HAZOP分析中LOPA的应用研究

通过分析危险与可操作性研究(HAZOP)方法的不足和保护层分析(LOPA)方法的功能,提出将LOPA融入HAZOP分析中,能进一步提高HAZOP的事故预防能力和丰富HAZOP的分析结果。介绍LOPA基本方法,阐述LOPA融入HAZOP的机理、衔接关系及分析步骤,并通过一个化工工艺流程危险性分析实例说明LOPA的作用及如何将LOPA融入HAZOP分析中。结果表明:在HAZOP分析中融入LOPA方法,能实现对现有保护措施的可靠性进行量化评估,确定其消除或降低风险的能力,从而寻求是否需要附加减少风险的安全保护措施。     

Layer of Protection Analysis – Quantifying human performance in initiating events and independent protection layers

Layer of Protection Analysis (LOPA) is widely used within the process industries as a simplified method to address risks and determine the sufficiency of protection layers. LOPA brings a consistent approach with added objectivity and a greater degree of understanding of the scenarios and risks as compared to purely qualitative studies such as Process Hazard Analyses. LOPA can be used to address a wide range of risk issues and serves as a highly effective aid to decision making.Incorporation of human performance within LOPA is recognized as an important, though often challenging, aspect of the analysis. The human role in potential initiating events or within human independent protection layers is important throughout the process industries, and becomes even more critical for batch processing facilities and in non-routine operations. The human role is key to process safety and the control of risks, necessitating the inclusion and quantification of human actions in independent protection layers for most companies. Human activities as potential initiating events and human performance within independent protection layers are reviewed and methods for quantification outlined. An extension into Human Reliability Analysis (HRA) is provided, including methods to develop Human Error Probabilities specific to the process safety culture and operations at a given plant site.     

基于LOPA逻辑的罐区多米诺效应定量风险评估*

为了更好地降低化工企业罐区事故造成多米诺效应的风险,提出1种基于保护层分析（LOPA）的定量风险评估程序。首先,阐述基于保护层分析(LOPA)逻辑的多米诺定量风险评估流程,即引入包括可用性、有效性及3种逻辑门定义及量化的安全屏障定量评估;然后,利用LOPA的分析逻辑将安全屏障融入多米诺定量风险评估框架中;最后,选取2×2 000 m3苯乙烯罐区为对象,识别防火层与喷淋冷却系统2种安全屏障并开展基于LOPA逻辑的罐区多米诺效应定量风险评估,得出安全屏障能有效地降低多米诺事故发生频率及罐区个人风险的结论。研究结果表明:该分析方法可为化工企业开展多米诺效应定量风险评估提供参考。     

Fuzzy logic for piping risk assessment (pfLOPA)

This paper explores the application of the fuzzy logic for risk assessment of major hazards connected with transportation of flammable substances in long pipelines. As a basis for risk assessment, the framework of the fuzzy Layer of Protection Analysis (fLOPA) was used. fLOPA presents a new approach to risk assessment based on two assumptions: 1. different effects of the layer of protection functions on particular elements of the risks (frequency and severity of consequence), and 2. the application of fuzzy logic system (FLS) composed of three elements: fuzzification, inference process and defuzzification. A further calculation follows LOPA methodology with the use of fuzzy logic system where fuzzy risk matrix is used for risk assessment. A typical case study comprising section of a long pipeline failure is performed and a comparison between the classical LOPA approach and fuzzy approach is made.     

Scenario identification and evaluation for layers of protection analysis

The identification and screening of scenarios has been identified as a source of variation in Layers of Protection Analysis (LOPA). Often the experience of the analyst is a significant factor in determining what scenarios are evaluated and the worst credible consequences. This paper presents a simplified chemical process risk analysis that is effective in providing a semi-quantitative measure of consequence that may include human harm and is independent of the analyst. This process may be used in evaluation of Management of Change, inherently safer design decisions for capital projects and LOPA re-validation. Conditional and relational logic may be captured with the use of simple spreadsheets to further improve overall efficiency. For example, this method minimizes the overall time required for scenario development and re-validation relative to Hazard and Operability studies (HAZOP).The technique simplifies established models used by engineers engaged in the operation or design of a chemical manufacturing facility without special software or training. The results of this technique are realistic and may be directly compared with corporate or regulatory guidelines for risk of fatality or injury. At each step in the risk analysis process, more detailed or sophisticated methods may be used to refine the technique. Furthermore, results from any step may indicate that the hazard from a specific scenario case is not sufficient to continue with subsequent analysis steps.     

