UPM共因失效分析方法在系统可靠性分析中的应用

本文对整合部分法(UPM)这个共因失效分析方法及其分析过程作了简要介绍,提出了采用UPM方法进行CANDU堆共因失效分析的技术要点,结合共因失效事件的分析实例及秦山第三核电厂一号停堆系统可靠性分析,对UPM的实际应用作了说明,并结合分析结果提出了一些建议.     

UPM共因失效分析方法在系统可靠性分析中的应用

本文对整合部分法(UPM)这个共因失效分析方法及其分析过程作了简要介绍,提出了采用UPM方法进行CANDU堆共因失效分析的技术要点,结合共因失效事件的分析实例及秦山第三核电厂一号停堆系统可靠性分析,对UPM的实际应用作了说明,并结合分析结果提出了一些建议.     

共因失效对平均失效概率计算结果的影响分析

为了评价共因失效(CCF)对平均失效概率(Pavg)计算结果的影响,建立了一个正常激励1oo2双通道系统的需求失效故障树模型。采用β模型,分别计算出不考虑CCF和考虑CCF 2种情况下的Pavg,发现CCF对Pavg的计算结果有较大的影响。相关分析表明,系统越安全(危险失效率越低,危险失效检测率越高),CCF对Pavg的计算结果影响越大。     

共因失效概率预测的离散化模型

对系统共因失效分析中涉及的概念,诸如共因失效的“根本原因”（root cause）和“耦合机制”（coupling mechanism）等,从载荷的随机性导致零件失效相关性这一观点给予了解释。同时还提出和讨论了“固有相关性”、“偶然相关性”、“绝对共因失效”和“相对共因失效”等概念。借助多维应力-强度干涉分析和对干涉模型进行的离散化处理,建立了根据零件/系统失效数据预测系统共因失效概率简单、实用的离散化的模型。     

冗余系统共因失效的载荷-性能分析与概率估算

从可靠性数学的角度,以环境载荷与零件性能的特征及其相互关系为背景,探讨了k/n(F)冗余系统共因失效的原因与机理,并致力于冗余系统共因失效概率预测的精确方法。分析表明,对于各零件处于同一载荷环境的系统,环境载荷的随机性是导致系统共因失效的最基本的原因。     

MGL 法在共因失效分析中的应用

本文用 MGL(Multiple Greek Letter)法对核电站应急柴油发电机组进行了定性和定量分析,说明了采用 MGL 模型进行共因失效分析的优越之处。     

基于GO法的反应堆补水系统共因失效分析

对反应堆补水系统进行可靠性分析时,按照其不同的工作状态分2个阶段来完成.第1阶段,分析共因部件组2对补水上充部分的影响;第2阶段,综合分析共因部件组1和2对整个补水系统的影响.本文采用GO法分别对补水系统的2个阶段进行系统可靠性分析.首先构造系统模型,通过系统分析建立GO图,并根据GO法关于共因失效的算法计算2个阶段的系统不可用度及共因失效对不可用度的贡献.分析结果表明,共因失效对系统可靠性产生很大影响,而GO法算法是进行系统共因失效分析的有效而实用的方法.     

核电厂安全系统维修活动风险评价过程中的共因失效研究

在电厂风险评价中,随着电厂组态的变化,共因失效的模化也需要相应变化。本文通过研究不同类型维修活动对于共因失效的影响,提出了一种合理可行的共因失效模化方法。并通过分析结果发现,不同类型的维修活动对于共因失效影响不同。相比于预防性维修活动,当设备由于纠正性维修退出服务后,系统的失效概率会有显著的增加。在此基础上,提出了风险指引安全系统后撤时间(AOT)优化中涉及的共因失效处理方式,该处理方式也可用于其他相关的风险评价工作中。     

EPR的二级概率安全评价

EPR设计广泛采用了概率安全分析（PSA）作为确定论分析的补充。PSA采用三级分析评价电厂运行所带来的风险。1级PSA用于导致堆芯损坏熔化事件的风险评价，并确定对风险有贡献的事件、系统失效及运行错误。2级PSA用于评价裂变产物从电厂释放到环境的风险，并对严重事故导致的放射性释放（通常称为源项）的频率和大小进行量化分析。3级PSA对事故所导致的放射性释放对社会造成的危害进行量化分析，也就是对健康和对食物链污染的可能影响。     

基于GO法的压水堆净化系统共因失效分析

应用GO法分析了共因失效对压水堆净化系统可靠性的影响.采用GO法的运算法则,求出净化系统状态概率表达式,并根据GO法的共因失效的算法计算出共因失效对系统不可用度的贡献.结果表明,共因失效对压水堆净化系统可靠性有很大影响.     

