Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
권호 표지
DOI QR코드

DOI QR Code

A novel reconstruction algorithm based on density clustering for cosmic-ray muon scattering inspection

  • Received : 2020.06.18
  • Accepted : 2021.01.12
  • Published : 2021.07.25
Download PDF
⟨ Previous Next ⟩

Abstract

As a relatively new radiation imaging method, the cosmic-ray muon scattering imaging technology can be used to prevent nuclear smuggling and is of considerable significance to nuclear safety. Proposed in this paper is a new reconstruction algorithm based on density clustering, aiming to improve inspection quality with better performance. Firstly, this new algorithm is introduced in detail. Then in order to eliminate the inequity of the density threshold caused by the heterogeneity of the muon flux in different positions, a new flux correction method is proposed. Finally, three groups of simulation experiments are carried out with the help of Geant4 toolkit to optimize the algorithm parameters, verify the correction method and test the inspection quality under shielded condition, and compare this algorithm with another common inspection algorithm under different conditions. The results show that this algorithm can effectively identify and locate nuclear material with low misjudging and missing rates even when there is shielding and momentum precision is low, and the threshold correcting method is universally effective for density clustering algorithms.

Keywords

References

  1. E.P. George, Cosmic Rays Measure Overburden of Tunnel, Commonwealth Engineer, 1955, p. 455.
  2. L.W. Alvarez, J.A. Anderson, F. El Bedwei, et al., Search for hidden chambers in the pyramids, Science 167 (3919) (1970) 832-839. https://doi.org/10.1126/science.167.3919.832
  3. K. Morishima, M. Kuno, A. Nishio, et al., Discovery of a big void in Khufu's Pyramid by observation of cosmic-ray muons, Nature 552 (2017) 386-390. https://doi.org/10.1038/nature24647
  4. H.K.M. Tanaka, T. Kusagaya, H. Shinohara, Radiographic visualization of magma dynamics in an erupting volcano, Nat. Commun. 5 (1) (2014) 1-9.
  5. G. Ambrosi, F. Ambrosino, R. Battiston, et al., The MU-RAY project: volcano radiography with cosmic-ray muons, Nucl. Instrum. Methods Phys. Res. A 628 (2011) 120-123. https://doi.org/10.1016/j.nima.2010.06.299
  6. F. Ambrosino, A. Anastasio, D. Basta, et al., The MU-RAY project: detector technology and first data from Mt. Vesuvius, J. Instrum. 9 (2) (2014) C02029. https://doi.org/10.1088/1748-0221/9/02/C02029
  7. J. Marteau, J. de Bremond d'Ars, D. Gibert, et al., DIAPHANE: muon tomography applied to volcanoes, civil engineering, archaelogy, J. Instrum. 12 (2) (2017) C02008. https://doi.org/10.1088/1748-0221/12/02/C02008
  8. F. Fehr, TOMUVOL Collaboration, Density imaging of volcanos with atmospheric muons, J. Phys.: Conference Series. IOP Publishing 375 (2012), 052019, 5.
  9. K.N. Borozdin, G.E. Hogan, C. Morris, et al., Surveillance: radiographic imaging with cosmic-ray muons, Nature 422 (2003) 277-278.
  10. T. Sugita, J. Bacon, Y. Ban, et al., Cosmic-ray muon radiography of UO2 fuel assembly, J. Nucl. Sci. Technol. 51 (7-8) (2014) 1024-1031. https://doi.org/10.1080/00223131.2014.919884
  11. C.L. Morris, J. Bacon, Y. Ban, et al., Analysis of muon radiography of the Toshiba nuclear critical assembly reactor, Appl. Phys. Lett. 104 (2) (2014), 024110. https://doi.org/10.1063/1.4862475
