LOPA两个关键因素的认识与应用

正保护层分析(LOPA)作为一种定量风险分析方法,主要是通过使用初始事件可能性、后果严重性和独立保护层(IPLs)失效概率的数量级类别来对一个或多个事故场景的风险进行评估。LOPA分析可应用于基础设计、详细设计、操作、维护、变更和退役的全生命周期的不同阶段。笔者通过对一些评估报告的评审,发现一些评估人员在进行LOPA分析时,对使能条件、修正     

HFL模型在海上压裂工艺过程风险评估中的应用

为有效降低海上压裂工艺过程事故发生的可能性,建立将危险与可操作性研究(HAZOP)、事故树分析(FTA)和保护层分析(LOPA)集成的量化风险评估模型(HFL模型)。阐述HFL模型的集成机理和分析流程。以海上压裂工艺过程高压管线危险性分析为实例,开展该模型的研究与应用。在运用HAZOP方法对危险源初步辨识基础上,构建高压管线超压的蝴蝶结模型(BTM),确定导致事故发生的9种风险因素和5种事故后果,并估算高压管线断裂事故场景的初始事件概率和剩余事故风险。结果表明,现有的独立保护层(IPL)即超压电子保护装置无法使事故风险达到可接受水平,需要通过增加新的IPL,即安装井口保护装置和泄压装置,提高压裂过程高压管线运行的可靠性,确保剩余事故风险处于可接受水平。     

危险化学品泄漏事故演化机理研究

为了分析危险化学品泄漏事故演化机理,简化其定量风险分析过程,先假设容器失效导致的初始事件为危险化学品泄漏事件,再根据危险化学品物质特性分类和中间演化事件场景,构建了常见的各类危险化学品发生泄漏初始事件后的通用事件树,并根据已有的研究成果,对事件树中各种中间演化事件概率进行取值研究。研究结果表明,通用事件树能很好地揭示基于物质特性和中间事件场景的泄漏事故演化规律,应用含中间演化事件概率的通用事件树能计算出各种事故后果发生的频率,对危险化学品事故的快速定量风险分析有十分重要的参考意义。     

保护层分析方法探讨北大核心

首先介绍了安全保护层类型、功能及设置,然后介绍了该方法的分析程序,指出了LOPA除了利用HAZOP进行融合外,还可以结合FTA、ETA分析初始事件、后果事件和工艺过程保护层,分析风险时可利用传统的风险矩阵、模糊逻辑和贝叶斯理论度量风险。最后指出了LOPA应用过程中要注意不宜过度使用,要合理设置保护层等问题。     

基于风险矩阵和LOPA的风险分析法在煤气柜中的应用

采用了风险矩阵和保护层的风险分析方法,对煤气柜在运行过程中的危险因素进行重点分析,建立煤气柜事故场景。针对煤气柜各事故场景,基于风险矩阵和LOPA分析法建立事故分析模型,应用LOPA方法辨别在煤气柜运行过程中各保护层的有效性,判定其风险结果是否位于可接受的水平,从而决定是否应该增加减少风险的安全措施。     

基于JC法的RBI通用失效概率修正模型研究

基于风险的检测技术失效概率的分析始于同类设备的失效频率数据库,然后通过设备修正因子和管理系统评价因子来修正这些同类频率。针对RBI的不足,结合可靠度理论,分析均值一次二阶矩法在实际应用过程中局限性,应用基于JC法的通用失效概率计算模型完成设备失效概率的修正。该方法适合任何概率分布下的情况,可以避免统计数据正态分布一刀切的缺点。     

基于OGP数据的点火概率在保护层分析中的研究与应用

保护层分析(LOPA)是一种数量级层面上的半定量风险评估方法,它通常以定性风险评估为基础,以相对定量风险分析更短的时间及更少的资源为特点而得到广泛应用.在利用LOPA进行风险分析时,需要确定各类场景修正因子,其中点火概率由于影响因素多、现有确定方法较为粗糙,导致较高的不确定性,使得LOPA分析结果的一致性难以保证.根据OGP提供的经验数据,对不同泄漏速率下的点火概率进行数据的完善与补充,得出简化后的点火概率计算模型,在确保点火概率相对准确的同时简化点火概率的计算方法,为LOPA中点火概率的取值提供了依据.同时采用显著性检验的分析方法研究了不同泄漏特征对于点火概率的影响,为LOPA分析中保护层的选取与设计提供了建议.     

