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YE J W, LIU P X, LI H G,et al.Cause analysis and prevention of tailings dam failures based on the AISM-MICMAC Model[J].Journal of Henan Polytechnic University(Natural Science) ,2025,44(6):75-82.

基于AISM-MICMAC模型的尾矿库溃坝原因分析及防控研究

叶佳文1, 刘珮勋2,3, 李海港2,3, 石萍萍1, 王雅莉4

1.江西理工大学 应急管理与安全工程学院，江西 赣州  341000；2.江西省应急管理科学研究院，江西 南昌  330000；3.安全生产风险监测预警与防控江西省重点实验室，江西 南昌  330000；4.矿冶科技集团有限公司，北京  100160

摘要: 目的 探究造成尾矿库溃坝各成因之间的关系，研究尾矿库溃坝不同因素之间的演化路径、影响因素之间驱动与依赖的影响关系，识别有较高驱动力和较高依赖度的因素，针对不同成因提出对应策略。  方法 采用AISM-MICMAC模型，系统研究影响因素之间的层级关系和及类别分布。  结果 分析事故案例，得到可能导致尾矿库溃坝因素共69个，分为10个层级，包括直接原因、中间原因和根本原因，位于结构底层的因素为根本原因，位于结构顶层的因素为直接原因。计算因素的驱动力值和依赖度值，得到驱动力值-依赖度值关系图。 结论 关系图揭示各因素所属层级及其演化关系，以及因素间影响关系的相互传递：根本原因具有较高的驱动力和较低的依赖度，直接原因具有较低的驱动力和较高的依赖度。四象限图可有效反映各因素的驱动力值和依赖度值，将各个因素的驱动力值和依赖度值可视化，甄别尾矿库溃坝的关键因素，根据不同象限的因素，提供防控思路和防控措施。

关键词:尾矿库;溃坝;AISM-MICMAC模型;层级划分

doi:10.16186/j.cnki.1673-9787.2025030058

基金项目:国家重点研发计划项目（2023YFC3012200）

收稿日期:2025/03/25

修回日期:2025/05/28

出版日期:2025/10/14

Cause analysis and prevention of tailings dam failures based on the AISM-MICMAC Model

Ye Jiawen1, Liu Peixun2,3, Li Haigang2,3, Shi Pingping1, Wang Yali4

1.School of Emergency Management and Safety Engineering， Jiangxi University of Science and Technology， Ganzhou  341000， Jiangxi， China；2.Jiangxi Academy of Emergency Management Science， Nanchang  330000， Jiangxi， China；3.Jiangxi Provincial Key Laboratory of Work Safety Risk Monitoring， Early Warning， Prevention and Control， Nanchang  330000， Jiangxi， China；4.Beijing General Research Institute of Mining & Metallurgy Technology Group， Beijing  100160， China

Abstract: Objectives To explore the relationships among the causes of tailings dam failures， examine the evolution paths of different factors， analyze the driving-dependence relationships， identify the factors with high driving force and high dependence， and propose corresponding strategies.  Methods The AISM-MICMAC Model was employed to systematically analyze the hierarchical relationships and categorical distribution of influencing factors.  Results Based on accident case analysis， 69 potential factors contributing to tailings dam failures were identified and classified into 10 levels， including direct， intermediate， and root causes. Factors at the bottom of the structure were defined as root causes， while those at the top were direct causes. The driving force and dependence values of the factors were calculated， and a driving-dependence diagram was constructed. Conclusions The diagram revealed the hierarchical levels of the factors， their evolutionary relationships， and the mutual transmission of influences. Root causes exhibited high driving force and low dependence， while direct causes showed low driving force and high dependence. The four-quadrant diagram effectively visualized the driving-dependence relationships， helping to identify key factors and propose targeted prevention and control measures.

Key words: tailings; dam break; AISM-MICMAC model; hierarchical division