Title :
Modeling of common cause failures (CCFs) by using beta factor parametric model
Author :
Qazi Muhammad Nouman Amjad;Muhammad Zubair;Gyunyoung Heo
Author_Institution :
Department of Basic Sciences, University of Engineering &
Abstract :
Nuclear accidents and incidents such as Three Mile Island (TMI-2) 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 significantly 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 significant finding 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.
Keywords :
"Parametric statistics","Safety","Mathematical model","Probability","Fault trees","Couplings","Electric shock"
Conference_Titel :
Energy Systems and Policies (ICESP), 2014 International Conference on
DOI :
10.1109/ICESP.2014.7347004