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The use of muon scattering tomography for the non-invasive characterisationof nuclear waste is well established. We report here on the application of acombination of feature discriminators and multivariate analysis techniques tolocate and identify materials in nuclear waste drums. After successful trainingand optimisation of the algorithms they are then tested on a range of materialconfigurations to assess the system's performance and limitations. The systemis able to correctly identify uranium, iron and lead objects on a ~few\text{cm} scale. The system's sensitivity to small uranium objects is alsoestablished as $0.90^{+0.07}_{-0.12}$, with a false positive rate of$0.12^{+0.12}_{-0.07}$.

Material Identification in Nuclear Waste Drums using Muon Scattering Tomography and Multivariate Analysis