Slope Stability Analysis: Implementing Discrete Failure Mechanisms and Horizontal Slice Limit Equilibrium Method

P Xu and GG Liu and ZQ Chen and SH Li, INTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS, 49, 2849-2863 (2025).

DOI: 10.1002/nag.4020

The safety factor of a slope is one of the most important indicators for evaluating slope stability. To more reasonably calculate the safety factor of slopes, this paper presents a new method combining discrete failure mechanisms and a horizontal slice method. This approach generates potential sliding surfaces using discrete techniques, calculates the safety factor of specific sliding surfaces via the horizontal slice method, and then transforms the slope stability analysis into a three-parameter optimization problem, which is solved quickly using a global optimization algorithm (gray wolf optimizer). Cases under static and dynamic conditions show that the safety factor calculated by this method has a relative error of less than 2% compared to those calculated by the strength reduction method and the Morgenstern-Price method, with the critical sliding surfaces also aligning well. In complex real-world slope scenarios, the critical slip surface identified using the proposed method more closely aligns with that obtained via the strength reduction approach than with the Morgenstern-Price method. Parametric analysis indicates that increasing the soil unit weight leads to a slight decrease in the maximum depth of the slip surface. The maximum depth is more sensitive to the horizontal seismic coefficient than to soil strength parameters; as the seismic coefficient increases, the slip surface deepens markedly. The proposed method is readily extendable to quasi-dynamic analytical models, allowing for more accurate assessment of seismic effects and demonstrating considerable scalability. Compared to the existing slice method, the proposed method not only ensures simplicity but also reasonably accounts for the heterogeneity of the geotechnical parameters of the slope, making it a potentially valuable tool for analyzing slope stability.

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