Investigation of Backscatter X-Ray Imaging Techniques for Uranium Dioxide Fuel Rods
Source abstract
Abstract
Radiography by selective detection (RSD), was investigated for its ability to determine the presence and types of defects in a UO2 fuel rod surrounded by zirconium cladding. Images created using a Monte Carlo model compared favorably with actual X-ray backscatter images from mock fuel rods. A fuel rod was modeled as a rectangular parallelepiped with zirconium cladding, and pencil beam X-ray sources of 160 kVp (79 keV avg) and 480 kVp (218 keV avg) were generated using the Monte Carlo N-Particle Transport Code (MCNP) to attempt to image void and palladium (Pd) defects in the interior and on the surface of the fuel pellet. It was found that the 160 kVp spectrum was unable to detect the presence of interior defects, whereas the 480 kVp spectrum detected them with both the standard and the RSD backscatter methods, though the RSD method was very inefficient. It was also found that both energy spectra were able to detect void and Pd defects on the surface using both imaging methods. Additionally, two mock fuel rods were imaged using a backscatter X-ray imaging system, one consisting of hafnium pellets in a Zircaloy-4 cladding and the other consisting of steel pellets in a Zircalloy-4 cladding which was then encased in a steel cladding (a double encapsulation configuration employed in irradiation and experiments). It was found that the system was capable of detecting individual HfO2 pellets in a Zircaloy-4 cladding and may be capable of detecting individual steel pellets in the double-encapsulated sample. It is expected that the system would also be capable of detecting individual UO2 pellets in a Zircaloy-4 cladding, though no UO2 fuel rod was available for imaging.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Nuclear Materials and Properties · Nuclear Physics and Applications · Advanced X-ray and CT Imaging
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (12)
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