基于风险矢量图的多场景保护层分析方法研究*

为解决多场景保护层分析（LOPA）存在的问题,建立风险矢量导图,将事故场景、独立保护层、修正因子、事故后果发生频率等因素进行系统分析,分别采用最大值法求和法计算后果发生频率,探讨多重初始事件导致事故发生频率的最优计算方法;阐述点火源、暴露因子以及致死概率等修正因子的使用方法并提出改进建议,避免常规LOPA下致死概率过高的问题。以柴油加氢装置原料油缓冲罐液位过高风险点为例,进行多场景LOPA,应用综合计算法得出多重初始事件导致的液位高后果失效频率为3.2E-02。结果表明:风险矢量导图和正确使用修正因子可有效提高LOPA的质量;不同初始事件导致的场景失效频率值相差较大或存在共用保护层的情况适用最大值法,其他情况则可采用求和法;如果多场景同时适用最大值法和求和法,则采用综合计算法;求和法过于保守,最大值法过于乐观,综合计算法更为准确。     

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.     

A formulation to optimize the risk reduction process based on LOPA

This paper presents a mixed integer nonlinear programming (MINLP) model to improve the computational use of the layer of protection analysis (LOPA). For a given set of independent protection layers to be implemented in a process, the proposed optimization model is solved to: a) Include costs associated with the different prevention, protection and mitigation devices, and b) Satisfy the risk level typically specified in the LOPA analysis through the occurrence probability. The underline purpose focuses on improving the analysis process and decision making to obtain the optimal solution in the safeguards selection that satisfies the requirements to be considered as IPL’s. The optimization is based on economic and risk tolerance criteria. As a first stage of this proposal, the safety instrumented system (SIS) design is optimized so that the selection of SIS components minimizes the risk and satisfies the safety integrity level (SIL) requirements. A case study is presented to validate the whole proposed approach.     

基于模糊保护层的池火灾事故风险分析

为计算引发池火灾事故的风险值,提高事故风险的量化水平,判断现有风险控制措施是否满足风险容忍度的要求,为制定减缓风险措施提供依据,给出了新的池火灾风险评估模型。基于传统的保护层分析模型(LOPA),结合模糊集合理论,引入模糊风险矩阵进行风险评估,构建适用于引发池火灾事故的模糊保护层(fL OPA)风险分析模型。该模型的特点是将模糊逻辑和保护层分析结合,减少了传统保护层分析方法计算过程中的不确定性因素,引入严重度减少指数(SRI)概念,使严重度计算、风险评估更加准确。运用该模型对原油储罐泄漏池火灾事故风险进行分析,给出风险决策方案,判断现有保护措施是否能控制风险在可容忍范围内,实例验证了模型的可行性。     

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.     

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.     

ExSys-LOPA for the chemical process industry

The chemical process industries are characterized by the use, processing, and storage of large amounts of dangerous chemical substances and/or energy. Among different missions of chemical plants there are two very important ones, which: 1. provide a safe work environment, 2. fully protect the environment. These important missions can be achieved only by design of adequate safeguards for identified process hazards. Layer of Protection Analysis (LOPA) can successfully answer this question. This technique is a simplified process of quantitative risk assessment, using the order of magnitude categories for initiating cause frequency, consequence severity, and the likelihood of failure of independent protection layers to analyze and assess the risk of particular accident scenarios. LOPA requires application of qualitative hazard evaluation methods to identify accident scenarios, including initiating causes and appropriate safeguards. This can be well fulfilled, e.g., by HAZOP Studies or What-If Analysis. However, those techniques require extensive experience, efforts by teams of experts as well as significant time commitments, especially for complex chemical process units. In order to simplify that process, this paper presents another strategy that is a combination of an expert system for accident scenario identification with subsequent application of LOPA. The concept is called ExSys-LOPA, which employs, prepared in advance, values from engineering databases for identification of loss events specific to the selected target process and subsequently a accident scenario barrier model developed as an input for LOPA. Such consistent rules for the identification of accident scenarios to be analyzed can facilitate and expedite the analysis and thereby incorporate many more scenarios and analyze those for adequacy of the safeguards. An associated computer program is under development. The proposed technique supports and extends the Layer of Protection Analysis application, especially for safety assurance assessment of risk-based determination for the process industries. A case study concerning HF alkylation plant illustrates the proposed method.     

