Stability assessment and dynamic analysis of a large iron mine waste dump in Panzhihua, Sichuan, China

  • Yiding Bao
  • Xiaohui Sun
  • Jianping ChenEmail author
  • Wen Zhang
  • Xudong Han
  • Jiewei Zhan
Original Article


Catastrophic landslides and flowslides usually occur at large waste dumps. Compared to normal slopes, waste dumps have unique topographical conditions and material properties that cause considerable challenges associated with hazard prediction and mitigation. This paper describes one of the largest and highest waste dumps in China, the Zhujiabaobao waste dump, which covers an area of 4 km2 and has a volume of 30,000 × 104 m3 mine waste. A field investigation in April 2016 indicated that the waste dump was unstable. To assess the stability of the slope and predict its hazard scale, the authors use a 3D slope model based on a discrete element method to achieve it. The model is first constructed based on field investigations, including reconnaissance, as well as geomorphological analysis and laboratory experiments. Then, the strength reduction technique is used to calculate the safety factor of a slope. The results show that the safety factor of the slope is 2.3, and compared to the normal limit equilibrium method, the safety factor calculated by the DEM simulation is more accurate and approximately about 15% larger, because it considers more realistic boundary conditions and material properties. During the calculation of the safety factor, the corresponding run-out process can be presented as well. The simulation shows that sliding masses at different parts have different mobility performances, which the upper and front particles presenting the potential to move farther and faster during the run-out process due to force conditions. Additionally, the proposed method shows that topography is a crucial factor for mass movement that requires special attention for the prevention and prediction of landslide hazards.


Zhujiabaobao waste dump Safety factor Mobility performance 3D discrete element model 



This work was supported by the National Natural Science Fund of China (Grant no. 41330636), and the Graduate Innovation Fund of Jilin University (Grant no. 2017137).


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Yiding Bao
    • 1
  • Xiaohui Sun
    • 1
  • Jianping Chen
    • 1
    Email author
  • Wen Zhang
    • 1
  • Xudong Han
    • 1
  • Jiewei Zhan
    • 1
  1. 1.College of Construction EngineeringJilin UniversityChangchunChina

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