ISSN 1003-8035 CN 11-2852/P
    LI Qiaochu,CHEN Junhua. Analysis and application of safety risks for gas pipelines in karst sinkhole-prone areas based on the D/I-MICMAC-VS integrated method[J]. The Chinese Journal of Geological Hazard and Control,2023,34(6): 158-166. DOI: 10.16031/j.cnki.issn.1003-8035.202209014
    Citation: LI Qiaochu,CHEN Junhua. Analysis and application of safety risks for gas pipelines in karst sinkhole-prone areas based on the D/I-MICMAC-VS integrated method[J]. The Chinese Journal of Geological Hazard and Control,2023,34(6): 158-166. DOI: 10.16031/j.cnki.issn.1003-8035.202209014

    Analysis and application of safety risks for gas pipelines in karst sinkhole-prone areas based on the D/I-MICMAC-VS integrated method

    • To mitigate the risk of gas pipelines in karst sinkhole-prone areas, this study employs the DEMATEL/ISM method to elucidate the hierarchical structure and causal relationships among various factors in the system, considering four categories of accident causes: human, material, environment and management. Additionally, the MICMAC method is utilized to analyze the dependence and driving force of risk factors. Utilizing the Visual Studio platform, the software for risk analysis of gas pipelines in karst sinkhole-prone areas is developed. This research introduces the D/I-MICMAC-VS integrated risk analysis method and provides an example analysis. The results demonstrate that: (1) The risk factors for gas pipelines in karst sinkhole-prone areas are distributed across six levels. The possibility of risk accidents can be reduced in the short term by rigorously managing surface-level direct factors, while middle-level indirect factors play an intermediary role in the system. Effective control of gas pipeline accidents can only be achieved by addressing deep-rooted factors fundamentally. (2) The spontaneous cluster serves as a key element for risk management and control of gas pipeline accidents, and prioritized intervention significantly aids in accident prevention. The independent cluster directly influences the system’s risk level through its own changes and development. The linkage cluster plays a pivotal role in transmitting and promoting the evolution and development of accidents. Effective risk management and control can be achieved by discerning the deep root factors that inducing changes in the dependency cluster.
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