Abstract
Runout prediction and deposit characteristics investigation for the long runout rock landslides are challenging and interesting problems nowadays. On a practical level, the landslide is a critical issue around the world which could lead to catastrophic consequences. One of the current typical instances is the successive Baige landslides in Tibet, China, where massive damages to infrastructure constructions led to evacuation of more than 86,000 people. The work is specially aimed at investigating the dynamic behaviors of the long runout rock landslides and predicting the potential impact region by numerical simulations. The focus is on the representation of the interaction between the constituent blocks and macro-scale response of landslides. In this case, the distance potential-based discrete element method is adopted to solve the above problems and reproduce the sliding process of the Baige landslides. Before applied in modeling the Baige landslides, performances of this method are firstly validated by two well-known benchmark experiments. The simulation results agree well with the existing experimental measurements and reported observations. It is proved that the method could predict a quantitative accumulation area of related landslides and provide a reference of hazard mitigation.
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Acknowledgments
This work is supported by the National Key R&D Program of China (Grant 2018YFC0406705), China Postdoctoral Science Foundation Funded Project (Grant 2019M651677), the 15th Fok Ying-Tong Education Foundation for Young Teachers in the Higher Education Institutions of China (Grant 151073), the Priority Academic Program Development of Jiangsu Higher Education Institutions (Grant YS11001), the 111 Project, and Qing Lan Project.
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Mao, J., Liu, X., Zhang, C. et al. Runout prediction and deposit characteristics investigation by the distance potential-based discrete element method: the 2018 Baige landslides, Jinsha River, China. Landslides 18, 235–249 (2021). https://doi.org/10.1007/s10346-020-01501-8
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DOI: https://doi.org/10.1007/s10346-020-01501-8