Reliability forecasting for operators’ situation assessment in digital nuclear power plant main control room based on dynamic network model

• We identified the influence factors associated with situation assessment (SA) reliability.
• We developed the SA reliability model.
• We proposed a reliability forecasting model for operators’ SA.
• The prediction results from experiments are consistent with measurement results.

With the technical development of computer hardware and software, digitalization is a trend in large-scale complex systems such as nuclear power plants (NPPs). It changes the way main control room (MCR) operators interact with systems. Faced with these technical changes, operators need to continue improving their situation assessment (SA) reliability level. In addition to evaluate operators’ SA reliability, managers and shift supervisors also want to forecast their SA reliability level. There have been many studies with respect to operators’ SA, but most of them are static analysis method and cannot be applied to predict operators’ SA reliability. So, on the basis of different forecasting approaches and observation data, how to predict the operators’ SA reliability level has became a problem that many analyst interest in. In this paper, first we identified the influence factors associated with SA reliability, and then we developed the SA reliability model, finally we proposed a reliability forecasting model by integrating time series forecasting method with dynamic network model (DNM). Our experiment verification focused on steam generator tube rupture (SGTR) event, using the forecasting model, we demonstrated how to predict operators’ SA reliability during the course, and the prediction results are consistent with measurement results.