Simulation of the Digital Image Processing Algorithm for the Coating Thickness Automatic Measurement of the TRISO-coated Fuel Particle

Woong-Ki Kim, Young-Woo Lee and Sung-Woong Ra
Volume: 1, No: 1, Page: 36 ~ 40, Year: 2005

Keywords: TRISO-coated Fuel Particle, Coating Thickness, X-ray CT, Computed Tomography, Filtered Backprojection, Automatic Measurement
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Abstract
TRISO (Tri-Isotropic)-coated fuel particle is widely applied due to its higher stability at high temperature and its efficient retention capability for fission products in the HTGR (high temperature gas-cooled reactor), one of the highly efficient Generation IV reactors. The typical balltype TRISO-coated fuel particle with a diameter of about 1 mm is composed of a nuclear fuel particle as a kernel and of outer coating layers. The coating layers consist of a buffer PyC, inner PyC, SiC, and outer PyC layer. In this study, a digital image processing algorithm is proposed to automatically measure the thickness of the coating layers. An FBP (filtered backprojection) algorithm was applied to reconstruct the CT image using virtual X-ray radiographic images for a simulated TRISO-coated fuel particle. The automatic measurement algorithm was developed to measure the coating thickness for the reconstructed image with noises. The boundary lines were automatically detected, then the coating thickness was circularly by the algorithm. The simulation result showed that the measurement error rate was less than 1.4%.

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Cite this article
IEEE Style
Woong-Ki Kim, Young-Woo Lee, and Sung-Woong Ra, "Simulation of the Digital Image Processing Algorithm for the Coating Thickness Automatic Measurement of the TRISO-coated Fuel Particle," Journal of Information Processing Systems, vol. 1, no. 1, pp. 36~40, 2005. DOI: .

ACM Style
Woong-Ki Kim, Young-Woo Lee, and Sung-Woong Ra, "Simulation of the Digital Image Processing Algorithm for the Coating Thickness Automatic Measurement of the TRISO-coated Fuel Particle," Journal of Information Processing Systems, 1, 1, (2005), 36~40. DOI: .