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Coupled Analysis of Risk Factor for Tailing Pond Dam Failure Accident Based on N–K Model and SNA

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  • Liwei Yuan

    (Faculty of Public Safety and Emergency Management, Kunming University of Science and Technology, Kunming 650093, China)

  • Di Chen

    (Faculty of Public Safety and Emergency Management, Kunming University of Science and Technology, Kunming 650093, China)

  • Sumin Li

    (Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China)

  • Guolong Wang

    (Yunnan Power Transmission and Transformation Engineering Co., Ltd., Kunming 650216, China)

  • Yanlin Li

    (Yongshan Jinsha Lead-Zinc Mine Co., Ltd., Zhaotong 657309, China)

  • Bin Li

    (Yongshan Jinsha Lead-Zinc Mine Co., Ltd., Zhaotong 657309, China)

  • Minghui Chen

    (Faculty of Public Safety and Emergency Management, Kunming University of Science and Technology, Kunming 650093, China)

Abstract

The failure of tailings pond dams represents a complex coupled system involving various risk factors, including human, governance, facilities, and environmental aspects. It is crucial to identify key risk factors at the system level to enhance the safety management of tailings ponds. We analyzed 74 cases of tailings pond dam failure accidents, both domestically and internationally, from the perspectives of human, governance, facility, and environment. We employed the 2–4 Model to identify and extract the causes of dam failures, summarizing these into four primary risk factors and 40 secondary risk factors, while constructing a risk coupling mechanism model. The natural killing (N–K) model was implemented to analyze the risk coupling values of primary risk factors and quantify these couplings. The N–K model facilitated an analysis of the risk coupling values of first-level risk factors, while social network analysis (SNA) was employed to visualize the relationships among second-level risk factors and assess the centrality and accessibility of nodes within the risk factor network. The out-degree of the risk nodes was corrected by integrating the N–K model with the SNA, leading to the identification of key risk factors associated with tailings pond dam failures and the formulation of corresponding safety prevention and control strategies. The findings indicate that managing multi-risk factor coupling is an effective approach to mitigating the occurrence of tailings pond dam failure accidents. Notably, unfavorable environmental risk factors significantly contribute to the coupling of human–governance–facility–environmental risks, necessitating targeted management strategies. Furthermore, inadequate safety supervision, weak safety awareness, inadequate receipt and inspection, and irregular operation represent additional key risk factors requiring focused prevention and control efforts.

Suggested Citation

  • Liwei Yuan & Di Chen & Sumin Li & Guolong Wang & Yanlin Li & Bin Li & Minghui Chen, 2024. "Coupled Analysis of Risk Factor for Tailing Pond Dam Failure Accident Based on N–K Model and SNA," Sustainability, MDPI, vol. 16(19), pages 1-20, October.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:19:p:8686-:d:1494378
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    References listed on IDEAS

    as
    1. Guo, Jian & Luo, Cheng & Ma, Kaijiang, 2023. "Risk coupling analysis of road transportation accidents of hazardous materials in complicated maritime environment," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    2. Jie Liu & Liting Wan & Wanqing Wang & Guanding Yang & Qian Ma & Haowen Zhou & Huyun Zhao & Feng Lu, 2023. "Integrated Fuzzy DEMATEL-ISM-NK for Metro Operation Safety Risk Factor Analysis and Multi-Factor Risk Coupling Study," Sustainability, MDPI, vol. 15(7), pages 1-26, March.
    Full references (including those not matched with items on IDEAS)

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