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

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.