Probabilistic stability analyses of slopes using the ANN-based response surface |
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| Authors: | Sung Eun Cho |
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| Institution: | Korea Institute of Water and Environment, Korea Water Resources Corporation, 462-1, Jeonmin-Dong, Yusung-Gu, Daejon 305-730, South Korea |
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| Abstract: | Slope stability analysis is a geotechnical engineering problem characterized by many sources of uncertainty. Some of these sources are connected to the uncertainties of soil properties involved in the analysis. In this paper, a numerical procedure for integrating a commercial finite difference method into a probabilistic analysis of slope stability is presented. Given that the limit state function cannot be expressed in an explicit form, an artificial neural network (ANN)-based response surface is adopted to approximate the limit state function, thereby reducing the number of stability analysis calculations. A trained ANN model is used to calculate the probability of failure through the first- and second-order reliability methods and a Monte Carlo simulation technique. Probabilistic stability assessments for a hypothetical two-layer slope as well as for the Cannon Dam in Missouri, USA are performed to verify the application potential of the proposed method. |
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| Keywords: | Slope stability Probabilistic analysis Response surface Artificial neural network |
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