Full Characterization of a Mock Nuclear Waste Barrel with Muon Tomography using Micromegas Detectors
Abstract
Muon tomography based on multiple Coulomb scattering provides a non-destructive method to image dense and shielded objects using naturally occurring cosmic-ray muons. In the context of nuclear waste characterization, we present the experimental imaging of a 205-L mock waste barrel using a dedicated 1m2 muon scattering tomography test bench. The system employs multiplexed resistive Micromegas detectors, enabling stable and high-precision muon tracking. Monte Carlo simulations are first used to characterize material-dependent scattering signatures and to quantitatively assess identification performance using statistical reconstruction. These simulation-based results are then used to define objective discrimination thresholds, which are subsequently applied to experimental data for the localization and identification of internal anomalies. Using an Angle Statistics Reconstruction algorithm, we achieve a spatial resolution of 10 mm and demonstrate the three-dimensional imaging of an internal structure containing both low- and high-radiation length materials. Material discrimination performance is evaluated using receiver operating characteristic analysis, yielding high identification efficiency for dense metallic inclusions such as lead and steel (AUC ≥ 0.96) within acquisition times of a few days, while cavities also exhibit strong contrast. Experimental results show good agreement with detailed Monte Carlo simulations. By establishing a continuous workflow from simulation-based performance characterization to practical application on measured data, this work provides a quantitatively validated framework for muon scattering tomography applied to complex, shielded objects.
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BibTeX
@misc{bajou2026full,
title = {{Full Characterization of a Mock Nuclear Waste Barrel with Muon Tomography using Micromegas Detectors}},
author = {Raphaël Bajou and David Attié and Héctor Gómez and Irakli Mandjavidze and Philippe Mas},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2606.02557},
eprint = {2606.02557},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2606.02557},
}
RIS
TY - UNPB
TI - Full Characterization of a Mock Nuclear Waste Barrel with Muon Tomography using Micromegas Detectors
AU - Raphaël Bajou
AU - David Attié
AU - Héctor Gómez
AU - Irakli Mandjavidze
AU - Philippe Mas
PY - 2026
DA - 2026/10/15
PB - arXiv
DO - 10.48550/arxiv.2606.02557
UR - https://arxiv.org/abs/2606.02557
AB - Muon tomography based on multiple Coulomb scattering provides a non-destructive method to image dense and shielded objects using naturally occurring cosmic-ray muons. In the context of nuclear waste characterization, we present the experimental imaging of a 205-L mock waste barrel using a dedicated 1m^2 muon scattering tomography test bench. The system employs multiplexed resistive Micromegas detectors, enabling stable and high-precision muon tracking. Monte Carlo simulations are first used to characterize material-dependent scattering signatures and to quantitatively assess identification performance using statistical reconstruction. These simulation-based results are then used to define objective discrimination thresholds, which are subsequently applied to experimental data for the localization and identification of internal anomalies. Using an Angle Statistics Reconstruction algorithm, we achieve a spatial resolution of 10 mm and demonstrate the three-dimensional imaging of an internal structure containing both low- and high-radiation length materials. Material discrimination performance is evaluated using receiver operating characteristic analysis, yielding high identification efficiency for dense metallic inclusions such as lead and steel (AUC ≥ 0.96) within acquisition times of a few days, while cavities also exhibit strong contrast. Experimental results show good agreement with detailed Monte Carlo simulations. By establishing a continuous workflow from simulation-based performance characterization to practical application on measured data, this work provides a quantitatively validated framework for muon scattering tomography applied to complex, shielded objects.
ER -