Quantitative risk assessment of domino effect in Natech scenarios triggered by lightning

Lightning strike is the natural event more frequency causing Natech accidents involving atmospheric storage tanks. Despite the resulting fires have usually limited severity and only local effects, domino effect may cause the escalation of these primary events, possibly affecting nearby pressurized storages and process equipment, thus resulting in relevant increase in the potential area impacted. A methodology was developed for the quantitative assessment of risk due to domino effects caused by Natech accidents triggered by lightning. A comprehensive procedure was obtained, tailoring lightning risk assessment to include probabilistic models for domino escalation based on probit approach and combinatorial analysis. The methodology was applied to a case-study to evidence the shift in risk figures due to domino effect and the credibility of the secondary domino scenarios. The results of the case-study show that an increase up to two orders of magnitude with respect to risk calculated for conventional scenarios is possible when considering lightning-induced Natech primary scenarios and their escalation.     

A Dynamic Bayesian Network-based approach to Resilience Assessment of Engineered Systems

Traditional risk assessment approaches mainly focus on the pre-failure scenarios with certain information. For complex systems, the scope of risk assessment needs to be extended to include the post-failure phase; because the emerging hazards of these systems cannot be wholly identified and are usually highly uncertain. Thus, resilience assessment needs to be investigated. Most of the existing literature quantify resilience based on a system's performance loss caused by disruptions. These studies fail to assess the probability of a system to sustain or restore to a normal operational state after disruptions occur, how this probability changes with time, and how fast the system can be restored. The dynamic and probabilistic characteristics of resilience must be considered in systemic resilience assessment, in which the engineered system, human and organizational factors, and external disruptions are considered. This paper aims to develop a dynamic Bayesian network (DBN)-based approach to the probabilistic assessment of the system resilience by incorporating temporal processes of adaption and recovery into the analysis of system functionality. The proposed method also provides a new way to define resilience in terms of the probability of system functionality change during and after a disruption. A case study on the Chevron refinery accident is used to demonstrate the applicability of the proposed methodology.     

Application of domino effect quantitative risk assessment to an extended industrial area

Escalation of primary accidental scenarios triggering a “domino effect” have caused extremely severe accidental events in the chemical and process industry. The identification of possible escalation events is required in the safety assessment of sites where relevant quantities of hazardous substances are stored or handled. In the European Union, “Seveso-II” Directive requires the assessment of on-site and off-site possible escalation scenarios in sites falling under the obligations of the Directive. In the present study, a methodology developed for the quantitative assessment of risk due to domino effect was applied to the analysis of an extended industrial area. Recently developed equipment damage probability models were applied for the identification of the final scenarios and for escalation probability assessment. The domino package of the Aripar-GIS software was used for risk recomposition. The results evidence that quantitative risk assessment of escalation hazard is of fundamental importance in order to identify critical equipment and to address prevention and protection actions.     

Multi-hazard failure assessment of atmospheric storage tanks during hurricanes

Hurricane as one of the most destructive natural hazards can make a devastating impact on the industrial equipment, especially atmospheric storage tanks, leading to the release of stored chemicals and disastrous safety and environmental issues. These catastrophic consequences are caused not only by strong winds but also by the torrential rainfall and inundating floods. The objective of this study is to present a risk-based methodology for assessing and reducing the vulnerability of atmospheric storage tanks to hurricanes. Considering the shell buckling, flotation, sliding, and roof sinking as dominant failure modes of atmospheric storage tanks during hurricanes, Bayesian network (BN) has been employed to combine the failure modes while considering their conditional dependencies. The probability updating feature of the developed BN was employed to indicate that the flood is the most critical hazard during hurricanes while the impact of wind and rainfall cannot be neglected. Extending the developed BN to an influence diagram, the cost-benefit filling of storage tanks with water prior to the advent of hurricanes was shown as a viable measure for reducing the damage probability. The results show that the proposed methodology can be used as an effective decision support tool for assessing and reducing the vulnerability of atmospheric storage tanks to natural hazards.     

Quantitative assessment of domino and NaTech scenarios in complex industrial areas

Since the late 80s the application of quantitative risk assessment to the issue of land-use planning with respect to major accident hazards emerged as a topic to be addressed within the safety assessment of chemical and process plants. However, in the case of industrial clusters or complex industrial areas specific methodologies are needed to deal with high-impact low-probability (HILP) events. In the present study, innovative methodologies developed for the quantitative assessment of risk due to domino and NaTech scenarios are presented. In recent years a set of models for the calculation of equipment damage probability were developed. A specific effort was dedicated to the improvement of models for the calculation of equipment damage probability in these accident scenarios. In the present study, the application of these models to case-studies was analyzed. The results of the improved models obtained for NaTech quantitative assessment were compared to previous results in the literature. A specific innovative approach was developed to multi-level quantitative assessment of domino scenarios, and its potential was analyzed. The results were examined also evidencing the role and the progress with respect to the pioneering work started on these topics by Franco Foraboschi.     

