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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 7
Geosci. Model Dev., 11, 3071-3088, 2018
https://doi.org/10.5194/gmd-11-3071-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 11, 3071-3088, 2018
https://doi.org/10.5194/gmd-11-3071-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Methods for assessment of models 31 Jul 2018

Methods for assessment of models | 31 Jul 2018

Bayesian inference of earthquake rupture models using polynomial chaos expansion

Hugo Cruz-Jiménez1, Guotu Li2, Paul Martin Mai1, Ibrahim Hoteit1, and Omar M. Knio1,2 Hugo Cruz-Jiménez et al.
  • 1King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia
  • 2Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708, USA

Abstract. 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.

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One of the most important challenges seismologists and earthquake engineers face is reliably estimating ground motion in an area prone to large damaging earthquakes. This study aimed at better understanding the relationship between characteristics of geological faults (e.g., hypocenter location, rupture size/location, etc.) and resulting ground motion, via statistical analysis of a rupture simulation model. This study provides important insight on ground-motion responses to geological faults.
One of the most important challenges seismologists and earthquake engineers face is reliably...
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