随着社会经济的发展，国家对煤矿安全的重视程度逐渐提高，但煤矿事故仍时有发生，为国家和企业造成了巨大损失。为提高煤矿瓦斯风险管控水平，减少瓦斯事故的发生，本文从隐蔽致灾视角对煤矿瓦斯风险管控进行研究。通过确定煤矿瓦斯重大隐蔽致灾风险，构建煤矿瓦斯重大隐蔽致灾风险管控系统动力学模型，仿真分析管控策略，以期能够优化煤矿瓦斯风险管控，指导和提升煤矿安全保障建设，为预防煤矿瓦斯事故，提高煤矿安全管理水平提供新的思路。本文的主要研究内容和结论如下：

（1）确定了煤矿瓦斯重大隐蔽致灾风险。通过扎根理论，分析得出煤矿瓦斯隐蔽致灾因素，在此基础上，结合三类危险源理论，将煤矿瓦斯隐蔽致灾风险分为环境及地质构造、人因及机械设备和组织管理；采用层次分析法和物元可拓模型对煤矿瓦斯隐蔽致灾风险进行分析与评价，综合指标权重与风险等级关联度，得出煤矿瓦斯重大隐蔽致灾风险。

（2）构建了煤矿瓦斯重大隐蔽致灾风险管控系统动力学模型。根据“瑞士奶酪”模型，建立煤矿瓦斯重大隐蔽致灾风险管控策略集；将煤矿瓦斯重大隐蔽致灾风险管控系统分为技术层面、管理层面和事后干预3个子系统，分析各子系统的因果关系和反馈回路；基于各子系统的路径分析，确定了煤矿瓦斯重大隐蔽致灾风险管控系统的变量类型及变量间的函数关系。

（3）煤矿瓦斯重大隐蔽致灾风险管控策略仿真分析。根据子系统及整体系统的仿真结果，得出各管控策略能够提高系统管控水平，且系统管控水平经历了缓慢上升和加速上升两个阶段；通过仿真对比分析，探讨各管控策略对子系统及整体系统管控水平的影响，分析得出各子系统的最优管控策略，在此基础上提出煤矿瓦斯重大隐蔽致灾风险管控的优化措施。

With the development of social economy, the national emphasis on coal mine safety has gradually increased, but coal mine accidents still occur from time to time, causing huge losses for the country and enterprises. In order to improve the level of coal mine gas risks control, and reduce the occurrence of gas accidents, this paper investigated gas risks control in coal mines from the perspective of concealed disaster. By identifying the major concealed disaster-causing risks of coal mine gas, constructing the system dynamics model of coal mine gas major concealed disaster-causing risks control, and simulating and comparing the control strategies, in order to improve the level of coal mine gas risks control, guide and enhance the construction of coal mine safety assurance, and provide new ideas for preventing coal mine gas accidents and improving coal mine safety management. The main research and findings of this paper are as follows.

(1) Identified the major concealed disaster-causing risks of coal mine gas. Through grounded theory, the concealed disaster-causing factors of coal mine gas were analyzed, based on which, combined with the theory of three types of hazards, the concealed disaster-causing risks of coal mine gas were classified into three types: environment and geological structure, human factors and mechanical equipment, and organizational management. Analytic Hierarchy Process and Matter Element Extension Model were used to analyze and evaluate the concealed risks of coal mine gas, integrated index weights and risks associated with the level of risks, to derive the major concealed disaster-causing risks of coal mine gas.

(2) The system dynamics model of coal mine gas major concealed disaster-causing risks control was constructed. Based on the Swiss Cheese Model, set of control strategies for the major concealed disaster-causing risks of coal mine gas was established. Divided the coal mine gas major concealed disaster-causing risks control system into 3 subsystems: technical aspects, management aspects and post-event intervention, and analyzed the cause-effect relationships and feedback loops of each subsystem. Based on the path analysis of each subsystem, the types of variables and the functional relationships between variables of the coal mine gas major concealed disaster-causing risks control system were determined.

(3) Simulation analysis of coal mine gas major concealed disaster-causing risks control strategies. According to the simulation results of the subsystems and the overall system, it was concluded that each control strategy could improve the control level of the system, and the control level of the system went through two stages of slow increase and accelerated increase. According to comparative analysis by simulation, explored the impact of each control strategies on the subsystems and the overall system control level, then derived the optimal control strategy in each subsystem. According to the optimal control strategies, the overall optimization measures of coal mine gas major concealed disaster-causing risks control were proposed.

