化工企业典型保护层中独立保护层的识别研究

按照独立保护层(IPL)独立性、功能性、完整性、可靠性、可审查性、安全许可保护性和变更管理的要求,对化工企业典型保护层进行了IPL识别.结果表明:本质安全设计、工厂和社区应急响应一般不作为IPL;作为IPL,基本过程控制系统(BPCS)应在物理上与安全仪表功能(SIF)分离,并满足要求时失效概率(PFD)的要求,在规定时间内完成所要求的动作;关键报警和人员响应应满足操作人员能得到采取行动的指示或报警,有足够的响应时间,任务应具有单一性和可操作性;SIF应在功能上独立于BPCS,SIF各元件应能及时提供响应,并满足相应SIL要求;物理保护和释放后保护设施应独立于其他IPL,并根据实际运行环境对其PFD进行修正.通过IPL的识别研究,可指导企业在进行保护层分析(LOPA)时正确的进行IPL识别,确保LOPA结果的准确有效.     

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。     

化工园区保护层研究

基于保护层分析(LOPA)的理论,对原油储罐一典型的独立保护层进行了分析,计算了保护层下油罐事故概率。分析现有保护层的效果,为构建化工园区典型危险源消防能力的保护层设施提供优化决策模型,给出化工园区消防安全的风险决策过程及相关改进建议。     

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。     

保护层分析方法应用简介

保护层分析(LOPA)方法是在定性危害分析的基础上,进一步评估保护层的有效性,并进行风险决策的系统方法.其主要目的是确定是否有足够的保护层来降低风险,使之满足企业的风险标准.概括来说,保护层分析是基于事故场景的一种半定量分析方法.     

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。     

保护层分析法在化工企业重大危险源罐区的应用研究

为了做好化工企业重大危险源罐区的风险管理,使罐区风险处于可接受水平,本文采用保护层分析法（LOPA）对罐区存在的风险进行风险评估,明确了各分析步骤的具体要求及独立保护层特性和类型,并应用具体实例在HAZOP分析的基础上进行LOPA的分析研究,为化工企业采用LOPA评估重大危险源罐区风险提供参考。     

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     

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.     

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。     

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.     

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.     

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。     

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.     

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.     

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。