基于贝叶斯—LOPA方法的深水钻井安全屏障可靠性分析

据统计,钻井过程是海上井喷事故的高发阶段,为保障钻井安全进行,安装了节流管线、防喷器等安全屏障减缓系统风险,安全屏障的可靠性直接影响钻井安全。利用贝叶斯—LOPA方法建立深水钻井安全屏障可靠性分析模型,以储层-溢流-井涌-井喷为事件链,运用三级井控理论建立独立保护层,每一保护层运用贝叶斯网络方法计算失效概率。在GeNIe软件中完成模型建立,并且完成后验概率计算、敏感性分析、影响力分析。通过分析计算结果给出风险控制关键事件和风险减缓措施,为钻井现场安全工作提出指导意见,确保深水钻井安全有序进行。     

保护层分析中独立保护层的识别研究

为阐述保护层分析(LOPA)中独立保护层(IPL)的识别规则,以及这些规则在实际应用中要注意的问题,以生产聚氯乙烯(PVC)的间歇聚合反应为例,对8个不同的LOPA场景进行分析,给出不同场景的IPL和要求时的失效概率(PFD),以及建议增加的IPL。分析结果表明,在进行IPL的识别时,应重点确认IPL的有效性和独立性。在评估IPL有效性时,应关注具有共同元件的IPL,IPL的行动能力、人员行动有效性及IPL的PFD等。在评估独立性时,应确保IPL独立于初始事件和同一场景中的其他IPL的任何构成元件。通过分析,发现PVC工艺中安全阀(PSV)设计、安全仪表功能(SIF)设计和人员行动等IPL中存在的问题,并提出相应的建议。     

因果图、CCA和LOPA三种安全分析方法的集成研究

因果图、原因-后果分析(CCA)、保护层分析(LOPA)作为重要的安全分析方法,在安全评价中得到广泛运用。针对各方法的优点和不足,提出了因果图、CCA和LOPA的集成研究,并开发出一种量化风险评价模型。先进行因果图分析,找出事故发生的所有原因;再进行CCA分析,从风险矩阵的角度量化风险;最后对较高风险事故场景进行LOPA分析,增加保护控制措施。在3种方法集成分析的基础上,形成一个闭合回路,实现信息和数据共享,提高了评价过程的客观性和评价结果的准确性。分析表明:该集成模型可将剩余事故风险降于可接受水平。     

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。     

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。     

基于事故发展与控制的隐患分级方法

为使隐患管理工作更加科学,对隐患与事故的关系进行研讨,提出隐患的根本属性是能够促使事故发生或发展。通过预估促使和控制(阻碍)事故发展的因素,来揭示隐患在事故过程中的作用机制。根据发生作用的时间将隐患分为第1类隐患和第2类隐患。在风险评估过程中,解决了具体隐患风险分级的问题,提出隐患暴露频率、其他条件的可能性、隐患纠正系数、事故后果初始分值、人员防护修正系数、人员暴露修正系数、应急处理与事故控制修正系数和财产损失修正系数等评价指标。通过隐患致因事故风险的计算,评估隐患的最终风险。     

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。     

Estimation of explosion energy based on fragment characteristics

Explosions of vessels containing high pressure gases or superheated liquids are a common accident in the chemical industry. Fragments are the most information-rich physical evidence in accident analysis. A method is presented to calculate the total explosion energy based on the characteristics of fragments from the scene of an accident, such as mass, horizontal displacement, etc. The implicit expressions of the initial velocity can be obtained through analysing the trajectory equations of the fragments and the data obtained from the scene of the accident. The total energy is calculated from the relationship between the total explosion energy and the kinetic energy of the fragment. During the calculation there are some uncertain parameters, e.g., the energy factor and the initial angle. To solve the parameter uncertainties, a Monte-Carlo simulation is introduced. Analysis of an industrial accident shows that it is feasible to estimate the total explosion energy using the maximum probability density interval with the proposed methodology.     

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.     

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.     

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.     

基于案例推理的地铁非常规突发事件应急决策方法研究

针对地铁非常规突发事故发生时,由于地下环境复杂且封闭,很难获取较全面、准确的事件信息等问题,非常规突发事件的地铁应急决策是一个复杂的过程。通过对地铁事件原则性机理进行分析和研究,得到地铁发生重大火灾事故情景分析的贝叶斯网络节点变量,借鉴CBR模型的思想,将基于结构和属性的双重情景检索的事故案例推理应急决策方法应用到地铁火灾非常规突发事件应急决策中,该方法排除了因属性值缺失造成相似度无法计算或计算有误的情况,可为地铁交通应急平台的后期建设提供理论支持     

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.