Response surface methods for slope reliability analysis: Review and comparison - Li, Dian-Qing; Zheng, Dong; Cao, Zi-Jun; Tang, Xiao-Song; Phoon, Kok-Kwang (Engineering geology, 2016)
This paper reviews previous studies on developments and applications of response surface methods (RSMs) in different slope reliability problems. Based on the review, four types of soil slope reliability analysis problems are identified from the literature, including single-layered soil slope reliability problem ignoring spatial variability, single-layered soil slope reliability problem considering spatial variability, multiple-layered soil slope reliability problem ignoring spatial variability, and multiple-layered soil slope reliability problem considering spatial variability, which are referred to as “Type I–IV problems” in this study. Then, the computational efficiency and accuracy of four commonly-used RSMs (namely single quadratic polynomial-based response surface method (SQRSM), single stochastic response surface method (SSRSM), multiple quadratic polynomial-based response surface method (MQRSM), and multiple stochastic response surface method (MSRSM)) are systematically compared for cohesive and c–ϕ slopes, and their feasibility and validity in the four types of slope reliability problems are discussed. Based on the comparison, some suggestions for selecting relatively appropriate RSMs in slope reliability analysis are provided: (1) SQRSM is suggested as a suitable method for the single-layered soil slope reliability problem ignoring spatial variability (i.e., Type I problem); (2) MQRSM is applicable to the multiple-layered soil slope reliability problem ignoring spatial variability (i.e., Type III problem); and (3) MSRSM is suggested to solve slope reliability problems (including single-layered and multiple-layered slopes) considering spatial variability (i.e., Type II and IV problems). •A review on response surface methods (RSMs) for slope reliability analysis is performed.•Four types of slope reliability analysis problems are identified from the literature.•Computational efficiency and accuracy of four commonly-used RSMs are explored and compared.•Suggestions on choosing relatively appropriate RSMs are provided.