[1] 中华人民共和国2021年国民经济和社会发展统计公报[J]. 中国统计, 2022, 483(03): 9-26.

[2] 范利民. 煤矿隐蔽致灾因素与探查[M]. 北京: 煤炭工业出版社, 2014.

[3] 吴敏杰, 王相业, 张金贵, 等. 神北矿区庙梁煤矿隐蔽致灾因素探查与分析[J]. 中国煤炭, 2023, 49(01): 35-43.

[4] 高建玲. 综合地质勘探方法在煤矿生产中的应用研究[J]. 华北自然资源, 2021(01): 36-37.

[5] 景国勋, 刘孟霞. 2015—2019年我国煤矿瓦斯事故统计与规律分析[J]. 安全与环境学报, 2022, 22(03): 1680-1686.

[6] 张以文, 郭海帅, 涂辉, 等. 基于随机隐含层权值神经网络的瓦斯浓度预测[J]. 计算机工程与科学, 2019, 41(04): 699-707.

[7] 齐庆杰, 刘文岗, 李首滨, 等. 煤矿事故隐患消除科技支撑对策研究[J]. 煤炭科学技术, 2021, 49(04): 20-27.

[8] 高午. 陕西省红石岩煤矿水害隐蔽致灾因素分析[C]//陕西省煤炭学会, 重庆市煤炭学会, 内蒙古煤炭工业协会, 青海省煤炭学会. 煤炭绿色开发地质保障技术研究——陕西省煤炭学会学术年会（2019）暨第三届“绿色勘查科技论坛”论文集. 北京: 应急管理出版社, 2019: 177-184.

[9] 牟义. 神府矿区隐蔽采空区相关致灾因素分析及勘查技术[J]. 地球物理学进展, 2020, 35(03): 1017-1024.

[10] 钟勇林, 廖文德, 邹云辉. 江西省乡镇煤矿瓦斯隐蔽致灾因素调查分析及应用[C]//安徽省煤炭学会, 江西省煤炭学会, 湖南省煤炭学会, 江苏省煤炭学会, 福建省煤炭学会. 皖赣湘苏闽鲁浙七省煤炭学会联合学术交流会论文集. 2018: 163-165.

[11] 柯仙烂. 煤矿隐蔽致灾因素普查方法研究[J]. 能源与环境, 2017, (01): 66-67.

[12] 赵亚飞, 王经明. 黔西北矿区隐蔽水害致灾因素及对策分析[J]. 华北科技学院学报, 2017, 14(01): 28-33.

[13] 秦永军. 煤矿隐蔽致灾因素探查的技术路线[C]//陕西省煤炭学会. 煤矿隐蔽致灾因素及探查技术研究. 北京: 煤炭工业出版社, 2015: 37-39.

[14] 张立辉, 李伟, 范文胜. 补连塔煤矿隐蔽致灾因素定向钻孔探查及防治技术[J]. 煤炭科学技术, 2018, 46(04): 46-51+57.

[15] Tian S C, Mao J R, Li H X. Disaster-causing Mechanism of Hidden Disaster-causing Factors of Major and Extraordinarily Serious Gas Explosion Accidents in Coal Mine Goafs[J]. Sustainability, 2022, 14(19): 12018.

[16] Xu D, Shao D. Identification Method for Covert Causal Factors of Water Disasters in Local Small Coal Mines[J]. J. Liaoning Technol. Univ. Nat. Sci, 2014, 33: 1599-1602.

[17] Liu S, Chen S, Xu K. Detection Technology of Ground-roadway DC Resistivity Method[J]. China Coal Soc, 2017, 42: 360-366.

[18] Zhao Y F, Tian S C. Identification of Hidden Disaster Causing Factors in Coal Mine Based on Naive Bayes Algorithm[J]. Journal of Intelligent & Fuzzy Systems, 2021, 41(02): 2823-2831.

[19] Gu B Z, Dai Z H, Li M X, et al. Construction Method on Transparent Geological Guarantee Technologies: A case study of Wuhai Mining Area[J]. Coal Geology & Exploration, 2022, 50(01): 136-143.

[20] Xia Y C, Wang R, Ma L. Identification and Evaluation of Mine Geological Disaster Elements and Geological Disaster Source Body[J]. China Coal Geology, 2019, 31(02): 51–55.