Probabilistic common cause failure modeling for auxiliary feedwater system after the introduction of flood barriers

Causal inference is capable of assessing common cause failure (CCF) events from the viewpoint of causes’ risk significance. Authors proposed the alpha decomposition method for probabilistic CCF analysis, in which the classical alpha factor model and causal inference are integrated to conduct a quantitative assessment of causes’ CCF risk significance. The alpha decomposition method includes a hybrid Bayesian network for revealing the relationship between component failures and potential causes, and a regression model in which CCF parameters (global alpha factors) are expressed by explanatory variables (causes’ occurrence frequencies) and parameters (decomposed alpha factors). This article applies this method and associated databases needed to predict CCF parameters of auxiliary feedwater (AFW) system when defense barriers against internal flood are introduced. There is scarce operation data for functionally modified safety systems and the utilization of generic CCF databases is of unknown uncertainty. The alpha decomposition method has the potential of analyzing the CCF risk of modified AFW system reasonably based on generic CCF databases. Moreover, the sources of uncertainty in parameter estimation can be studied. An example is presented to demonstrate the process of applying Bayesian inference in the alpha decomposition process. The results show that the system-specific posterior distributions for CCF parameters can be predicted.     

Summary of NET plant probabilistic safety approach and results by means of ENEA fusion plant safety assessment (EFPSA)

This paper summarizes the probabilistic safety assessment for the main accident scenarios associated with failures originating in the In-Vessel Plant Area of the Next European Torus (NET). The assessment refers to the Basic Performance Phase of operation under normal running and conditioning. For the corresponding accident sequences, the values of the annual expected frequency and the seriousness of consequences expressed as early dose to the Most Exposed Individual (MEI) of the public are listed.     

Reliability model of the digital reactor protection system considering the repair time and common cause failure

Reliability of the digital reactor protection system (RPS) is intensively researched as it is designed and installed to ensure the safety and economy which can be measured respectively by the probability of failure on demand (PFD) and probability of spurious trip (PST). Meanwhile, by analyzing the failure modes of the digital RPS, the failure on demand and spurious trip are the two main modes that should be evaluated for the reliability of digital RPS. Therefore, this paper develops the PFD and PST calculation formulas considering the module repair time as the repair takes some time, and during the repair duration, the digital system is operated in the degraded configuration and the common cause failure (CCF) which would severely impact the system in the event of occurrence. Considering the failure phenomenon of the digital RPS, the binomial failure rate (BFR) model is adopted for CCF. And the fault-tolerance techniques and their fault coverage are considered when calculating the PFD and PST. The quantitative results show that, in the example, CCF dominates the PFD while CCF is one of the major factors that result in PST but the main contributor is the independent failure. Also it can be concluded that the discovery time for the undetected failures dominates the PFD and PST when it costs long time to discover the failures even though the uncovered failures are very few. Thus, the failures should be covered by the fault-tolerance techniques as much as possible when designing the digital RPS.     

Fuzzy probability on reliability study of nuclear power plant probabilistic safety assessment: A review

Fault tree analysis (FTA) is a graphical model which has been widely used as a deductive tool for nuclear power plant (NPP) probabilistic safety assessment (PSA). The conventional one assumes that basic events of fault trees always have precise failure probabilities or failure rates. However, in real-world applications, this assumption is still arguable. For example, there is a case where an extremely hazardous accident has never happened or occurs infrequently. Therefore, reasonable historical failure data are unavailable or insufficient to be used for statistically estimating the reliability characteristics of their components. To deal with this problem, fuzzy probability approaches have been proposed and implemented. However, those existing approaches still have limitations, such as lack of fuzzy gate representations and incapability to generate probabilities greater than 1.0E-3. Therefore, a review on the current implementations of fuzzy probabilities in the NPP PSA is necessary. This study has categorized two types of fuzzy probability approaches, i.e. fuzzy based FTA and fuzzy hybrid FTA. This study also confirms that the fuzzy based FTA should be used when the uncertainties are the main focus of the FTA. Meanwhile, the fuzzy hybrid FTA should be used when the reliability of basic events of fault trees can only be expressed by qualitative linguistic terms rather than numerical values.     

