Material parameter estimation in distributed plasticity FE models using the unscented Kalman filter

Rodrigo Astroza, Hamed Ebrahimian, Joel P. Conte

Resultado de la investigación: Contribución a una conferenciaArtículo

Resumen

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.
Idioma originalInglés estadounidense
DOI
EstadoPublicada - 1 ene. 2015
Evento12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015 -
Duración: 1 ene. 2015 → …

Conferencia

Conferencia12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015
Período1/01/15 → …

Huella

Profundice en los temas de investigación de 'Material parameter estimation in distributed plasticity FE models using the unscented Kalman filter'. En conjunto forman una huella única.

Citar esto