基于混合因果逻辑的化工园区雷击储罐风险评估

doi:10.16265/j.cnki.issn1003-3033.2024.09.0090

摘要/Abstract

摘要：

沿海化工园区的雷击事故时有发生,对园区生产安全构成严重威胁。为评估化工园区雷击储罐引发的Natech事故,提出一种基于混合因果逻辑(HCL)的风险评估方法。首先,采用事件序列图(ESD)和故障树分析法(FTA),定性分析雷击储罐导致Natech事故的演化路径,为阻断事故传递过程提供可视化基础;其次,采用贝叶斯网络(BN)定量解算人因失误概率,评估雷击储罐事故的混合因果关系;最后,采用混合因果逻辑方法,实现可视化解构雷击储罐Natech事故的复杂性和不确定性。研究结果表明:决策失误是人因失误模型的首要风险源;组织氛围、心理状态、工作环境不佳及监管不力是导致人因失误频繁的主要因素;防雷设施有效性缺失是雷击储罐事故链的诱因;降低风险场景的严重性需要重点加强对全液面火灾和池火灾的管控。

关键词: 混合因果逻辑(HCL), 化工园区, 雷击储罐, 风险评估, 贝叶斯网络(BN), 事件序列图(ESD)

Abstract:

Coastal chemical industrial parks have frequently experienced lightning strikes, which seriously threaten production safety. A risk assessment method based on HCL methodology was proposed to assess Natech (Natural-technological) accidents triggered by lightning strikes on storage tanks in these parks. Firstly, ESD and Fault Tree Analysis(FTA) were employed to qualitatively analyze the evolution paths of Natech accidents caused by lightning strikes on storage tanks, providing a visual foundation for blocking the accident transmission process. Secondly, BN were used to quantitatively calculate human error probabilities and assess the hybrid causal relationships of lightning-induced storage tank accidents. Finally, HCl methodology was applied to visually deconstruct the complexity and uncertainty of Natech accidents caused by lightning strikes on storage tanks. The research results indicate that decision-making error is the primary risk source in the human error model. Organizational atmosphere, psychological state, poor working environment and inadequate supervision are identified as the main factors leading to frequent human errors. The lack of effectiveness of lightning protection facilities is recognized as the trigger in the accident chain of lightning strikes on storage tanks. To reduce the severity of risk scenarios, emphasis needs to be placed on strengthening the control of full-surface fires and pool fires.

Key words: hybrid causal logic (HCL), chemical park, lightning strike on storage tank, risk assessment, Bayesian network (BN), event sequence diagram (ESD)

中图分类号:

X937

杨震, 梁峻铭, 郭梨, 董晓斌. 基于混合因果逻辑的化工园区雷击储罐风险评估[J]. 中国安全科学学报, 2024, 34(9): 174-182.

YANG Zhen, LIANG Junming, GUO Li, DONG Xiaobin. Risk assessment of chemical industrial park storage tanks struck by lightning based on hybrid causal logic methodology[J]. China Safety Science Journal, 2024, 34(9): 174-182.

