5-9 September 2016
Prague Congress Centre
Europe/Prague timezone

P4.199 Minimising Operator Neutron Dose During JET Shutdown using Virtual Reality

8 Sep 2016, 14:20
1h 40m
Foyer 2A (2nd floor), 3A (3rd floor) (Prague Congress Centre)

Foyer 2A (2nd floor), 3A (3rd floor)

Prague Congress Centre

5. května 65, Prague, Czech Republic
Board: 199
Poster J. Power Plants Safety and Environment, Socio-Economics and Technology Transfer P4 Poster session

Speaker

Jonathan Naish (Technology)

Description

Effective data visualisation is a key part of the scientific process with complex geometric datasets.  It is the bridge between the quantitative content of the data and human intuition.  Immersion in virtual reality (VR) provides benefits beyond the traditional “desktop” visualization tools and it leads to a demonstrably better perception of dataspace geometry, more intuitive data understanding, and a better retention of the perceived relationships in the data. VR has a great potential for fusion research and in the analysis of its complex physics-based datasets.  The work presented in this paper is one of the applications that have been implemented at UKAEA which combines shutdown dose calculations with a virtual reality model of the Joint European Tokamak (JET). The shutdown dose calculations were performed for various time steps during the JET DTE2 campaign using the UKAEA code MCR2S which links MCNP and FISPACT-II using the rigorous two step method. The 3 Dimensional dose and activation data created by MCR2S is integrated into the game engine Unity using C# routines. A virtual reality model has been created from JET CAD data combined with the 3-dimensional radiation and activation data to create of virtual model of the radiological environment after the DTE2 campaign. This model enables more precise planning of operational procedures by having the operator/planner walk around the virtual environment using a virtual reality headset such as the Oculus rift or the HTC vive. In this virtual environment there is a visual representation of the received biological dose. This can be used to help reduce the doses received by workers by allowing multiple routes to an area of interest to be tried and thus avoiding areas of high dose. This model also provides safe virtual operational training and rehearsal, visualization of radiation dose rates, and estimation of doses received by workers.

Co-author

Jonathan Naish (Technology, UKAEA, Oxfordshire, United Kingdom)

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