International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP) (12th : 2015)

Material parameter estimation in distributed plasticity FE models using the unscented Kalman filter Astroza, Rodrigo; Ebrahimian, Hamed; Conte, Joel P.

Abstract

This paper describes a novel framework that combines advanced mechanics-based nonlinear (hysteretic) finite element (FE) models and a nonlinear stochastic filtering technique, the unscented Kalman filter (UKF), to estimate unknown time-invariant parameters of nonlinear inelastic material models used in the FE model. The proposed framework updates the nonlinear FE model of the structure using input-output data recorded during earthquake events. The updated model can be directly used for damage identification. A two-dimensional 3-bay 3-story steel moment-resisting frame is used to verify the convergence, robustness, and accuracy of the proposed methodology. The steel frame is modeled using fiber-section beam-column elements with distributed plasticity and is subjected to a ground motion recorded during the 1989 Loma Prieta earthquake. The results indicate that the proposed framework provides accurate estimation of the unknown material parameters of the nonlinear FE model.

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Attribution-NonCommercial-NoDerivs 2.5 Canada

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