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参考文献 21

[1]	SHOWALTER P S, MYERS M F. Natural disasters in the United States as release agents of oil, chemicals, or radiological materials between 1980—1989: analysis and recommendations[J]. Risk Analysis, 1994, 14(2): 169-182.
[2]	杨运锋. 典型自然灾害诱发的化工园区多米诺效应事故链路概率预测与风险防控[D]. 广州: 华南理工大学, 2021.
	YANG Yunfeng. Risk prevention and control and probabilistic prediction for accidental chains of domino effects triggered by typical natural disasters in chemical industrial parks[D]. Guangzhou: South China University of Technology, 2021.
[3]	RASMUSSEN K. Natural events and accidents with hazardous materials[J]. Journal of Hazardous Materials, 1995, 40(1): 43-54.
[4]	NECCI A, ANTONIONI G, COZZANI V, et al. A model for process equipment damage probability assessment due to lightning[J]. Reliability Engineering and System Safety, 2013, 115: 91-99.
[5]	NECCI A, ARGENTI F, LANDUCCI G, et al. Accident scenarios triggered by lightning strike on atmospheric storage tanks[J]. Reliability Engineering and System Safety, 2014, 127: 30-46.
[6]	YANG Yunfeng, CHEN Guohua, CHEN Peizhu. The probability prediction method of domino effect triggered by lightning in chemical tank farm[J]. Process Safety and Environmental Protection, 2018, 116: 106-114.
[7]	CHENG Yulong, LUO Yun. Analysis of Natech risk induced by lightning strikes in floating roof tanks based on the Bayesian network model[J]. Process Safety Progress, 2021, 40(1): 1-8.
[8]	ZHANG Di, HAN Zhepeng, ZHANG Kai, et al. Use of hybrid causal logic method for preliminary hazard analysis of maritime autonomous surface ships[J]. Journal of Marine Science and Engineering, 2022, 10(6): 1-26.
[9]	张锴. 基于混合因果逻辑的自主货物运输船舶风险辨识研究[D]. 武汉: 武汉理工大学, 2020.
	ZHANG Kai. Study on risk identification of maritime autonomous surface ship based on hybrid causal logic methodology[D]. Wuhan: Wuhan University of Technology, 2020.
[10]	XU Sheng, KIM E. Hybrid causal logic model for estimating the probability of an icebreaker-ship collision in an ice channel during an escort operation along the Northeast Passage[J]. Ocean Engineering, 2023, 284: 1-16.
[11]	THOMAS S, GROTH K M. Toward a hybrid causal framework for autonomous vehicle safety analysis[J]. Journal of Risk and Reliability, 2023, 237(2): 367-388.
[12]	张冰鉴, 苏秦, 刘海龙. 基于FTA-BN的云ERP不安全事件的人因失误分析[J]. 中国安全科学学报, 2023, 33(2): 38-47. doi: 10.16265/j.cnki.issn1003-3033.2023.02.0412
	ZHANG Bingjian, SU Qin, LIU Hailong. Human error analysis for unsafe events of cloud ERP based on FTA-BN[J]. China Safety Science Journal, 2023, 33(2): 38-47. doi: 10.16265/j.cnki.issn1003-3033.2023.02.0412
[13]	寇兴怡, 帅斌, 黄文成. 基于贝叶斯网络的高速动车组运营故障分析[J]. 中国安全生产科学技术, 2020, 16(4): 63-69.
	KOU Xingyi, SHUAI Bin, HUANG Wencheng. Analysis on operation fault of high-speed EMU based on Bayesian network[J]. Journal of Safety Science and Technology, 2020, 16(4): 63-69.
[14]	姚诗忆. 基于模糊贝叶斯网络的综合交通枢纽地铁车站安全风险评价研究[D]. 广州: 华南理工大学, 2022.
	YAO Shiyi. Research on Safety risk assessment of metro station in integrated transportation hub based on fuzzy bayesian network[D]. Guangzhou: South China University of Technology, 2022.
[15]	程玉龙. 油库雷电火灾耦合致灾机理及防控策略[D]. 北京: 中国地质大学(北京), 2020.
	CHENG Yulong. Study on coupling mechanism of lightning induced fire disasters and pre-control strategy in oil depots[D]. Beijing: China University of Geosciences (Beijing), 2020.
[16]	YANG Zhen, DONG Xiaobin, GUO Li. Scenario inference model of urban metro system cascading failure under extreme rainfall conditions[J]. Reliability Engineering and System Safety, 2023, 229: 1-12.
[17]	WIEGMANN D A, SHAPPELL S A. A human error analysis of commercial aviation accidents using the human factors analysis and classification system (HFACS)[J]. Aviation, Space, and Environmental Medicine, 2001, 72(11): 1006-1016.
[18]	刘全龙, 彭雨蒙, 赵盼, 等. 基于HFACS模型的制造企业机械伤害事故致因分析[J]. 中国安全科学学报, 2023, 33(3): 51-59. doi: 10.16265/j.cnki.issn1003-3033.2023.03.1128
	LIU Quanlong, PENG Yumeng, ZHAO Pan, et al. Analysis of causes of mechanical injury accidents in manufacturing enterprises based on HFACS model[J]. China Safety Science Journal, 2023, 33(3): 51-59. doi: 10.16265/j.cnki.issn1003-3033.2023.03.1128
[19]	RENNI E, KRAUSMANN E, COZZANI V. Industrial accidents triggered by lightning[J]. Journal of Hazardous Materials, 2010, 184(1/2/3): 42-48.
[20]	李子杰. 典型自然灾害引发的罐区事故风险与储罐安全间距研究[D]. 上海: 华东理工大学, 2021.
	LI Zijie. Study on accident risk and safety distance of tank farm caused by typical natural disasters[D]. Shanghai: East China University of Science and Technology, 2021.
[21]	NECCI A, ANTONIONI G, BONVICINI S, et al. Quantitative assessment of risk due to major accidents triggered by lightning[J]. Reliability Engineering and System Safety, 2016, 154: 60-72.

