Abstract
Abstract The paper concerns to the reliability analysis of slopes in strain-softening cohesive soils, using the first order reliability method (FORM). The performance function is based on the Bishop simplified method adapted to take strain-softening into account in terms of the residual factor R F over a potential slip surface, estimated based on a progressive failure model available in the literature. The reliability analysis is carried out on the surface of minimum factor of safety determined using the sequential quadratic programming (SQP). The random shear strength parameters are assumed to follow normal distribution while the residual factor has been considered both as a deterministic parameter and a beta-distributed random variable. The results obtained for an illustrative example shows substantial reduction (21 %) in the value of reliability index when R F is considered as a random variable with an assumed COV of 0.3. Results of FORM-based sensitivity analyses also reveal that R F has the most dominating influence on reliability and thus justifies its inclusion as one of the random variables. A parametric study, varying the assumed correlation coefficient between the random shear strength parameters from 0 to 1, shows that there is a maximum reduction of 16 % in reliability index.
Highlights
It is essential to understand the basic causes and mechanisms of slope failures which are often associated with the progressive mechanism of failure involving decreased shear strength and increased pore water pressure
Limit equilibrium based slope stability analyses have conventionally been performed in a deterministic manner and the entire process consists of two joint tasks, namely, computation of factor of safety of a trial slip surface using a method of slices, and search for the critical slip surface having the minimum factor of safety FSmin using an optimization technique
The optimization problem involved in the deterministic slope stability analysis has been solved using the sequential quadratic programming (SQP) [10] technique which has been rated as a powerful optimization technique [5] and can be implemented in the MATLAB platform with its optimization toolbox
Summary
It is essential to understand the basic causes and mechanisms of slope failures which are often associated with the progressive mechanism of failure involving decreased shear strength and increased pore water pressure. During the process of deformation, shear strength decreases till it reaches the lower limit called the ‘residual’ shear strength The extent of strain-softening along a potential slip surface in a slope may vary from 0 to 100 % depending on how much of the slip surface length is at residual shear strength. Historical factors which would influence the extent of strain-softening within a slope include the process of slope formation, fluctuations in pore water pressure over time, seismic activity and other processes.
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