Quantitative analysis of domino effects in large tank farms under various wind conditions and accident scenarios

doi:10.16085/j.issn.1000-6613.2024-0146

Abstract

Abstract:

An efficient Bayesian network (BN) construction and analysis method is proposed for multi-level domino accidents within large chemical tank farms. Leveraging probabilistic graphical model decomposition and integration, the method addresses various wind conditions and common accident modes adhering to quantitative risk assessment guidelines. It is capable of managing domino accidents involving over 10² tanks and 10⁶ possible scenarios, facilitating automated causal and diagnostic inference. The method was applied to an example tank area derived from a realistic large chemical logistics facility in Shanghai. It revealed that domino accidents significantly contribute to the overall tank failure risk, particularly in facilities comprising numerous atmospheric-pressure liquid tanks or those situated downwind from pressurized spherical tanks. Seasonality plays a crucial role in the spatial distribution of domino accident risks due to the impact of wind on incidents like vapor cloud explosions. BN’s automatic inference capabilities were employed to identify the most probable accident sequences and infer unobserved parameters, such as leak sizes, based on actual accident progression. The approach proves invaluable for pre-accident prevention, emergency response, and post-accident investigations.

Key words: chemical tank farm, domino effect, Bayesian network, safety, process systems, computer simulation

摘要：

针对大型危险化学品储罐区多级多米诺事故，提出一种基于概率图分解与综合的贝叶斯网络（BN）高效构建与分析方法。在综合考虑多种风速风向组合以及定量风险评价标准规范涵盖的常见事故模式时，能够处理10²个储罐和10⁶个独立场景以上规模的多米诺事故，实现自动因果推理与诊断推理分析。基于上海某大型化工企业实际布局构建示例罐区，进行多米诺事故案例分析。结果表明：较多常压液体储罐的区域以及位于压力球罐下风向的储罐区受多米诺事故影响较大；由于蒸气云爆炸等事故范围受风速风向影响巨大，全罐区多米诺事故风险空间分布呈现显著的季节性变化。通过BN自动推理，不仅绘制出各罐区最可能的事故路径，还可以根据实际事故发展推测泄漏孔径等难以直接观测的情境参数，为事故预防、应急处置和事故调查提供了有力的分析工具。

关键词: 化学品罐区, 多米诺效应, 贝叶斯网络, 安全, 过程系统, 计算机模拟

CLC Number:

X937

ZHANG Qian, LIU Xin, WANG Bing, XU Jing, CAO Chenxi. Quantitative analysis of domino effects in large tank farms under various wind conditions and accident scenarios[J]. Chemical Industry and Engineering Progress, 2025, 44(2): 1170-1182.

张迁, 刘鑫, 王冰, 徐晶, 曹晨熙. 复杂风速风向与事件树下储罐区多米诺事故分析[J]. 化工进展, 2025, 44(2): 1170-1182.

Figures/Tables 26

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泄漏状态	泄漏孔径/mm	最长泄漏时间/min
大孔泄漏	100	10
中孔泄漏	25	20
小孔泄漏	5	30
完全破裂	—	5

泄漏状态	泄漏孔径/mm	最长泄漏时间/min
大孔泄漏	100	10
中孔泄漏	25	20
小孔泄漏	5	30
完全破裂	—	5

物质分类	连续释放	瞬时释放	立即点燃概率
类别0 （中/高活性）	<10kg/s	<1000kg	0.2
	10~100kg/s	1000~10000kg	0.5
	>100kg/s	>10000kg	0.7
类别0 （低活性）	<10kg/s	<1000kg	0.02
	10~100kg/s	1000~10000kg	0.04
	>100kg/s	>10000kg	0.09
类别1	任意速率	任意量	0.065
类别2	任意速率	任意量	0.01
类别3或类别4	任意速率	任意量	0

物质分类	连续释放	瞬时释放	立即点燃概率
类别0 （中/高活性）	<10kg/s	<1000kg	0.2
	10~100kg/s	1000~10000kg	0.5
	>100kg/s	>10000kg	0.7
类别0 （低活性）	<10kg/s	<1000kg	0.02
	10~100kg/s	1000~10000kg	0.04
	>100kg/s	>10000kg	0.09
类别1	任意速率	任意量	0.065
类别2	任意速率	任意量	0.01
类别3或类别4	任意速率	任意量	0

物质类别	燃烧性	条件
类别0	极度易燃	闪点<0℃、沸点≤35℃的液体或暴露于空气中，在正常温度和压力下可以点燃的气体
类别1	高可燃性	闪点<21℃的液体，但不是极度易燃的
类别2	可燃	21℃≤闪点≤55℃的液体
类别3	可燃	55℃<闪点≤100℃的液体
类别4	可燃	闪点>100℃的液体