危化品储运事故事理图谱构建与分析

为避免危化品储运事故演变导致次生事故的发生,改善事故风险识别领域依赖于人工的状况,应用事理图谱模型解析危化品事件之间的影响关系。首先,分析危化品储运事故语料库语义特征,抽取事故报告中危化品事件因果关系模式;然后,采用基于句向量的事件节点泛化方法,构建了基于因果情景的危化品储运事故事理图谱模型;最后,借助社会网络分析法对情景事件节点的度、特征向量中心性、介数中心性关键指标进行分析,得到了情景事件节点在演化模型中的关键程度。结果表明,通过构建事理图谱模型,发现事故演化中的关键节点,对危化品事故的发展能够进行直观的展示,可为危化品储运事故的分析提供新的思路,有助于提高企业避免连锁事故发生的应急水平。     

危化品事故多层级链式推演模型及案例分析

为提升危化品企业的风险防控能力,支撑事故发生后迅速地进行应急决策研判,基于灾害链理论,从热辐射、毒气、超压3类危化品事故关键致灾因子出发,提出灾害链多层级链式推演模型。采用流体扩散模型和Probit模型,分别构建危化品容器起火概率及顺序预测算法和危化品爆炸点火时刻估计算法,实现对危化品事故中燃烧和爆炸演化过程的定量计算分析。并以广东省某树脂生产厂为研究案例,建立1条由危化品泄漏事故引发的灾害链,推演分析灾害链各节点的演化时间和发生概率。分析结果表明：灾害链推演模型能有效定量化分析实际危化品厂区事故的演化过程、预测事故节点发生概率及时间,并在一定程度上帮助检验危化品厂区布局安全。     

基于贝叶斯网络的危化品爆炸事故电力系统风险评估模型

为提高危化品爆炸事故电力应急预警的准确性,建立基于贝叶斯网络的危化品爆炸事故电力系统风险评估模型.基于危化品爆炸事故电力应急典型情景分析,建立综合考虑突发事件、承灾载体和应急管理等风险因素的贝叶斯网络结构.应用概率刻画风险因素信息的不确定性及其相互影响,定量分析事件后果.结合一般条件和典型情景等的应用实例,分析评价方法...     

基于贝叶斯网络的城镇洪涝应急情景推演研究

为处理城镇洪涝灾害复杂演变过程,结合证据理论与知识元模型,利用贝叶斯网络,针对城镇洪涝灾害进行应急情景推演研究。将城镇洪涝灾害情景推演要素归类为孕灾环境、致灾因子、承灾体和应急管理,并分析各要素之间的作用关系,建立城镇洪涝灾害应急情景贝叶斯网络,以验证应急管理措施的科学性和有效性,并通过2016年武汉市洪涝灾害进行实例分析。结果表明:知识元模型能建构城镇洪涝灾害应急情景的复杂演化路径,证据理论能处理应急情景演化中的不确定性信息,而贝叶斯网络能有效仿真推演并评价应急管理措施。     

基于贝叶斯网络的化工企业火灾爆炸事故情景推演

为了解火灾爆炸事故的演化路径,为事故应急救援相关方提供相应的决策依据,基于“情景—应对”方法,选取情景状态、承载环境、应急措施和处置目标作为主要情景要素,并通过知识元理论构建情景概念模型,明确各要素之间的相互关系;再利用贝叶斯网络进行情景推演,确定各节点要素的先验概率和条件概率,借助Netica软件计算出各节点的状态概率;最后以山东石大科技石化有限公司“7.16”较大着火爆炸事故为例进行案例验证研究。研究获得事故的情景演变路径一般遵循泄漏、火灾和爆炸的顺序;通过推演得到发生概率较大的4个情景节点,并提出针对性较强的控制措施。可为类似事故应急救援和事后整改措施的制定提供参考。     

基于动态贝叶斯网络情景推演的危化品事故应急处置研究

由于危险化学品事故的演化路径具有不确定性和动态性的特点,往往很难科学地采取应急处置措施。以天津港"8·12"事故为例,基于外部环境、事件情景、应急处置3类情景要素分析危险化学品事故的情景演变路径,结合动态贝叶斯网络构建情景推演模型,利用联合概率公式计算情景发生概率,来实现危险化学品事故中关键情景的推演,便于有针对性地采取应急处置措施。推演结果表明:应加强事故初期的应急处置力度,遏制事态发展;事故发展中期,救援难度非常大,宜尽量争取应急疏散时间,避免人员伤亡;进行应急处置时,要统筹考虑各种内外部因素及事故演变的具体情况,特别要阻止向事故扩大的趋势转变。     

