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Determination of the critical failure surface for slope stability analysis using ant colony optimization

机译:使用蚁群算法确定边坡稳定性分析的临界破坏面

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Slope stability analysis of any natural or artificial slope aims at determining the factor of safety of the slip surface that possesses the lowest factor of safety. In this study, an ant colony optimization (ACO) algorithm is developed to solve this factor-of-safety minimization problem. Factors of safety of slip surfaces are found by using the Morgenstern-Price method, which satisfies both force and moment equilibrium. Nonlinear equations from the Morgenstern-Price method are solved numerically by the Newton-Raphson method. In the proposed ACO algorithm, the initiation point and the shape of the slip surface are treated as the search variables. The proposed heuristic algorithm represents slip surfaces as piecewise-linear curves and solves for the optimal curve yielding the minimum factor of safety. To demonstrate its applicability and to investigate the validity and effectiveness of the algorithm, four examples with varying complexity are presented. The obtained results are compared with the available literature and are found to be in agreement.
机译:任何自然或人工边坡的边坡稳定性分析旨在确定具有最低安全系数的滑面的安全系数。在这项研究中,开发了一种蚁群优化(ACO)算法来解决此安全系数最小化问题。使用Morgenstern-Price方法可以找到滑动面的安全因素,该方法既满足力平衡又满足力矩平衡。通过牛顿-拉夫森方法,数值求解了Morgenstern-Price方法产生的非线性方程。在提出的ACO算法中,将滑移面的起始点和形状视为搜索变量。所提出的启发式算法将滑动表面表示为分段线性曲线,并求解产生最小安全系数的最佳曲线。为了证明其适用性并研究该算法的有效性和有效性,给出了四个具有不同复杂度的示例。将获得的结果与现有文献进行比较,发现是一致的。

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