Bayesian inference of earthquake rupture models using polynomial chaos expansion

Published

Journal Article

© 2018 Copernicus GmbH. All rights reserved. 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.

Full Text

Duke Authors

Cited Authors

  • Cruz-Jiménez, H; Li, G; Martin Mai, P; Hoteit, I; Knio, OM

Published Date

  • July 31, 2018

Published In

Volume / Issue

  • 11 / 7

Start / End Page

  • 3071 - 3088

Electronic International Standard Serial Number (EISSN)

  • 1991-9603

International Standard Serial Number (ISSN)

  • 1991-959X

Digital Object Identifier (DOI)

  • 10.5194/gmd-11-3071-2018

Citation Source

  • Scopus