Development of a New Method for Strong Ground Motion Selection Considering Joint Probability Distribution

Abstract

This study addresses limitations in current ground motion selection practices by introducing a sophisticated methodology considering the joint probabilistic behavior of multiple intensity measures (IMs). The research classifies regional data catalogs based on critical ground motion properties, such as site location and near- or far-field distinctions, aiming to identify ground motions aligned with specific site characteristics. By examining IMs across time and frequency domains and assessing correlations between pairs, essential IMs are identified. These IMs then are used to generate a comprehensive joint probability density function (PDF) through copula analysis. The approach prioritizes pairs with one measure in each domain and low correlations, ensuring broad representation in the PDF. A fitting copula function refines the selection of ground motions based on return period–specific volume. The study hypothesizes that this approach enhances the depiction of strong ground motions, particularly regarding structural responses. The method was tested within a dual framework incorporating performance-based and risk-based methodologies to demonstrate the proposed approach’s superiority in capturing the dynamics of strong ground motions, addressing traditional method shortcomings and advancing seismic studies.