© Springer-Verlag Berlin Heidelberg 2015

Enhancement of random finite element method in reliability analysis and risk assessment of soil slopes using Subset Simulation Abstract Random finite element method (RFEM) provides a rigor-ous tool to incorporate spatial variability of soil properties into reliability analysis and risk assessment of slope stability. However, it suffers from a common criticism of requiring extensive computa-tional efforts and a lack of efficiency, particularly at small probability levels (e.g., slope failure probability Pf<0.001). To address this prob-lem, this study integrates RFEM with an advanced Monte Carlo Simulation (MCS) method called “Subset Simulation (SS) ” to devel-op an efficient RFEM (i.e., SS-based RFEM) for reliability analysis and risk assessment of soil slopes. The proposed SS-based RFEM expresses the overall risk of slope failure as a weighed aggregation of slope failure risk at different probability levels and quantifies the relative contributions of slope failure risk at different probability levels to the overall risk of slope failure. Equations are derived for integrating SS with RFEM to evaluate the probability (Pf) and risk (R) of slope failure. These equations are illustrated using a soil slope example. It is shown that the Pf and R are evaluated properly using the proposed approach. Compared with the original RFEM with direct MCS, the SS-based RFEM improves, significantly, the compu-tational efficiency of evaluating Pf and R. This enhances the applica-tions of RFEM in the reliability analysis and risk assessment of slope stability. With the aid of improved computational efficiency, a sen-sitivity study is also performed to explore effects of vertical spatial variability of soil properties on R. It is found that the vertical spatial variability affects the slope failure risk significantly