Earthquake-induced economic loss estimation of eccentrically braced frames through roof acceleration-based nonmodel approach

Abstract

This paper develops a nonmodel-based approach for seismic loss assessment of buildings with eccentrically braced frames (EBFs). An extensive database is utilized to predict engineering demand parameters (EDPs), including, peak and residual story drift ratios, peak story link rotations, and also peak floor absolute accelerations, along with the height of the buildings. The estimated EDPs are used to assess the total economic losses associated with the collapse, demolition, and repair of structural and/or non-structural components. The database includes seismic intensity measure, improved wavelet-based refined damage-sensitive feature (rDSF) assembled only by the roof absolute acceleration response, geometric information, and EDPs of the 4-, 8-, and 16-story prototype models, extracted from incremental dynamic analyses subjected to 44 far-field ground motions. The nonlinear model of the aforementioned structures was already developed by the authors to capture the response of the structures up to collapse. Symbolic and Bayesian regressions are carried out in addition to ordinary least square linear regression to develop the empirical equations. Moreover, a thorough study is performed on the optimal selection of the intensity measures proposed in the literature as the input variable of the predictive equations through reliability-based sensitivity analysis. To estimate the first mode period of the considered structures to compute the improved wavelet-based rDSF and promote a nonmodel-based approach, Auto-Regressive model with exogenous input is employed. The results show that the story-based EDPs and also the corresponding expected economic losses of EBF buildings are accurately predicted compared with those obtained from incremental dynamic analyses. Consequently, the proposed nonmodel-based approach paves the path for rapid earthquake-induced economic loss assessment of EBF buildings in emergency operations.