Abstract
Loss of power supply from the diesel generator system (DGS) after loss of offsite power (LOOP) will pose great threat to the safety of GEN-II pressurized water reactors (PWR). Therefore, it is very desirable to evaluate the DGS’s reliability. The traditional analyzing tools are limited to static approaches neglecting the dynamic sequence failure behaviors, such as reliability block diagram (RBD), static fault tree (SFT). Static reliability modeling techniques are not capable of capturing the dynamic sequence-dependent failure behaviors typically existing in NPP safety systems such as DGS, and thus often overestimate the unreliability of systems. In this paper, motivated to study the effects of sequence failure behaviors, dynamic fault tree (DFT) is applied to evaluate the reliability of the DGS of one Chinese 1000MWe Nuclear Power Plant (NPP), and an integrated two-phased Markov Chain model is also developed, which can be considered as a contribution of this article. Comparative study of DGS reliability between DFT and SFT is carried out. The results indicate that compared with the result derived from the DFT model, the unreliability of DGS calculated by SFT is greatly overestimated by about one to two orders of magnitude. Therefore, DFT has a potential to improve the economy of NPP by relaxing the overestimated unreliability of nuclear power systems.
Highlights
In an Nuclear Power Plant (NPP), most active systems and equipment’ functions are dependent on uninterrupted power supply (UPS)
To deal with this new situation and perform the reliability analysis of the diesel generator system (DGS), in this contribution, dynamic fault tree (DFT) are adopted to model DGS graphically, and an integrated two-phased Markov Chain model and the corresponding computing algorithm were developed based on sequential failure scenarios derived from the built DFT, which are contributions of this work
The components’ failure and repair rates λ and μ can be randomly selected by Monte Carlo simulation method as: λi uλi + r · δλi; μi uμi + r · δμi, where r is a random that follows Gaussian distribution with mean value 0 and standard variance 1, and it can be produced by applying any of the standard random number generator
Summary
In an NPP, most active systems and equipment’ functions are dependent on uninterrupted power supply (UPS). For the DGS of one Chinese 1000MWe PWR, the features of its failure behaviors lie in: 1) Having sequential failure behaviors; 2) Component’ reparability being different at different phases, that is to say, some component is non-repairable at one phase, and becomes repairable at the other phase To deal with this new situation and perform the reliability analysis of the DGS, in this contribution, DFTs are adopted to model DGS graphically, and an integrated two-phased Markov Chain model and the corresponding computing algorithm were developed based on sequential failure scenarios derived from the built DFT, which are contributions of this work.
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