Stochastic analysis method of critical slip surfaces in soil slopes considering spatial variability

Xiao Hui Qi, Dian Qing Li*, Chuang Bing Zhou, Kok Kwang Phoon

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)

Abstract

The effect of spatial variability in soil parameters on the critical slip surfaces has not been investigated substantially. Therefore, this paper aims to propose a stochastic method to determine the critical slip surfaces in soil slopes considering spatial variability of soil strength properties. First, the spectral representation method is adopted to simulate random field of spatially varying soils. Based on this random field model, the critical slip surface is determined by means of the auto-searching method with SIGMA/W and SLOPE/W. Second, the effect of spatial variability in soil parameters on the characteristics of the critical slip surfaces is investigated using a non-intrusive stochastic analysis method. Finally, an illustrative example is presented to demonstrate the validity of the proposed method. The results indicate that the proposed stochastic method can determine the characteristics of the critical slip surfaces effectively. The spatial variability has a significant influence on the position and scale of the critical slip surfaces. The longer the scale of fluctuation is, the wider the critical slip surface distribution is. The possibility of upper-located local sliding increases with the increasing ratio of horizontal fluctuation scale to vertical fluctuation scale. As the coefficients of variation of soil parameters increase, the range of critical slip surface will increase, and small-scale local sliding is more likely to happen.

Original languageEnglish
Pages (from-to)745-753
Number of pages9
JournalYantu Gongcheng Xuebao/Chinese Journal of Geotechnical Engineering
Volume35
Issue number4
Publication statusPublished - Apr 2013
Externally publishedYes

Keywords

  • Critical slip surface
  • Factor of safety
  • Non-intrusive stochastic analysis
  • Slope stability
  • Spatial variability

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