Methodologies For The Analysis Of Passive Safety System Function Failure

Passive systems are gaining more and more applications in the second generation and the third generation advanced PWR AP1000 and Hualong One. Passive systems can’t fully guarantee the safety of the reactor which also have the corresponding failure modes. Failure of passive systems should include the conventional component failure and the failure of physical processes.First, propose function reliability analysis method of passive system (FRPS) to research the effects of the different initial parameter combinations to the output parameters at the time of loss of feedwater accident (LOFA) in the AP1000 passive residual heat removal system (PRHRS). The main calculation process is:analysis the system function, select the critical parameters, quantify the distribution of the key parameter, sample to obtain the input vector, run Relap5 code to get the output, combine the input with the output as well as the failure criterion to establish the response surface, and finally calculate the probability by Monte Carlo method. Base on the FRPS method, the failure probability is 9.4304E-6 in the case of 106 times Monte Carlo simulation and is 9.7762E-7 and 9.7875E-7 respectively in the case of 107 times and 5×107 times Monte Carlo simulation. So the physical process failure probability can be considered in the degree of 1E-6 by the FRPS method. Also, get the importance degree order by genetic neural network (GNN) analysis.Secondly, introduce the root cause analysis to find the reason why operating parameters deviate from their design values. Attribute the failure of the physical process caused by the operating parameters deviating from its designed values to the failure of specific components. Then, calculate the probability caused by the operating parameters deviating from its designed values by build the fault tree through the RiskSpectrum code.The root cause analysis method’s results showed that the probability of failure for the physical process is 2.73E-6, which is in the same magnitude with the first method’s results.Finally, study the structural arrangement of AP1000 passive residual heat removal system and then build the fault tree by means of RiskSpectrum software and calculate the probability of the conventional component failure. The failure fault tree analysis of AP1000 passive residual heat removal system showed that the component failure probability is 9.559E-6, and the probability is on the same order of magnitude with the failure of physical processes.Assess the physical processes reliability of passive system through the method of function reliability of passive system and the method based on root cause analysis. At the same time, calculate the probability of the component failure through the method of conventional probability safety assessment (PSA). Then, compare the probability of the conventional component failure and the physical processes failure to perfect the research on physical processes reliability of passive systems.