Numerical Modeling of Kinetic Features and Stability Analysis of Jinpingzi Landslide

Jiaxuan Huang (), Weichao Du and Mowen Xie
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Jiaxuan Huang: Chinese-German Institute of Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China
Weichao Du: 32023 Troops, Dalian 116023, China
Mowen Xie: Department of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China

Land, 2023, vol. 12, issue 3, 1-17

Abstract: The kinetic features of a slow-moving landslide situated above the Wudongde hydropower station were analyzed using particle flow code 3D (PFC3D) software. This research was based on geological investigations, remote sensing interpretation, and digital elevation models to build the structure of the Jinpingzi landslide. Finite element analysis (FEM) was used to determine the sliding surface. Strength reduction theory (SRT) and particle flow code coupling were used to invert the macro-strength parameters into micro-strength parameters. Finally, the slope failure process was simulated. Meanwhile, the displacement vector angle (DVA) and velocity were used for stability analysis. The simulation results of the kinetic features of slow-moving landslides show that the initial stage begins with accelerated movement, followed by constant-velocity movement and instability failure. The larger the reduction coefficient is, the shorter the duration of each stage is. A two-parameter instability criterion is proposed based on velocity, DVA, and reduction coefficient. Using this criterion, the critical velocity was 200 mm/s, and the critical DVA was 28.15°. The analysis results agree with the actual field monitoring results and motion process. This work confirms that the PFC3D modeling method is suitable for simulating the motion features of landslides.

Keywords: PFC3D; Jinpingzi landslide; kinetic features; stability analysis; strength reduction theory; displacement vector angle (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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