Probability Methods for Stability Design of Open Pit Rock Slopes: An Overview

Abstract

The rock slope stability analysis can be performed using deterministic and probabilistic approaches. The deterministic analysis based on the safety concept factor uses fixed representative values for each input parameter involved without considering the variability and uncertainty of the rock mass properties. Probabilistic analysis with the calculation of probability of failure instead of the factor of safety against failure is emerging in practice. Such analyses offer a more rational approach to quantify risk by incorporating uncertainty in the input variables and evaluating the probability of the failure of a system. In rock slope engineering, uncertainty and variability involve a large scatter of geo-structural data and varied geomechanical test results. There has been extensive reliability analysis of rock slope stability in the literature, and different methods of reliability are being employed for assessment of the probability of failure and the reliability of a slope. Probabilistic approaches include Monte Carlo simulation (MCS), the point estimate method (PEM), the response surface method (RSM), first- and second-order reliability methods (FORMs and SORMs), and the first-order second-moment method (FOSM). Although these methods may be complicated, they provide a more complete definition of risk. Probabilistic slope stability analysis is an option in most commercial software; however, the use of this method is not common in practice. This paper provides an overview of the literature on some of the main probabilistic reliability-based methods available for the design of the rock slope in open pit mining. To demonstrate its applicability, the paper investigates the stability of a rock slope in an open pit mine in the Goldfields region, Western Australia. Two different approaches were adopted: deterministic stability analysis using two-dimensional limit equilibrium and finite element shear strength reduction methods using SLIDE and RS2 software, respectively, and probabilistic analysis by applying the MCS and RSM methods in the limit equilibrium method. In this example, the slope stability analysis was performed using the Spencer method with Cuckoo search optimization to locate the critical slip surface. The results obtained were compared and commented on.

Choosing between prediction and explanation in geological engineering: lessons from psychology

“…However, the contribution of these models to improving predictive power is questioned, as there are many sources of uncertainty, including aleatoric and epistemic uncertainties. Hence, the overall degree of uncertainty cannot be assessed quantitatively (Abdulai and Sharifzadeh 2021).…”

Disaster cassification net: A disaster classification algorithm on remote sensing imagery

“…In order to further verify the algorithm effect, the D-Net was compared with the Transformer algorithm ViT, DeepViT (Zhou et al, 2021), CaiT (Martín Sujo et al, 2021), CCT (Tang et al, 2021), PiT (Abdulai and Sharifzadeh, 2021), LeViT (Levit and Malenko, 2011) and CvT (Wu et al, 2021) models. It can be seen from Table 4 that It can be seen from Figure 5 and Figure 6 that the Accuracy and Loss of the D-Net algorithm tend to be stable after 100 iterations, which proves that it is effective to set the number of iterations to 100 in Frontiers in Environmental Science frontiersin.org our experiments.…”

Probabilistic assessment of slope stability at ore mining with steep layers in deep open pits

“…The research purpose is to develop a methodology for the current prediction of the geomechanical situation when mining an ore deposit with steep-dipping layers. The methodology is based on a combination of numerical (finite element) analysis of changes in the rock SSS caused by design changes in the overall open-pit slope angle, as well as stochastic simulation [40]- [42], which makes it possible to assess random risks associated with natural variations in the object state [43].…”