Loss of Coolant Accident (LOCA) Analysis for McMaster Nuclear Reactor Through Probabilistic Risk Assessment (PRA)

Abstract

A probabilistic risk assessment (PRA) was conducted for the loss of coolant accident (LOCA) sequence in the McMaster Nuclear Reactor (MNR). A level 1 PRA was completed including event sequence modeling, system modeling, and quantification. To support the quantification of the accident sequence identified, data analysis using the Bayesian method and human reliability analysis (HRA) using the ASEP approach were performed. Since human performance in research reactors is significantly different from that in power reactors, a different time-oriented HRA model was proposed and applied for the estimation of the human error probability (HEP) of core relocation. This HEP estimate was less than that by the ASEP approach by a factor of about 2. These two HEP estimates were used for sensitivity analysis, and modeling uncertainty in the PRA models was quantified. This showed the necessity of appropriate human reliability models in PRA for research reactors. This method could be implemented for the operators’ actions which require extensive manual execution with little cognitive load, as might be the case for some maintenance operations in power reactors.