Probabilistic stability analyses of slopes using the ANN-based response surface

✍ Scribed by Sung Eun Cho

• Publisher: Elsevier Science
• Year: 2009
• Tongue: English
• Weight: 583 KB
• Volume: 36
• Category: Article
• ISSN: 0266-352X
• DOI: 10.1016/j.compgeo.2009.01.003

✦ Synopsis

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.