[21] 张利华. 煤矿瓦斯爆炸危险源SD模型构建及仿真研究[D]. 西安: 西安科技大学, 2012.

[22] 张涛伟, 田水承, 李树刚. 基于险兆事件的煤与瓦斯突出灾害概率模型构建[J]. 煤矿安全, 2014, 45(03): 156-159.

[23] 张鹏翔, 李绍泉. 林华煤矿煤与瓦斯突出构造控制及其分形特征[J]. 中国安全生产科学技术, 2013, 9(10): 94-97.

[24] Wang L, Cheng Y P, Liu H Y. An Analysis of Fatal Gas Accidents in Chinese Coal Mines[J]. Safety Science, 2014, 62: 107-113.

[25] Fu G, Zhao Z, Hao C, et al. The Accident Path of Coal Mine Gas Explosion Based on 24Model: A case study of the Ruizhiyuan gas explosion accident[J]. Processes, 2019, 7(02): 73.

[26] Nie F, Wang H, Qiu L. Research on the Disaster-inducing Mechanism of Coal-gas Outburst[J]. Advances in Civil Engineering, 2020, 2020(06): 1-12.

[27] Li D, Cheng Y. Evaluation of Gas Control Ability of a Coal and Gas Outburst Mine[J]. Energy Sources Part A Recovery Utilization & Environmental Effects, 2014, 36(21-24): 2401-2409.

[28] Dennis, Black J. Review of Current Method to Determine Outburst Threshold Limits in Australian Underground Coal Mines[J]. International Journal of Mining Science and Technology, 2019, 29(06): 48-54.

[29] Li M, Wang H, Wang D, et al. Risk Assessment of Gas Explosion in Coal Mines Based on Fuzzy AHP and Bayesian Network[J]. Process Safety and Environmental Protection, 2020, 135: 207-218.

[30] Tomizuka T, Kuwana K, Mogi T, et al. A Study of Numerical Hazard Prediction Method of Gas Explosion[J]. International Journal of Hydrogen Energy, 2013, 38(12): 5176-5180.

[31] Zhao D, Zhang H, Pan J. Solving Optimization of a Mine Gas Sensor Layout Based on a Hybrid GA-DBPSO Algorithm[J]. IEEE Sensors Journal, 2019, 19(15): 6400-6409.

[32] Zhang J, Ai Z, Guo L, et al. Research of Synergy Warning System for Gas Outburst Based on Entropy-weight Bayesian[J]. International Journal of Computational Intelligence Systems, 2020, 14(01): 376-385.

[33] 邓敢博. 基于数据融合的瓦斯灾害信息系统设计[J]. 煤炭技术, 2021, 40(8): 116-119.

[34] 李爽, 李丁炜, 犹梦洁, 等. 基于BN-ELM的煤矿瓦斯安全态势预测方法[J]. 系统工程, 2020, 38(03): 132-140.

[35] 吴波, 陈辉浩, 黄惟. 基于模糊-熵权理论的铁路瓦斯隧道施工安全风险评估[J]. 安全与环境学报, 2021, 21(06): 2386-2393.

[36] 李冰. 基于深度学习和多源信息融合的煤与瓦斯突出预警方法研究[D]. 徐州: 中国矿业大学, 2021.

[37] 王斌国. 面向矿山瓦斯预警应用的多元多尺度数据融合方法研究[D]. 青岛: 山东科技大学, 2019.

[38] 邱黎明, 李忠辉, 王恩元, 等. 煤与瓦斯突出远程智能监测预警系统研究[J]. 工矿自动化, 2018, 44(01): 17-21.

[39] 王蓬. 煤矿通风瓦斯融合分析及其应用技术研究[D]. 西安: 西安科技大学, 2018.

[40] 吴立云. “三软”煤层瓦斯参数变化特征及突出预警模型研究[D]. 焦作: 河南理工大学, 2014.

[41] 王恩元, 李忠辉, 李德行, 等. 电磁辐射监测技术装备在煤与瓦斯突出监测预警中的应用[J]. 煤矿安全, 2020, 51(10): 46-51.

[42] Shi H, Li W. Application of Matter-elements Model to Dangers Analysis of Coal and Gas Outburst[C]//2009 Third International Symposium on Intelligent Information Technology Application. Nanchang: IEEE, 2009: 618-621.

[43] He J, Lei W, Zheng C. Study on Geological Structure and Gas Content Occurrence Regularity of Gas Mine[C]//IOP Conference Series: Earth and Environmental Science. Nanchang: IOP Publishing, 2020: 012006.

