Optimization of operating conditions for Gamma Emission Tomography to improve partial-defect detection accuracy within PWR-type spent nuclear fuel
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The Spent Nuclear Fuel (SNF) contains a variety of nuclear material that can be diverted for military purposes and unauthorized proliferation. To ensure safety management and non-proliferation of SNF, an effective inspection method, such as Gamma Emission Tomography (GET) is necessary. In the previous study, the Yonsei Single-photon Emission Computed Tomography (YSECT) instrument was proposed and developed. To improve inspection accuracy in the central region containing the high-density SNF rod, the operating conditions, such as energy window and rotation interval, of the YSECT instrument are optimized in this study. The tomographic images were obtained under various operating conditions, and each condition was optimized by evaluating the quality of the tomographic image. Based on the results, the optimal energy window and rotation interval were determined to be 1274 keV region and 1-degree, respectively. The Signal-to-Noise Ratio (SNR) was improved 1.32-fold with optimized energy window compared to conventional energy window (6.98 of SNR for 662 keV region). Also, the streak artifact was reduced through the application of the optimized rotation interval. These optimized conditions improved inspection accuracy for partial-defect detection. In the future, the experimental study with the mock-up of SNF and pool will be conducted to validate the optimized operating conditions.
Abstract
The Spent Nuclear Fuel (SNF) contains a variety of nuclear material that can be diverted for military purposes and unauthorized proliferation. To ensure safety management and non-proliferation of SNF, an effective inspection method, such as Gamma Emission Tomography (GET) is necessary. In the previous study, the Yonsei Single-photon Emission Computed Tomography (YSECT) instrument was proposed and developed. To improve inspection accuracy in the central region containing the high-density SNF rod, the operating conditions, such as energy window and rotation interval, of the YSECT instrument are optimized in this study. The tomographic images were obtained under various operating conditions, and each condition was optimized by evaluating the quality of the tomographic image. Based on the results, the optimal energy window and rotation interval were determined to be 1274 keV region and 1-degree, respectively. The Signal-to-Noise Ratio (SNR) was improved 1.32-fold with optimized energy window compared to conventional energy window (6.98 of SNR for 662 keV region). Also, the streak artifact was reduced through the application of the optimized rotation interval. These optimized conditions improved inspection accuracy for partial-defect detection. In the future, the experimental study with the mock-up of SNF and pool will be conducted to validate the optimized operating conditions.