Probabilistic updating of fishbone model for assessing seismic damage to beam-column connections in steel moment-resisting frames

摘要

This article presents a probabilistic method of updating fishbone models for assessing seismic damage on beam-column connections in steel moment-resisting frames. Fishbone models enable explicitly identifying the rotational stiffness of beams, which is not possible with a shear building model commonly used in Bayesian model updating approaches. Necessary formulations to utilize fishbone models for model updating with measured floor accelerations under small-amplitude loadings including ambient excitations were first formulated. To accommodate the incompleteness of modal data to update unknown parameters of fishbone models, that is, the stiffness of rotational springs, a hierarchical Bayesian model updating algorithm is implemented. Seismic damage of beam-column connections are estimated by making a comparison of the identified rotational stiffness of springs in the fishbone models before and after earthquakes. The effectiveness of the proposed method is first examined with numerical simulations using a 10-story building model. Then, the applicability to realistic beam damage, that is, not artificially introduced, is evaluated through a full-scale steel frame test at the E-Defense shaking table facility. The article also discusses coefficients of variation of the identified stiffness and influence of modeling error on estimation of realistic damage to check the credibility of the method for real-life applications.