Refined multivariate return period-based ground motion selection and implications for seismic risk assessment

摘要

A multivariate return period (MRP)-based ground motion selection methodology was recently proposed to identify hazard-consistent ground motions by holistically incorporating the joint rate of exceedance of vector conditioning intensity measures (IMs). Despite these advances, the high computational cost involved in target spectra identification hinders the use of high-dimensional vector conditioning IMs and especially for large return periods, and thus may limit the practical application of this ground motion selection methodology. In this paper, we introduce a two-step adaptive refinement procedure to substantially alleviate the computational hurdle, while still offering reliable target spectra selection. The refined MRP-based ground motion selection then further facilitates the development of a MRP-based seismic risk assessment (SRA) framework to extend its applicability into risk-based assessment. The efficacy and computational efficiency of the proposed refinement are evaluated through comparison with the original unrefined approach, and the unbiasedness and variability of the risk estimates under different use cases of SRA are thoroughly examined and validated through case-study analyses. Aiming at facilitating more confident and reliable seismic risk estimates, implications and advantages of leveraging the MRP-based ground motion selection in SRA are elaborated.