Developing Data-Driven Stochastic Seismological Parameters of CENA from the NGA-East Database

Date: 4/25/2019

Time: 06:00 PM

Room: Grand Ballroom

The fundamental idea of this project is to obtain a set of self-consistent stochastic seismological parameters for Central and Eastern United States (CENA). We are using median 5% damped pseudo-spectral acceleration (ROTD50) with rupture distances (Rrup) less than 500 km from the NGA-East database and the point source stochastic model (Boore 2003) to determine seismological parameters that minimize the residuals over the usable frequencies of the data using a genetic algorithm. The final product of this study is a set of well correlated seismological parameters compatible with single and generalized double corner frequency models.

Parameters obtained in this study include a tri-linear geometric spreading model, site kappa, frequency dependent quality factor, eight magnitude dependent parameters of generalized additive double corner frequency model (Boore et al., 2014), and magnitude dependent point-source correction factor (also known as pseudo depth). The double corner frequency can easily be converted to single corner frequency model and a magnitude dependent stress drop parameter and corner frequency, which is also data-driven and self-consistent.

The final objective of this research is to develop an updated hybrid empirical ground motion model to map the ground motion of the higher magnitudes from a richer database by scaling the ground motion in the target region (CENA) by the ratio of stochastic over empirical ground motion obtained in a target region.

Presenting Author: Nima Nazemi

Authors