No abstract

No abstract

No abstract

As a clean and safe energy, nuclear power plays an important role in solving the increasingly prominent environmental problems in the world. Researches on the reliability analysis and risk assessment for the safety operation of Nuclear Power Plants (NPPs) have been paid much more attention due to several accidents in the past decades. GO-FLOW is a methodology for analyzing the reliability of dynamic systems with common cause failures (CCFs), man-machine failures, and time-dependent mission issues. The traditional GO-FLOW methodology presents a set of operators each of which stands for a relatively basic reliability logic. Complex behavior of a physical component may be simply described by one operator or a combination of operators. Therefore the GO-FLOW chart of a system is much more similar to its physical structure diagram than other reliability models such as Fault Tree. In a previous study by authors, a Living PSA technology based on GO-FLOW was proposed which utilizes a group of interrelated GO-FLOW operators to describe the potential change of states of a physical component between operation, standby, failure, preventive and corrective maintenance. The proposed Living PSA technology is intended to provide a convenient way for the safety engineers to update the PSA models for risk assessment. However, it will make the PSA models complex, quite different from their physical structure diagram and therefore difficult to check. This paper presents a hierarchical modeling method of GO-FLOW. The GO-FLOW model of a system will be organized at different layers, including system layer, structure layer and component layer. The proposed Living PSA technology is only applied at component layer and different level of layers are interrelated by introduction of new GO-FLOW operators and equivalent relations. Thus, the GO-FLOW models at the higher layers are more similar to their physical structures of system for understanding and checking. A bottom-up calculation algorithm for the reliability analysis is also presented. An Auxiliary Feedwater System (AFWS) of PWR plant is taken as a study case to show to modeling and analyzing a system for reliability and risk assessment based on this new technology.

No abstract