HAZOP-LOPA方法与SIL定级在电镀废水处理中的应用

为了保证电镀废水处理工艺的安全性,首先采用危险与可操作性分析(HAZOP)方法定性辨识工艺中潜在的危险和危害,并提出安全对策措施;然后采用保护层分析(LOPA)方法定量计算现有保护措施是否能够将风险控制在可接受范围;如果风险较高,通过增加安全仪表等级(SIL)降低风险值。并通过实例分析证明HAZOP-LOPA分析方法能够有效地实现电镀废水处理工艺的风险评价。     

Beyond-compliance uses of HAZOP/LOPA studies

Recent years have seen a convergence of scenario-based Hazard and Operability (HAZOP) studies, Layer of Protection Analyses (LOPAs), and safety integrity level (SIL) determinations. These can all be performed using order-of-magnitude estimates for the initiating cause frequency, the effectiveness of protection layers, the severity of loss event consequences, and the inclusion of other risk-reduction factors. Conducting a HAZOP study or a HAZOP/LOPA study in this manner makes it possible to extend the study results to not only determine required SILs, but also to sum scenario risks by process unit and show the quantitative benefit of implementing risk-reduction measures. The aggregated risk can be compared to process-wide tolerable risk criteria, in addition to comparing each scenario to a risk matrix or risk magnitude. This presentation demonstrates how a true risk-based HAZOP study can be performed with little additional effort over that required for commonly performed cause-by-cause HAZOP studies, and how facility managers and engineers can then use the results when deciding on and implementing risk-reduction measures.     

A fuzzy logic and probabilistic hybrid approach to quantify the uncertainty in layer of protection analysis

Layer of protection analysis (LOPA) is a widely used semi-quantitative risk assessment method. It provides a simplified and less precise method to assess the effectiveness of protection layers and the residual risk of an incident scenario. The outcome failure frequency and consequence of that residual risk are intended to be conservative by prudently selecting input data, given that design specification and component manufacturer's data are often overly optimistic. There are many influencing factors, including design deficiencies, lack of layer independence, availability, human factors, wear by testing and maintenance shortcomings, which are not quantified and are dependent on type of process and location. This makes the risk in LOPA usually overestimated. Therefore, to make decisions for a cost-effective system, different sources and types of uncertainty in the LOPA model need to be identified and quantified. In this study, a fuzzy logic and probabilistic hybrid approach was developed to determine the mean and to quantify the uncertainty of frequency of an initiating event and the probabilities of failure on demand (PFD) of independent protection layers (IPLs). It is based on the available data and expert judgment. The method was applied to a distillation system with a capacity to distill 40 tons of flammable n-hexane. The outcome risk of the new method has been proven to be more precise compared to results from the conventional LOPA approach.     

A cascaded fuzzy-LOPA risk assessment model applied in natural gas industry

Natural gas plants demand high amount of energy provided through immense fuel gas units that may suffer risk hazards. Implementing a safety management system is the most efficient way of allocating resources for safety. This paper adopts The Layer of Protection Analysis (LOPA) risk Management associated with Fuzzy Logic methodology to prevent or limit industrial accidents. We provide an innovative cascaded fuzzy-LOPA model for certain hazardous scenarios and at different frequencies of occurrence. The introduced model is tested at moderate and high risk levels controlled in its practical limits through the use of Safety Integrity Functions (SIF). Obtained results show how this fuzzy-LOPA achieves better results to maintain the Safety Integrity Level (SIL) rating to acceptable limits.     

