城市燃气事故不安全行为风险评估

doi:10.16265/j.cnki.issn1003-3033.2022.12.0586

摘要/Abstract

摘要：

为预防城市燃气事故的发生,首先,通过“2-4”模型(24 Model)不安全动作原因因素编码和生产过程危险有害因素代码,分析90起城市燃气死亡事故不安全动作;然后,以修正的不安全动作发生概率和事故危险指数为基础,构建并优化城市燃气事故行为风险评估模型;最后,采用蒙特卡罗法研究4类城市燃气事故相关方的行为风险后果值,并运用敏感度分析得到每类相关方的不安全动作对行为风险影响程度。结果表明:燃气经营者行为风险最大,其次是燃气使用者和燃气工程参与者行为风险,其他第三方单位行为风险最小;事故隐患排查治理工作不落实、燃气燃烧器具或燃气设施使用不合规、未按规范实施职业安全卫生管理或技术服务这3种不安全动作对城市燃气事故行为风险影响较大。

关键词: 城市燃气事故, 不安全动作, 风险评估, “2-4”模型(24 Model), 蒙特卡罗法

Abstract:

In order to prevent the occurrence of urban gas accidents, unsafe acts of 90 urban gas fatal accidents were firstly analyzed through the code of unsafe act factors of 24Model, and classification and code for hazardous and harmful factors in production process. Then, based on the modified probability of unsafe acts and accident risk index, the behavioral risk assessment model of urban gas accidents was constructed and optimized. Finally, the Monte Carlo method was used to study behavioral risk consequence values of four types of parties relating to urban gas accident, and sensitivity analysis was used to obtain the influence degree of unsafe acts of each type of related party on behavioral risk. The results shows that the behavior risk of gas operators is the highest, followed by gas users and gas engineering participants. The risk of other third party units is the lowest. In addition, three kinds of unsafe acts have great impacts on the risk of urban gas accident behavior, including "insufficient implementation of accident hidden danger investigation and rectification", "non-compliant use of gas appliances or facilities" and "illegal implementation of occupational safety and health management or technical services".

Key words: urban gas accidents, unsafe acts, risk assessment, "24 Model"(24Model), Monte Carlo method

张小良, 梁梵洁, 许素睿. 城市燃气事故不安全行为风险评估[J]. 中国安全科学学报, 2022, 32(12): 125-132.

ZHANG Xiaoliang, LIANG Fanjie, XU Surui. Risk assessment of urban gas accident unsafe behavior[J]. China Safety Science Journal, 2022, 32(12): 125-132.

