Stochastic field simulation of slope stability problems: Improvement and reduction of computational effort

Abstract

In recent years, stochastic simulation has obtained increasing attention in geomechanics as it allows to consider uncertainties in geomaterials’ properties. Spatial uncertainties may influence simulation results and lead to either unsafe or uneconomic designs. By implementing stochastic random field algorithms in Finite-Element simulations, the impact of such uncertainty can be integrated in the simulation results. However, the application of such algorithms implicates new requirements in understanding the relationships between correlation length, mesh coarseness, and required number of Finite-Element simulations. The present study intends to provide a deeper understanding of such aspects. In the presented approach, stochastic random fields analysis is applied in a Finite-Element code by remote scripting. Considering a slope stability analysis and using Monte-Carlo Simulations, the impact of varying mesh coarseness and the correlation length on the obtained safety factor is investigated. As for large numbers of mesh elements, computational costs increase rapidly, the study expands its investigations by employing two further advanced methods, namely mesh adaptivity and subset simulation. These state-of-the-art methods allow to reduce calculation efforts, once by iterative remeshing, once by selective sampling according to failure probability. The results show promising improvements in the concept of computational efforts.