DomPrevPlanning: User-friendly software for planning domino effects prevention

Chains of accidents, in literature generally referred to as domino effects, knock-on effects, cascade effects or escalation effects occur very infrequently but with disastrous consequences. There exist very few software packages to study such domino accidents in complex industrial areas and to forecast potential catastrophes caused by secondary order (involving a sequence of three installations submitted to two consecutive accidents), tertiary order or even higher order accidents. Moreover, available domino software focuses on risk assessment and on consequence assessment. None of these toolkits specifically addresses the prioritization of installation sequences in an industrial area in order to facilitate objective prevention decisions about domino effects. This paper describes the application of a new computer-automated tool designed to support decision-making on preventive and protective measures to alleviate domino effects in a complex surrounding of chemical installations. Using a holistic approach and thus looking at the entire industrial area as a whole, all sequences of three installations in the area are ranked according to their danger contribution to domino effects. An example of a cluster of chemical plants demonstrates the level of qualitative and quantitative input data required. The example is also used to explain the toolkit results, as well as the surplus value and the benefits for company safety managers and regulators.     

危险品区多米诺效应的风险分析

根据多米诺效应的特点,提出了一种针对危险品区域的多米诺效应的风险分析方法.通过多米诺效应事故场景的辨识、设备的概率损坏模型和多米诺分析技术,分析区域内所有危险设备的多米诺效应风险指数和设备在多米诺事故链中的传播作用,定量分析多米诺事故后果.通过该方法可以得到区域内设备的多米诺效应风险指数和多米诺事故的后果风险.通过该方法可建立起区域的安全防范措施,从而有效预防潜在的多米诺效应,降低事故风险.     

多米诺效应下化工储罐区的脆弱性分析

为有效地减少和控制事故的多米诺效应,对影响事故扩展的关键装置,即脆弱单元的辨识及其有效控制措施进行了研究。根据具体的设计方案,依次选定不同储罐作为初始事故单元,借助ALOHA软件计算各储罐之间热辐射及冲击波相互作用强度的大小,与损伤阈值进行比较,并考虑设备间的协同作用,从而确定可能发生的多米诺事故;运用Probit模型计算事故扩展概率,根据计算结果通过Bayes Server软件建立贝叶斯网络,利用先验概率来进行整体脆弱性分析,从而确定各个方案的安全性;对优选的方案通过后验概率进行单元脆弱性分析,从而确定脆弱单元;在此基础上提出相应的控制措施。通过实例计算验证了该方法的可行性,结果表明,该方法能够在多米诺效应的预防和控制方面有效发挥作用。     

Modeling and algorithm of domino effect in chemical industrial parks using discrete isolated island method

Studies on domino effect in chemical industrial parks are crucial for avoiding accident escalation. Domino effect network (DEN) may be formed as a consequence of widely distribution of major hazard installations (MHIs) in chemical industrial parks. To decrease accident scale and prevent catastrophic consequence, it is essential to cut off the relations between entities in a DEN during accident periods. Focusing on this aspect, based on the conceptual model of discrete isolated island (DII) discussed, an objective function was brought out to evaluate the linking level of the whole park; while to help determine the dominant MHI (namely Domino hub in a DEN), equations for calculating accident escalation factor (AEF) was advanced. Further, an algorithm was developed for the proposed model. Application showed that the proposed model, which is capable of providing possible ways to determine the dominant MHI contributing to domino effect, was quite useful and effective for choosing technical prevention measures to enhance the safety level of chemical industrial parks.     

Safety evaluation of major hazard installations based on regional disaster system theory

Major accidents have catastrophic effects on humans and all of society. To prevent the occurrence of major accidents, it is essential to strengthen the management of major hazard installations. Generally, effective identification and reasonable evaluation of major hazard installations are the basic steps in safety management. At present, the evaluation methods for major hazard installations mainly focus on consequence analysis and probabilistic analysis without considering the vulnerability of hazard-affected bodies. Therefore, the proposed method will introduce regional disaster system theory and comprehensively analyze hazard-formative factors, the hazard-formative environment and hazard-affected bodies to achieve a more complete and effective assessment of major hazard installations. Hazard-formative factors are evaluated based on the rapid ranking method, hazard-formative environments are evaluated based on Bayesian networks, and hazard-affected bodies are evaluated based on the fuzzy comprehensive evaluation method. A tank group and a chemical industrial park are used to verify the feasibility and effectiveness of the new method.     

