Characteristics of Muon Computed Tomography of Used Fuel Casks Using Algebraic Reconstruction

Conference · Sun Oct 01 04:00:00 EDT 2017

DOI:https://doi.org/10.1109/NSSMIC.2017.8532834· OSTI ID:1486925

Liu, Zhengzhi ^[1]; Chatzidakis, Stylianos ^[2]; Liao, Can ^[3]; Yang, Haori ^[3]; Hayward, Jason ^[4]

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1. University of Tennessee, Knoxville (UTK)
2. ORNL
3. Oregon State University, Corvallis
4. The University of Tennessee, Knoxville

Cosmic raymuons passing through matter lose energy from inelastic collisions with electrons and are deflected from nuclei due to multiple Coulomb scattering (MCS). The recent developments in position sensitive muon detectors that can measure incoming and outgoing trajectories of individual muons indicate that MCS could be an excellent candidate for spent nuclear fuel imaging. The main purpose of this paper is to evaluate tomographic scanning of spent nuclear fuel stored within vertical and horizontal dry storage casks. A quantitative analysis of the characteristics of images obtained with filtered back projection (FBP) and algebraic reconstruction techniques (ART) are presented herein, as such a comparison has not been carried out in the past. FBP is a fast tool to determine object boundaries. ART can include muon path models and prior knowledge that can improve resolution and reduce measurement time. The results demonstrate that missing fuel assemblies can be identified with more than 5 projections and that use of muon momentum significantly increases image resolution. It is expected that MCS can be used to successfully reconstruct the dry cask contents and allow identification of all described scenarios in hours. It is also expected that when total variation minimization and a non-local mean filter are applied, ART may yield much better image quality than FBP.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1486925
• Country of Publication: United States
• Language: English