Application of fuzzy logic to explosion risk assessment

Safety and health of workers potentially being at risk from explosive atmospheres are regulated by separate regulations (ANSI/AIHA in USA and ATEX in the European Union). The ANSI/AIHA does not require risk assessment whereas it is compulsory for ATEX. There is no standard method to do that assessment. For that purpose we have applied the explosion Layer of Protection Analysis (ExLOPA), which enables semi-quantitative risk assessment for process plants where explosive atmospheres occur. The ExLOPA is based on the original work of CCPS for LOPA taking into account an explosion accident scenario at workplace. That includes typical variables appropriate for workplace explosion like occurrence of the explosive atmosphere, the presence of effective ignition sources, activity of the explosion prevention and mitigation independent protection layers as well as the severity of consequences. All those variables are expressed in the form of qualitative linguistic categories and relations between them are presented using expert based engineering knowledge, expressed in the form of appropriate set of rules. In this way the category of explosion risk may be estimated by the semi-quantitative analysis. However, this simplified method is connected with essential uncertainties providing over or under estimation of the explosion risk and may not provide real output data.In order to overcome this problem and receive more detailed quantitative results, the fuzzy logic system was applied. In the first stage called fuzzification, all linguistic categories of the variables are mapped by fuzzy sets. In the second stage, the number of relation between all variables of analysis are determined by the enumerative combinatorics and the set of the 810 fuzzy rules “IF-THEN” is received. Each rule enables determination of the fuzzy risk level for a particular accident scenario. In the last stage, called defuzzification, the crisp value of final risk is obtained using a centroid method. The final result of the risk presents a contribution of each risk category represented by the fuzzy sets (A, TA, TNA and NA) and is therefore more precise and readable than the traditional approach producing one category of risk only. Fuzzy logic gives a possibility of better insights into hazards and safety phenomena for each explosion risk scenario. It is not possible to receive such conclusions from the traditional ExLOPA calculation results. However it requires the application of computer-aided analyses which may be partially in conflict with a simplicity of ExLOPA.The practical example provides a comparison between the traditional results obtained by ExLOPA and by fuzzy ExLOPA methods.     

Bayesian networks make LOPA more effective,QRA more transparent and flexible,and thus safety more definable!

Quantitative risk analysis is in principle an ideal method to map one’s risks, but it has limitations due to the complexity of models, scarcity of data, remaining uncertainties, and above all because effort, cost, and time requirements are heavy. Also, software is not cheap, the calculations are not quite transparent, and the flexibility to look at various scenarios and at preventive and protective options is limited. So, the method is considered as a last resort for determination of risks. Simpler methods such as LOPA that focus on a particular scenario and assessment of protection for a defined initiating event are more popular. LOPA may however not cover the whole range of credible scenarios, and calamitous surprises may emerge.In the past few decades, Artificial Intelligence university groups, such as the Decision Systems Laboratory of the University of Pittsburgh, have developed Bayesian approaches to support decision making in situations where one has to weigh gains and costs versus risks. This paper will describe details of such an approach and will provide some examples of both discrete random variables, such as the probability values in a LOPA, and continuous distributions, which can better reflect the uncertainty in data.     

工艺安全管理系统中的工艺危害分析方法比较

简要介绍了工艺安全管理系统,其中工艺危害分析是工艺安全管理系统中的核心要素。对通常采用的故障假设/检查表、故障类型及影响分析、事故树分析、危险与可操作性研究、保护层分析五种分析方法进行了比较,得出了它们的优点、缺点、适用范围及应用时机。故障假设/检查表分析法比较容易使用,适用于工艺的初次评估;故障类型及影响分析、事故树分析适用于高危险性工艺中的工段、组件或单元操作的分析;危险与可操作性研究可以非常系统、全面的对工艺进行分析,是最有效的工艺危害分析方法。保护层分析方法是一种半定量的风险评价方法,它通过分析系统中各个防护层的失效概率来评估潜在事故的危险性,并与可接受标准进行比较,从而实现对防护系统防护性能的判断。通过对分析方法的比较可以指导化工企业选用合适的分析方法来进行工艺危害分析。     

性能化设计思想在化工设施布局安全设计中的应用

指令性规范是目前化工设施平面布局安全设计的主要依据,但其在应用中存在着条款僵化、安全理论基础不全面、可拓展性不明确等问题。本文将性能化设计思想引入到化工企业平面布局安全设计中,初步提出了一种包含危险辨识、性能化目标确定、后果评估及安全设施效用评估等主要组成部分的基于性能化设计思想的平面布局安全设计体系。对体系中最重要的部分—性能化目标确定进行了重点分析,将化工设施布局安全设计分为装置内设备之间的位置设计、厂区内装置区之间的位置设计以及厂区与外部单位之间的位置设计三个级别,从工艺关联性等角度对各级别布局设计中事故场景选择及设施可接受受损水平进行分析,并提出了通过匹配事故场景和设施可接受受损水平来确定性能化目标的方法。     

The role of people and human factors in performing process hazard analysis and layers of protection analysis

