Material identification in nuclear waste drums using muon scattering tomography and multivariate analysis

Michael Weekes, Ahmad Alrheli, Dominic Barker, Daniel Kikola, Anna K Kopp, Mohammed Mhaidra, Patrick Stowell, Lee Thompson, Jaap J Velthuis

Research output: Contribution to journalArticle (Academic Journal)peer-review

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 languageEnglish
Article numberP05007
Number of pages27
JournalJournal of Instrumentation
Volume16
Issue number5
DOIs
Publication statusPublished - 6 May 2021

Bibliographical note

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© 2021 The Author(s).

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