The stability assessment and potential sliding surface determination of open-pit mine slopes are pivotal topics in mine safety.
Focusing on an open-pit limestone mine slope in Hebei Province, China, this study proposes a systematic and practical methodology for
modeling, stability analysis, and critical sliding surface determination of three-dimensional (3D) slopes in engineering projects. A 3D
grid model of mine slope characterized by a complex surface configuration was constructed through a series of meticulous operations
using high-quality point cloud data. The safety factor and critical failure state of the slope were determined using a compressive strength
reduction strategy based on the generalized Hoek–Brown criterion. The critical sliding surface of the 3D slope was comprehensively analyzed based on the stress, strain, displacement, and velocity data of the grid model at the critical failure state. First, the potential sliding zone of the 3D slope was identified through combined stress and strain analysis. Furthermore, two innovative approaches for determining the critical sliding surface of the 3D mine slope model were proposed. One method is based on the displacement change rate, which involves
slicing the slope at appropriate angles and analyzing the displacement field of each slice. The other method employs a clustering algorithm to classify the slope grids into stable and sliding groups, with the interface of the two groups representing the sliding surface. Finally, a thorough error analysis was conducted on the critical sliding surfaces obtained from both methods. The sliding surface identified by K-medoids clustering closely matches the one based on the displacement change rate with an acceptable height error (root mean square error=2.76 m). The results indicate a significant similarity in the sliding surface positions obtained by both methods, confirming their feasibility and reliability. Compared to traditional methods, such as displacement contour line and shear strain increment thresholds, the two proposed methods can achieve more precise localization of sliding surfaces.
