危化品事故情景推演网络构建及关键节点分析*

为有效应对危化品事故发生与演变时存在的动态性及不确定性问题,基于事故演变过程中的关键情景状态及对应孕灾环境、应急活动和处置目标等要素,引入动态贝叶斯网络方法,构建危化品事故情景推演网络,并结合复杂网络知识,对孕灾环境和应急活动2类事故影响因素节点进行敏感性和重要度分析。结果表明:情景推演网络计算的情景节点概率符合事故发生的实际情况,能够对危化品事故在不同孕灾环境和应急救援下的演变路径进行推演,并且分析得到燃烧物、消防力量、火场环境和建筑密度等关键影响因素节点,研究结果可为事故处理提供应急辅助决策支持。     

基于情景构建的危化品事故应急疏散模拟研究

为有效控制危化品企业的事故风险,预防重大火灾爆炸事故发生,以天津港"8·12"特别重大火灾爆炸事故为例,建立贝叶斯与元胞自动机(CA)耦合模型,模拟重建事故情景,分析事故各演变环节,探寻事故演化规律,找到该类危化品港口储存行业潜在事故隐患。依据蚁群算法(ACO)建立应急疏散模型,在Matlab平台上模拟仿真受灾最严重小区的居民疏散情况,找到最佳疏散路径,计算得出将周边居民、相关人员疏散到安全区域的响应时间点。结果表明:依据计算机模拟仿真结果规划应急疏散路径,能够提高应急疏散的效率,减少事故的影响。     

危化品爆炸事故人员搜救应急处置分析

为提高危化品爆炸事故人员搜救的应急处置能力,本文在分析危化品爆炸事故特点和人员被困特点的基础上,从人员搜救应急准备、快速研判与确认搜救方案、风险预判与临机决策、搜救过程中安全保护、人员搜救方法5个方面探讨危化品爆炸事故人员搜救应急处置方法.研究表明:在危化品爆炸事故人员搜救应急处置中运用科学的方法,是实现快速、安全施救的有效途径.     

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...     

危险化学品仓储事故演化规律及消防力量需求研究

危险化学品仓储火灾事故复杂,处置难度大,易引发事故多米诺效应,对人民的生命和财产造成严重威胁。本文分析了危化品仓储火灾爆炸事故的演化规律和事故风险,结合事故案例剖析危化品仓储火灾爆炸事故后果及对周边区域的影响。针对危险化学品仓储火灾爆炸事故,建立危化品仓储火灾扑救泡沫需求评价二级指标体系,采用模糊层次分析法建立了泡沫灭火剂用量评价数学模型,并根据救援力量类别需求、各种应急救援装备与作战人员需求建立危化品火灾消防力量需求预测模型,准确预测危化品仓储事故消防力量需求。     

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。     

基于贝叶斯网络的输油管道泄漏事故情景推演

为提高输油管道企业应急管理水平,采用情景分析和动态贝叶斯网络(BN)相结合的方法,研究输油管道泄漏事故情景演化过程。通过分析典型输油管道泄漏事故案例,选取事故情景状态、应急措施、驱动因素和应急目标为关键要素,结合动态BN构建输油管道泄漏事故情景推演模型,研究输油管道泄漏事故情景演化的特征与路径;将该模型运用到我国某油气管道公司发生的一起输油管道泄漏事故中,计算情景状态概率,从而推演情景发展趋势。结果表明:引起事故发生风险概率较高的情景状态依次为"第三方施工开挖导致管道破损,原油泄漏"、"地面出现明火"、"地面残火"、"路面残油燃烧"。     