基于DBN的气体泄漏事故情景推演与节点分析

化工园区危险化学品气体泄漏事故在演化过程中具有路径复杂和发展动态性高的特点,为解决气体泄漏事故难以快速有效应对的问题,以张家口“11·28”重大爆燃事故为例构建推演模型。首先基于动态贝叶斯方法构建基于情景状态、外部环境和应急措施的灾害链情景演化模型,利用联合概率公式计算情景状态概率,实现气体泄漏事故的动态推演;然后结合复杂网络拓扑结构相关知识,利用综合重要度公式,探究事故情景推演过程中的关键节点;最后提出基于数据参考的针对性断链措施。研究表明：基于动态贝叶斯的情景推演模型可以在事故演化路径中起到预测作用,推演结果为相关事故灾前预测、灾中应急和灾后恢复提供更为科学有效的依据。     

基于贝叶斯网络的电镀企业火灾事故情景推演

为有效解决电镀企业火灾事故情景演化路径复杂、火灾扑救困难等问题,提高电镀火灾应急处置能力,采用情景分析与贝叶斯网络(BN)相结合的方法,对电镀企业火灾演化路径进行推演。首先分析电镀火灾特点,确定情景状态、应急驱动、承灾要素和处置目标4种情景要素;然后基于动态BN确定情景间的关系,运用D-S证据理论处理优化,构建电镀企业火灾情景推演模型;最后将其应用于某电镀火灾实例,通过Netica软件得到各节点的状态概率,找出事故的发展趋势和情景演化路径。结果表明：该事故所有可能的演化路径中,预热槽体起火(情景S₁)是事故发生概率最大的情景,概率达81.2%;需在此处采取有效措施,使火灾消失概率达到62.3%。     

易燃易爆危险化学品道路运输事故情景分析

为探究易燃易爆危险化学品道路运输事故情景演变趋势,发掘事故后果类型预测方法,首先搜集、统计2013—2018年国内983起易燃易爆危化品道路运输事故数据,从中提取事故发展过程中各个环节的特征参数,并将其作为网络节点;然后借助Netica软件进行参数学习,并构建易燃易爆危化品道路运输事故情景分析贝叶斯网络(BN)模型,最后进行后验概率推理,提出"初发事故—危化品事故"模式的事故链预测方法。研究表明:该事故情景分析模型可有效评估各类因素对事故情景演化的影响程度,并预测事故情景演化态势和导致特定事故后果的最可能出现的情景。     

景区密集人群踩踏事故情景分析

为提高景区密集人群应急管控能力,采用情景分析和动态贝叶斯网络相结合的方法,研究景区密集人群踩踏事故情景演化过程。通过分析景区密集人群踩踏事故,选取情景状态、致灾体、承灾体、驱动要素为关键要素,探索密集人群踩踏事故情景演化的特征与路径;运用动态贝叶斯网络构建密集人群踩踏事故情景网络,从情景状态概率推演情景发展趋势。结果表明:引起事故发生风险概率较高的情景状态依次为人群跌倒、人群僵持、人群流量剧增和人群聚集;预防准备不充分、景区安保管理不足、人流监测设备和人群限流设施不完善等相应驱动要素的介入是造成事故发生的主要原因。     

Evaluation on consequences prediction of fire accident in emergency processes for oil-gas storage and transportation by scenario deduction

