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A BBO-based algorithm for slope stability analysis by locating critical failure surface

机译:一种基于BBO的斜率稳定性分析算法,通过定位临界失败表面

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摘要

Determination of the critical failure surface is performed in stability evaluation process for road cut slope, embankments, dam, excavations, retaining walls and many more. Finding the critical failure surface in a rock or soil slope is very cumbersome and becomes a difficult constrained global optimization problem. Due to existence of discontinuous function and strong multiple local minima points, researchers are facing difficulties to employ trial-and-error methods in a large search space. Thus, classical optimization techniques fail to converge to a valid solution. In this study a stochastic method called biogeography-based optimization algorithm was adopted for analyzing the factor of safety. Based on the finding from the implementation and quantitative evaluation, it was found that the proposed method for locating critical failure surface in homogeneous soil slope acquires more efficient results over other implemented methods such as grid search and genetic algorithm. The validation and effectiveness of the proposed method are investigated by solving two benchmark case studies from the literature, while the simulation design for slip surfaces is carried out using 'Rocscience slide' software tool for comparing the results.
机译:临界失效表面的测定是在道路切割斜坡,堤坝,大坝,挖掘,挡土墙等的稳定性评估过程中进行的。在岩石或土坡中找到临界失败表面非常麻烦,并且成为一个难以受到约束的全局优化问题。由于存在不连续功能和强大的多个本地最小值,研究人员面临困难,在大型搜索空间中使用试验和错误方法。因此,经典优化技术无法收敛到有效的解决方案。在这项研究中,采用一种称为生物地基优化算法的随机方法来分析安全因子。基于实施和定量评估的发现,发现均匀土壤斜坡中的临界失效表面的提出方法在其他实施方法中获得更有效的结果,例如网格搜索和遗传算法。通过解决文献中的两个基准案例研究来研究所提出的方法的验证和有效性,而Slip曲面的仿真设计是使用“RocScience Slide”软件工具进行比较结果。

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