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Enhancing Workload Assessments for Validation Activities Associated with DBA and BDBA Scenarios

Aaron Derouin, Alice Salway

Nuclear Technology / Volume 201 / Number 2 / February 2018 / Pages 165-173

Technical Paper /

Received:September 20, 2017
Accepted:December 4, 2017
Published:January 19, 2018

After the Fukushima Daiichi accident, nuclear regulators around the world have required that power reactor licensees develop more extensive emergency mitigating responses and severe accident management provisions beyond the defense-in-depth measures for design-basis accidents previously in place. Workload assessments represent common validation techniques that are used to demonstrate that workers are able to perform tasks without unacceptable performance degradation. High workload is known to induce stress and fatigue and may severely diminish a worker’s capacity to perceive, recognize, and respond appropriately during emergency or unanticipated events, which may result in undesirable consequences. In estimating workload during emergency and severe accident scenarios, power reactor licensees tend to rely on subjective measures of workload, such as the NASA Task Load Index. Because of reported mismatches in the literature between subjective and physiologically derived estimates of workload, it is prudent to see what more can be done to improve the current state of practice in the context of emergency and severe accident conditions.

To improve confidence in workload estimates, it is advocated that the nuclear industry integrate physiologically based measures into current practices by making use of on-body or wearable physiological sensors. In this paper, an overview of three different approaches to the empirical measurement of workload is provided. The advantages of wearable physiological sensors are considered in the context of extreme environments and occupations, with tangible examples including heat stress and pupillometry. Suggestions for a consensus forum on workload are provided, and a research plan directed at improving the current practice of workload estimation is offered for consideration.

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