[44] Huang D M, Chang X K, Liu Y J, et al. Design of Early-warning System Model for Gas Explosion[C]//Applied Mechanics and Materials. Hong Kong: Trans Tech Publications Ltd, 2012: 2643-2647.

[45] Li D, Cheng Y. Evaluation of Gas Control Ability of a Coal and Gas Outburst Mine[J]. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2014, 36(21): 2401-2409.

[46] Liu X L, Zhao X S, Dong G G. Study on Early Warning System of Coal and Gas Outburst[C]//Advanced Materials Research. Trans Tech Publications Ltd, 2013: 1146-1150.

[47] Hu D H. The Study of Forewarning Management Control System on Coal Mine[C]//Advanced Materials Research. Guangzhou: Trans Tech Publications Ltd, 2011: 2432-2435.

[48] Li Z, Saydam S, Mitra R, et al. Potential Use of Thin Spray-on Liners for Gas Management in Underground Coal Mines[J]. Journal of the Southern African Institute of Mining and Metallurgy, 2016, 116(12): 1091-1100.

[49] Qiao M, Ren T, Roberts J, et al. Improved Computational Fluid Dynamics Modelling of Coal Spontaneous Combustion Control and Gas Management[J]. Fuel, 2022, 324: 124456.

[50] You B, Li B, Shi S L, et al. The Research of Coal and Gas Outburst Warning Based on Logistic Regression and Geographic Information System[J]. Shock and Vibration, 2021, 2021: 1-8.

[51] Zou Y. Construction and Application of Comprehensive Early Warning System for Coal and Gas Outburst in Xinjing Coal Mine[C]//E3S Web of Conferences. Shenyang: EDP Sciences, 2021: 01016.

[52] Zeng J, Li Q. Research on Prediction Accuracy of Coal Mine Gas Emission Based on Grey Prediction Model[J]. Processes, 2021, 9(07): 1147.

[53] Dong D W, Wang H G, Jia P T. Mine Gas Concentration Pre-warning Based Monitoring Data Relational Analysis[C]//Advanced Materials Research. Trans Tech Publications Ltd, 2013: 3655-3659.

[54] Deng M, Liu D F, Chen Q H. Application of Weighted Moving Average Model on the Pre-warning of Coal and Gas Outburst[C]//Advanced Materials Research. Hohhot: Trans Tech Publications Ltd, 2012: 535-538.

[55] 葛悦, 谢诗艺. 档案文创产品用户满意度影响因素探析-基于《第七档案室》解谜书的扎根分析[J]. 档案与建设, 2022(11): 56-59.

[56] 田水承, 李红霞, 王莉, 等. 从三类危险源理论看煤矿事故的频发[J]. 中国安全科学学报, 2007(01): 10-15+177+179.

[57] John, Haynes. Risk as an Economic Factor[J]. Quarterly Journal of Economics, 1895.

[58] 张华锋. 基于网格化的车务系统职工安全行为风险管控模型研究[D]. 北京: 北京交通大学, 2020.

[59] 李素鹏. ISO风险管理标准全解[M]. 北京: 人民邮电出版社, 2012.

[60] 杨有红. 整合内部控制与风险管理 助推企业可持续性发展[J]. 财会月刊, 2022(16): 18-22.

[61] Zuo F, Zhang K. Selection of Risk Response Actions with Consideration of Secondary Risks[J]. International Journal of Project Management, 2017, 36(02): 241-254.

[62] 周椿奇, 向月, 岑炳成, 等. 清洁能源发展场景下电动汽车入网对区域碳排放的系统动力学建模与分析[J]. 电力科学与技术学报, 2021, 36(03): 36-45.

[63] 田水承, 范彬彬, 杨鹏飞, 等. 基于扎根理论的建筑坍塌险兆事件的影响因素[J]. 西安科技大学学报, 2021, 41(01): 23-28.

[64] 田水承, 樊梦琰, 韩旭, 等. 煤矿险兆事件风险评价指标及分级方法[J]. 矿业安全与环保, 2021, 48(04): 123-127+134.

[65] 钱新明, 陈宝智. 危险源辨识与安全分析[J]. 劳动保护科学技术, 1994, (06): 7-10.

[66] 郭昕曜. 高突矿井瓦斯风险评估方法与管控技术研究[D]. 武汉: 武汉理工大学, 2019.