This paper takes the safety in emergency processes as the starting point, from the perspective of scenario deduction, to study the consequences of fire accidents for oil-gas storage and transportation. Through the statistical analysis of actual accident cases, 19 frequently occurring basic scenarios in emergency processes are summarized. The scenario evolution paths of fire accidents for oil-gas storage and transportation are given by analyzing the evolution law of the accident development. Fuzzy numbers are introduced to express experts' qualitative judgment on accident scenarios. The empirical probabilities of scenario nodes are obtained by defuzzification calculation, and the state probability of each scenario node is calculated by using the dynamic Bayesian network joint probability formula. Under the comprehensive consideration about the probability statistics of actual accident cases, the critical scenario nodes on the evolution path and their final scenario probabilities are jointly determined to realize the optimization of the scenario evolution path. By constructing the correlation between the optimized scenario evolution path and the accident consequences, an accident consequence prediction model is established. The occurrence probability of accident consequences is calculated by the defuzzification method and dynamic Bayesian network. The accuracy of the consequence prediction model is verified by the July 16 Dalian's Xingang Harbor oil pipeline explosion accident. The research results provide scientific basis for helping decision makers to make the effective emergency measures that are most conducive to the rapid elimination of accidents and reducing the severity of accident consequences.     

考虑结构特性的化工事故关键致因网络分析*

为揭示化工事故发生机理,考虑事故链中因素的因果关系与事故网络的结构特性,基于复杂网络研究化工事故的关键致因因素,以事故案例中因素与结果为网络节点,因素间的因果关系为边,建立化工事故网络模型,分析网络中节点的度值、结构洞,构建化工事故凝聚网络,分析凝聚节点之间的因果关系。结果表明:在化工事故网络中存在8种致因因素,人的不安全行为与环境的不安全状态占比高达87.5%。通过结构洞分析可有效找出网络中具有较强影响力的潜在致因因素;通过凝聚网络分析,人的不安全行为致使设备的不安全状态与环境的不安全状态连接比例高达29%,存在显著的因果关系。     

Scenario deduction of Natech accident based on dynamic Bayesian network: A case study of landslide accident in a liquor storage tank area in Guizhou Province,China

Industrial technical accidents caused by natural disasters are defined as Natech accidents, such as earthquakes and landslides, which can cause tremendous damage to industrial storage tanks, and lead to accidental leakage and even serious fire and explosion accidents. In this study, a landslide-induced storage tank accident model under earthquake disasters was proposed, and the relationship between landslide mass impact and target impact resistance was taken into account. Also, tank failure and the formation of the pool fire were considered to be the consequences of the Natech accident. Through scenario deduction, the dynamic process of landslide Natech was transformed qualitatively into a disaster chain network diagram composed of a scenario state, a disaster-causing factor and emergency management. The Bayesian network was used to learn and deduce the parameters of the network diagram, and in this process, the prior probability and conditional probability of nodes were obtained primarily by Monte Carlo simulation, and by an improved expert scoring method based on the fuzzy set theory. Through visualization software, the sensitivity analysis of landslide Natech was achieved. Finally, a case study of a liquor storage tank area in Guizhou Province, China was carried out, and the results show that a large amount of hazardous material leakage caused by buckling is key to the formation of pool fire accidents, and several prevention measures for earthquake-induced landslide Natech was proposed according to the sensitivity analysis.     

隧道突泥涌水情景构建及演化状态预测模型

为实现对隧道突泥涌水事故的有效管控,基于情景分析理论,采用演化路径网络和演化矩阵模型,针对隧道突泥涌水灾害进行情景推演预测。将隧道突泥涌水情景要素归类为孕灾环境、致灾因子、驱动要素和承灾体,研究各要素的属性参数;基于承灾体损失将隧道突泥涌水情景分为6级,分析灾害情景的演化规律;建立灾害全过程的演化路径网络,构建预测灾害情景状态的演化矩阵模型,提出情景状态等级的概率分布算法。将该模型应用于雅叶高速公路折多山隧道,结果表明：该方法可准确地模拟隧道突泥涌水全过程的演化路径及情景状态,预测结果有助于隧道建设单位摸清既有能力和明确防灾任务,为其应急能力建设提供重要依据。     

基于动态贝叶斯网络的石化装置火灾事故动态风险分析

为揭示石油炼化装置事故风险动态特性和事故情景演变路径,在对石化装置进行风险因素分析的基础上构建石化装置火灾事故故障树,基于贝叶斯网络非常规突发事故的演变过程,构建情景演变下的动态贝叶斯网络模型,在综合考虑应急措施的基础上,利用MATLAB软件和联合概率公式计算出各种事故场景的状态概率.以丙烯精馏装置火灾事故为例,结果表...     

