Metamodel-Based Slope Reliability Analysis—Case of Spatially Variable Soils Considering a Rotated Anisotropy

Tingting Zhang,Xiangfeng Guo,Daniel Dias,Julien Baroth

doi:10.3390/geosciences11110465

Abstract

A rotation of the anisotropic soil fabric pattern is commonly observed in natural slopes with a tilted stratification. This study investigates the rotated anisotropy effects on slope reliability considering spatially varied soils. Karhunen–Loève expansion is used to generate the random fields of the soil shear strength properties (i.e., cohesion and friction angle). The presented probabilistic analyses are based on a meta-model combining Sparse Polynomial Chaos Expansion (SPCE) and Global Sensitivity Analysis (GSA). This method allows the number of involved random variables to be reduced and then the computational efficiency to be improved. Two kinds of deterministic models, namely a discretization kinematic approach and a finite element limit analysis, are considered. A variety of valuable results (i.e., failure probability, probability density function, statistical moments of model response, and sensitivity indices of input variables) can be effectively provided. Moreover, the influences of the rotated anisotropy, autocorrelation length, coefficient of variation and cross-correlation between the cohesion and friction angle on the probabilistic analysis results are discussed. The rotation of the anisotropic soil stratification has a significant effect on the slope stability, particularly for the cases with large values of autocorrelation length, coefficient of variation, and cross-correlation coefficient.

Highlights

Inherent spatial variability of soil properties plays a significant role in probabilistic analyses
Griffiths et al [7] demonstrated that the rotated anisotropy has a very significant effect on slope failure probability and found that the failure probability is higher when the soil stratification is parallel to the slope surface
This study aims to perform a probabilistic stability analysis of slopes with consideration of the soil rotated anisotropy by using the DSG–MG procedure, which includes the deterministic method discretization kinematic approach (DKA) and the probabilistic methods Sparse Polynomial Chaos Expansion (SPCE)/Global Sensitivity Analysis (GSA) and Monte Carlo Simulation (MCS)

Summary

Introduction

Inherent spatial variability of soil properties plays a significant role in probabilistic analyses. Random field theory has been widely used to model this feature to discuss the soil spatial variability effects on slope reliability [1,2,3,4,5]. Huang et al [8] investigated the rotated anisotropy effect on slope stability considering conditional random fields and found that different sampling patterns may lead to significantly different failure probabilities. These works provide interesting insights into the slope reliability analysis with consideration of the rotated anisotropy.

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