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Comparison of prediction models for Cherenkov light emissions from nuclear fuel assemblies
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.ORCID iD: 0000-0001-8207-3462
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics.ORCID iD: 0000-0002-3136-5665
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

The Digital Cherenkov Viewing Device (DCVD) is a tool used by nuclear safeguards inspectors to verify irradiated nuclear fuel assemblies in wet storage based on the Cherenkov light produced by the assembly. Verification that no rods have been substituted in the fuel, so-called partial-defect verification, is made by comparing the intensity measured with a DCVD with a predicted intensity, based on operator fuel declaration.

The prediction model currently used by inspectors is based on simulations of Cherenkov light production in a BWR 8x8 geometry. This work investigates prediction models based on simulated Cherenkov light production in a BWR 8x8 and a PWR 17x17 assembly, as well as a simplified model based on a single rod in water. Cherenkov light caused by both fission product gamma and beta decays were considered.

The simulations reveal that there are systematic differences between the models, most noticeably with respect to the fuel assembly cooling time. Consequently, a prediction model that is based on another fuel assembly configuration than the fuel type being measured, will result in systematic over or underestimation of short-cooled fuel as opposed to long-cooled fuel. While a simplified model may be accurate enough for fuel assemblies with fairly homogeneous cooling times, the prediction models may differ by up to 18  % for more heterogeneous fuel. Accordingly, these investigations indicate that the currently used model may need to be exchanged with a set of more detailed, fuel-type specific models, in order minimize the model dependant systematic deviations.

National Category
Subatomic Physics
Research subject
Physics with specialization in Applied Nuclear Physics
Identifiers
URN: urn:nbn:se:uu:diva-309739OAI: oai:DiVA.org:uu-309739DiVA: diva2:1052812
Funder
Swedish Radiation Safety Authority, SSM2012-2750Swedish National Infrastructure for Computing (SNIC), p2007011
Available from: 2016-12-07 Created: 2016-12-07 Last updated: 2016-12-09
In thesis
1. Studies of Cherenkov light production in irradiated nuclear fuel assemblies
Open this publication in new window or tab >>Studies of Cherenkov light production in irradiated nuclear fuel assemblies
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The Digital Cherenkov Viewing Device (DCVD) is an instrument used by authority inspectors to assess irradiated nuclear fuel assemblies in wet storage for the purpose of nuclear safeguards. Originally developed to verify the presence of fuel assemblies with long cooling times and low burnup, the DCVD accuracy is sufficient for partial defect verification, where one verifies that part of an assembly has not been diverted. Much of the recent research regarding the DCVD has been focused on improving its partial defect detection capabilities.

The partial-defect analysis procedure currently used relies on comparisons between a predicted Cherenkov light intensity and the intensity measured with the DCVD. Enhanced prediction capabilities may thus lead to enhanced verification capabilities. Since the currently used prediction model is based on rudimentary correlations between the Cherenkov light intensity and the burnup and cooling time of the fuel assembly, there are reasons to develop alternative models taking more details into account to more accurately predict the Cherenkov light intensity.

This work aims at increasing our understanding of the physical processes leading to the Cherenkov light production in irradiated nuclear fuel assemblies in water. This has been investigated through simulations, which in the future are planned to be complemented with measurements.

The simulations performed reveal that the Cherenkov light production depends on fuel rod dimensions, source distribution in the rod and initial decay energy in a complex way, and that all these factors should be modelled to accurately predict the light intensity. The simulations also reveal that for long-cooled fuel, Y-90 beta-decays may contribute noticeably to the Cherenkov light intensity, a contribution which has not been considered before.

A prediction model has been developed in this work taking fuel irradiation history, fuel geometry and Y-90 beta-decay into account. These predictions are more detailed than the predictions based on the currently used prediction model. The predictions with the new model can be done quickly enough that the method can be used in the field. The new model has been used during one verification campaign, and showed superior performance to the currently used prediction model. Using the currently used model for this verification, the difference between measured and predicted intensity had a standard deviation of 15.4% of the measured value, and using the new model this was reduced to 8.4%.

Place, publisher, year, edition, pages
Uppsala universitet, 2016. 36 p.
Keyword
DCVD, Cherenkov light, Geant4, Nuclear fuel, Nuclear safeguards
National Category
Subatomic Physics
Research subject
Physics with specialization in Applied Nuclear Physics
Identifiers
urn:nbn:se:uu:diva-307952 (URN)
Presentation
2016-12-15, 2002, Ångströmlaboratoriet, Uppsala, 10:15 (English)
Opponent
Supervisors
Funder
Swedish Radiation Safety Authority, SSM2012-2750Swedish National Infrastructure for Computing (SNIC), p2007011
Available from: 2016-12-08 Created: 2016-11-23 Last updated: 2016-12-22Bibliographically approved

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