危化品事故应急救援能力提升方法研究——基于天津港“8·12”瑞海公司危险品仓库特别重大火灾爆炸事故教训

为提升危化品事故应急救援能力,保障消防救援队员救援时安全,基于2015年天津港“8·12”瑞海公司危险品仓库特别重大火灾爆炸事故教训,从应急管理生命周期的角度构建危化品应急管理体系,研究危化品事故应急救援能力提升方法。结果表明:事故发生及特大伤亡与预防和应急准备工作不足有密切关系。构建基于应急管理生命周期的危化品企业、有关监管部门、技术服务机构、消防队联动应急管理体系是提升危化品应急救援能力的重要方法。危化品企业、有关监管部门、技术服务机构、消防队应做好危化品事故预防与应急准备工作,通过充足的预防和准备工作促使有效应急响应。事故发生后,危化品企业做好早期处置利于消防队采取针对性应急救援方案。对于复杂性危化品事故,及时成立抢险救援指挥部,科学应急响应,可保障消防救援的安全有效。     

关注国内外危险化学品应急救援

正危险化学品具有种类繁多、应用广泛、高温高压、易燃易爆、有毒有害等特点,安全风险高,如何有效防范事故风险,最大限度减少生命财产损失,是世界各国必须面对和亟需解决的重大课题。当前,化工行业已成为我国重要支柱产业,危险化学品(以下简称"危化品")储运量持续扩大,危化品安全风险、应急救援难度不断增大。中国为应对危化品事故救援,已初步建立了国家危化品应急救援管理工作机制,成功举办两届全国性的危化品应急救援技术     

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。     

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.     

Operational risk assessment: A case of the Bhopal disaster

Accidental releases of hazardous chemicals from process facilities can cause catastrophic consequences. The Bhopal disaster resulting from a combination of inherently unsafe designs and poorly managed operations is a well-known case. Effective risk modeling approaches that provide early warnings are helpful to prevent and control such rare but catastrophic events. Probability estimation of these events is a constant challenge due to the scarcity of directly relevant data. Therefore, precursor-based methods that adopt the Bayesian theorem to update prior judgments on event probabilities using empirical data have been proposed. The updated probabilities are then integrated with consequences of varying severity to produce the risk profile.This paper proposes an operational risk assessment framework, in which a precursor-based Bayesian network approach is used for probability estimation, and loss functions are applied for consequence assessment. The estimated risk profile can be updated continuously given real-time operational data. As process facilities operate, this method integrates a failure-updating mechanism with potential consequences to generate a real-time operational risk profile. The real time risk profile is valuable in activating accident prevention and control strategies. The approach is applied to the Bhopal accident to demonstrate its applicability and effectiveness.     

Dynamic risk assessment using failure assessment and Bayesian theory

To ensure the safety of a process system, engineers use different methods to identify the potential hazards that may cause severe consequences. One of the most popular methods used is quantitative risk assessment (QRA) which quantifies the risk associated with a particular process activity. One of QRA's major disadvantages is its inability to update risk during the life of a process. As the process operates, abnormal events will result in incidents and near misses. These events are often called accident precursors. A conventional QRA process is unable to use the accident precursor information to revise the risk profile. To overcome this, a methodology has been proposed based on the work of Meel and Seider (2006). Similar to Meel and Seider (2006) work, this methodology uses Bayesian theory to update the likelihood of the event occurrence and also failure probability of the safety system. In this paper the proposed methodology is outlined and its application is demonstrated using a simple case study. First, potential accident scenarios are identified and represented in terms of an event tree, next, using the event tree and available failure data end-state probabilities are estimated. Subsequently, using the available accident precursor data, safety system failure likelihood and event tree end-state probabilities are revised. The methodology has been simulated using deterministic (point value) as well as probabilistic approach. This Methodology is applied to a case study demonstrating a storage tank containing highly hazardous chemicals. The comparison between conventional QRA and the results from dynamic failure assessment approach shows the significant deviation in system failure frequency throughout the life time of the process unit.     

