Multi-view tomography optimization for nuclear waste storage verification

There is currently a lack of long-term storage solutions for many types of radioactive material, ranging from spent nuclear fuel to lower-level waste streams. While permanent storage solutions develop, these materials are stored in sealed and shielded interim containers such as dry cask storage. Smaller waste streams can be cemented within containers, like steel drums. In both cases, containers are designed to significantly reduce radiation emissions. These containers create verification difficulties that typically require removal of the radioactive material from the containers, which can be an expensive and tedious process. Cosmic-ray muon scattering tomography has been explored as an in-situ verification technique that can be used to confirm the presence and location of radioactive material within heavily shielded storage containers. In the work presented here, experimental multi-orientation muon tomography results are presented imaging a steel drum filled with concrete and metal wedges of varying size and composition.  As muon rates are limited we are examining several data analysis approaches for improving imaging with low statistics.  We compared image reconstruction using both a traditional backprojection reconstruction technique and a new combined depth of field image reconstruction technique.. Both techniques were characterized by using several metrics to determine which technique could be used to create images that are the most useful in identifying the wedge compositions and locations, using increasingly limited amounts of data. Results show clear images for both approaches with sufficient data, and that a combined depth of field reconstruction technique resulted in more useful images using fewer target object orientations and more statistically limited data sets. The performance of the technique using limited data sets is especially important as the long measurement times have historically limited the attractiveness of cosmic-ray muon imaging techniques for verification applications. This characterization will be used to minimize data collection requirements in future cosmic-ray muon imaging measurements that will be performed on dry cask storage containers.