Probabilistic prediction of ground-motion intensity for regions lacking strong ground-motion records

Abstract

Probabilistic prediction of ground-motion intensity in regions lacking strong ground-motion records is a vital issue for seismic structural design. Several approaches have been suggested for this purpose, and nearly all of them directly import and adjust the ground-motion prediction equation (GMPE) of ground-motion measures such as the peak ground acceleration (PGA) or spectral acceleration (SA) from data-rich regions. However, as the transmissions of PGA and SA from the source to the site correspond to nonlinear processes, this import and adjustment may lead to an unrealistic evaluation of ground motion. In this study, a novel probabilistic prediction method of ground-motion intensity for such regions is proposed. In contrast to the current approach wherein the GMPE of ground-motion measures such as PGA or SA is directly used, a Fourier amplitude spectral (FAS) model is suggested to express the seismic transmission process from the source to the site. The ground-motion intensities of PGA or SA are obtained from the FAS model using the random vibration theory. The exceedance probability of ground-motion intensity is calculated based on Monte Carlo simulations. As the FAS conforms to the linear system theory and the determination of FAS model does not require too many ground-motion records, the proposed method should be convenient for the probabilistic prediction of ground-motion intensity in regions lacking strong ground-motion records.