A prototype multi-instrument quality assurance system for responsive nuclear fuel manufacturing

A. Parker; M. Bandala; P. Chard; N. Cockbain; D. Dunphy; D. Eaves; D. Hutchinson; X. Ma; S. Marshall; P. Murray; P. Stirzaker; J. Taylor; J. Zabalza; M. Joyce

doi:10.1109/nss/mic/rtsd57108.2024.10656207

A prototype multi-instrument quality assurance system for responsive nuclear fuel manufacturing

A. Parker
, M. Bandala
, P. Chard
, N. Cockbain
, D. Dunphy
, D. Eaves
, D. Hutchinson
, X. Ma
, S. Marshall
, P. Murray
, P. Stirzaker
, J. Taylor
, J. Zabalza
, M. Joyce

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

Abstract

A prototype apparatus for in line quality control assessment of sintered uranium dioxide fuel pellets has been demonstrated. In this work we combine γ-ray spectrometer, laser profilometer, and hyperspectral and RGB cameras in a single system. The combination of instruments provides analytical data on uranium enrichment, pellet geometry, physical defects, and potential chemical contamination. The images and spectra are analyzed using a convolutional neural network and an automated quality control decision taken. The prototype was deployed at the National Nuclear Laboratory, Preston site to analyze Advanced Gas Cooled sintered UO 2 pellets. Results from the pellet analysis are added automatically to a pellet data library for future nuclear security and safeguards auditing and model-training to improve quality assurance decision-making.

Original language	English
Title of host publication	2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD)
Place of Publication	Piscataway, NJ
Publisher	IEEE
Number of pages	2
ISBN (Electronic)	9798350388152
ISBN (Print)	9798350388169
DOIs	https://doi.org/10.1109/nss/mic/rtsd57108.2024.10656207
Publication status	Published - 25 Sept 2024
Event	2024 IEEE Nuclear Science Symposium, Medical Imaging Conference, and Room-Temperature Semiconductor Detectors Symposium - Tampa, United States Duration: 26 Oct 2024 → 2 Nov 2024

Publication series

Name	IEEE Symposium on Nuclear Science (NSS/MIC)
ISSN (Print)	1082-3654
ISSN (Electronic)	2577-0829

Conference

Conference	2024 IEEE Nuclear Science Symposium, Medical Imaging Conference, and Room-Temperature Semiconductor Detectors Symposium
Abbreviated title	2024 NSS MIC RTSD
Country/Territory	United States
City	Tampa
Period	26/10/24 → 2/11/24

Keywords

convolutional neural network
hyperspectral
combination of instruments
physical defects
uranium enrichment
nuclear security

Access to Document

10.1109/nss/mic/rtsd57108.2024.10656207

Autonomous Inspection for Responsive and Sustainable Nuclear Fuel Manufacture (Responsive Manufacturing) (AIRS-NFM)
Murray, P. (Principal Investigator), Marshall, S. (Co-investigator) & Zabalza, J. (Co-investigator)
EPSRC (Engineering and Physical Sciences Research Council)
1/09/21 → 5/10/25
Project: Research

Cite this

Parker, A., Bandala, M., Chard, P., Cockbain, N., Dunphy, D., Eaves, D., Hutchinson, D., Ma, X., Marshall, S., Murray, P., Stirzaker, P., Taylor, J., Zabalza, J., & Joyce, M. (2024). A prototype multi-instrument quality assurance system for responsive nuclear fuel manufacturing. In 2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD) (IEEE Symposium on Nuclear Science (NSS/MIC)). IEEE. https://doi.org/10.1109/nss/mic/rtsd57108.2024.10656207

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title = "A prototype multi-instrument quality assurance system for responsive nuclear fuel manufacturing",

abstract = "A prototype apparatus for in line quality control assessment of sintered uranium dioxide fuel pellets has been demonstrated. In this work we combine γ-ray spectrometer, laser profilometer, and hyperspectral and RGB cameras in a single system. The combination of instruments provides analytical data on uranium enrichment, pellet geometry, physical defects, and potential chemical contamination. The images and spectra are analyzed using a convolutional neural network and an automated quality control decision taken. The prototype was deployed at the National Nuclear Laboratory, Preston site to analyze Advanced Gas Cooled sintered UO 2 pellets. Results from the pellet analysis are added automatically to a pellet data library for future nuclear security and safeguards auditing and model-training to improve quality assurance decision-making.",

keywords = "convolutional neural network, hyperspectral, combination of instruments, physical defects, uranium enrichment, nuclear security",

author = "A. Parker and M. Bandala and P. Chard and N. Cockbain and D. Dunphy and D. Eaves and D. Hutchinson and X. Ma and S. Marshall and P. Murray and P. Stirzaker and J. Taylor and J. Zabalza and M. Joyce",

year = "2024",

month = sep,

day = "25",

doi = "10.1109/nss/mic/rtsd57108.2024.10656207",

language = "English",

isbn = "9798350388169",

series = "IEEE Symposium on Nuclear Science (NSS/MIC)",

publisher = "IEEE",

booktitle = "2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD)",

note = "2024 IEEE Nuclear Science Symposium, Medical Imaging Conference, and Room-Temperature Semiconductor Detectors Symposium, 2024 NSS MIC RTSD ; Conference date: 26-10-2024 Through 02-11-2024",