Application of a multi-plant QRA: A case study investigating the risk impact of the construction of a new plant on an existing chemical plant's risk levels

The construction of chemical clusters whereby a variety of chemical plants are located next to each other provides great economic benefits. However, in such clusters, due to the mere scale on which hazardous materials are processed, stored and handled, the potential of various accidents is much higher than in single companies. Furthermore, the close proximity of process installations and storage tanks in such areas gives rise to the risk of domino effects. Therefore, land use planning and layout design has always been a challenge within such clusters.In this paper, a Quantitative Risk Assessment (QRA) is carried out and used as a decision making tool to evaluate the acceptability of constructing a new chemical plant adjacent to an existing one. For this purpose, standard parameters such as individual risk and societal risk were quantified, before and after the new plant would come into operation. Given the experience of past accidents in the process industries, the likelihood of domino accidents in the two neighboring plants has also been analyzed.     

Optimal Assignments of Allocating and Scheduling Emergency Resources to Accidents in Chemical Industrial Parks

Accidents in chemical industrial parks can result in mass casualties and the risk usually escalates due to domino effects. However, most of the existing models of emergency logistics do not account for domino effect and may be unsuitable for emergency response to accidents in chemical industrial parks. This paper presents a mathematical model proposed for optimal assignments of allocating and scheduling emergency resources for rescuing victims and preventing accident spreading simultaneously. The detailed characteristics of accident scenarios and emergency resources are taken into account. Based on this, the efficiency of emergency response is evaluated by the total number of fatalities and the amount of losses caused by domino effects which are the optimal objectives of the model. A numerical case study was conducted by solving the model using a designed heuristic algorithm. The results showed the applicability and reliability of the proposed model for making optimal assignments for emergency response to accidents in chemical industrial parks.     

The analysis of domino effect impact probability triggered by fragments

Explosion fragments are the main cause of domino effect in accidents of the chemical and process industry. A number of significant studies have been conducted to further our understanding of the mutual impact of two major hazard installations (MHIs). This work focused on the development of a new model for the impact probability of domino effect triggered by fragments. Firstly, an expression for the initial projection velocity of fragments was founded by taking the explosion moment as a polytropic process and solving energy transformation equation, then the flight trajectory and velocity were represented by some equations with the flight boundary conditions in flight process under gravity and air friction. With the obtained equations as the objective function, the projection uncertainty was analyzed through sampling of the random variables. Finally, a new systemic model for the impact probability of domino effect is put forward by integrating the flight laws and projection uncertainty of fragments, and the impact probability linear equations with the coefficient matrix of secondary effect were built up in order to calculate the impact probability of domino effect. The study on domino effect impact probability provides some useful insights into the generation mechanism, projection features, flight laws and impacts on targets of the fragments, and also lays a foundation for analysis of domino chain risk caused by explosive fragments in chemical industrial complex.     

Optimizing the design of storage facilities through the application of ISD and QRA

Four strategies can be used to achieve safety in chemical processes: inherent, passive, active and procedural. However, the strategy that offers the best results is the inherent safety approach, especially if it is applied during the initial stages of a project. Inherently Safer Design (ISD) permanently eliminates or reduces hazards, and thus avoids or diminishes the consequences of incidents. ISD can be applied using four strategies: substitution, minimization, moderation and simplification. In this paper, we propose a methodology that combines ISD strategies with Quantitative Risk Assessment (QRA) to optimize the design of storage installations. As 17% of major accidents in the chemical industry occur during the storage process and cause significant losses, it is essential to improve safety in such installations. The proposed method applies QRA to estimate the risk associated with a specific design. The design can then be compared to others to determine which is inherently safer. The risk analysis may incorporate complex phenomena such as the domino effect and possible impacts on vulnerable material and human elements. The methodology was applied to the San Juanico tragedy that occurred in Mexico in 1984.     

Bayesian estimation and consequence modelling of deliberately induced domino effects in process facilities

Process facilities handling hazardous chemicals in large quantities and elevated operating conditions of temperature/pressure are attractive targets to external attacks. The possibility of an external attack on a critical installation, performed with an intention of triggering escalation of primary incidents into secondary and tertiary incidents, thereby increasing the severity of consequences needs to be effectively analysed. A prominent Petrochemical Industry located in Kerala, India was identified for studying the possibility of a deliberately induced domino effect. In this study, a dedicated Bayesian network is developed to model the domino propagation sequence in the chemical storage area of the industry, and to estimate the domino probabilities at different levels. This method has the advantage of accurately quantifying domino occurrence probabilities and identifying possible higher levels of escalations. Moreover, the combined effect from multiple units can be modelled easily and new information can be added into the model as evidences to update the probabilities. Phast (Process hazard analysis) software is used for consequence modelling to determine the impact zones of the identified primary and secondary incidents. The results of the case study show that such analyses can greatly benefit green field and brown field projects in determining the appropriate safety and security measures to be implemented or strengthened so as to reduce its attractiveness to external threat agents.     

