Study on operator's SA reliability in digital NPPs. Part 2: Data-driven causality model of SA

Abstract

This paper tries to overcome shortcomings of the traditional assessment method of situation awareness (SA) reliability and build more robust causality model of SA. Firstly, the organization-oriented analysis framework or method of SA error was used to analyze human factor events in nuclear power plants (NPPs) and the data of 132 samples were obtained. Then, the correlation analysis method is used to identify the correlation relationships between factors influencing SA and next factor analysis method is used to identify the scenes triggering SA error. It includes: operator’s mental level, operator's work attitude, stress level and system situation display level. Finally, based on the study of the results highlighted above, a data-driven SA causality model is established. These results shows that, the data-based SA causality model can identify the scenes triggering SA error, and it is very useful to improve the accuracy of quantitative assessment of SA reliability because of considering the causality relationships of performance shaping factors (PSFs).