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Parker, A, Bandala, M, Chard, P, Cockbain, N, Dunphy, D, Eaves, D, Hutchinson, D, Ma, X, Marshall, S, Murray, P, Stirzaker, P, Taylor, J, Zabalza, J & Joyce, M 2024, A prototype multi-instrument quality assurance system for responsive nuclear fuel manufacturing. in 2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD). IEEE Symposium on Nuclear Science (NSS/MIC), IEEE, Piscataway, NJ, 2024 IEEE Nuclear Science Symposium, Medical Imaging Conference, and Room-Temperature Semiconductor Detectors Symposium, Tampa, Florida, United States, 26/10/24. https://doi.org/10.1109/nss/mic/rtsd57108.2024.10656207

A prototype multi-instrument quality assurance system for responsive nuclear fuel manufacturing. / Parker, A.; Bandala, M.; Chard, P. et al.
2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD). Piscataway, NJ: IEEE, 2024. (IEEE Symposium on Nuclear Science (NSS/MIC)).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

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AU - Parker, A.

AU - Bandala, M.

AU - Chard, P.

AU - Cockbain, N.

AU - Dunphy, D.

AU - Eaves, D.

AU - Hutchinson, D.

AU - Ma, X.

AU - Marshall, S.

AU - Murray, P.

AU - Stirzaker, P.

AU - Taylor, J.

AU - Zabalza, J.

AU - Joyce, M.

PY - 2024/9/25

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N2 - A prototype apparatus for in line quality control assessment of sintered uranium dioxide fuel pellets has been demonstrated. In this work we combine γ-ray spectrometer, laser profilometer, and hyperspectral and RGB cameras in a single system. The combination of instruments provides analytical data on uranium enrichment, pellet geometry, physical defects, and potential chemical contamination. The images and spectra are analyzed using a convolutional neural network and an automated quality control decision taken. The prototype was deployed at the National Nuclear Laboratory, Preston site to analyze Advanced Gas Cooled sintered UO 2 pellets. Results from the pellet analysis are added automatically to a pellet data library for future nuclear security and safeguards auditing and model-training to improve quality assurance decision-making.

AB - A prototype apparatus for in line quality control assessment of sintered uranium dioxide fuel pellets has been demonstrated. In this work we combine γ-ray spectrometer, laser profilometer, and hyperspectral and RGB cameras in a single system. The combination of instruments provides analytical data on uranium enrichment, pellet geometry, physical defects, and potential chemical contamination. The images and spectra are analyzed using a convolutional neural network and an automated quality control decision taken. The prototype was deployed at the National Nuclear Laboratory, Preston site to analyze Advanced Gas Cooled sintered UO 2 pellets. Results from the pellet analysis are added automatically to a pellet data library for future nuclear security and safeguards auditing and model-training to improve quality assurance decision-making.

KW - convolutional neural network

KW - hyperspectral

KW - combination of instruments

KW - physical defects

KW - uranium enrichment

KW - nuclear security

U2 - 10.1109/nss/mic/rtsd57108.2024.10656207

DO - 10.1109/nss/mic/rtsd57108.2024.10656207

M3 - Conference contribution book

SN - 9798350388169

T3 - IEEE Symposium on Nuclear Science (NSS/MIC)

BT - 2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD)

PB - IEEE

CY - Piscataway, NJ

T2 - 2024 IEEE Nuclear Science Symposium, Medical Imaging Conference, and Room-Temperature Semiconductor Detectors Symposium

Y2 - 26 October 2024 through 2 November 2024

ER -

Parker A, Bandala M, Chard P, Cockbain N, Dunphy D, Eaves D et al. A prototype multi-instrument quality assurance system for responsive nuclear fuel manufacturing. In 2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD). Piscataway, NJ: IEEE. 2024. (IEEE Symposium on Nuclear Science (NSS/MIC)). doi: 10.1109/nss/mic/rtsd57108.2024.10656207

A prototype multi-instrument quality assurance system for responsive nuclear fuel manufacturing

Abstract

Publication series

Conference

Keywords

Access to Document

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Projects

Autonomous Inspection for Responsive and Sustainable Nuclear Fuel Manufacture (Responsive Manufacturing) (AIRS-NFM)

Cite this