Quantitative Analysis of Safety Margin Reduction of Power Uprate in MBLOCA

Abstract

Nuclear Energy Agency of OECD has developed a methodology in the Safety Margin Action Plan (SMAP) to quantify the reduction of safety margin due to power uprate. The methodology combines the probabilistic and deterministic approaches of safety analyses. In the present study, the SMAP methodology is adopted to quantify the reduction of safety margin of a 5 % power uprate of Maanshan nuclear power plant (NPP) of Taiwan Power Company. The sequence selected to demonstrate the methodology is a medium break cold leg loss of coolant accident. An evaluation model code, RELAP5-3D/K is used in the LOCA analysis. Based on the plant specific PSA model, two dominant accident sequences of the medium LOCA are analyzed. Minimum success criterion of the PSA model is used. Phenomenon Identification and Ranking Table (PIRT) for parameters that are important for the medium break LOCA analyses and their distribution are identified. Two sets of calculations for each accident scenarios are performed to determine PCT at 102 and 105 % rated power. The data of the predicted PCTs are analyzed parametrically and nonparametrically (rank statistics) to determine PCT of the 95th percentile with 95 % of confidence. The results show that the nonparametric results always giving higher 95/95 PCT value and therefore, smaller safety margin. The change of safety margin after SPU is different for different accident scenarios. When the best estimated value is determined parametrically, the safety margin before power uprate is 12.3 and after power uprate is 11.8. There is 4.2 % reduction of safety margin when power is elevated from 102 to 105 % rated power. When the best estimated value is determined nonparametrically, the safety margin before SPU is 10.17 and after SPU is 10.42. The margin increases slightly after SPU. From these results, it can be concluded that the impact of SPU on the safety margin of PCT is very insignificant. The results also demonstrate that, among the parameters in PIRT, the parameter, PBOT, represents the axial power distribution has the largest impact on the predicted PCT. When the power distribution is bottom peaked, the predicted PCT is lower. It can be concluded that the steam cooling effect after core uncover plays a significant role in removing heat from the uncovered portion of the core.