Integration of process control protection layer into a simulation-based HAZOP tool

This paper discusses the framework methodology behind the proposed simulation-based HAZOP tool. Simulation-based approach is one of the many ways to support conventional HAZOP by its automation. Compared to knowledge-based and other approaches, a HAZOP software tool based on deviations simulation is able to examine the investigated process more into detail and so find root causes of hazardous consequences. Another advantage is the ability to identify also potential hazards which did not occur in the past and might be overlooked. The presented framework methodology uses a layer of protection analysis (LOPA) concept of independent protection layers (IPLs) testing. Control system integrated into the raw process design represents the first of various protection layers of the LOPA concept. As a case study, a CSTR chemical production with nonlinear behavior under Proportional-Integral-Derivative (PID) actions as the predominant type of classical feedback control strategy is used. The presented tool identifies hazardous regimes under conditions when control loop introduces hazardous consequences or even acts synergically with existing hazardous events. Risk derived from different consequences is ranked by the risk assessment matrix (RAM) as a part of the conventional quantitative HAZOP study.     

Design support for the systematic integration of risk reduction into early chemical process design

Design for safety in the chemical industry is becoming a more explicit and well-organised process. However, it requires additional support tools to enable designers to pay attention to safety from the earliest conceptual design stage and through the subsequent detailing and to design more cost-effectively. This paper presents a more explicit approach called design for safety (DfS), which links with approaches already in use, such as layers of protection approach (LOPA). The method consists of two elements, a technology management environment (TME) aimed at supporting the interaction between the many contributors to safe design and a safety modelling language (SML). This provides a rigorous object-oriented language for conceptualising the requirements for risk control (barriers) and analysing their vulnerability to degradation or attack by other system elements or conditions. The method provides a focus for organising and applying existing knowledge about risk control and systematically learning from new knowledge to be gathered and supplied in supporting databases.     

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.     

石化装置火灾爆炸贝叶斯网络与防护层集成分析

复杂的石油化工装置在运转过程中存在诸多不确定因素,易发生火灾、爆炸等重大事故,给安全生产带来极大威胁。考虑到传统的系统安全分析方法在风险评估中存在一定局限性,引入贝叶斯网络与防护层集成分析模型。应用GeNIe软件将系统故障树转成贝叶斯网络,根据贝叶斯双向推理进行故障预测和诊断,快速识别系统薄弱环节并确定为风险贝叶斯故障节点,结合防护层分析提出相应的独立防护层,确定剩余风险水平。实例应用表明,所构建的贝叶斯网络与防护层集成分析模型对复杂系统进行风险评估是可行的,较传统的事件树、故障树分析方法更加科学、合理。     

过程工业计算机辅助安全防护层分析技术进展

介绍当前过程工业安全防护层分析(LOPA)的基本内容,研讨LOPA方法与深层次的危险和可操作性分析方法(HAZOP)之间的关系以及计算机辅助HAZOP的研究进展。针对人工LOPA方法的缺点,开发了SDG-HAZOP软件平台,为计算机辅助LOPA平台研发创造了先决条件。应用计算机辅助LOPA方法,使防护层的设置具有更好的针对性、合理性和有效性,发挥对事故的预防和预警作用,并具有良好的发展前景。     

3-Parameters SPW technique: A new method for evaluation of target safety integrity level

Introduced by IEC-61508 standard, safety integrity levels (SIL) have been used for assessing the reliability of safety instrumented functions (SIF) for protection of the system under control in abnormal conditions. Different qualitative, semi-qualitative and quantitative methods have been proposed by the standard for establishing target safety integrity levels amongst which “Risk Graph” has gained wide attention due to its simplicity and easy-to-apply characteristics. However, this method is subject to many deficiencies that have forced industry men and experts to modify it to fit their demands. In this paper, a new modification to risk graph parameters has been proposed that adds more flexibility to them and reduces their subjective uncertainties but keeps the method as simple as before. Three parameters, namely severity (S), hazard avoidance probability (P), and demand rate (W) are used instead of former four parameters. Hence, the method is named SPW. The outcome results of this method can be directly converted to probability of failure on demand (PFD) or risk reduction factor (RRF). The proposed method has been tested on an example case that has been studied before with conventional risk graph and LOPA techniques. The results show that new method agrees well with LOPA and reduces costs imposed by conservative approximations assumed during application of conventional risk graph.     

