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.

This study investigates the influence of Magnetic Field-Assisted natural aging on the mechanical properties of AA7075 aluminum alloys. Specimens that were naturally aged under a 3 T magnetic field for up to 168 hours exhibited hardness increases of up to 13.8% compared with those naturally aged under conventional (0 T) conditions. Furthermore, specimens subjected to 24 hours of natural aging under magnetic field followed by artificial aging at 120 °C for 72 hours under 3 T demonstrated a pronounced enhancement in peak hardness, along with a reduction in the required aging time. These results indicate that the application of a magnetic field during the NA process accelerates precipitation kinetics and enhances the strength of these alloys. Overall, magnetic field-assisted aging presents a promising strategy to improve mechanical performance along with significant reductions in processing time for AA7XXX-series aluminum alloys.