图/表 8

表1

表2

表3

表4

表5

表6

城市燃气事故相关方不安全动作的行为风险因素概率分布及事故危险指数

燃气事故相关方	编号	发生次数	总数及占比/%	发生概率 P₁	不安全动作的修正概率 P₂	事故严重程度 CI	事故危险指数 RI
燃气经营者	A	14	312, 36	0.045	0.058	3.75±1.90	1.93±0.89
	B	8		0.026	0.033	4.06±1.86	2.06±0.89
	C	19		0.061	0.079	4.47±1.58	2.23±0.78
	D	13		0.042	0.054	4.81±2.16	2.42±1.00
	F	8		0.026	0.033	5.94±2.29	0.58±0.20
	G	2		0.006	0.008	3.75±1.77	0.38±0.17
	H	11		0.035	0.046	4.55±1.88	2.28±0.91
	I	25		0.080	0.104	4.50±1.91	2.27±0.92
	J	10		0.032	0.042	4.25±2.06	0.43±0.19
	K	8		0.026	0.033	4.69±1.60	0.47±0.16
	L	21		0.067	0.087	4.17±1.83	2.12±0.88
	N	9		0.029	0.037	4.44±2.08	0.45±0.19
	O	14		0.045	0.058	3.75±1.90	1.92±0.89
	P	3		0.010	0.012	2.50±0.01	0.25±0.01
	Q	4		0.013	0.017	6.25±1.44	0.62±0.14
	R	8		0.026	0.033	5.00±2.31	0.50±0.21
	S	6		0.019	0.025	5.42±1.02	0.54±0.10
	T	44		0.141	0.183	4.77±2.08	2.40±0.97
	U	8		0.026	0.033	4.38±1.77	2.21±0.86
	V	5		0.016	0.021	4.50±2.09	0.46±0.19
	W	42		0.135	0.174	4.11±1.73	4.14±1.65
	X	13		0.042	0.054	3.85±1.30	1.94±0.65
	Y	9		0.029	0.037	4.17±2.17	2.13±1.00
	Z	8		0.026	0.033	4.69±2.09	2.35±0.98
燃气事故相关方	编号	发生次数	总数及占比/%	发生概率 P₁	不安全动作的修正概率 P₂	事故严重程度 CI	事故危险指数 RI
燃气使用者	B	5	302, 35	0.017	0.020	3.50±1.37	0.35±0.13
	D	28		0.093	0.114	4.11±1.70	2.07±0.83
	E	40		0.132	0.162	4.06±1.76	4.11±1.70
	F	24		0.079	0.097	4.27±1.88	2.15±0.90
	G	2		0.007	0.008	2.50±0.01	0.25±0.01
	H	16		0.053	0.065	4.22±1.51	2.10±0.74
	I	33		0.109	0.134	4.39±1.66	2.20±0.82
	J	4		0.013	0.016	3.75±2.50	0.41±0.22
	L	7		0.023	0.028	5.00±1.44	0.50±0.15
	N	23		0.076	0.093	4.46±1.68	2.24±0.83
	Q	7		0.023	0.028	5.36±2.25	0.53±0.21
	R	7		0.023	0.028	3.93±1.34	0.39±0.13
	T	39		0.129	0.158	4.17±1.84	2.11±0.87
	V	3		0.010	0.012	5.00±2.50	0.50±0.22
	W	29		0.096	0.118	3.62±1.43	1.81±0.70
	X	5		0.017	0.020	5.00±1.77	0.50±0.17
	Y	14		0.046	0.057	4.11±1.58	2.06±0.78
	Z	16		0.053	0.065	4.38±1.71	2.19±0.84
燃气工程参与者	B	3	181, 21	0.017	0.022	4.17±1.44	0.42±0.14
	D	34		0.188	0.248	4.71±2.11	2.36±0.99
	F	6		0.033	0.044	4.58±2.46	0.47±0.22
	G	3		0.017	0.022	3.33±1.44	0.34±0.14
	H	2		0.011	0.015	3.75±1.77	0.38±0.17
	I	11		0.061	0.080	3.64±2.05	1.91±0.93
	K	4		0.022	0.029	3.75±1.44	0.38±0.14
	L	2		0.011	0.015	7.50±0.01	0.75±0.01
	M	16		0.088	0.117	4.22±1.51	2.11±0.75
	P	12		0.066	0.087	5.00±1.51	2.49±0.75
	Q	3		0.017	0.022	4.17±2.89	0.45±0.23
	R	8		0.044	0.058	3.44±1.86	0.36±0.17
	T	38		0.210	0.277	4.54±2.24	2.30±1.03
	V	10		0.055	0.073	4.25±2.37	2.20±1.05
	W	6		0.033	0.044	3.75±2.09	0.39±0.19
	X	7		0.039	0.051	3.93±1.97	0.40±0.18
	Y	10		0.055	0.073	3.50±2.11	1.86±0.95
	Z	6		0.033	0.044	4.17±2.58	0.44±0.22
其他第三方单位	D	11	70, 8	0.157	0.207	4.09±1.69	2.06±0.81
	F	3		0.043	0.057	5.00±0.01	0.50±0.01
	H	2		0.029	0.038	5.00±0.01	0.50±0.01
	I	5		0.071	0.094	4.50±1.12	0.45±0.11
	J	5		0.071	0.094	4.50±1.12	0.45±0.11
	M	9		0.129	0.170	3.89±1.82	1.98±0.87
	P	5		0.071	0.094	4.50±1.12	0.45±0.11
	R	6		0.086	0.113	4.17±1.29	0.42±0.13
	T	14		0.200	0.264	3.75±1.90	1.93±0.90
	V	2		0.029	0.038	5.00±0.01	0.50±0.01
	X	5		0.071	0.094	3.50±1.37	0.35±0.13
	Y	3		0.043	0.057	5.00±0.01	0.50±0.01

