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Design and optimization of an integrated gamma ray scanning system for the uranium sample

  • Suxia Hou EMAIL logo and Jijun Luo
Published/Copyright: February 14, 2022
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Abstract

An integrated gamma ray scanning system has been designed and built to extend that localizes and quantifies highly enriched uranium sample. The detection mechanisms of the two modes (segmented gamma scanner and tomographic gamma scanning) are analyzed respectively. Moreover, the parameters influence of speed and the deviation of the measurement accuracy are analyzed for the uranium sample. In view of these problems, the system has improved by the optimization processing, which include the optimization of the collimator opening for detector, the crosstalk and the time step. Finally, the experiment were investigated and discussed in detail. The single measurement time of the system can reduce to about 30 min with an error of less than ±5%, so the measurement accuracy and the speed are enhanced effectively. The system has broad application prospects in the fields of nuclear safety, radioactive recyclables and non-destructive measurement of nuclear waste.


Corresponding author: Suxia Hou, Shaanxi Engineering Research Center of Controllable Neutron Source, School of Science, Xijing University, Xi’an, 710123, China, E-mail:

Funding source: National Nature Science Fund of China

Award Identifier / Grant number: 51309228

Award Identifier / Grant number: 2013M542459

Funding source: Shaanxi Technology Committee Natural Science Basic Research Project

Award Identifier / Grant number: 2016JM6026

Acknowledgments

We would like to acknowledge the technical supports from Professor Quanhu Zhang (Xi’an Research Institute of Hi-Tech). The authors also thank the technical supports for experimental data measurement from China Institute of Atomic Energy. The authors are grateful to the precious comments made by anonymous reviewers.

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission. Suxia Hou and Jijun Luo contributed equally to this work.

  2. Research funding: The authors extend their sincere thanks to The National Nature Science Fund of China Grants Agreement Number 51309228 for the financial support for this work. The authors also thank the Postdoctoral Science Foundation of China for financial supporting this work (No.2013M542459), and Shaanxi Technology Committee Natural Science Basic Research Project for financial supporting this work (No. 2016JM6026).

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

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Received: 2021-05-19
Published Online: 2022-02-14
Published in Print: 2022-02-23

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