The rock-soil mass, subjected to complex and lengthy geological processes, exhibits heterogeneity which induces variations in mechanical properties, thereby affecting the overall stability of slopes. In this paper, a novel numerical model that incorporates the Weibull distribution function into the meshless numerical manifold method based on the strength reduction method (MNMM-SRM) to account for the slope soils heterogeneity and their influence on the factor of safety () and the critical sliding surface (CSS). Initially, the Weibull distribution is introduced into the MNMM-SRM model based on the complementary theory of subspace tracking, addressing the issue of multiple yield surface corners in the Mohr-Coulomb framework while simultaneously considering the heterogeneous nature of rock and soil formations. Subsequently, an intelligent method based on unsupervised learning is proposed to obtain reasonable CSS, utilizing the total displacement field at slope nodes and the equivalent plastic strain field as input variables. The results serve as criteria for terminating the strength reduction in the MNMM-SRM. The applicability of this method is verified through three typical examples, demonstrating its potential for widespread application in the assessment of heterogeneous slope stability.

中文翻译：

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强度折减无网格数值流形法与无监督学习相结合在异质边坡稳定性分析中的应用


岩土体经历了复杂而漫长的地质过程，表现出非均质性，导致其力学特性发生变化，从而影响边坡的整体稳定性。本文提出了一种新颖的数值模型，将威布尔分布函数纳入基于强度折减法（MNMM-SRM）的无网格数值流形方法中，以考虑边坡土体的非均质性及其对安全系数（）和临界滑动面（CSS）。首先，基于子空间跟踪互补理论，将Weibull分布引入MNMM-SRM模型中，解决了Mohr-Coulomb框架中的多个屈服面角点问题，同时考虑了岩土层的非均质性。随后，提出了一种基于无监督学习的智能方法，利用斜坡节点处的总位移场和等效塑性应变场作为输入变量来获得合理的CSS。结果作为终止 MNMM-SRM 强度降低的标准。通过三个典型算例验证了该方法的适用性，展示了其在非均质边坡稳定性评价中的广泛应用潜力。