Looking for situation awareness in nuclear power plant: uncovering information requirement and influencing factors through a goal-directed task analysis

Abstract Improving the level of situational awareness (SA) can effectively decrease the occurrence of human errors in nuclear power plants (NPPs). However, a significant gap exists in systematically identifying the specific information require to build SA and in quantifying the key influencing factors that influence information acquisition. To address this gap, this study proposed a mixed-methods framework to uncover SA requirements in the context of the water supply deaerator system (ADG). Firstly, this study employed Goal-Directed Task Analysis (GDTA) through interviews with experienced operators to establish a hierarchical model of SA information needs. This model was used to reveal the operator’s SA information requirement during the operation of ADG system, and the information was divided into three levels. Subsequently, the combination of the entropy weight and the coefficient of variation methods were used to determine the relative importance of SA influencing factors. This research contributes a detailed, operationalized SA information model for a specific NPPs system, and it provides an empirically-grounded basis for the targeted optimization of human-computer interface (HCI) design and operator training programs, ultimately enhancing NPPs safety.