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.

doi:10.16186/j.cnki.1673-9787.2025030058

Received: 2025/03/25

Revised: 2025/05/28

Published: 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