Reliability evaluation of slope considering geological uncertainty and inherent variability of soil parameters

Zhi Ping Deng, Dian Qing Li*, Xiao Hui Qi, Zi Jun Cao, Kok Kwang Phoon

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)

Abstract

Geological uncertainty is often ignored in slope reliability analysis, even though the inherent variability of soil parameters is considered. This paper aims to propose a method for slope reliability analysis by considering both the inherent variability of soil parameters and geological uncertainty. A coupled Markov chain (CMC) model is used to simulate the geological uncertainty. An implementation procedure for slope reliability considering the aforementioned two types of uncertainty is provided. A slope reliability problem is analyzed to validate the proposed method with the borehole data from Perth, Australia. Different borehole layout schemes are designed to reflect the effect of both number and location of boreholes on slope reliability. Moreover, which type of uncertainty mentioned above has a greater impact on slope reliability is explored. The results indicate that the proposed method can effectively evaluate the slope reliability considering these two types of uncertainty. If only the inherent variability is considered, the accuracy of reliability analysis mainly depends on the used geological profiles. Borehole layout scheme has a significant effect on slope reliability. Both probability of failure (Pf) and mean of factor of safety (FS) of slope do not monotonously vary with an increasing number of boreholes. The boreholes designed in the critical influence zone can provide more information to improve the accuracy of slope reliability. The coefficients of variation (COVs) of shear strength parameters and the discrepancy among the means of shear strengths for different soils play different and major role between the two types of uncertainty in the reliability analysis of soil slope.

Original languageEnglish
Pages (from-to)121-131
Number of pages11
JournalComputers and Geotechnics
Volume92
Early online date8 Aug 2017
DOIs
Publication statusPublished - 1 Dec 2017
Externally publishedYes

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