[67] 景国勋, 陈纪宏. 基于SPA-VFS耦合模型的瓦斯爆炸风险评价[J/OL]. 安全与环境学报: 1-11[2023-05-24].

[68] Li G, Kou C, Wang Y, et al. System Dynamics Modelling for Improving Urban Resilience in Beijing, China[J]. Resources Conservation and Recycling, 2020, 161: 104954.

[69] Moradi M, Kazeminezhad M H, Kabiri K. Integration of Geographic Information System and System Dynamics for Assessment of the Impacts of Storm Damage on Coastal Communities-Case Study: Chabahar, Iran[J]. International Journal of Disaster Risk Reduction, 2020, 49: 101665.

[70] Bahadir M C, Akdag H C. The System Dynamics Modelling for Container Capacity & Transportation Planning Policies[J]. The Asian Journal of Shipping and Logistics, 2019, 35(04): 200-212.

[71] MD Shakib. Using System Dynamics to Evaluate Policies for Industrial Clusters Development[J]. Computers & Industrial Engineering, 2020: 106637.

[72] Larouzee J, Coze J. Good and Bad Reasons: The Swiss Cheese Model and its critics[J]. Safety Science, 2020, 126: 104660.

[73] Bevilacqua M, Ciarapica F E. Human Factor Risk Management in the Process Industry: A case study[J]. Reliability Engineering & System Safety, 2018, 169: 149-159.

[74] Bonsu J, Van Dyk W, Franzidis J P, et al. A Systems Approach to Mining Safety: An application of the Swiss Cheese Model[J]. Journal of the Southern African Institute of Mining and Metallurgy, 2016, 116(8): 776-784.

[75] 田水承, 景国勋. 安全管理学[M]. 北京: 机械工业出版社, 2022.

[76] Zhong S, Lin D. Evaluation of the Coordination Degree of Coal and Gas Co-Mining System Based on System Dynamics[J]. Sustainability, 2022, 14(24): 16434.

[77] Mohammadi A. Identifying Safety Archetypes of Construction Workers Using System Dynamics and Content Analysis[J]. Safety science, 2020, 129(01).

[78] 程晓强, 崔峰, 陈建强, 等.基于系统动力学的煤矿投入管理仿真分析[J]. 矿业安全与环保, 2019, 46(06): 124-130.

[79] 钟永光, 贾晓菁, 钱颖. 系统动力学. 第2版[M]. 北京: 科学出版社, 2013.

[80] 林佳, 宋戈, 张莹. 国土空间系统“三生”功能协同演化机制研究-以阜新市为例[J].中国土地科学, 2019, 33(04): 9-17.

[81] 马恒, 苗倩斐, 韩宝华, 等. 矿井通风系统稳定性SD预测仿真分析[J]. 中国安全生产科学技术, 2019, 15(12): 108-114.

[82] 李乃文, 张丽, 牛莉霞. 煤矿井下安全系统脆弱性的系统动力学仿真研究[J]. 中国安全生产科学技术, 2017, 13(10): 86-92.

[83] Wu B, Wang J, Qu B, et al. Development, Effectiveness, and Deficiency of China’s Coal Mine Safety Supervision System[J]. Resources Policy, 2023, 82: 103524.

[84] Deng Y, Song L, Zhou Z, et al. An approach for Understanding and Promoting Coal Mine Safety by Exploring Coal Mine Risk Network[J]. Complexity, 2017, 2017.

[85] 何叶荣, 范志豪. 煤矿安全管理双权重风险评价方法研究[J]. 西安科技大学学报, 2022, 42(03): 600-606.

[86] 乔万冠, 李新春, 石甜, 等. 基于系统动力学煤矿事故风险耦合度量研究[J]. 数学的实践与认识, 2019, 49(06): 191-198.

[87] Li S, You M, Li D, et al. Identifying Coal Mine Safety Production Risk Factors by Employing Text Mining and Bayesian Network Techniques[J]. Process safety and environmental protection, 2022, 162: 1067-1081.

[88] Bai J, Zheng D, Jia C. Safety Technology Risks and Countermeasures in the Intelligent Construction of Coal Mines[J]. Geofluids, 2022, 2022: 1-8.

[89] 徐美玲, 薛晔, 李凡, 等. 基于PSO-BP-DEMETEL模型的煤矿瓦斯爆炸风险因素分析[J]. 煤矿安全, 2022, 53(05): 164-170.