Abstract

The risk-based maintenance strategy has received special attention in the safe operation of nuclear power plants. Simultaneous quantification of the positive and negative effects of maintenance activities and components degradation effect makes it possible to accurately evaluate the risk criterion for safety systems of nuclear power plants. However, it is difficult to integrate the effects of maintenance and components degradation into the standard reliability approaches. A straightforward approach for considering components degradation and different maintenance policies is to make use of Markov maintenance models. In this article, the effectiveness of maintenance activities (including changes in the surveillance test intervals and alteration in the different maintenance policies) on the components unavailability with considering aging effects is quantified using Markov maintenance models and then by coupling these models and the fault tree method, the risk measure is upgraded from the component level to the system level. The proposed models are applied to evaluate the unavailability of two safety systems of VVER-1000/V446 nuclear power plants as case studies. The results show that the Markov method due to its multi-state nature is effective in the conservative evaluation of risk measures so that the unavailability computed by the coupling process is higher than the original unavailability (calculated by system fault tree using PSA data of nuclear power plants) for all maintenance policies. In addition, this study illustrates that the developed Markov maintenance models could be applied to the large-scale whole plant level and provides a proper transition from the classical PSA methods to new techniques. This approach integrates the effects of maintenance strategies and components degradation. Also, it provides a practical and a more accurate tool to determine the technical specification of a real nuclear power plant from the risk point of view.

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