Dio Alif Hutama


Slope stability design charts are commonly used to estimate the factor of safety of slope with simple geometry, isotropic, and homogeneous soil properties. However, most of the design charts proposed by previous researchers are only focus on determination of factor of safety that the appreciation of the probability offailure of the slope cannot be made. The paper by Javankhoshdel and Bathurst (2014) is the first that introduced a series of probabilistic slope stability design charts for cohesive-frictional (c-φ) soils. In this paper, the results of probabilistic slope stability analysis using those design charts are compared and validated with theresults obtained from Monte Carlo simulation using Slide 6.0. At the first stage, 42 slope models withvariation of slope angle(α) and mean friction angle(μφ) are built. Then, probabilistic slope stability analysis is conducted using both methods. Two statistical parameters including R-square (R2 ) and standard error (SE) are used to assess the correlation of the results obtained from both methods. Based on the statistical analysis, the following data are obtained:R 2 of mean factor of safety, probability of failure with COVc=COVφ=0.1, and probability of failure with COVc=0.5, COVφ=0.2are 0.9902; 0.9934; 0.9942, respectively. Moreover, SE of mean factor of safety, probability of failure with COVc=COVφ=0,1, and probability of failurewith COVc=0.5, COVφ=0.2are 0.060; 3.789; 3.112, respectively.The results of statistical analysis indicate that the results of probabilistic slope stability analysis using design chart and Slide 6.0 have strong correlation. It also confirms that the probabilistic slope stability design charts proposed by Javankhoshdel and Bathurst (2014) are valid.


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