Representing context, cognition, and crew performance in a shutdown risk assessment

This paper presents a potentially practical treatment of dynamic operator-system interactions. The approach employs a dynamic event tree framework to explicitly address plant dynamics, system indications, crew-plant interactions, time available, crew cognition, errors of commission (mistakes), and multiple planning and diagnosis possibilities. The approach is applied in an analysis of a hypothesize medium break loss of coolant accident for a test reactor that occurs during plant shutdown. This transient was selected on the basis of: a significant cognitive component being present, high consequences being associated with operator actions, and the importance of event timing to scenario progression. The results presented show how quantitative risk predictions are affected by the treatment of dynamics, and demonstrate how non-proceduralized recovery actions and a number of performance shaping factors (e.g., crew experience, stress, and confidence) can be explicitly treated. Insights and lessons learned regarding the performance of a dynamic assessment are also presented.