Quasi-Monte Carlo Simulation with Low-Discrepancy Sequence for Reinforced Soil Slopes

This paper describes a precise numerical technique to compute the limit state exceedance probability of geosynthetic reinforced soil (GRS) slopes with normally distributed backfill and foundation soils by using the low-discrepancy sequence Monte Carlo (LDSMC) and importance sampling with LDSMC (ISLDSMC) methods. The LDSMC and ISLDSMC methods can effectively compute an accurate limit state exceedance probability of GRS slopes with a limited number of simulations. By using importance sampling, random variables can be generated in an expected failure region, thereby enabling enumeration by the Monte Carlo simulation. The failure region can be searched by the conventional first-order reliability method. To increase the computational efficiency, a low-discrepancy sequence, which is a sequence of quasi-random numbers with uniform distribution, is adopted in this study. The numerical simulation in this study revealed that the LDSMC and ISLDSMC methods can effectively compute an accurate limit state exceedance probability of GRS slopes by performing comparatively fewer simulations than the conventional crude Monte Carlo simulation.