| Citation: | CHEN Yingxian,YE Yongchao,YANG Hongxia,et al. Determination of the 3D most dangerous sliding surfacefor open-pit mine slopes based on multiple cross-profiles[J]. Bulletin of Geological Science and Technology,2025,44(6):1-10 doi: 10.19509/j.cnki.dzkq.tb20230690 |
At present, the two-dimensional (2D) profiles are widely used for slope stability analysis, which has proved to be efficient and relatively accurate.
However, the two-dimensional profile cannot describe the 3D spatial morphology of the most dangerous sliding surface sliding mass.
To address the limitation, based on the stability analysis of the two-dimensional profile slope, the three-dimensional most dangerous sliding surface of the slope is fitted using the spline function by associating multiple profiles with the three-dimensional slope model. Firstly, the relationship between the two-dimensional profile and the three-dimensional slope space is established by setting the profile name, horizontal coordinate positioning and elevation positioning of the graphic elements in the profile line and the two-dimensional profile. Secondly, the most dangerous sliding surface lines of each profile are automatically generated by using the multi-profile resultant force method, and the most dangerous sliding surface lines of each two-dimensional profile are converted to three-dimensional slope space by using the coordinate transformation formula. Finally, the spline function interpolation is used to fit the most dangerous sliding surface lines in the three-dimensional space to construct the three-dimensional most dangerous sliding surface. Taking the southwest slope of an open-pit mine in Xilinhot, Inner Mongolia as an example, a three-dimensional engineering geological model of the slope is established, and five two-dimensional profiles for slope stability analysis are generated. Through this method, the three-dimensional most dangerous sliding surface and three-dimensional sliding mass are successfully generated and their rationality is verified.
The research results provide new insights for predicting the location, scale, and damage degree of potential slope sliding masses.
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