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| Topological feature study of slope failure process based on persistent homology machine learning |
| Received:May 13, 2020 Revised:June 27, 2020 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx20200513002 |
| KeyWord:slope persistent homology bar code map feature selection topological analysis |
| Author | Institution |
| 陈龙飞 |
湘潭大学 土木工程与力学学院, 湘潭 |
| 游世辉 |
枣庄学院 机电工程学院, 枣庄 |
| 刘小飞 |
湘潭大学 土木工程与力学学院, 湘潭 |
| 赵小英 |
莫斯科大学, 莫斯科 |
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| Abstract: |
| Firstly,this paper uses software UDEC to simulate the instability failure process of a slope under seismic load,studies the dynamic response of slope failure,obtains the deformation characteristics and displacement cloud map of the slope,then analyzes the instability state of the slope by using the theory of persistent homology,generates bar code map,and extracts the topological characteristics of the slope from its bar code map.The topological characteristics corresponding to the critical state of slope instability are found,and the relationship between the topological characteristics and the instability evolution is established.Finally,it provides a topological research tool for slope failure prediction.The results show that the change of the longest Betty 1 bar code reflects the evolution process of the slope and the law of instability failure.Using discrete element method and persistent homology theory to study the failure characteristics of the slope under external load can better understand the failure mechanism of the slope,provide theoretical basis for engineering protection,and also provide a new mathematical method for slope safety design and disaster prediction research. |
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