Articles | Volume 11, issue 7
https://doi.org/10.5194/gmd-11-3071-2018
https://doi.org/10.5194/gmd-11-3071-2018
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-Jiménez, Guotu Li, Paul Martin Mai, Ibrahim Hoteit, and Omar M. Knio

Viewed

Total article views: 3,475 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,379 1,001 95 3,475 108 105
  • HTML: 2,379
  • PDF: 1,001
  • XML: 95
  • Total: 3,475
  • BibTeX: 108
  • EndNote: 105
Views and downloads (calculated since 05 Feb 2018)
Cumulative views and downloads (calculated since 05 Feb 2018)

Viewed (geographical distribution)

Total article views: 3,475 (including HTML, PDF, and XML) Thereof 3,227 with geography defined and 248 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 21 Feb 2025
Download
Short summary
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.
Share