Passive containment cooling system (PCCS) is an important safety-related system in AP1000 nuclear power plant, by which heat produced in reactor is transferred to the heat sink – atmosphere – based on natural circulation, independent of human response or the operation of outside equipments, so the reactor capacity of resisting external hazards (earthquake, flood, etc.) is improved. However since the system operation based on natural circulation, many uncertainty factors such as temperatures of cold and heat sources will affect the system reliability, and physical process failure becomes one of the important contributors to system failure, which is not considered in the active system reliability analysis. That is, the system will lose its function since the natural circulation cannot be established or kept even when the equipments in the system can work well.

The function of PCCS in AP1000 is to transfer the heat produced in the containment to the environment and to keep the pressure in the containment below its threshold. After accidents the steam is injected to the containment and can be cooled and condensed when it arrives at the containment wall, then the heat is transferred to the atmosphere through the steel vessel. So the peak value of the pressure is influenced by the steam situation which is injected into the containment and the heat transfer and condensate processes under the accidents. In this paper the dynamic thermal-hydraulic (T-H) model simulating the fluid performance in the containment is established, based on which the system reliability model is built. Here the total pressure in the containment is used as the success criteria. Apparently the system physical process failure may be related to the system working state, the outside conditions, the system structure parameters and so on, and it’s a heavy work to analyze the influences of all the factors, so only the effects of important ones are included in the model. Monte Carlo (MC) simulation is used to evaluate the system reliability, in which the input parameters such as air temperature are sampled based on their probabilistic density distributions. The pressure curves along with the accident development are gained and the system reliabilities under different accidents are gotten as well as the main contributors. The results illustrate that the system physical process failure probabilities are varied under different climate conditions, which result in the system reliability and the main contributors to system failure changing, so the different methods can be taken to improve the system reliability according to the local condition of the nuclear power plant.

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