Publications

Abstract not provided.

Human reliability analysis (HRA) is used in the context of probabilistic risk assessment (PRA) to provide risk information regarding human performance to support risk-informed decision-making with respect to high-reliability industries. In the current state of the art of HRA, variability in HRA results is still a significant issue, which in turn contributes to uncertainty in PRA results. The existence and use of different HRA methods that rely on different assumptions, human performance frameworks, quantification algorithms, and data, as well as inconsistent implementation from analysts, appear to be the most common sources for the issue, and such issue has raised concerns over the robustness of HRA methods. In two large scale empirical studies (Bye et al., 2012; Forester et al., 2012), the Accident Sequence Evaluation Program (ASEP) HRA Procedure, along with other HRA methods, was used to obtain HRA predictions for the human failure events (HFEs) in accident scenarios. The predictions were then compared with empirical crew performance data from nuclear power plant (NPP) simulators by independent assessors to examine the reasonableness of the predictions. This paper first provides a brief overview of the study methodology and results, and then discusses the study findings with respect to ASEP and their implications in the context of challenges to HRA in general.