Probabilistic analysis of simple slopes with cohesive soil strength using RLEM and RFEM

Probabilistic Analysis of Layered Slopes with Linearly Increasing Cohesive Strength and 2D Spatial Variability of Soil Strength Parameters Using Non-Circular RLEM Approach

“…As shown in Figure 6, for small values of spatial correlation length the mean Fs is less than 1. Thus, as reported by Javankhoshdel et al (2017), decreasing spatial correlation length increases probability of failure in this case. However, in the three other cases, a correlation length approximating infinity (i.e.…”

“…The combination of refined search with optimization and random fields generated using LAS helps to locate the critical slip surface in the spatially variable field. The disadvantage of the circular RLEM is that the circular RLEM cannot capture irregular shapes of failure (Javankhoshdel et al 2017). This is especially noticeable in cases with highly fluctuating random fields.…”

“…The influence of spatial variability of soil properties on probability of failure using conventional limit equilibrium slope stability analyses and random field generation techniques has been investigated by El-Ramly et al (2002), Low (2003), Babu and Mukesh (2004), Low et al (2007), Hong and Roh (2008), Cho (2010), Wang et al (2011), Tabarroki et al (2013), Javankhoshdel and Bathurst (2014) and Javankhoshdel et al (2017). Important contributions to the influence of spatial variability of soil properties on stability of slopes have been made by Griffiths and Fenton (2004) using the two-dimensional (2D) random finite element method (RFEM), which combines the finite element method, strength reduction method and Monte Carlo (MC) sampling of soil properties from random fields that are generated using the local average subdivision (LAS) method.…”

“…Important contributions to the influence of spatial variability of soil properties on stability of slopes have been made by Griffiths and Fenton (2004) using the two-dimensional (2D) random finite element method (RFEM), which combines the finite element method, strength reduction method and Monte Carlo (MC) sampling of soil properties from random fields that are generated using the local average subdivision (LAS) method. Javankhoshdel et al (2017) investigated the influence of spatial variability of soil strength parameters on probability of failure for simple slopes with stationary mean undrained shear strength. However, the main focus of the paper was on the influence of method of analysis on numerical outcomes.…”

On the reliability assessment of a controlled dyke failure

“…Vanmarcke, 1977;Campanella et al, 1987;Wickremesinghe & Campanella, 1993;Phoon & Kulhawy, 1999;Lloret-Cabot et al, 2014;Fenton et al, 2018;de Gast et al, 2019), and into probabilistic methods of analysis for propagating the effects of uncertainty from the material level to the geotechnical structure level. These methods have included semi-analytical methods, such as the point estimate method (Rosenblueth, 1975), first-order reliability method (Ang & Tang, 1984) and first-order second moment method, as well as computational methods, such as those linking random fields with various limit equilibrium methods (Cho, 2007;Jiang et al, 2014;Javankhoshdel et al, 2017), sometimes referred to as the random limit equilibrium method (RLEM), and the random finite-element method (RFEM) (Griffiths & Fenton, 1993;Fenton & Griffiths, 2008). There now exists a wide body of literature investigating the influence of spatial variability (in so-called uniform layers of soil) on the performance of geotechnical structures, although the practical application of probabilistic methods remains low, especially for those methods that are computationally intensive.…”