Process hazard analysis (PHA) and Layers of Protection Analysis (LOPA) studies address human failures in operating and maintaining processes and the human factors that influence them, amongst other types of failures. People perform PHA and LOPA studies and, therefore, such studies themselves are subject to various possible human failures. Much less attention has been paid to the human factors that influence the performance of PHA and LOPA studies than human factors that influence hazard scenarios. Human failures in the performance of PHA and LOPA studies should be of significant concern to practitioners as such studies are difficult and time-consuming activities that place significant demands on participants, which increases the chance that errors will be made. Human factors such as willingness to rely on the unsubstantiated opinions of others, groupthink, underestimation of the frequencies of low-probability, high-consequence events, and allowing a false sense of accomplishment to distract from implementing study results must be recognized and addressed.This paper identifies and discusses various human factor issues that can influence the quality of PHA and LOPA studies covering preparing for, conducting, recording, documenting, and following-up on studies. Guidelines are provided to help minimize the extent to which these human factor issues may impair study quality.     

基于危险的事故场景及其形式化描述

事故场景的鉴别是复杂装备系统安全风险分析的基础,其完备性直接影响风险评估的有效性,因为任何事故场景的遗漏即意味着设计上可能存在潜在的事故隐患。提出从鉴别系统危险出发。建立危险与其原因(关联引发事件)、事件与系统要素以及系统各要素之间的映射关系,通过对这些关系的运算来获取事故场景的新方法并给出其形式化表述,以期在理论上确保事故场景鉴别的完备性。     

HAZOP、LOPA和SIL方法的应用分析

通过概括介绍危险与可操作性分析(HAZOP)、保护层分析(LOPA)和安全完整性等级分析(SIL)三种方法的特点,总结三种分析方法之间的关系.LOPA分析是HAZOP分析的继续,可以解决HAZOP分析中残余风险不能定量化的不足,是对HAZOP分析结果的丰富和补充;SIL分析则在LOPA分析的基础上,进一步对需要增加的安全仪表系统(SIS)进行设计,并对LOPA分析结果进行验证,即HAZOP、LOPA分析是SIL分析的前期准备工作.因此,在详细介绍SIS的组成、安全生命周期阶段、SIL的选择确定方法以及SIL分析流程之前,也简要介绍了HAZOP、LOPA分析方法,梳理了两种方法的分析流程.最后通过引入示例来展示三种分析方法之间的关系.     

Mechanism analysis and risk assessment of escalation scenario in chemical industry zones

Many major hazard installations (MHIs) are located in chemical industry zones and escalation effect may be triggered when the fire or explosion occurs on a MHI. To investigate the mechanism of the accident escalation, a systematic quantitative assessment methodology is proposed by the considering the feature and uncertainty of the escalation scenario. The main accident energy carriers of the escalation are heat radiation, overpressure of blast and fragments. The escalation probability, joint influence of the three energy carriers and risk characterization of the accident scenarios are carried out. By the new methodology, the escalation scenario in chemical industry zones can be analyzed and the risk escalation morphology is demonstrated by the simulation software. The visualized risk cloud figure gives a supplementary way to prevent the escalation scenario in chemical industry zones planning.     

A criterion for developing credible accident scenarios for risk assessment

Maximum credible accident analysis is one of the most widely used concepts in risk assessment of chemical process industries. Central to this concept is the aspect of ‘credibility’ of envisaged accident scenarios. However, thus far the term credibility is mostly treated qualitatively, based on the subjective judgement of the concerned analysts. This causes wide variation in the results of the studies conducted on the same industrial unit by different analysts.

This paper presents an attempt to develop a criterion using which credible accident scenarios may be identified from among a large number of possibilities. The credible scenarios thus identified may then be processed for detailed consequence analysis. This would help in reducing the cost of the analysis and prevent undue emphasis on less credible scenarios at the expense of more credible ones.     

安全系统安全完整性等级确定方法比较研究

安全完整性等级的确定是开发和设计安全相关系统的前提和基础。为避免因方法选择不当而导致安全完整性等级确定不恰当的问题,针对常用的后果法、风险矩阵法、改进的HAZOP法、风险图法、保护层分析法和定量分析法进行了对比研究。在阐述和分析安全完整性等级内涵及其确定原理的基础上,根据每种方法自身的特点,从准确性、可量化性、工作量和运用的难易程度等方面对其进行了对比和研究,并分析和探讨了选择安全完整性等级确定方法时应重点考虑的因素。研究结果对合理选择安全完整性等级确定方法具有一定的实用价值和借鉴意义。