## 1 Introduction  
Metallic ore deposits are generally formed through magmatic intrusions, followed by metamorphism [1]. The regions where these deposits are located often exhibit complex geological structures with well-developed joints and fractures, as well as common fault fracture zones. The mechanical parameters of the surrounding rock show significant variability. This variability necessitates a thorough consideration of the influence of complex geological structures, such as faults and weak planes, as well as the heterogeneity of rock mass mechanical parameters during rock mass stability analysis [2, 3]. Currently, a variety of methods have been developed by both domestic and international scholars to study the stability of the surrounding rock in mining projects. The most traditional and widely used approach is the in situ monitoring method. This technique involves installing various sensors, such as acoustic emission monitors [4], displacement meters [5], and stress meters [6], to collect real-time monitoring data for the dynamic analysis of rock stability. While this method is rooted in actual field conditions and provides reliable data, it requires sophisticated equipment, involves complex data analysis, and makes it difficult to integrate data collected over different time periods. As a result, it often fails to establish consistent and meaningful patterns and may produce contradictory results that are hard to interpret [7]. Another method is the physical modeling approach, which involves constructing scaled or proportional models under laboratory conditions to simulate the mechanical behavior and mechanisms of real engineering structures or geological conditions. This method is particularly suitable for studying the interactions within complex systems, such as changes in rock mass strength under multi-field coupling [8] and the cooperation between the anchor support and the rock mass [9]. It provides scientific evidence for optimizing on-site structural designs, as well as for predicting and improving rock mass stability. With the rapid advancement of computer hardware and software technologies, numerical simulation methods have been increasingly applied in mining engineering to address the growing complexity of mining safety challenges. These methods now cover key issues such as rock instability, seepage failure, and surface deformation [10; 11; 12]. In mining projects, numerical simulation has become one of the primary methods for solving complex problems due to its flexibility and versatility. By selecting appropriate constitutive models, numerical simulations can accurately reflect the complex physical properties of rock masses. Additionally, using techniques such as the finite element method (FEM) [13] and the discrete element method (DEM) [14] provides results that are closely aligned with real-world conditions. Despite the advantages of numerical simulation methods, such as being cost-effective and efficient, they are prone to inaccuracies in mining projects with complex geological conditions. These inaccuracies can lead to distorted simulation outcomes, affecting the reliability of the results. In actual mining projects, faults and heterogeneous rock masses significantly influence the stability of the surrounding rock. To improve accuracy, key geological units, such as ore bodies and fault zones, must be modeled with high precision. Increasing the mesh density and the number of elements, while accounting for complex geological structures such as faults and weak planes, is essential for improving the accuracy of numerical simulations [15]. To make simulation results more representative of actual engineering conditions, it is crucial to fully consider the heterogeneous nature of rock masses. The mechanical properties of rock masses vary significantly from the microscopic to the macroscopic scale, and the presence of fractures, joints, faults, and different lithification processes can lead to substantial variation in the strength parameters of rock in different spatial locations [16].