表6

图1

图2

参考文献 26

[1]	张静远. 燃气管网相邻地下空间爆炸危险性评估方法及其应用[D]. 北京: 北京理工大学, 2016.
	ZHANG Jingyuan. Explosion risk assessment method and application on underground space adjacent to gas pipeline[D]. Beijing: Beijing Institute of Technology, 2016.
[2]	LI Ru, HUANG Hui, ZHANG Jia, et al. Research status and hot spot visualization analysis of "gas safety" based on CiteSpace[C]. E3S Web of Conferences, 2021: DOI:10.1051/e3sconf/202122801012. doi: 10.1051/e3sconf/202122801012
[3]	HEINRICH H W, PETERSEN D C, HAZLETT R S. Industrial accident prevention[M]. New York: McGraw-Hill Companies, 1931:45-46.
[4]	田云祥, 吕莉, 王汉生, 等. 浅谈城镇燃气风险管理中人的不安全行为分析与对策措施[J]. 城市燃气, 2017(3):31-38.
[5]	WANG Wenhe, MOU Dan, LI Feng, et al. Dynamic failure probability analysis of urban gas pipeline network[J]. Journal of Loss Prevention in the Process Industries, 2021, 72:DOI:10.1016/j.jlp.2021.104552. doi: 10.1016/j.jlp.2021.104552
[6]	LI Xinhong, ZHANG Yi, ABBASSI R, et al. Dynamic probability assessment of urban natural gas pipeline accidents considering integrated external activities[J]. Journal of Loss Prevention in the Process Industries, 2021, 69:DOI:10.1016/j.jlp.2020.104388. doi: 10.1016/j.jlp.2020.104388
[7]	孙世梅, 高小迪, 孙赫, 等. 天然气管道施工事故行为原因研究[J]. 中国安全科学学报, 2020, 30(6):8-13. doi: 10.16265/j.cnki.issn1003-3033.2020.06.002
	SUN Shimei, GAO Xiaodi, SUN He, et al. Study on causes of accidents in construction of natural gas pipelines[J]. China Safety Science Journal, 2020, 30(6):8-13. doi: 10.16265/j.cnki.issn1003-3033.2020.06.002
[8]	陈璐瑶, 温钰梅, 王冶. 基于24模型的城市燃气管道维修抢险事故分析[J]. 化工管理, 2021(7):128-129.
	CHEN Luyao, WEN Yumei, WANG Ye. Cause analysis of urban gas pipeline maintenance accident based on the 24 Model[J]. Chemical Management, 2021(7):128-129.
[9]	GUO Zhanglin, SUN Lifang, BO Lilei. Application of the fuzzy comprehensive evaluation model based on entropy to the risk evaluation of urban gas pipeline system[C]. 2010 International Conference on Computer and Communication Technologies in Agriculture Engineering, 2010:DOI:10.1109/ICIEEM.2011.6035104. doi: 10.1109/ICIEEM.2011.6035104
[10]	姚天野, 刘威. 基于AHP-熵权法组合赋权的燃气管网风险评估方法研究[J]. 结构工程师, 2019, 35(6):93-101.
	YAO Tianye, LIU Wei. Risk assessment of gas network based on AHP-Entropy weight method[J]. Structural Engineers, 2019, 35(6):93-101.
[11]	史运涛, 党亚光, 雷振伍, 等. 基于图神经网络的社区户内燃气系统动态风险评估[J]. 安全与环境工程, 2021, 28(5):1-9.
	SHI Yuntao, DANG Yaguang, LEI Zhenwu, et al. Dynamic risk assessment of community indoor gas system based on graph neural network[J]. Safety and Environmental Engineering, 2021, 28(5):1-9.
[12]	许素睿. 基于蒙特卡罗法的煤矿工人不安全行为风险评估[J]. 中国安全科学学报, 2020, 30(4):172-178. doi: 10.16265/j.cnki.issn1003-3033.2020.04.027
	XU Surui. Risk assessment on unsafe behavior of coal miner based on Monte Carlo method[J]. China Safety Science Journal, 2020, 30(4):172-178. doi: 10.16265/j.cnki.issn1003-3033.2020.04.027
[13]	王雅先, 潘琰, 张苏. 建筑电气火灾事故人员不安全行为风险评估[J]. 安全, 2021, 42(9):39-44.
