Dimensional Reduction-Based Moment Model for Probabilistic Slope Stability Analysis

Uncertainty is an inevitable factor that influences the function analysis, design, and safe operation in engineering systems. Due to complexity property unclear failure mechanism, uncertainty intrinsic of slope engineering. Hence, stability analysis design cannot meet demands based on traditional deterministic method, which deal with uncertainty. In this study, a practical reliability approach was developed consider by combining multiplicative dimensional reduction method (MDRM) first-order second moment (FOSM). MDRM used approximate complex, nonlinear, high-dimensional, implicit limit state function. The statistical safety estimated using MDRM. FOSM adopted compute index factor. proposed illustrated verified infinite analytical solution. probability were compared Monte Carlo simulations (MCS) various cases. Then, it applied numerical solutions. results show feasible effective for probabilistic analysis. obtained from shows high consensus response surface (RSM). It effective, efficient, accurate. provides practical, simple, efficient approach.