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.     

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。     

考虑非独立保护层影响的LOPA改进策略研究

针对LOPA在识别保护层方面的局限性,通过考虑非独立保护层的影响,将非独立保护层分为不满足有效性与不满足独立性2类进行分析,针对不同类型的非独立保护层分别应用引入削减系数以及与故障树分析（FTA）集成的方法对传统LOPA进行改进,并结合具体案例验证其适用性。研究结果表明:改进方法的计算结果较传统方法计算结果降低了1个数量级,避免了传统方法过于保守的评价结果;通过对传统方法的改进,克服了LOPA在识别保护层方面以及场景频率计算方面的局限性,有助于拓展其使用范围。     

Value at Risk Perspective on Layers of Protection Analysis

Layers of protection analysis (LOPA) is an established tool for designing, characterizing, and evaluating risk in the chemical process industry. Value at risk (VaR) is a method first introduced in the financial sector for modeling potential loss in a complex venture. In this paper we demonstrate the application of VaR principles to the LOPA of an ethylene refrigeration compressor. We calculate the changes in risk profile (probability versus loss) associated with adding or removing different safety interlocks around the compressor. The VaR analysis shows that the benefits of a given layer of protection are not necessarily captured by a single average number, since the entire probability–value curve is affected. This type of analysis will aid in the allocation of limited resources to process risk interventions.     

Application of human factors evaluation in engineering design and safe operation of dense phase ethylene treaters

Ethylene treaters are widely used in the petrochemical industry to remove impurities from ethylene feedstock imported from pipeline networks or storage caverns. The safety concerns of dense phase ethylene treaters due to the reactive and highly flammable nature of ethylene are well known and studied. Under certain conditions, ethylene may self-polymerize and decompose violently with heat release. Under other conditions, ethylene will auto-refrigerate, generating cold liquids that may cause potential brittle fracture hazards. Therefore, dense phase ethylene treaters present design challenges with the unique combination of high temperature decomposition and cold temperature brittle fracture hazards.Due to these safety concerns, it is important to select the appropriate engineering design options for dense phase ethylene treaters and the associated regeneration facilities. Totally automated treater regeneration systems add complexity and instrument maintenance requirements while manually operated systems rely heavily on operator training and procedures. Unfortunately, little or no information or design guidance is available from published research findings in the literature on the evaluation and risk assessment of current industrial design options and practices for dense phase ethylene treaters.This paper presents a systematic risk assessment method to evaluate the engineering design and safe operation options for dense phase ethylene treaters. The proposed risk assessment method integrates human factors task analysis into the traditional HAZOP, LOPA and fault tree analysis to allow evaluation of automated, manual and hybrid approaches with a goal of selecting and optimizing design options to ensure plant safety. This approach provides a realistic assessment of the operational risk and allows identification of fit-for-purpose risk reduction. Applying this systematic risk assessment approach, a simpler and more cost effective design solution can be justified, thereby avoiding the need for a high integrity protective system.     

Villains,victims, and heroes: Accounting for the roles human activity plays in LOPA scenarios

When a team is analyzing a LOPA scenario, the team needs to consider all three roles played by human interaction in the scenario: that of cause, as a result of human error; that of receptor, both in terms of safety impacts (inside the fence line) and community impacts (outside the fence line); and that of independent layer of protection (IPL), considering both administrative controls and human responses. Frequently, the nature of these three roles are inter-related, and setting guidance that is internally consistent is important to using LOPA to assess risk rather than as a means to game the analyses to simply achieve a wished-for result.A number of criteria have been proposed to quantify human involvement, typically as cause, as receptor, or as IPL. Establishing a framework to look at all three in a unified way is more likely to result in analyses that are consistent from scenario to scenario.This paper describes such a framework and presents it in a way that allows organizations to review their own criteria for quantifying human involvement in LOPA. It also examines some of the published LOPA criteria for human involvement and looks at them in terms of consistency of approach between evaluation of cause, receptor, and IPL. Finally the paper makes suggestions to use in calibrating LOPA methodologies to achieve consistent and believable results in terms of human interaction within and between scenarios that have worked for other organizations.     

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.