Pre-evacuation path planning in chemicals-concentrated areas with risk assessment and individual character analysis

With the ever-increasing development of those chemical parks (concentrated areas), the inherent hazards may remain the major leading cause of serious casualties, causing dramatic increases in deaths and injuries. Despite this, proper path beforehand can effectively minimise the number of deaths or injured. In this study, in order to better address the aforesaid issue, the pre-evacuation path planning was adopted to do so. This method can serve to prepare emergency response in case of extreme events, such as fires, explosions, or dangerous leakages, because these accidents could happen in chemical parks (concentrated areas). To that end, a framework was therefore proposed. First, the general risk representation was conducted. After the main hazards as well as the vulnerability within the facilities was identified, the interaction between those two factors could be expressed with matrices. This was followed by the analysis of the domino effect, which tends to occur under such circumstances. Second, individuals' visibility and inclination at each location to choose the nearest exit gate or shelter zone were analyzed by space syntax analysis. Third, a weighted risk map mainly composed of risk, individual's visibility, and inclination of exits was therefore generated. And the lowest cumulative risk path was simulated and analyzed accordingly. Finally, the map modified with received risks suggests that each individual's safest route from their current locations can be possibly simulated with Dijkstra's algorithm, which corresponds to the lowest cumulative risk. For the purposes of illustration and validation, a real case was adopted. The results demonstrated that this framework could provide both technical and theoretical support for the pre-evacuation path planning in chemicals-concentrated areas like chemicals-concentrated areas.     

Resilience-based optimal firefighting to prevent domino effects in process plants

Domino effects triggered by fire can cause extremely severe damages to the chemical and process plants. In the need of a more effective prevention of fire domino effects, the present study focuses on firefighting which has received less attention compared to passive and active fire protection systems. Considering both the vulnerability and recoverability phases during fire domino effects, we have introduced a methodology for optimal identification of firefighting strategies so as to increase the resiliency of process plants in dealing with fire escalation scenarios. The area above the resilience curve (AARC), which is equal to the accumulation of loss of resilience over time, was considered as the metric to identify the optimal firefighting strategies. In other words, the strategy leading to the lowest AARC can be selected as the optimal strategy from a resiliency perspective.     

博弈论在预防化工园区事故多米诺效应中的应用

针对化工园区内各单元不愿意为预防相邻单元事故多米诺效应进行安全投入的问题,提出采用博弈论分析化工园区内各单元预防事故多米诺效应的投入意愿,将化工园区内2个相邻单元预防事故多米诺效应的关系定义为2人博弈的过程,构建2人博弈的支付函数与支付矩阵,讨论不同参数情形下的纳什均衡点,将实际均衡点与理想均衡点进行比较,判断园区管理者或政府机构是否应当采取相关措施。结果表明:实际化工园区所处的博弈情形与各单元均选择为预防园区事故多米诺效应的投入值有关,不同取值范围的纳什均衡点不同,园区管理者根据均衡点的不同选择相应措施。     

New methodologies for security risk assessment of oil and gas industry

The oil and gas industry forms a vital and large part of the economy of any country. It provides crucial support to transport, manufacturing and energy sectors, produces valuable exports and provides huge employment. This industry along with fertilizer plants, petrochemical plants, etc., which handle hazardous chemicals, are potential targets for deliberate actions by terrorists, criminals and disgruntled employees. The process industries face different levels of threats. It is imperative to analyze the entire threat scenario before taking steps to counter it, otherwise each and every threat will have to be treated as most severe, thus resulting in a huge and wasteful expenditure.The Security Risk Factor Table (SRFT) and a Stepped Matrix Procedure (SMP) have been developed to assess the security risk of oil and gas industry as well as the other chemical process industries. While the SRFT deals with the effects of individual threats, the SMP deals with the cascading/domino effects which a lone, low probability event can cause. A case study of a refinery has been performed to show the application of the ideas presented.     

