This research demonstrates the efficacy of muon tomography for monitoring nuclear waste, highlighting the importance of imaging algorithms and particle detectors.
Over the past few decades, research in a form of Non-Destructive Evaluation (NDE), muon tomography, also known as muography, has gained significant attention. In this study, GEANT4 simulations have been used to evaluate the performance of various position-sensitive particle detectors for muography. Detectors with position resolutions ranging from 0 µm (ideal one) to 1000 µm were tested, focusing on developing an imaging algorithm to monitor nuclear waste drums. Additionally, the shape of materials inside nuclear waste drums was analyzed using a Pattern Recognition Method (PRM). The study highlights the importance of storage geometry, track reconstruction and machine-learning algorithms.
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Mukherjee et al. (2025) studied this question.
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