Ground Motion Intensity Measures for Post-Earthquake Evaluation using Strong Motion Building Response Data

Recent efforts have sought to apply performance-based earthquake engi12 neering (PBEE) principles to post-event decision-support systems that utilize strong motion building response data in near real time. The rela14 tive effectiveness of different ground motion intensity measures (IMs) in structural response prediction is a core issue within the PBEE paradigm. This problem has been well-studied in the context of numerical simu17 lations. However, the effectiveness of alternative IMs for reconstructing structural responses in the post-earthquake environment has not been investigated. This study evaluates the performance of several IMs in estimating displacement and acceleration-based responses using building strong motion data. In addition to the efficiency and sufficiency criteria, the IMs are evaluated using causal inference principles. The data set of strong motion structural responses includes recordings from 150 buildings and 35 earthquakes. The study finds that peak ground velocity (PGV) and peak ground acceleration (PGA) outperform the other IMs in terms of their efficiency in estimating peak story drift ratios (PSDR) and peak floor accelerations (PFA), respectively. PGV, cumulative absolute velocity (CAV) and arias intensity (Ia) are sufficient with respect to magnitude (M) and distance (R) for PSDR, whereas for PFA, only the spectral IMs are sufficient with respect to M. The causal analysis finds that when a functional form is not assumed, the IM-EDP relationships are generally linear (in logarithmic space) with reduced effects for some IMs at the tail ends of their distributions. When a linear relationship is assumed, CAV outperforms the other IMs when estimating both PSDR and PFA