Sparse-view muon computed tomography of an operating research reactor

Directional radiography maps and projected computed tomography images of the ZED-2 research reactor facility at Canadian Nuclear Laboratories (CNL) have been reconstructed using a sparse, asymmetric, and time-restricted set of muon flux measurements. The accuracy of the radiography maps in representing the dominant infrastructure surrounding each detector position confirms MuPIC’s radiography capabilities for the first time in the field. Computed tomography images are reconstructed using variants of a least squares conjugate gradient technique, the Simultaneous Iterative Reconstruction Technique (SIRT), and the L1NORM technique, of which SIRT variants are found to be the most stable overall. Despite significant artifacts due to the sparsity of the data set, the dominant features of the reactor well are visible in the computed tomography projections—including reactor well walls, the graphite calandria, and fuel structure—further providing a first field validation of CNL’s computed tomography algorithm.

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Publication Details

Journal
Journal of Applied Physics
Published
2025-10-23
DOI
https://doi.org/10.1063/5.0287881
Primary Topic
Particle Detector Development and Performance
Type
article
Field-Weighted Citation Impact
0.00

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article

Sparse-view muon computed tomography of an operating research reactor

G. Harrisson, A. Erlandson, K. Hartling, Alexander E. Dunn et al.
Journal of Applied Physics
Particle Detector Development and Performance
article

Sparse-view muon computed tomography of an operating research reactor

G. Harrisson, A. Erlandson, K. Hartling, Alexander E. Dunn, D. Pérez–Loureiro, Dominique Godin
article en

Abstract

Directional radiography maps and projected computed tomography images of the ZED-2 research reactor facility at Canadian Nuclear Laboratories (CNL) have been reconstructed using a sparse, asymmetric, and time-restricted set of muon flux measurements. The accuracy of the radiography maps in representing the dominant infrastructure surrounding each detector position confirms MuPIC’s radiography capabilities for the first time in the field. Computed tomography images are reconstructed using variants of a least squares conjugate gradient technique, the Simultaneous Iterative Reconstruction Technique (SIRT), and the L1NORM technique, of which SIRT variants are found to be the most stable overall. Despite significant artifacts due to the sparsity of the data set, the dominant features of the reactor well are visible in the computed tomography projections—including reactor well walls, the graphite calandria, and fuel structure—further providing a first field validation of CNL’s computed tomography algorithm.

Journal of Applied PhysicsVol. 138(16)
Canadian Nuclear Laboratories (CA)
Atomic Energy of Canada Limited, Canadian Nuclear Laboratories
Openalex Percentile: Top 86%
Particle Detector Development and Performance
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