## 1 Introduction
However, the test results above suggest that the occurrence of the rock block destroys the original structure of the soil matrix, leading to the non-homogeneous and discontinuous structural characteristics of soil-rock mixture, especially under uniaxial compression conditions. [PERSON] et al. [17] demonstrated that the uniaxial compressive strength (UCS) of soil-rock mixture significantly decreased as rock content increased, with more pronounced ductileness characteristics. Similar findings were also found by [PERSON] [18] and [PERSON] [19]. However, the keynote of experimental studies mainly focuses on the effect of varying rock content on the UCS of soil-rock mixture from a quantitative perspective. The mechanism of the derived soil-rock interface on the failure characteristics and strength response of soil-rock mixture is still not sufficiently and comprehensively understood. Given the limitations of experimental methods in discussing the influence of the soil-rock interface, numerical methods have been widely adopted to effectively investigate the destruction process of soil-rock mixture. So far, researchers have chosen continuous medium mechanical calculation methods--such as the finite element method (FEM) [20; 21; 22], finite difference method (FDM) [23; 24; 25], and numerical manifold method (NMM) [26; 27; 28]--as well as discontinuous medium mechanical calculation methods, such as the discrete element method (DEM) [29; 30; 31], to analyze the mechanical characteristics of soil-rock mixture under different loading conditions. Based on experimental and simulation results, the neural network method has been widely applied to assess the structural and mechanical characteristics of geotechnical materials, greatly improving the effectiveness and efficiency of calculations [32; 33; 34]. However, compared to the extensive parameter data available for soils or jointed rock, the limitations of soil-rock mixture databases results in prediction outcomes that are not yet comprehensive. Among these, DEM provides an effective approach to simulating the macroscopic mechanical properties of the internal soil, block, and soil-rock interfaces, respectively, by precisely controlling the microscopic contact models among the ball (or block) elements. Additionally, DEM can effectively simulate the large deformation and localized failure processes of S-RM by modeling the breakage and re-connection of contacts between elements, thereby addressing the limitations of the continuous medium mechanical calculation methods and experimental approaches [35; 36]. The key to ensuring high accuracy in DEM numerical simulation results lies in developing a precise meso-structure model which can characterize the basic features of the multi-phase compositions of the material. The modeling methods of meso-structure for soil-rock mixture can be broadly classified into the image analysis method and stochastic generation method, depending on how internal rock blocks are generated. The image analysis method constructs the soil-rock mixture model based on processed images, offering higher accuracy. However, this method is time-consuming, costly, and challenging when it comes to acquiring morphological data on rock blocks with a small size. The stochastic generation method, on the other hand, allows for the batch generation of polygonal rock blocks of random sizes based on mathematical statistics and random placement theory. This method requires conflict judgment to prevent rock block overlap, resulting in rock block models that differ from actual distributions [20]. Therefore, the method for generating small, irregular rock blocks based on real block morphology remains a critical challenge in constructing accurate microscopic structural models of soil-rock mixture. The results of the aforementioned studies indicate that significant progress has been made in understanding the mechanical characteristics of soil-rock mixture under uniaxial conditions.