Abstract
In the digital main control rooms (MCRs) of nuclear power plants (NPPs), the role and responsibility of operators as well as their communication ways are changed by the digitization of the human-machine interface, which leads to some new team situation awareness (TSA) errors and different error distribution. In order to identify the interaction mechanism among a team during collecting information and consistently understanding the system/component status, an team interaction model is established by field observation, video analysis, operator interview and event report analysis. Furthermore, the model-based TSA error classification is developed and the influencing factors of TSA error are identified. On this basis, a number of human factor event reports are analyzed and combining with statistical analysis to identify the main TSA errors and influencing factors in digital NPPs. It provides theoretical support for the prevention and control of TSA errors.
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Acknowledgments
The financial support by the National Natural Science Foundation of China (No. 51674145, 71771084), Postdoctoral Science Foundation of China (No. 2016M600633), Natural Science Foundation of Hunan Province (No. 2017JJ2222), Humanities and Social Science Projects of Ministry of Education (No. 11YJC630207) and Social Science Projects of Hunan Province (No. 16YBA314) are gratefully acknowledged. We would like to express gratitude to the staff in a Chinese nuclear power plant (LingAo-II) for the interviews and investigations, which facilitate the research included in this paper.
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Li, P., Li, X., Dai, L., Zhang, L., Jin, X. (2019). Analysis of Team Situation Awareness Errors in Digital Nuclear Power Plants. In: Boring, R. (eds) Advances in Human Error, Reliability, Resilience, and Performance. AHFE 2018. Advances in Intelligent Systems and Computing, vol 778. Springer, Cham. https://doi.org/10.1007/978-3-319-94391-6_7
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DOI: https://doi.org/10.1007/978-3-319-94391-6_7
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