The categorization of Structures, Systems and Components (SSCs) is one of the foundations in the design of the nuclear reactor. The regulation requirements based on the current deterministic categorization are over-conservative in some aspects; on the other hand, some requirements for the nonsafety-related components are too loose. In order to make the requirements reasonable, the risk-informed significance categorization of SSCs has been presented. Risk-informed significance categorization (RISC) is to categorize structures, systems, or components (SSCs) of a nuclear power plant (NPP) into two or more groups, according to their significance using both probabilistic and deterministic insights. The SSCs are quantitatively categorized by their importance measures; Fussell–Vesely (FV) and Risk Achievement Worth (RAW) are widely used. But in conventional methods for the RISC, first, a component will be categorized as significance once the value of FV or RAW is over the thresholds. So the significant components are treated equally regardless of the difference between FV and RAW, that is not suitable. Second, the component RAW derived from the sum or maximum of the basic events is not realistic. Third, the categorization threshold for FV is not uniform, different reactors have the different thresholds. The three key problems will be researched in this paper, the quartered way will be presented base on the discussion about combination of the two importance measures (binary importance decision). And then through transferring the additivity from FV to RAW, the realistic component RAW derived from FV will be got. Finally, according to the relationship between FV and RAW, the threshold for FV will be gained similar to RAW. In the study, the author will use the new method to make a practice on the Daya Bay Nuclear Power Plant, 43% components of the low pressure safety injection system which are safety-related are categorized as low significant; 2.6% components which are nonsafety-related of the auxiliary feed water system are categorized as significant.

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