乏燃料组件被动伽玛发射断层扫描(PGET)的燃料棒分类

Riina Virta, Rasmus Backholm, T. Bubba, T. Helin, M. Moring, S. Siltanen, P. Dendooven, Honkamaa Tapani
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引用次数: 1

摘要

保障乏核燃料在地质处置库中的处置需要一个有效、高效、可靠和强大的非破坏性分析(NDA)系统,以确保处置前燃料的完整性。在芬兰地质储存库的背景下,被动伽马发射断层扫描(PGET)将是这种NDA系统的一部分。我们在此报告2017-2020年间芬兰核电站的PGET测量结果。通过旋转探测器阵列,从各个角度记录伽马活动剖面,探测器阵列围绕已插入环面中心的燃料组件旋转。从生成的层析数据重建图像被定义为具有数据保真度项和正则化项的约束最小化问题。活度图和衰减图,以及探测器灵敏度校正,是最小化过程中的变量。正则化项确保考虑了燃料棒(可能)位置及其直径的先验信息。燃料棒分类是PGET方法的主要目的,它基于燃料棒与其相邻燃料棒的活度差异,同时考虑到燃料棒与装配中心的距离。通过支持向量机进行分类。我们报告了10种不同燃料类型的结果,燃烧在5.72和55.0 GWd/tU之间,冷却时间在1.87和34.6年之间,初始富集在1.9和4.4%之间。对于所有测量的燃料组件,缺失的燃料棒,部分燃料棒和水道被正确分类。可燃吸收剂燃料棒被归类为燃料棒。在极少数情况下,存在的燃料棒被错误地归类为丢失。结果表明,PGET装置与图像重建方法的结合为燃料棒分类提供了可靠的基础。
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Fuel rod classification from Passive Gamma Emission Tomography (PGET) of spent nuclear fuel assemblies
Safeguarding the disposal of spent nuclear fuel in a geological repository needs an effective, efficient, reliable and robust non-destructive assay (NDA) system to ensure the integrity of the fuel prior to disposal. In the context of the Finnish geological repository, Passive Gamma Emission Tomography (PGET) will be a part of such an NDA system. We report here on the results of PGET measurements at the Finnish nuclear power plants during the years 2017-2020. Gamma activity profiles are recorded from all angles by rotating the detector arrays around the fuel assembly that has been inserted into the center of the torus. Image reconstruction from the resulting tomographic data is defined as a constrained minimization problem with a data fidelity term and regularization terms. The activity and attenuation maps, as well as detector sensitivity corrections, are the variables in the minimization process. The regularization terms ensure that prior information on the (possible) locations of fuel rods and their diameter are taken into account. Fuel rod classification, the main purpose of the PGET method, is based on the difference of the activity of a fuel rod from its immediate neighbors, taking into account its distance from the assembly center. The classification is carried out by a support vector machine. We report on the results for ten different fuel types with burnups between 5.72 and 55.0 GWd/tU, cooling times between 1.87 and 34.6 years and initial enrichments between 1.9 and 4.4%. For all fuel assemblies measured, missing fuel rods, partial fuel rods and water channels were correctly classified. Burnable absorber fuel rods were classified as fuel rods. On rare occasions, a fuel rod that is present was falsely classified as missing. We conclude that the combination of the PGET device and our image reconstruction method provides a reliable base for fuel rod classification.
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