等级	语义值	模糊数
7	非常高	(0.9, 1.0, 1.0)
6	高	(0.7, 0.9, 1.0)
5	偏高	(0.5, 0.7, 0.9)
4	中等	(0.3, 0.5, 0.7)
3	偏低	(0.1, 0.3, 0.5)
2	低	(0, 0.1, 0.3)
1	非常低	(0, 0, 0.1)

编号	描述
PE₁	雷电击中储罐,防雷设施发挥作用
PE₂	一、二次密封区气体浓度达到爆炸极限,雷击引燃
PE₃	固定灭火系统有效,扑灭密封圈火灾
PE₄	固定灭火系统自启失效,人员介入
PE₅	储罐侧壁被雷电击穿导致原油泄漏
PE₆	储罐存储区出现热源,引燃泄漏原油

编号	描述
ES₁	防雷设施完好,无事故发生
ES₂	密封圈发生火灾后及时响应事故终止
ES₃	密封圈火灾烧穿密封圈,引燃原油液面
ES₄	泄漏原油漫延,遇明火发生池火灾
ES₅	原油泄漏

编号	模型层级	人为因素	描述
BN₁	组织影响	组织氛围	组织内部的工作氛围,企业文化等
BN₂	组织影响	组织过程缺陷	组织决策和规则管理存在缺陷
BN₃	不安全监督	操作计划恰当性	操作计划是否合适
BN₄		已知问题的纠正	管理存在未纠正的风险
BN₅		监管违规	监管人员无视制度授权不安全作业
BN₆	不安全行为的前提条件	心理状态	由于心理行为导致工作出错
BN₇		生理状态	能够对安全生产造成影响的生理状况
BN₈		能力局限	承担的任务超出员工能力
BN₉		工作环境	包括生产环境和厂区环境
BN₁₀	不安全行为	技术性失误	基础技能导致的失误
BN₁₁		决策性失误	在面对不确定性时决策出现差错
BN₁₂		感知性失误	个人感知与现实世界存在偏差
BN₁₃		习惯性违规	违反规章制度但被监管人员忽视
BN₁₄		偶然性违规	由于不确定偶然违反规章制度
BN₀	—	人因失误	人为因素导致的失误

编号	事件	排序	ϕ_i	P_i
BE₁	无排风系统	7^th	0.4	0.144
BE₂	排风系统故障	3^rd	0.8	0.289
BE₃	板式弹簧故障	5^th	0.6	0.217
BE₄	靴板故障	10^th	0.1	0.036
BE₅	一次密封防蒸发膜损坏	2^nd	0.9	0.325
BE₆	一次密封紧固连接件故障	8^th	0.3	0.108
BE₇	支撑板故障	6^th	0.5	0.181
BE₈	密封刮板损坏	4^th	0.7	0.253
BE₉	二次密封防蒸发膜损坏	1^st	1	0.361
BE₁₀	二次密封紧固连接件故障	9^th	0.2	0.072