改进广义灰色关联故障树的危化品LSSC可靠性诊断

为了探究影响危化品物流整体运作的关键事故因素,提出一种改进广义关联故障树的危化品LSSC可靠性诊断方法。结合实例构建危化品LSSC系统失效故障树,运用灰色关联技术对以最小割集构造的标准故障模式向量和底事件概率重要度组成的待检模式向量进行相关性分析,得到系统失效概率等级与失效故障模式可能性排序,确定系统关键薄弱环节。研究结果表明:该方法能够快速识别危化品物流运作系统关键事故因素,为危化品LSSC风险等级控制和分级防范措施制定提供参考和借鉴。     

基于“纵深防御”原则的危化企业事故预防系统建立

危险化学品生产是当前的高危行业和安全管理的重点领域。面对事故频发的严峻形势,如何开展好危险化学品生产企业的安全管理,建立事故预防系统防止事故的发生非常关键。“纵深防御”原则作为核电厂实现核安全的一项基本原则,为核电厂长期稳定安全的发展奠定了坚实的基础,对危化企业提升事故预防能力,建立事故预防系统有较强的借鉴意义。借鉴“纵深防御”原则,文章分析危化企业应用“纵深防御”原则预防和减少事故发生的必要性,结合生产特点建立了事故纵深防御系统,对企业提高安全管理水平,预防事故的发生有重要的意义。     

Quantitative risk assessment model of hazardous chemicals leakage and application

The hazardous chemical accidents remain a matter of major concern. However, there is a dearth of practical measures about the emergency management of hazardous chemicals leakage. Therefore, in order to provide more accurate management plan, quantitative risk assessment has become a critical issue in chemical industry. The main aim of this study is to quantify the risk of hazardous chemicals leakage, and take precautions against the accidents. In this study, a Fire-Explosion-Poisoning Quantitative Probability Model (FEPQPM) has been established. The paper introduced the probability analysis methods to analyze derivative accidents caused by hazardous chemicals leakage, established quantitative risk assessment models, and made acceptable risk level analysis. This model has been applied to quantitatively assess an enterprise’s storage tank at Changshou Chemical Industrial Distripark (CID) in Chongqing, China. Evaluation results are in line with the actual situation of the CID. It is shown that the probability of poisoning is very large, causing more economic loss than the other two types of accidents, and death toll of leakage accident increases over time, resulting in greater economic losses. The risk level of leakage accident involving poisoning is unacceptable.     

“数字化集中仓”模式下危化品仓储安全监管的演化博弈分析

针对利用数字化技术提高危化品仓储安全监管水平问题,考虑政府搭建“危化品集中式仓储中心+数字化网络监管平台”策略,基于演化博弈理论,构建危化品仓储安全监管演化博弈模型,分析建立数字化集中仓概率(本文简称“建仓概率”)对相关政府部门和危化品仓储企业行为演化规律的影响,探讨数字化集中仓模式下,危化品仓储企业合规仓储的驱动因素。研究结果表明：当建仓概率低于某临界值时,政府部门和危化品仓储企业会疏于监管违规仓储;随着建仓概率提高,政府部门和危化品仓储企业策略呈现周期性波动现象;当建仓概率很高时,虽然数字化集中仓一定程度上可提高政府监管便利性,但从长远看会使政府监管部门放松对危化品仓储安全的监管。研究结果可为政府推行数字化监管新模式和危化品仓储企业实施智能仓储管理提供一定决策支持。     

基于贝叶斯网络的养老院火灾风险评估方法研究

为预防养老院火灾事故,结合事故树法(FTA)和贝叶斯网络法(BN),建立了一套养老院火灾风险定量评估模型。首先,采用事故树法建立潜在的养老院火灾事故场景;其次,考虑到养老院火灾事故场景中不确定因素的影响,将事故树模型转化为贝叶斯网络模型,并结合有人员伤亡的养老院火灾事故发生发展实际优化模型;最后,以某市养老院为例,结合调研、文献及统计数据确定先验概率及条件概率,并用GENIE 2.0软件实现贝叶斯图形化,分析验证该模型逻辑可行性。结果表明:通过该模型和方法,不仅可以预测养老院火灾事故中各场景发生发展概率,还能对各风险因素敏感度和最大致因链进行分析,提高了风险因素辨识和评价的准确性,可以为养老院火灾风险分析和防控提供参考。