Critical slip line recognition and extraction method of slope based on modified k-medoid clustering algorithm

• Published in: Computers and geotechnics 2023-02, Vol.154, p.105125, Article 105125
• Main Authors: Chen, Yifan, Li, Hongsheng, Lin, Hang, Wang, Yixian, Zhao, Yanlin, Chen, Yizhou
• Format: Article
• Language: English
• Subjects: Critical slip line; K-medoid clustering algorithm; Numerical simulation; Slope stability; Strength reduction method
• ISSN: 0266-352X; 1873-7633
• DOI: 10.1016/j.compgeo.2022.105125

Previous studies in the field of slope stability mostly concentrate on the calculation of the safety factor, while critical slip line recognition and extraction are rarely noticed. Since the popular strength reduction method can only provide an approximate slip region, an automatic recognition and rapid extraction method for the slip line of a slope was proposed. Its core lies in the separation of slip mass and stable mass, which was realized by the modified k-medoid clustering algorithm according to the horizontal displacement difference of nodes, and the boundary was regarded as the critical slip line of the slope. In particular, for slopes requiring high slip line accuracy, it is recommended that discrete point networks can be arranged at custom intervals in the slip region, and the horizontal displacement of each point is calculated by the inverse transformation method of isoparametric elements. On this basis, a more accurate slip line is identified and extracted by the modified k-medoid clustering algorithm. This method reduces the influence of grid size and avoids the subjectivity of defining the slip line artificially. Ultimately, based on the published slope cases, the slip lines extracted by the proposed method were compared with those obtained by previous methods, which verifies its validity and reflects the advantages.