	WANG Yaxian, PAN Yan, ZHANG Su. Risk assessment on unsafe behavior of electrical fire accidents in buildings[J]. Safety & Security, 2021, 42(9):39-44.
[14]	佟瑞鹏, 马晓飞. 基于蒙特卡罗法的家具制造工人不安全行为风险评估[J]. 中国安全生产科学技术, 2018, 14(7):187-192.
	TONG Ruipeng, MA Xiaofei. Risk assessment on unsafe behavior of furniture manufacturing workers based on Monte Carlo method[J]. China Safety Science Journal, 2018, 14(7):187-192.
[15]	TONG Ruipeng, YANG Yunyun, MA Xiaofei, et al. Risk assessment of miners' unsafe behaviors:a case study of gas explosion accidents in coal mine, China[J]. International Journal of Environmental Research and Public Health, 2019, 16(10):DOI:10.3390/ijerph16101765. doi: 10.3390/ijerph16101765
[16]	GB/T 13861—2022, 生产过程危险和有害因素分类与代码[S].
	GB/T 13861-2022, Classification and code for the hazardous and harmful factors in process[S].
[17]	何立胜. 城市燃气管网安全管理体系研究[J]. 内蒙古煤炭经济, 2021(7):114-115.
[18]	鲁征, 傅贵, 薛忠智. 天津港“8·12”危险品仓库火灾爆炸事故行为原因研究[J]. 灾害学, 2017, 32(1):205-211.
	LU Zheng, FU Gui, XUE Zhongzhi. Research on behavioral causes of a fire and explosion accident of 8·12 in Tianjin Port[J]. Journal of Catastrophology, 2017, 32(1):205-211.
[19]	傅贵, 王秀明, 李亚. 事故致因“2-4 ”模型及其事故原因因素编码研究[J]. 安全与环境学报, 2017, 17(3):1003-1008.
	FU Gui, WANG Xiuming, LI Ya. On the 2-4Model and the application of its causative codes to the analysis of the related accidents[J]. Journal of Safety and Environment, 2017, 17(3):1003-1008.
[20]	傅贵, 陈奕燃, 许素睿, 等. 事故致因“2-4 ”模型的内涵解析及第6版的研究[J]. 中国安全科学学报, 2022, 32(1):12-19. doi: 10.16265/j.cnki.issn1003-3033.2022.01.002
	FU Gui, CHEN Yiran, XU Surui, et al. Detailed explanations of 24Model and development of its 6th version[J]. China Safety Science Journal, 2022, 32(1):12-19. doi: 10.16265/j.cnki.issn1003-3033.2022.01.002
[21]	TONG Ruipeng, LI Hongwei, ZHANG Boling, et al. Modeling of unsafe behavior risk assessment:a case study of Chinese furniture manufacturers[J]. Safety Science, 2021, 136:DOI:10.1016/j.ssci.2020.105157. doi: 10.1016/j.ssci.2020.105157
[22]	JIA Qingsong, FU Gui, XIE Xuecai, et al. LPG leakage and explosion accident analysis based on a new SAA method[J]. Journal of Loss Prevention in the Process Industries, 2021, 71(5):DOI:10.1016/j.jlp.2021.104467. doi: 10.1016/j.jlp.2021.104467
[23]	赵孟孟, 亢永, 吴壮. 城市燃气爆炸事故及其防治措施[J]. 北京石油化工学院学报, 2021, 29(2):61-66.
	ZHAO Mengmeng, KANG Yong, WU Zhuang. City gas explosion accident and its prevention measures[J]. Journal of Beijing Institute of Petrochemical Technology, 2021, 29(2):61-66.
[24]	KHOSRAVI Y, ASILIAN-MAHABADI H, HAJIZADEH E, et al. Factors influencing unsafe behaviors and accidents on construction sites:a review[J]. International Journal of Occupational Safety and Ergonomics, 2014, 20(1):111-125. doi: 10.1080/10803548.2014.11077023
[25]	国务院. 生产安全事故报告和调查处理条例[Z]. 2007-04-09.
[26]	KETABDARI M, GIUSTOZZI F, CRISPINO M. Sensitivity analysis of influencing factors in probabilistic risk assessment for airports[J]. Safety Science, 2018, 107:173-187. doi: 10.1016/j.ssci.2017.07.005

