Evaluation of Temperature Variation on Pccs Function Al Failure Probability in Rm Model for Ap1000 Nuclear Power Plant

Abstract

Risk Monitor (RM) model is developed based on benchmark PSA to reflect the real-time risk level of Nuclear Power Plant (NPP) for management and decision making. The safety function of Passive Containment Cooling System (PCCS) is accomplished mainly based on natural circulations and atmosphere is used as the ultimate heat sink. Environmental factors, such as air temperature will have significant effect on the system operation and should be considered in the evaluation of PCCS reliability in Risk Monitoring. Since air temperature is a parameter that varies continuously, the method of analyzing the effect of equipment state changes on system failure probability in RM doesn’t have enough ability to deal with air temperature. In this paper, a method based on interval partition is put forward to evaluate the effect of air temperature in RM model, and the interval division is correlated with the seasonal variation. The functional failure probability of PCCS in AP1000 nuclear power plant is evaluated as an example of Risk Monitoring based on seasonal variation. In the study, Loss of Coolant Accident (LOCA) and Steam Line Break (SLB) accidents are analyzed, and the influence of temperature variation on PCCS system reliability under such two accidents is evaluated. The results show that the physical process failure probability changes with seasonal variations, especially the system failure probability in summer is higher than in other seasons, and the influence of temperature on system reliability differs under different accidents. The system failure probability in different intervals can be used to reflect the risk level of the nuclear power plant at its current state.

Keywords: Passive system reliability analysis, Passive Containment Cooling System, Risk Monitoring, Seasonal variation