A quantitative assessment of Imaging High-Z and Medium-Z materials using Muon Scattering Tomography

Muon Scattering Tomography (MST) has been shown to be a powerful technique for the non-invasive imaging of high-shielded objects. We present here the application of the MST technique to investigate two types of nuclear waste packages, a small-steel drum and a large nuclear waste cask, namely, a CASTOR V/52. We have developed a quantitative method using the contrast-to-noise ratio (CNR) to evaluate the performance of an MST detector system in differentiating between high-, medium-, and low-Z materials inside nuclear waste packages with different shielding types. This study reveals that our MST detector system is able to differentiate between a (10 $\times$ 10 $\times$ 10 cm$^3$) uranium cube, embedded within a concrete matrix inside the small-steel drum, and regions of background signal in six hours of muon exposure time with a CNR value of 3.1$\pm$0.2. During our investigation of the highly-shielded cask, the reconstructed images of the cask contents indicated the ability of our system to detect irregular baskets, such as empty baskets, with a CNR value of 5.0$\pm$0.3 after 30 days of muon exposure. These studies were done using a Monte Carlo simulation tuned to the performance of resistive plate chambers (RPCs) based muon tomography system built by the University of Bristol, which had a reported position resolution of 350 micron. Here we also report the dependence of the performance on the position resolution. We argue that using a combination of RPC and drift chambers (DC) detectors with 700 micron and 4 mm position resolutions respectively is able to generate tomographic images of well-shielded materials in a few hours of muon exposure time. With these position resolutions, our system needs six hours of muon exposure time to produce a good quality image of a cube of uranium with side-length of 10 cm shielded by a concrete matrix with CNR value of 2.4$\pm$0.25.Comment: 27 pages, 19 figures (53 figures as sub-figures), 2 table