Publications 2018

​Bayesian inference of earthquake rupture models using polynomial Chaos expansion
H. Cruz-Jimenez, G. Li, P. M. Mai, I. Hoteit, and O. Knio
Geoscientific Model Development, 11, 3071-3088, 2018
H. Cruz-Jimenez, G. Li, P. M. Mai, I. Hoteit, and O. Knio
Bayesian analysis, Earthquake hypocentere, Erthquake rupture, Environmental modeling, Equation
2018

​In this paper, we employed polynomial chaos (PC) expansions to understand earthquake rupture model responses to random fault plane properties. A sensitivity analysis based on our PC surrogate model suggests that the hypocenter location plays a dominant role in peak ground velocity (PGV) responses, while elliptical patch properties only show secondary impact. In addition, the PC surrogate model is utilized for Bayesian inference of the most likely underlying fault plane configuration in light of a set of PGV observations from a ground-motion prediction equation (GMPE). A restricted sampling approach is also developed to incorporate additional physical constraints on the fault plane configuration and to increase the sampling efficiency. 




DOI: 10.5194/gmd-11-3071-2018