Mine slope design is a complex task that requires consideration of geotechnical analysis, structural stability, economics and the environment. Economic factors usually drive mine slope design, particularly in the case of open-pit designs, where the process of steepening slope walls by several degrees can have profound financial implications. Due to the risks associated with catastrophic slope collapse, slope stability analysis is an integral component of open-pit engineering projects. However, initial design concepts and geotechnical assessments are often considered separately. In this study, a technique is developed that combines the scaled boundary finite element method (SBFEM) with genetic algorithms (GAs) to simultaneously perform slope stability analysis and optimise the slope profile. The iterative design approach optimises characteristics of the slope profile such as the slope height, width, angle and number of benches while ensuring the factor of safety (FoS) remains above a threshold value. A salient feature of the technique is the ability to automatically address the modifications to the geometry of the slope by updating the digital images used in the analysis to assess the stability of each instance in the optimisation process and determine the optimum slope geometry. The results highlight the application of the developed technique to determine appropriate slope excavation designs as well as slope backfilling scenarios. The method is exemplified in several cases where complex stratigraphies and spatially variable materials are considered. As such, the GA-driven slope design process conveys an optimised, automated tool, combining mine slope design and slope stability analysis.

中文翻译：

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使用遗传算法和基于图像的全自动分析同时进行边坡设计优化和稳定性评估

矿山边坡设计是一项复杂的任务，需要考虑岩土分析、结构稳定性、经济性和环境。经济因素通常会推动矿山边坡设计，特别是在露天矿设计中，将边坡墙倾斜几度的过程可能会产生深远的财务影响。由于与灾难性边坡坍塌相关的风险，边坡稳定性分析是露天工程项目的一个组成部分。然而，最初的设计概念和岩土工程评估通常是分开考虑的。在这项研究中，开发了一种将缩放边界有限元法 (SBFEM) 与遗传算法 (GA) 相结合的技术，以同时进行边坡稳定性分析和优化边坡剖面。迭代设计方法优化了斜坡轮廓的特性，例如斜坡高度、宽度、角度和长凳数量，同时确保安全系数 (FoS) 保持在阈值以上。该技术的一个显着特点是能够通过更新分析中使用的数字图像来自动解决对斜坡几何形状的修改，以评估优化过程中每个实例的稳定性并确定最佳斜坡几何形状。结果突出了开发技术在确定适当的边坡开挖设计以及边坡回填方案方面的应用。该方法在考虑复杂地层和空间可变材料的几种情况下得到了例证。因此，遗传算法驱动的斜坡设计过程传达了一种优化的自动化工具，