Layered rock slopes with structural discontinuities pose significant challenges for stability assessment under complex geological conditions. This study presents an integrated approach combining unmanned aerial vehicle (UAV) photogrammetry, 3D numerical modeling, and the Statistical Mechanics of Rock Masses (SMRM) constitutive model to evaluate slope stability. Focusing on a layered tuffaceous sandstone slope in Shaoxing, China, UAV-derived point cloud data were processed via CloudCompare and Rhino software to generate a high-resolution 3D geological model. The CC-Griddle-Flac3D workflow enabled efficient meshing and integration with Flac3D for numerical analysis. The SMRM model was implemented to quantify anisotropic deformation, stress distribution, rock mass quality, and failure probability. Results demonstrated that the proposed modeling framework effectively captured slope deformation trends and stress heterogeneity, The direction of the structural plane is highly consistent (24 ° simulated vs. 23 ° observed), which indicates that the SMRM constitutive model shows high accuracy in characterizing the anisotropic properties of materials. The SMRM-based stability metrics revealed localized weak zones (Grade IV rock mass) with elevated reinforcement demands (Δσ₃ = 0.0126 MPa) and failure probabilities (60%), while maintaining an overall stability coefficient of 2.0. This method enhances the spatial visualization of rock mass parameters, enabling targeted reinforcement strategies. The study provides a validated technical pathway for rapid slope stability evaluation in geologically complex regions, supporting data-driven disaster prevention decisions.
Shan et al. (Thu,) studied this question.