Modeling Of Common Cause Failures (CCFs) by using Beta Factor Parametric Model Qazi Muhammad Nouman Amjad, Muhammad Zubair Department Of Basic Sciences University Of Engineering & Technology, Taxila.
[email protected] Abstract Nuclear accidents and incidents such as Three Mile Island (TMI2) accident (1979), Chernobyl disaster (1986) and the recent Fukushima nuclear disaster (2011) have caused people to be suspicious of the safety of nuclear energy, and have reduced the level of trust among public. Common cause failure (CCF) has been a major element of such accidents in terrestrial nuclear power reactors because of high redundancy built into the systems and susceptibility of these redundant systems to CCF mechanisms. For this purpose, ad hoc approaches used to be taken to address vulnerabilities to CCF by operating staff of the plants. A CCF event is a result of simultaneous failure of two or more individual components. Such an event can signi¿cantly affect the availability of safety systems and has long been recognized as an important issue in the probabilistic safety assessment (PSA). So a complicated and unresolved problem in the subject of safety and reliability is to model CCF in PSA. To overcome this problem the present research highlights a mathematical model to estimate system unavailability in nuclear power plants (NPPs) as well as in other industries. This mathematical model is based on Beta Factor parametric model. The motivation for development of this model lays in the fact that one of the most widespread software such as for fault tree (FT) and event tree (ET) modeling as part of the PSA does not comprise the option for simultaneous assignment of single failure event to multiple CCF groups. A signi¿cant ¿nding from such modeling is that, in contrast to common expectations, a too early nuclear phase-out will not serve the deployment of renewable energy sources and rational use of energy. The proposed method can be seen as an advantage of the explicit modeling of CCF.
1. Introduction The common cause failures (CCFs) refer to a speci¿c class of dependent failure events that are considered to have a potential of simultaneous occurrence due to a shared cause. This shared cause is an implication of a simultaneous existence of a root cause and a coupling mechanism. The root cause is identi¿ed as the most basic cause of component failure which, if corrected, would prevent reoccurrence of the cause. The coupling mechanism implicates the condition for multiple components to be affected by the same cause. In general, the susceptibility of a system containing redundant components to dependent failures, as opposed to independent failures, is determined by the presence of the coupling mechanisms. CCFs are being acknowledged as one of the most challenging issues in the probabilistic safety assessment University of Engineering and Technology, Taxila, Pakistan. Kyung Hee University, South Korea.
Gyunyoung Heo Department of Nuclear Engineering, Kyung Hee University, South Korea. (PSA), especially within PSA fault tree (FT) modeling of safety systems in nuclear power plants. The issue of CCF has attracted a substantial academic attention, through years as well as lately. This paper presents a convenient method for explicit modeling of single component failure event simultaneously within several different common cause failure groups (CCFGs). Each CCFG is de¿ned on the basis of speci¿c coupling mechanism. The presented methodology that accommodates single component failure event to be simultaneously assigned to different CCFGs given different coupling mechanisms is based on a modi¿cation of the frequently used and to the scienti¿c community well-known Beta Factor parametric model. It is the most commonly used CCF-model, and was originally proposed by Fleming [1]. This model assumes that a certain percentage of all failures are CCFs. When using the beta-factor model, we have to assume that each element of a system can fail in two different ways: as an independent failure that only affects the element considered, or as a dependent failure (CCF) where all the elements in the subsystem fail at the same time (or within a short time interval).The motivation for this study is the incapability of one of the most widespread PSA software for FT and event tree (ET) modeling [2], for simultaneous assignment of one single component failure event in more than one CCFG within the fault tree analysis (FTA) technique. 2. Modeling of common cause failures in the probabilistic safety assessment 2.1. Overview of PSA PSA is being acknowledged as the most effective tool for safety and risk management in NPPs. The two most commonly used techniques for system modeling within PSA for NPPs are the fault tree analysis (FTA) and the event tree analysis (ETA). The purpose of system modeling in PSA is to provide an abstract representation of the ways in which systems can fail to perform their intended functions FTA and the ways in which system successes and failures interact with one another in the course of accident sequence progressions ETA [3]. FTA is a tool to identify and assess all combinations of undesired events in the context of system operation and its environment that can lead to the undesired state of a system. Undesired state of the system is represented by a top event. Logical gates connect the basic events (BEs) to the top event. BEs are the ultimate parts of the FTA, representing
different undesired events such as component failures, missed actuation signals, human errors and common cause contributions [4,5]. The qualitative phase of the analysis solves the system logic function in terms of the minimal cut sets (MCSs), which are combinations of the smallest number of component faults that may cause the system fault. Each of the MCSs is calculated as a Boolean logical product of basic events. The quantitative phase calculates the probability of system failure, i.e. the fault tree top event probability of occurrence PTOP : N
¦ PMCSn ( BE1 ,......,BExn ) _ n =1
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MCS n ( BE1 ,......,BExn ) ∩
MCS n ( BE1 ,......, BExi ......)
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