Abstract
The use of muon scattering tomography for the non-invasive characterisation of nuclear waste is well established. We report here on the application of a combination of feature discriminators and multivariate analysis techniques to locate and identify materials in nuclear waste drums. After successful training and optimisation of the algorithms they are then tested on a range of material configurations to assess the system’s performance and limitations. The system is able to correctly identify uranium, iron and lead objects on a few cm scale. The system’s sensitivity to small uranium objects is also established as 0•.90+0•.07-0•.12, with a false positive rate of 0•.12+0.•12-0•.07.
Original language | English |
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Article number | P05007 |
Number of pages | 27 |
Journal | Journal of Instrumentation |
Volume | 16 |
Issue number | 5 |
DOIs | |
Publication status | Published - 6 May 2021 |
Bibliographical note
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