DOI QR코드

DOI QR Code

Design and characterization of a Muon tomography system for spent nuclear fuel monitoring

  • Park, Chanwoo (Department of Radiation Convergence Engineering, College of Health Science, Yonsei University) ;
  • Baek, Min Kyu (Department of Radiation Convergence Engineering, College of Health Science, Yonsei University) ;
  • Kang, In-soo (Department of Radiation Convergence Engineering, College of Health Science, Yonsei University) ;
  • Lee, Seongyeon (Department of Radiation Convergence Engineering, College of Health Science, Yonsei University) ;
  • Chung, Heejun (Korea Institute of Nuclear Nonproliferation and Control) ;
  • Chung, Yong Hyun (Department of Radiation Convergence Engineering, College of Health Science, Yonsei University)
  • Received : 2021.01.04
  • Accepted : 2021.08.25
  • Published : 2022.02.25

Abstract

In recent years, monitoring of spent nuclear fuel inside dry cask storage has become an important area of national security. Muon tomography is a useful method for monitoring spent nuclear fuel because it uses high energy muons that penetrate deep into the target material and provides a 3-D structure of the inner materials. We designed a muon tomography system consisting of four 2-D position sensitive detector and characterized and optimized the system parameters. Each detector, measuring 200 × 200 cm2, consists of a plastic scintillator, wavelength shifting (WLS) fibers and, SiPMs. The reconstructed image is obtained by extracting the intersection of the incoming and outgoing muon tracks using a Point-of-Closest-Approach (PoCA) algorithm. The Geant4 simulation was used to evaluate the performance of the muon tomography system and to optimize the design parameters including the pixel size of the muon detector, the field of view (FOV), and the distance between detectors. Based on the optimized design parameters, the spent fuel assemblies were modeled and the line profile was analyzed to conduct a feasibility study. Line profile analysis confirmed that muon tomography system can monitor nuclear spent fuel in dry storage container.

Keywords

Acknowledgement

This work was supported by the Nuclear Safety Research Program through the Korea Foundation Of Nuclear Safety (KoFONS) using the financial resource granted by the Nuclear Safety and Security Commission (NSSC) of the Republic of Korea. (No. 1804025).

References

  1. J. Medalia, Detection of Nuclear Weapons and Materials:Science, Technologies, Observations, CRS Report for Congress, 2009, p. R40154.
  2. IAEA, Design of Spent Fuel Storage Facilities, IAEA Safety Series No.116), 1994.
  3. NRC, Licensing Requirements for the Independent Storage of Spent Nuclear Fuel and High-Level Radioactive Waste (US 10-CFR-72), 1997.
  4. IAEA, The Present Status of IAEA Safeguards on Nuclear Fuel Cycle Facilities, vol. 22, IAEA-BULLETIN, 1994. NO.3/4.
  5. R.C. Runkle, A. Bernstein, P. Vanier, Securing special nuclear material: recent advances in neutron detection and their role in nonproliferation, J. Appl. Phys. 108 (2010) 111101. https://doi.org/10.1063/1.3503495
  6. J.M. Durham, D. Poulson, et al., Verification of spent nuclear fuel in sealed dry storage casks via measurements of cosmic-ray muon scattering, Phys. Rev. Appl. 9 (2018), 044013. https://doi.org/10.1103/physrevapplied.9.044013
  7. D. Poulson, J.M. Durham, et al., Cosmic ray muon computed tomography of spent nuclear fuel in dry storage casks, Nucl. Instrum. Methods A 842 (2017) 48-53. https://doi.org/10.1016/j.nima.2016.10.040
  8. S. Pesente, et al., First results on material identification and imaging with a large-volume muon tomography prototype, Nucl. Instrum. Methods A 604 (2009) 738-746. https://doi.org/10.1016/j.nima.2009.03.017
  9. H. Miyadera, K.N. Borozdin, S.J. Greene, et al., Imaging fukushima daiichi reactors with muons, AIP Adv. 3 (5) (2013), 052133. https://doi.org/10.1063/1.4808210
  10. M. Hohlmann, P. Ford, K. Gnanvo, et al., GEANT4 simulation of a cosmic ray muon tomography system with micro-pattern gas detectors for the detection of high-Z materials, IEEE Trans. Nucl. Sci. 56 (3) (2009) 1356-1363. https://doi.org/10.1109/TNS.2009.2016197
  11. G. Bonomi, Progress in Muon Tomography, EPS Conference on High Energy Physics, 2017. Venice, Italy.
  12. L.J. Schultz, et al., Image reconstruction and material Z discrimination via cosmic ray muon radiography, Nucl. Instrum. Methods A 519 (2004) 687. https://doi.org/10.1016/j.nima.2003.11.035
  13. J.M. Durham, et al., Cosmic ray muon imaging of spent nuclear fuel in dry storage casks, J. Nucl. Mater. Manag. 44 (3) (2016).
  14. S. Agostinelli, et al., Geant4-a simulation toolkit, Nucl. Instrum. Methods A 506 (2003) 250. https://doi.org/10.1016/S0168-9002(03)01368-8
  15. D. Sunday, Distance between lines and segments with their closest point of approach. http://geomalgorithms.com/a07-_distance.html, 2012.
  16. V. Anghel, A. Erlandson, D. Waller, et al., A plastic scintillator-based muon tomography system with an integrated muon spectrometer, Nucl. Instrum. Methods A 798 (2015) 12-23. https://doi.org/10.1016/j.nima.2015.06.054
  17. United States Nuclear Regulatory Commission, Available methods for functional monitoring of dry cask storage systems, U.S. NRC Contract, 2014. NRC-HQ-12-C-02-0089.
  18. J.D. Werner, US Spent Nuclear Fuel Storage, CRS Report for Congress, Congressional Research Service, Washington, DC, 2012.
  19. C. Patrignani, et al., Particle data group), review of particle physics, Chin. Phys. C40 (2016) 100001.