Method for quantitative assessment of the domino effect in industrial sites

Accidents caused by the domino effect are the most destructive accidents related to industrial sites. The most typical primary incidents for a domino effect sequence are explosions (57%), followed by fires (43%) (Abdolhamidzadeh et al., 2010). These former can generate three escalation vectors (heat load, overpressure, and fragments), and may affect the surrounding equipments and/or facilities. If the affected targets are damaged, they may also explode and generate other threats to other surrounding facilities and so on. These chains of accidents may lead to catastrophic consequences and may affect not only the industrial sites, but also people, environment and economy. This paper presents a methodology for quantitative assessment of domino effects caused by fire and explosion on storage areas. The individual and societal risks are also estimated.     

基于DEA对抗交叉评价模型的化工园区脆弱性评价

化工园区的脆弱性是评估园区安全现状的重要指标,采用DEA对抗交叉评价方法对某省5个化工园区的脆弱性进行了评价研究。首先从园区固有危险性、园区承灾体脆弱性以及事故后果损失程度3个方面构建了化工园区脆弱性评估指标体系,通过DEA对抗交叉评价模型得出的效率值对园区事故成灾效率进行了评估,成灾效率越大说明脆弱性越大,反之,脆弱性越小;最后,探讨了5个化工园区脆弱性等级,对其进行了优劣排序,分析了园区脆弱性的影响因素;可为化工园区的管理者提供理论支持。     

Resilience assessment of chemical industrial areas during Natech-related cascading multi-hazards

In chemical industrial areas, technological accidents triggered by natural events (Natech events) may escalate. Complex cascading multi-hazard scenarios with high uncertainties may be caused. Resilience is an essential property of a system to withstand and recover from disruptive events. The present study focuses on the change of the resilience level due to (possible) interactions between cascading hazards, chemical installations and safety barriers during the dynamic evolution of fire escalations triggered by a natural hazard (certain cascading multi-hazard scenarios). A quantitative resilience assessment method is developed to this end. The state transition of a system facing accidents in the context of resilience is explored. Moreover, the uncertainties accompanying an accident evolution are quantified using a Dynamic Bayesian Network, allowing a detailed analysis of the system performance in different time steps. System resilience is measured as a time-dependent function with respect to the change of system performance. The applicability of the proposed methodology is demonstrated by a case study, and the effects of different configurations of safety barriers on improving resilience are discussed. The results are valuable to support disaster prevention within chemical industrial areas.     

基于蒙特卡洛模拟的多米诺事故风险量化管理*

为降低危化品相关的化工事故造成的人员伤亡和财产损失,以化工多米诺事故为研究对象,探讨由初始事故引发1个或多个次生事故的连锁反应机理与风险评估方法。提出应用蒙特卡洛模拟对多米诺事故风险进行动态量化的方法,梳理化工多米诺事故风险的识别、分析、评定、处理全周期管理流程,并以1个天然气压气站为案例,验证基于蒙卡模拟的化工多米诺事故风险量化方法的有效性。结果表明:该方法可以更准确地对化工多米诺事故风险进行定量评估。多米诺事故风险全周期管理流程的梳理能够有效指导化工企业开展安全管理、事故预防等工作。     

化工储罐区池火灾多米诺效应风险评估

化工储罐区储罐数量较多且集中,一旦发生事故很可能诱发多米诺效应造成灾难性的后果。在分析池火灾多米诺效应作用模式的基础上,建立了池火灾多米诺效应风险评估模型,并对某化工储罐区进行了实例计算,分析了单一储罐池火灾事故引发其他储罐池火灾的风险。分析结果表明,池火灾是诱发化工储罐多米诺事故的重要因素,且会造成风险的显著增加,但并非所有的池火灾事故都会诱发多米诺效应。此外,将多米诺效应评价方法应用于化工储罐池火灾事故风险评估中可有效地预测次生事故的发生概率和后果,从而提出针对性措施。     

Hierarchical pre-positioning of emergency resources for a chemical industrial parks concentrated area

Accidents in chemical industrial parks always cause fateful damage which can be reduced greatly by providing emergency resources sufficiently and timely. One effective way to enhance the emergency response capacity and agility is by pre-positioning of emergency resources for the potential accidents. The Yangtze River Delta of China is a large region where a large number of chemical industrial parks are concentrated. According to the distributing characteristics of demand points in this region, a mathematical model of hierarchical pre-positioning of emergency resources is proposed to ensure that accidents in all chemical industrial parks in this region can be responded timely and effectively. Considering accident domino effect and minimizing the total cost, the model gives optimal decisions of pre-positioning emergency resources, including the location and inventory of depots. The innovative hierarchical pre-positioning method greatly reduces the total cost in the premise of sufficient preparation for supplying emergency resources. Finally, in a visual graph of the Yangtze River Delta, the model is applied and the result shows its applicability.