Stochastic simulation of ground motions based on NGA-West2 strong motion records

Stochastic modeling of ground motion is a simple tool to predict ground shaking level for future earthquake and less time consuming than physics-based deterministic modeling. In this paper, a record-based stochastic method that considers the time- and frequency-evolution of ground motion is used to estimate ground motion for scenario earthquakes in tectonic active region. The stochastic method employs a time-domain modulation function to describe the temporal nonstationarity and a filter impulse response function that describe the evolution of frequency content. For characterizing the modulation function and the filter impulse function, six parameters (I_a, D_5-95, t_mid, ω_mid, ω', ξ_f) are defined, and 2,571 pairs of ground motion recording in the NGA-west2 database are selected to identify the six parameters. Probabilistic density function is assigned to each of the parameter by fitting the frequency distribution histogram. The parameters are then transformed into standard normal space where regression analysis is performed by considering each parameter as function of moment magnitude, rupture distance, v_S30 (The time-averaged shear wave velocity of the top 30 m of soil). The prediction equations are used to generate ground motions for several scenario earthquakes and compared to NGA-West2 GMPEs.