Quantitative common cause failure modeling for auxiliary feedwater system involving the seismic-induced degradation of flood barriers

Flood barriers are important defenses which will reduce the internal flood-induced failure risk of safety-related equipment in the turbine building. Contrarily, the degradation of flood barriers will increase the risk of internal flood-induced common cause failure (CCF). Two layouts of auxiliary feedwater pumps system are compared to demonstrate the quantitative risk assessment of the possible degradation of flood barriers. The alpha decomposition method has been developed by the authors in order to quantitatively evaluate the CCF parameters based on the causal inference. Occurrence frequency and CCF triggering ability are two important elements which will decide the CCF risk significance of potential common causes. The seismic-induced internal flood combining with the degradation of flood barriers is analyzed. The degradation of flood barriers is treated as a stochastic process and a Markov model is applied to consider the time-dependent states. The failure time of three auxiliary feedwater pumps is calculated based on the water flow rate through flood barriers. CCF triggering abilities of internal floods are calculated which are represented as decomposed alpha factors. This article shows the updating process of CCF parameters according to Bayesian inference and hypothetical databases. It is concluded that the issue of CCF modeling is not only decided by the number of redundant components but also decided by causes and plant-specific design.     

RiskA和Risk Spectrum故障树计算的比较分析

对FDS团队研发的国产PSA软件RiskA进行了大量系统性的测试,采用完整的核电站真实系统模型,分别用RiskA和国际同类流行软件如Risk Spectrum进行了故障树的定性及定量分析,测试结果表明RiskA与国际同类软件相比,结果正确、模型可靠、算法精确.而Risk Spectrum在测试过程中暴露出了一些问题,如分析中采用阶数截断时单个最小割集的定量计算不正确等,对该问题进行了理论证明及初步的原因分析.     

Important factors affecting fault detection coverage in probabilistic safety assessment of digital instrumentation and control systems

As digital instrumentation and control (I&C) systems are gradually introduced into nuclear power plants (NPPs), concerns about the I&C systems’ reliability and safety are growing. Fault detection coverage is one of the most critical factors in the probabilistic safety assessment (PSA) of digital I&C systems. To correctly estimate the fault detection coverage, it is first necessary to identify important factors affecting it. From experimental results found in the literature and the authors’ experience in fault injection experiments on digital systems, four system-related factors and four fault-related factors are identified as important factors affecting the fault detection coverage. A fault injection experiment is performed to demonstrate the dependency of fault detection coverage on some of the identified important factors. The implications of the experimental results on the estimation of fault detection coverage for the PSA of digital I&C systems are also explained. The set of four system-related factors and four fault-related factors is expected to provide a framework for systematically comparing and analyzing various fault injection experiments and the resultant estimations on fault detection coverage of digital I&C systems in NPPs.     

Estimation of common cause failure parameters for essential service water system pump using the CAFE-PSA

This paper presents the estimation results of the common cause failure (CCF) parameters of essential service water system (ESWS) pump failure to run for KX nuclear power plant (NPP) in Korea. Until now, the generic values of the CCF parameters have been mainly used in most probabilistic safety assessment (PSA) projects for the Korean NPPs. The PSA results for KX NPP showed that the CCF events of ESWS pump failure to run was identified as one of dominant contributors to its internal event core damage frequency (CDF). Thus, we performed the plant specific detailed CCF analysis to estimate CCF parameters of ESWS pump failure to run for KX NPP with the CAFE-PSA, a program to analyze CCF events in the ICDE database. Reasonable values of CCF parameters were obtained through performing plant specific detailed CCF analysis. The estimated Alpha Factor with three out of three failure criterion was about one half of that for recent US NRC CCF parameters. The re-quantification results on the CDF of KX NPP with the new estimated Alpha Factor showed that originally estimated CDF with generic Alpha Factor decreased by 16.84% and the contribution of the sum of cutsets for the CCF events of ESWS pump failure to run to internal event CDF decreased from 20% to 3.29%.     

Success criteria analysis in support of probabilistic risk assessment for nuclear power plants: application on SGTR accident

Success criteria analysis (SCA) bridges the gap between deterministic and probabilistic approaches for risk assessment of complex systems.To develop a risk model,SCA evaluates systems behaviour in response to postulated accidents using deterministic approach to provide required information for the probabilistic model.A systematic framework is proposed in this article for extracting the front line systems success criteria.In this regard,available approaches are critically reviewed and technical challenges are discussed.Application of the proposed methodology is demonstrated on a typical Westinghouse-type nuclear power plant.Steam generator tube rupture is selected as the postulated accident.The methodology is comprehensive and general;therefore,it can be implemented on the other types of plants and complex systems.