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.
In an effort to develop computer-generated forces (CGFs) that behave more realistically, Micro Analysis and Design, in conjunction with the U.S. Army Research Institute, developed algorithms and data structures that allow human performance models to be affected by key features of training. As part of this effort, the effects of other performance shaping factors (PSFs) on human performance were also examined. An abundance of empirical data has been cdllected on the independent effects of several PSFs on human performance. However, very little empirical data has been collected on combined effects of multiple PSFs. Thus, developing models that accurately represent these effects is extremely difficult. Two different techniques were identified that represent the combined effects of PSFs. This report describes a study that examined performance in a simple movement-to-contact scenario within a human performance model. The effects of both heat and fatigue on performance were tested under varying levels using both of these techniques. Two important results were found. First, both techniques produced results with high face validity. Soldier performance was best when both PSFs were at low levels and worse when they were both at high levels. Low levels of one PSF combined with high levels of the other PSF produced results inbetween. Second. almost all of the results oroduced by the two techniques were nof significantly different from each other.
The use of Computer Generated Forces (CGF) in simulations ranges from small human performance models to large scale Advanced Distributed Simulations (ADS). CGF have been used to assess human performance aspects of system designs and to augment man-in-the-loop simulators with friendly and opposing forces to make simulated battlefield training exercises realistic. However, the current human performance models and ADS available to system designers, trainers, and resource allocation analysts do not include the effects of training on the performance of the CGF. For the most part, the CGF entities in these simulations reflect a constant level of training. This paper discusses a methodology for modeling the effects of training in CGF and other human performance models
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