An Evaluation of Task Network Modeling for Use in Simulating Situation Awareness
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To achieve its mission of regulating the commercial nuclear power industry, the U.S. Nuclear Regulatory Commission (NRC) periodically commissions research studies to investigate potential safety issues. These include operational studies involving operator and crew performance. A main objective of these research projects is to provide information and knowledge that can be used in the development of regulation, regulatory guidance, and improved methods for collecting and analyzing personnel performance data to assist in regulatory inspections, investigations, and evaluations. The Halden Man-Machine Laboratory (HAMMLAB) in Halden, Norway recently conducted a study using professional nuclear power plant operators to investigate the effect of different alarm systems and display types on operator performance. Dependent variables in the Halden Alarm study included a mix of plant performance measures, operator task performance measures, operator cognitive processes, and subjective evaluations. Operator cognitive process measures included measures of Situation Awareness (SA) using an adaptation of the Situation Awareness Global Assessment Technique (SAGAT). Through the NRC, Micro Analysis and Design was allowed access to the work being performed at Halden in order to evaluate the use of Task Network Modeling (TNM) to simulate human behavior in a nuclear power plant. The alarm system, a turbine trip scenario and data from Halden were used as the basis for the model developed in this project. For part of this project, we also developed a model to simulate SA that was representative of how it was measured in the Halden Alarm study. This model was then integrated into our model that represented a disturbance scenario at a nuclear power plant. Data generated by the task network simulation was then compared to data collected from the nuclear power plant simulator at the HAMMLAB. Statistical tests showed no significant differences between the SA scores of actual operators and those SA scores predicted by the model. Thus, results indicate that a simple representation of SA within TNM can be used to accurately predict situation awareness given this measuring technique. Implications of this finding and recommendations for improving the model are discussed.