Research on the prediction model of hazardous chemical road transportation accidents

In recent years, hazardous chemicals road transport accidents have occurred frequently, causing huge casualties and property losses, and accident risk assessment has become the focus of researchers' research. To predict the risk probability value of hazardous chemical road transport accidents, first, we compiled data on road transportation accidents of hazardous chemicals in China in the past five years. And the nine nodes in the Bayesian network (BN) structure were defined in combination with relevant classification standards. The optimal Bayesian network structure for hazardous chemical road transport accidents was determined based on the K2 algorithm and the causalities between the nodes. Second, the node conditional probabilities were derived by parameter learning of the model using Netica, and the validity of the model was verified using the 5-fold cross-validation method. Last, the Bayesian network model of hazardous chemical road transport accidents is used to analyze accident examples, and the accident chain of “rear-end-leakage” is predicted, and the accident is most likely to be disposed of within 3–9 h. The study shows that the derived accident prediction model for hazardous chemical road transportation can reason reasonably about the evolution of accident scenarios and determine the probability values of accident risks under different parameter conditions.     

Scenario derivation and consequence evaluation of dust explosion accident based on dynamic Bayesian network

In order to clarify the correlation between the evolution path of dust explosion accidents and emergency decision-making, and to accurately predict the disaster damage levels of various disaster bearing bodies. This paper extracts 56 key scenario elements from four aspects, namely state, answer, goal and environment, based on the analysis of typical dust explosion accident cases. At the same time, a general scenario evolution path of dust explosion accident is constructed. Using fuzzy number set theory and dynamic Bayes joint probability model, the accurate solution of scenario state probability was realized. With the help of accident cases and dynamic Bayes approach, the dust explosion consequence prediction index system and evaluation criteria were constructed, covering factors such as dust explosion intensity, casualties, direct economic losses, equipment damage, building damage, environmental damage and other factors. A polyethylene wax dust explosion accident in a city of China was used to verify the dust explosion accident scenario evolution model and consequences prediction model. The predicted results were in good agreement with the actual damage of various carriers of the accident, which indicated that the model could be used for dust explosion accident prediction and disaster loss prediction. The research results provided reference and technical support for the prediction of dust explosion accident evolution direction, emergency aid measures decision and deployment, disaster damage prediction and evaluation.     

基于事故演化网络的旅游安全及风险防控研究

为做好旅游活动的安全管理和风险防控,构建旅游安全事故演化网络,从旅游事故演化的角度分析旅游中常见的事故类型及其演化过程;根据旅游事故发生的时序和相关程度将旅游安全事故分为4级,从事故节点的出入度、子网节点数和支链数进行分析,判断不同旅游事故的风险大小;此外,从不同结构演化链的角度,总结旅游事故演化的特征.结果表明:旅游...     

基于HFACS-BN模型的危险化学品事故人因路径分析*

为提高危险化学品安全管理水平,收集我国134起以人为主因的危险化学品事故,构建危险化学品事故的HFACS-BN模型,并基于贝叶斯网络对危险化学品事故中的人因路径及各因素灵敏度进行分析。研究结果表明:行为违规是导致事故的最主要不安全行为;在复杂路径中,环境因素和操作者状态具有较高的灵敏度,与其相关的风险认知与处理不当是阻碍事故预防的关键因素;在非复杂路径中,操作者状态与运行计划不当具有较高的灵敏度,其所涉及的监督违规、组织过程和组织氛围,是导致危险化学品事故的根本起点,并可依此分析事故直接原因和间接原因;操作者状态在2种路径中均表现出高灵敏度,因此化工企业在人员管理上要加强关注职工状态,减少不安全行为的出现。     

基于动态元网络的地铁施工安全事故致因分析

为有效避免地铁施工安全事故的发生,将动态元网络的分析方法应用于地铁施工安全事故致因分析,建立地铁施工安全事故网络节点体系,提出重点控制因素。以杭州地铁一号线施工安全事故为例,在充分考虑人的主观能动性后,建立以人员、行为、事件和组织为节点的节点体系,确定节点的数量及节点之间的相互关系,建立施工安全事故网络模型并进行分析,对打击效果进行对比分析,找到比较理想的打击策略,确立节点的重要度排序,研究结果表明:应重点控制有效的监督相关节点,即可有效地避免或者减少此类事故的发生。得出的结论与事故通报结果基本相符,这为避免地铁施工安全事故提供了新的研究思路。