Non-destructive characterization of advanced nuclear fuel materials using neutron imaging

Yuxuan Zhang; Kristian G. Myhre; Hassina Z. Bilheux; Jared A. Johnson; Jean C. Bilheux; Chad M. Parish; Andrew J. Miskowiec; Rodney D. Hunt; Jiao Y.Y. Lin

doi:10.1016/j.nme.2023.101434

Non-destructive characterization of advanced nuclear fuel materials using neutron imaging

Yuxuan Zhang, Kristian G. Myhre, Hassina Z. Bilheux, Jared A. Johnson, Jean C. Bilheux, Chad M. Parish, Andrew J. Miskowiec, Rodney D. Hunt, Jiao Y.Y. Lin

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4 Scopus citations

Abstract

Attenuation-based neutron computed tomography (CT) has been used to non-destructively characterize the uncoated tristructural-isotropic (TRISO) nuclear fuel kernels in this work. Particularly, the effect of two different types of carbon blacks (Raven 3500 and Mogul L) on the internal gelation process of UO₃-C kernels has been investigated. With 3D reconstructed kernel volumes and digital imaging processing techniques, heterogenous density distributions are mapped in both types of kernels. It is found that the kernels produced with Mogul L are ∼ 20 % denser and ∼ 10 % larger (in equivalent diameter) than the Raven 3500 kernels. Furthermore, less neutron attenuating regions, which are most likely to be carbon agglomerates as scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) results show, are observed in the Mogul L kernels. The size distribution of such carbon agglomerates (ranges from 50 μm to 850 μm with a peak at ∼ 200 μm) has been determined by analyzing the CT data. Furthermore, multiple metrics, including equivalent diameter, surface area, volume, sphericity, have been extracted to evaluate the fuel kernels. This work demonstrates that neutron imaging is an excellent, nondestructive tool to efficiently characterize, understand, and explore fuel materials for nuclear material research and development.

Original language	English
Article number	101434
Journal	Nuclear Materials and Energy
Volume	35
DOIs	https://doi.org/10.1016/j.nme.2023.101434
State	Published - Jun 2023

Funding

This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( https://energy.gov/downloads/doe-public-access-plan ). Research sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U. S. Department of Energy. This research used resources at the High Flux Isotope Reactor, a DOE Office of Science User Facility operated by the Oak Ridge National Laboratory.

Funders	Funder number
U.S. Department of Energy
Office of Science
Oak Ridge National Laboratory

Keywords

Neutron imaging
Non-destructive characterization
Nuclear fuel
TRISO kernel

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10.1016/j.nme.2023.101434

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title = "Non-destructive characterization of advanced nuclear fuel materials using neutron imaging",

abstract = "Attenuation-based neutron computed tomography (CT) has been used to non-destructively characterize the uncoated tristructural-isotropic (TRISO) nuclear fuel kernels in this work. Particularly, the effect of two different types of carbon blacks (Raven 3500 and Mogul L) on the internal gelation process of UO3-C kernels has been investigated. With 3D reconstructed kernel volumes and digital imaging processing techniques, heterogenous density distributions are mapped in both types of kernels. It is found that the kernels produced with Mogul L are ∼ 20 % denser and ∼ 10 % larger (in equivalent diameter) than the Raven 3500 kernels. Furthermore, less neutron attenuating regions, which are most likely to be carbon agglomerates as scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) results show, are observed in the Mogul L kernels. The size distribution of such carbon agglomerates (ranges from 50 μm to 850 μm with a peak at ∼ 200 μm) has been determined by analyzing the CT data. Furthermore, multiple metrics, including equivalent diameter, surface area, volume, sphericity, have been extracted to evaluate the fuel kernels. This work demonstrates that neutron imaging is an excellent, nondestructive tool to efficiently characterize, understand, and explore fuel materials for nuclear material research and development.",

keywords = "Neutron imaging, Non-destructive characterization, Nuclear fuel, TRISO kernel",

author = "Yuxuan Zhang and Myhre, {Kristian G.} and Bilheux, {Hassina Z.} and Johnson, {Jared A.} and Bilheux, {Jean C.} and Parish, {Chad M.} and Miskowiec, {Andrew J.} and Hunt, {Rodney D.} and Lin, {Jiao Y.Y.}",

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year = "2023",

month = jun,

doi = "10.1016/j.nme.2023.101434",

language = "English",

volume = "35",

journal = "Nuclear Materials and Energy",

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AU - Zhang, Yuxuan

AU - Myhre, Kristian G.

AU - Bilheux, Hassina Z.

AU - Johnson, Jared A.

AU - Bilheux, Jean C.

AU - Parish, Chad M.

AU - Miskowiec, Andrew J.

AU - Hunt, Rodney D.

AU - Lin, Jiao Y.Y.

PY - 2023/6

Y1 - 2023/6

N2 - Attenuation-based neutron computed tomography (CT) has been used to non-destructively characterize the uncoated tristructural-isotropic (TRISO) nuclear fuel kernels in this work. Particularly, the effect of two different types of carbon blacks (Raven 3500 and Mogul L) on the internal gelation process of UO3-C kernels has been investigated. With 3D reconstructed kernel volumes and digital imaging processing techniques, heterogenous density distributions are mapped in both types of kernels. It is found that the kernels produced with Mogul L are ∼ 20 % denser and ∼ 10 % larger (in equivalent diameter) than the Raven 3500 kernels. Furthermore, less neutron attenuating regions, which are most likely to be carbon agglomerates as scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) results show, are observed in the Mogul L kernels. The size distribution of such carbon agglomerates (ranges from 50 μm to 850 μm with a peak at ∼ 200 μm) has been determined by analyzing the CT data. Furthermore, multiple metrics, including equivalent diameter, surface area, volume, sphericity, have been extracted to evaluate the fuel kernels. This work demonstrates that neutron imaging is an excellent, nondestructive tool to efficiently characterize, understand, and explore fuel materials for nuclear material research and development.

AB - Attenuation-based neutron computed tomography (CT) has been used to non-destructively characterize the uncoated tristructural-isotropic (TRISO) nuclear fuel kernels in this work. Particularly, the effect of two different types of carbon blacks (Raven 3500 and Mogul L) on the internal gelation process of UO3-C kernels has been investigated. With 3D reconstructed kernel volumes and digital imaging processing techniques, heterogenous density distributions are mapped in both types of kernels. It is found that the kernels produced with Mogul L are ∼ 20 % denser and ∼ 10 % larger (in equivalent diameter) than the Raven 3500 kernels. Furthermore, less neutron attenuating regions, which are most likely to be carbon agglomerates as scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) results show, are observed in the Mogul L kernels. The size distribution of such carbon agglomerates (ranges from 50 μm to 850 μm with a peak at ∼ 200 μm) has been determined by analyzing the CT data. Furthermore, multiple metrics, including equivalent diameter, surface area, volume, sphericity, have been extracted to evaluate the fuel kernels. This work demonstrates that neutron imaging is an excellent, nondestructive tool to efficiently characterize, understand, and explore fuel materials for nuclear material research and development.

KW - Neutron imaging

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KW - TRISO kernel

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Non-destructive characterization of advanced nuclear fuel materials using neutron imaging

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