Cryer, A., Kapellmann-Zafra, G., Abrego, S. orcid.org/0000-0001-9074-7113 et al. (2 more authors) (2019) Advantages of virtual reality in the teaching and training of radiation protection during interventions in harsh environments. In: Proceedings of 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 10-13 Sep 2019, Zaragoza, Spain. IEEE , pp. 784-789. ISBN 9781728103044
Abstract
Human interventions in radioactive environments have high stakes. They are often time-sensitive and radiation exposure must be minimised for the safety of personnel. Existing sites were not developed with remote decommissioning in mind, therefore human intervention remains the preferred approach for dexterous manual labour over robotic systems.For ageing sites, knowledge transfer after retirement is an increasingly relevant problem for maintenance and decommissioning tasks, where new workers lack the in-depth “on the ground” experience of the installation.Virtual Reality provides workers the agency to explore an accurate representation of the area, enabling them to gain experience without undue radiation exposure.This paper explores and discusses the teaching and training applications of a Virtual Reality environment with integrated radiation dose maps, and looks at where the system may be developed further.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > Department of Physics and Astronomy (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 Jun 2019 11:50 |
Last Modified: | 17 Oct 2020 00:38 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/ETFA.2019.8869433 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:147263 |