序号	不安全动作类别	编号		序号	不安全动作类别	编号
1	违法充装或销售液化气	A		14	燃气燃烧器具或燃气设施管理不当	N
2	违规安装维修燃气燃烧器具或燃气设施	B		15	燃气使用安全宣传不到位	O
序号	不安全动作类别		编号	序号	不安全动作类别	编号
3	违规送气		C	16	违法违规承揽、转包或分包工程	P
4	未按规定施工作业		D	17	项目违规建设或设施设备违规运行	Q
5	燃气燃烧器具或燃气设施使用不合规		E	18	违规指挥施工或作业	R
6	应急处置措施不当		F	19	未供应符合国家质量标准的燃气	S
7	作业期间擅自脱岗		G	20	未按规范实施职业安全卫生管理或技术服务	T
8	安全责任制和管理制度不完善或未落实		H	21	未及时组织有效的维抢操作	U
9	安全教育、考核和操作技能培训不足		I	22	职业安全卫生管理机构设置和岗位人员配备不健全	V
10	承包商管理工作缺失		J	23	事故隐患排查治理工作不落实	W
11	档案资料管理不善		K	24	作业现场安全监管缺失或监护失误	X
12	非法经营		L	25	操作规程、实施方案及安全措施不完善	Y
13	监理人员未履行职责		M	26	应急预案编制、培训、演练、评估不规范或不到位	Z

范围值	影响因素
范围值	a		b		c		d		e		f		g
0~3	优秀		完善		足够		较高		良好		良好		良好
范围值		影响因素
范围值		a		b		c		d		e		f		g
4~6		一般		一般		中等		一般		一般		一般		一般
7~10		错误		欠缺		不足		较低		不好		不好		不好

相关方	影响因素
相关方	a	b	c	d	e	f	g
燃气经营者	4~6	4~6	4~6	7~10	7~10	4~6	7~10
燃气使用者	4~6	7~10	7~10	7~10	7~10	4~6	4~6
燃气工程参与者	4~6	4~6	7~10	7~10	4~6	4~6	4~6
其他第三方单位	4~6	4~6	7~10	7~10	4~6	4~6	4~6

事故的可能性	分值
不可能的	0.05
偶尔的	0.1
可能的	0.5
极有可能的	1

人员伤害程度及范围	估算损失/万元	分值
1~2人死亡	[500,1 000)	2.5
3~9人死亡	[1 000,5 000)	5
10~29人死亡	[5 000,10 000)	7.5
30人以上死亡	[10 000,+∞)	10