Probabilistic back analysis of slope failure - A case study in Taiwan

Lei Wang, Jin Hung Hwang, Zhe Luo, C. Hsein Juang, Junhua Xiao

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87 Scopus citations

Abstract

In this paper, the authors present a probabilistic back-analysis of a recent slope failure at a site on Freeway No. 3 in northern Taiwan. Post-event investigations of this failure found uncertain strength parameters and deteriorating anchor systems as the most likely causes for failure. Field measurement after the event indicated an average slip surface of inclination 15°. To account for the uncertainties in input parameters, the probabilistic back analysis approach was adopted. First, the Markov Chain Monte Carlo (MCMC) simulation was used to back-calculate the geotechnical strength parameters and the anchor force. These inverse analysis results, which agreed closely with the findings of the post-event investigations, were then used to validate the maximum likelihood (ML) method, a computationally more efficient back-analysis approach. The improved knowledge of the geotechnical strength parameters and the anchor force gained through the probabilistic inverse analysis better elucidated the slope failure mechanism, which provides a basis for a more rational selection of remedial measures.

Original languageEnglish
Pages (from-to)12-23
Number of pages12
JournalComputers and Geotechnics
Volume51
DOIs
StatePublished - Jun 2013

Keywords

  • Back analysis
  • Case study
  • Dip slope
  • Markov Chain Monte Carlo
  • Maximum likelihood method
  • Slope failure
  • Uncertainty

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