Technical modeling in integrated risk assessment of chemical installations

This paper presents the technical model of an Integrated Quantitative Risk Assessment method, taking into account management as well as technical design and producing risk level measures. The basic steps of the technical model consist in developing a Master Logic Diagram (MLD) delineating the major immediate causes of Loss of Containment and associated quantitative models for assessing their frequency. Appropriate management models quantify the parameters of the technical model on the basis of the safety management system of the installation. The methodology is exemplified through its application on the risk assessment of a LPG scrubbing tower of an oil refinery. A detailed technical model simulating the response of the system to various initiating events is developed, along with a detailed model simulating the influence of the plant-specific management and organizational practices. The overall effect is quantified through the frequency of release of LPG as a result of a Loss of Containment in scrubbing towers of the refinery.     

基于AHP-模糊方法的某化工园区应急能力评估

化工园区应急能力评估是化工园区风险评估及应急管理的重要内容,化工园区建立应急能力评估体系一方面可以提高园区企业及管理部门的应急响应能力,另一方面可以增强政府各部门对事故的应急管理能力。在对某化工园区现场调研的基础上,结合国内外研究成果,确定了化工园区应急能力的多级指标,并运用AHP-模糊方法对该园区进行了应急能力评估。     

基于改进层次分析法的化工园区应急能力评估研究

本文采用诱导矩阵的方法对层次分析法进行改进,并将整个计算过程计算机程序化。再利用改进的层次分析法计算出化工园区应急能力各因素的权重。最后根据各因素权重以及各因素的打分情况得到园区的应急能力等级。结果表明：对改进的层次分析法程序化会提高分析速度和精度,并且通过各因素权重分析,对园区的应急能力的改善提出针对性建议。     

山区二级公路运营期常态交通风险评价

为客观准确地评价山区二级公路常态交通风险,将风险源分为动态风险源和静态风险源.首先,基于白化权函数的综合评价法建立事故后果模型,基于历史事故数据建立事故概率模型,以评价静态风险;其次,结合白化权函数和层次分析法(AHP)建立事故后果模型,采用有序Logit模型建立事故概率模型,以评价动态风险;最后综合动静态风险结果评价...     

剧毒化学品甲苯-2，4-二异氰酸酯运输危险性评估

为探讨低挥发性剧毒化学品甲苯-2,4-二异氰酸酯在运输过程中大量泄漏引起群体中毒事故的可能性以及对环境的影响,对本品的急性毒性、扩散模型、环境转归、生态毒性,以及运输泄漏事故资料进行综合分析和评估。评估结果本品吸人中毒的潜在危险性指数为低度危险物质;扩散模型运输泄漏模拟危险区域下风向距离小于某些非剧毒品;环境转归研究显示本品在环境介质中没有持久性,没有明显的生物蓄积性,生态毒性较低;历年来运输泄漏事故分析未见发生大规模严重群体中毒和环境污染事故。认为本品在运输过程中大量泄漏,不会大范围扩散引起严重群体中毒事故,也不会对环境造成严重和长期的危害,建议在运输环节中运输条件适当放宽,按照一般有毒品进行管理。     

An evaluation of risk assessment framework for industrial accidents in India

Due to rapid industrialization, with high population density and constraints of land, it is expected that level of risks arising from the hazardous industries will increase in India in the coming decades. However, 30 years after the Bhopal accident (1984), except a few discrete regulations, there is as yet no integrated system for assessing and managing risks arising out of these hazardous industries in India. The gravity of aspects related to the management of industrial risk still remains crucially important. In particular, there is no standard guideline on risk analysis methodology, acceptability or tolerability criteria, nor is there an accident database or a risk reduction strategy for the areas where risk levels are already high. On top of this, there are technical and legislative gaps in the institutional framework to implement any of the above mentioned issues. With the backdrop of the Bhopal gas tragedy, the objective of this paper is therefore to evaluate the effectiveness of a comprehensive risk assessment framework for the emerging economy of India, in order to control and/or to reduce the risk level that exists. In this context, regulations and policies pertaining to industrial risk assessment were reviewed.     

Resilience-based approach to safety barrier performance assessment in process facilities

The performance assessment of safety barriers is essential to find vulnerable elements in a safety barrier system. Traditional performance assessment approaches mainly focus on using several static indicators for quantifying the performance of safety barriers. However, with the increasing complexity of the system, emerging hazards are highly uncertain, making it challenging for the static indicators to assess the performance of safety barriers. This paper proposes a resilience−based performance assessment method for safety barriers to overcome this problem. Safety barriers are classified according to their functions first. The dynamic Bayesian network (DBN) is then introduced to calculate the availability function under normal and disruption conditions. The ratio of the system's availability, when affected by the disruption, to the initial availability, is used to determine the absorption capacity of the system. The ratio of the quantity of availability recovery to the total quantity of system represents the adaptation and restoration capacity of the system. The system's resilience is represented by the sum of absorption, adaptation, and restoration capacities. The wax oil hydrogenation process is used to demonstrate the applicability of the proposed methodology.