Inter-region variability of Robertson and Wride method for liquefaction hazard analysis

J. Zhang, C. H. Juang, J. R. Martin, H. W. Huang

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Semi-empirical models used for liquefaction potential evaluation are often developed based on lumping data from different regions around the world. The accuracy of a semi-empirical model developed in such a way may vary from one region to another, which has been seldom studied previously. Thus, in this paper, a probabilistic method is suggested to characterize the inter-region variability of the model bias factor of a semi-empirical model for liquefaction potential evaluation. As an illustration, the proposed approach is used to characterize the inter-region variability of the model bias factor of the Robertson and Wride model (called RW model for short herein). It is found that substantial inter-region variability exists in the model bias factor of the RW model. For a region not in the calibration database, the uncertainty associated with the model bias factor is significantly larger than that of a region in the calibration database. For regions in the calibration database, the uncertainty associated with the model bias factor in a region also changes with the amount and the type of the calibration data available in that region. It is thus important to collect region-specific performance data for model calibration to achieve accurate liquefaction potential evaluation. For ease of practical application, equations are provided for estimating the liquefaction probability based on the factor of safety (FOS) computed with the RW model for different regions. The suggested method can also be used to characterize the inter-region variability of other semi-empirical models and to derive region-specific relationships between FOS and liquefaction probability for these models.

Original languageEnglish
Pages (from-to)191-203
Number of pages13
JournalEngineering Geology
Volume203
DOIs
StatePublished - 25 Mar 2016

Keywords

  • Bayesian method
  • Earthquake
  • Inter-region variability
  • Liquefaction
  • Reliability

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