The primary aim of every twenty-first century mining operation is to extract as much ore as possible in a safe and economical manner. Failure in mine excavation occurs when the shear stress acting on the rock is greater than the shear strength of the rock mass. The stability of rock slopes in open-pit mine and quarry operations is extremely important from both economic and safety points of view because unstable slopes can result in the loss of human life and damage to properties. This paper presents an overview of several case studies of slope failure in mining operations and explains various modes of failure in rock slopes, as well as factors that influence the stability of slope walls. With the aim of enforcing the importance of monitoring and evaluating slope stability in mining, both linear equilibrium and numerical modeling techniques were reviewed to elaborate their importance in designing stable slopes. In addition, the process of slope failure was discussed, and key signs of failure were indicated. In an effort to prevent mines from experiencing the hazards of slope failure, this study reports previous work performed in determining slope failure and the current state-of-the-art models, which entail the integration of analytical methods with artificial intelligence techniques. This innovation would help overcome the drawbacks of conventional prediction techniques that are cumbersome and ambiguous.

The discrete fracture networks (DFN) have become indispensable tools for geomechanical modelling of jointed rock masses. The technology creates a three-dimensional (3D) representation of fracture geometry used in the construction of surface and subsurface engineering projects in mining, civil engineering, and fracturing of the reservoir in the oil and gas industry. The approach depends on the accuracy of the data obtained during site investigation to create models that represent the fracture geometry of the structure. The better the acquired information available, the better the stochastic analysis that determines the engineering applications and designs that can be carried out. Therefore, it is important to use instruments that can capture fracture distribution characteristics such as fracture intensity, fracture orientation, spatial distribution, fracture length, fracture aperture, and size. This study provides a detailed review of the recent advances in the application of a DFN for modelling jointed rock masses in different engineering applications. The paper shows the principles of modelling in a DFN, including various data-capturing methodologies, and the general application of DFN in various fields. Several case studies where the DFN method was applied are presented in the paper. These include evaluation of slope in an open pit mine, modelling of discontinuity in tunneling, stability evaluation of coal seam longwall, the design of high-level radioactive waste, prediction of groundwater flow, fracturing of petroleum reservoirs, and geothermal cracking of shale gas in the coal bed. However, despite the versatility of the DFN technique, there are still some limitations and challenges to the integration of complexities encountered in rock masses within DFN models.