Analysis of dependencies among performance shaping factors in human reliability analysis based on a system dynamics approach

Performance shaping factors (PSFs) describe the influence of given contexts on human performance and are used to quantify human error probabilities (HEPs). HEPs are calculated within human reliability analysis, which is a part of probabilistic risk assessment. One challenge lies in the fact that the dependencies among PSFs are neglected, which leads to the poor estimation of HEPs. The objective of this research is to apply a system dynamics approach to the modeling and analysis of the dependencies of PSFs within the standardized plant analysis of risk–human reliability analysis method. Dependencies are built on the causalities of PSFs and are determined by the mutual information theory and the analytic hierarchy process.
The method is demonstrated on three human failure events. The first one is the failure of initiating reactor coolant system depressurization. The second one is the failure of throttling the high-pressure injection to reduce reactor coolant system pressure. The third one is the failure of diagnosing the steam generator tube rupture. The sensitive analysis results show that our model is reasonable and robust when dependencies are taken into account.