CHEN Da, XUE Xicheng, WEI Jiangbo. Simulation of failure process of Liujian landslide based on PFC2D[J]. COAL GEOLOGY & EXPLORATION, 2018, 46(4): 115-121. DOI: 10.3969/j.issn.1001-1986.2018.04.019
Citation: CHEN Da, XUE Xicheng, WEI Jiangbo. Simulation of failure process of Liujian landslide based on PFC2D[J]. COAL GEOLOGY & EXPLORATION, 2018, 46(4): 115-121. DOI: 10.3969/j.issn.1001-1986.2018.04.019

Simulation of failure process of Liujian landslide based on PFC2D

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National Natural Science Foundation of China(41302276)

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  • Received Date: January 06, 2018
  • Published Date: August 24, 2018
  • In this paper, Liujian landslide in Luonan County, Shaanxi Province was taken as the research object, particle flow discrete element method was used to simulate the movement and failure process. First the meso structure parameters of saturated soil of the landslide were calibrated through the biaxial numerical test, compared with the macro mechanical parameters of saturated soil mass in laboratory test, by verification the meso parameters could be applied to the analysis of the movement and failure of landslide, and then introduced to the particle flow(PFC2D) program in parallel bond model, the landslide model was established by using ball-wall modeling method, the displacement and speed of particles in different key parts of the landslide were monitored to clarify the characteristics of movement and failure. Simulation results show that the rainfall was the direct factors inducing Liujian landslide, the slope deformation and failure mode of the landslide was sliding collapse induced by traction caused by excavation at the slope toe from the leading edge to the rear and the forward movement of the rear by pore water pressure. The overall characteristics were that the upper part was thrusted, the middle sheared, the lower dragged; The maximum sliding speed of the landslide was 13.4 m/s, the maximum slippage was 170 m, and the sliding stage lasted for 25 s. The simulation of the movement and failure process of landslide through particle flow method has good applicability and can provide basis for engineering decision-making.
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