Abstract:

A new optimization approach for reliability analysis proposed by Low & Tang is introduced and applied to slope reliability analysis. The optimization approach has many advantages: it is applicable to correlated variables with any probability distributions; it need not compute the equivalent normal means and standard deviations and independence transform of correlated variables. It can obtain the minimum reliability index and the probabilistic critical slip surface within the original variable space, and it is very simple to implement with any appropriate optimization method. Two slip surfaces are often used in slope reliability analysis: the deterministic critical slip surface of the minimum factor of safety at mean variable and the probabilistic critical slip surface of the minimum reliability index. However, there are circumstances where the two slip surfaces are quite different. A simple method proposed by Hassan & Wolff to obtain the probabilistic one seems questionable due to its simplicity. The results of example slope reliability analysis show that the probabilistic critical slip surface obtained by optimization approach is quite close to that obtained by Hassan & Wolff’s simplified method, which shows that the simplified method is efficient and can be used in practice.

Key words: slope reliability, soil slope, optimization approach, probabilistic critical slip surface, deterministic critical slip surface