain-cantilever model that accounts for both flexural and shear deformations. It is shown that the approach has the capability to accurately estimate the time-history response and engineering demands of interest, such as floor displacements and accelerations, inter-story drifts, base shear, and overturning moment induced by strong base excitations where the structure experienced considerable nonlinear excursions. The estimated demands are subsequently used to compute damage measures to perform a quantitative assessment of the state of structural integrity.

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