Abstract
The slope stability is a very important problem in geotechnical engineering. This paper presents an approach for slope reliability analysis based on the maximum-entropy method. The key idea is to implement the maximum entropy principle in estimating the probability density function. The performance function is formulated by the Simplified Bishop’s method to estimate the slope failure probability. The maximum-entropy method is used to estimate the probability density function (PDF) of the performance function subject to the moment constraints. A numerical example is calculated and compared to the Monte Carlo simulation (MCS) and the Advanced First Order Second Moment Method (AFOSM). The results show the accuracy and efficiency of the proposed method. The proposed method should be valuable for performing probabilistic analyses.
Highlights
Stability analysis of earth slopes is a geotechnical engineering problem dominated by uncertainties.In slope stability computations, various sources of uncertainties are encountered, such as the variability of soil parameters involved in the analysis
Conventional slope stability analysis has relied on a factor of safety approach for dealing with the uncertainties associated with soil properties
The problem we address in this paper is the use of moments to construct a probability density function (PDF) of a performance function
Summary
Stability analysis of earth slopes is a geotechnical engineering problem dominated by uncertainties. Various sources of uncertainties are encountered, such as the variability of soil parameters involved in the analysis. Conventional slope stability analysis has relied on a factor of safety approach for dealing with the uncertainties associated with soil properties. The possibility that values of shear strength and other parameters may vary is considered, providing a means of evaluating the degree of uncertainty associated with the computed factor of safety. The maximum entropy method provides a flexible and powerful means for density approximation and estimation given a finite number of moments. The maximum entropy method (MEM), which is based on Shannon’s measure of uncertainty, has been used for estimating distribution functions [16,17,18].
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