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Identification of Collectible Items in the Rancor Microworld Simulator Compared to Full-Scope Studies

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Advances in Safety Management and Human Performance (AHFE 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1204))

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Abstract

Most studies on collecting reliability data in human reliability analysis (HRA) have concentrated on research using full-scope simulators and actual operators. However, researchers have discovered challenges in collecting various items and amount of data needed to support HRA. As an opposite and complementing approach to a full-scope study, Idaho National Laboratory (INL) developed Rancor Microworld, a simplified simulator, to generate HRA data from student subjects. This paper aims to identify collectible items in Rancor Microworld versus those in full-scope simulators. In this paper, collectible items and their varying analysis levels in Rancor Microworld are identified in comparison with full-scope simulators. The appropriate method for treating the items is suggested through experiment directions for the future.

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Acknowledgements

This work of authorship was prepared as an account of work sponsored by Idaho National Laboratory, an agency of the U.S. Government. Neither the U.S. Government, nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe on privately-owned rights. Idaho National Laboratory is a multi-program laboratory operated by Battelle Energy Alliance, LLC, for the U.S. Department of Energy under Contract DE-AC07-05ID14517.

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Correspondence to Ronald L. Boring .

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Park, J., Ulrich, T.A., Boring, R.L., Lee, S., Kim, J. (2020). Identification of Collectible Items in the Rancor Microworld Simulator Compared to Full-Scope Studies. In: Arezes, P., Boring, R. (eds) Advances in Safety Management and Human Performance. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1204. Springer, Cham. https://doi.org/10.1007/978-3-030-50946-0_48

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  • DOI: https://doi.org/10.1007/978-3-030-50946-0_48

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-50945-3

  • Online ISBN: 978-3-030-50946-0

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