Domain- and task-analytic workload (DTAW) method: a methodology for predicting mental workload during severe accidents in nuclear power plants

Abstract

Excessive mental workload reduces operators’ performance and threatens the safety of nuclear power plants (NPPs) in severe accident management (SAM). Given the lack of suitable mental workload measurement methods for SAM tasks, we proposed a Domain- and Task-Analytic Workload (DTAW) method to predict SAM workload. The DTAW method is developed in three stages: scenario construction based on work domain analysis, task analysis, and workload estimation with eight workload components scored through task-analytic and projective methods. To demonstrate its utility, we applied the method to construct two SAM scenarios and predict the mental workload demand of operators in these scenarios as compared to two design basis accident scenarios. With statistical analysis, the DTAW method can predict the overall subjective workload rated by NPP operators, be used to identify high-load tasks, cluster tasks with similar workload patterns, and provide direct implications for improving SAM strategies and supporting systems. Practitioner summary: To predict mental workload in severe accident management (SAM) scenarios in nuclear power plants, we proposed an analytic method and applied it to estimate mental workload in two SAM scenarios and two design basis accident (DBA) scenarios. We found that the workload pattern in SAM scenarios is different from that in DBA scenarios.