Advanced thermal hydraulic simulations for human reliability assessment of nuclear power plants

Abstract

Human Risk Assessment (HRA) in the nuclear power industry has advanced in the last two decades. However, there is a lack of understanding of the magnitude of the effect of thermal hydraulic (TH) uncertainties upon the failure probabilities of the operator actions of nuclear units. I demonstrate in this work that there is an effect of TH uncertainties on the operating crew's probability of recognizing errors during a loss of coolant accident (LOCA) initiating event. The magnitude of the effect of the TH uncertainty on the operator's ability to recognize errors is dependent upon the size of the break, the operating state of the plant (in operation or shutting down), and the error that is committed. I utilized an uncertainty software, Dakota, coupled with an advanced TH software, MAAP4, to perform a Monte Carlo analysis to propagate selected TH uncertainties through a LOCA initiating event in which the automatic safety coolant injection system fails to automatically actuate. The operator mission is to manually actuate the safety coolant injection system. Two errors that the operating crew could make are 1) entering fire procedures and 2) testing for saturation of the primary system before the saturation occurs. I calculate the operator failure probabilities using the MERMOS HRA methodology (used by the French electric utility company Electricité de France, EdF). My results show a reduction in scenario failure probability from the values reported by EdF in its published MERMOS Catalogue of more than 80% for the operator recognizing the the error in entering fire procedures. For the error in testing for saturation of the primary system before saturation occurs, I calculated a scenario failure probability in Mode B of 0.0033, while the MERMOS Catalogue listed the scenario failure probability as negligible. My results show that there is an effect from TH uncertainties on operator failure probabilities. This research provides a method of improving the accuracy of failure probabilities in established HRA methodologies using TH simulations.