Multivariate return period-based ground motion selection for improved hazard consistency over a vector of intensity measures

摘要

Ground motion selection is a crucial step in probabilistic seismic performance assessment of structural systems. Particularly, identifying ground motion records compatible with a specific hazard level has been the major focus of past studies. We propose a multivariate return period (MRP)-based record selection methodology to further improve the multivariate hazard consistency over a vector of intensity measures (IMs). Unlike the traditional univariate return period anchored on a scalar IM, MRP generalizes the return period concept by accommodating the joint rate of exceedance of a vector of IMs, thereby providing more holistic seismic hazard characterization. By leveraging MRP in linking the seismic hazard to a vector IMs, the proposed MRP-based ground motion selection methodology for the first time offers a mathematically rigorous yet practical solution for multivariate hazard consistency in ground motion selection. The merit of the MRP-based ground motion selection is demonstrated by comparing the resulting target spectra and seismic demand estimates for several case-study structures with other state-of-the-art ground motion selection alternatives. From the results, the MRP-based ground motion selection employing Kendall's distribution function turns out to be a promising alternative, offering favorable new features including (a) moderate target spectra intensity and moderately low target spectra standard deviation; (b) superior convergence with the increase of the conditioning IM dimension and ability to approximate higher-dimensional multivariate hazard consistency with lower dimensional conditioning IMs; and (c) capability to realistically capture the multimodal spectral shape owing to the incorporation of multivariate Gaussian mixture distribution in generating target spectra.