  12. J. Perry, M. Azzouz, J. Bacon, et al., Imaging a nuclear reactor using cosmic ray muons, J. Appl. Phys. 113 (18) (2013) 184909. https://doi.org/10.1063/1.4804660
  13. K. Borozdin, et al., Cosmic ray radiography of the damaged cores of the Fukushima reactors, Phys. Rev. Lett. 109 (15) (2012) 152501. https://doi.org/10.1103/PhysRevLett.109.152501
  14. H. Miyadera, K. Borozdin, S. Greene, Imaging Fukushima Daiichi reactors with muons, AIP Adv. 3 (5) (2013), 052133. https://doi.org/10.1063/1.4808210
  15. K. Takamatsu, H. Takegami, C. Ito, et al., Cosmic-ray muon radiography for reactor core observation, Ann. Nucl. Energy 78 (2015) 166-175. https://doi.org/10.1016/j.anucene.2014.12.017
  16. N. Kume, H. Miyadera, C.L. Morris, et al., Muon trackers for imaging a nuclear reactor, J. Instrum. 11 (9) (2016) P09008. https://doi.org/10.1088/1748-0221/11/09/P09008
  17. J.M. Durham, E. Guardincerri, C.L. Morris, et al., Tests of cosmic ray radiography for power industry applications, AIP Adv. 5 (6) (2015), 067111. https://doi.org/10.1063/1.4922006
  18. G. Blanpied, S. Kumar, D. Dorroh, et al., Material discrimination using scattering and stopping of cosmic ray muons and electrons: differentiating heavier from lighter metals as well as low-atomic weight materials, Nucl. Instrum. Methods Phys. Res. A 784 (2015) 352-358. https://doi.org/10.1016/j.nima.2014.11.027
  19. L.J. Schultz, et al., Image reconstruction and material Z discrimination via cosmic ray muon radiography, Nucl. Instrum. Methods Phys. Res. A 519 (3) (2004) 687-694. https://doi.org/10.1016/j.nima.2003.11.035
  20. L.J. Schultz, G.S. Blanpied, K.N. Borozdin, et al., Statistical reconstruction for cosmic ray muon tomography, IEEE Trans. Image Process. 16 (8) (2007) 1985-1993. https://doi.org/10.1109/TIP.2007.901239
  21. G. Wang, L.J. Schultz, J. Qi, Bayesian image reconstruction for improving detection performance of muon tomography, IEEE Trans. Image Process. 18 (5) (2009) 1080-1089. https://doi.org/10.1109/TIP.2009.2014423
  22. C.J. Benton, N.D. Smith, S.J. Quillin, C.A. Steer, Most probable trajectory of a muon in a scattering medium, when input and output trajectories are known, Nucl. Instrum. Methods Phys. Res. A 693 (2012) 154-159. https://doi.org/10.1016/j.nima.2012.07.008
  23. G. Jonkmans, V.N.P. Anghel, C. Jewett, M. Thompson, Nuclear waste imaging and spent fuel verification by muon tomography, Ann. Nucl. Energy 53 (2013) 267-273. https://doi.org/10.1016/j.anucene.2012.09.011
  24. M. Stapleton, J. Burns, S. Quillin, C. Steer, Angle statistics reconstruction: a robust reconstruction algorithm for muon scattering tomography, J. Instrum. 9 (2014) P11019. https://doi.org/10.1088/1748-0221/9/11/P11019
  25. C. Thomay, J.J. Velthuis, P. Baesso, et al., A novel technique to detect special nuclear material using cosmic rays, in: 2012 IEEE Nuclear Science Symposium and Medical Imaging Conference, Anaheim, CA, USA, 27 Oct.-3 Nov, 2012.
  26. C. Thomay, J.J. Velthuis, P. Baesso, et al., A binned clustering algorithm to detect high-Z material using cosmic muons, J. Instrum. 8 (10) (2013) P10013. https://doi.org/10.1088/1748-0221/8/10/P10013
  27. W.T. Scott, The theory of small-angle multiple scattering of fast charged particles, Rev. Mod. Phys. 35 (2) (1963) 231. https://doi.org/10.1103/RevModPhys.35.231
  28. C.T. Case, E.L. Battle, Moliere's theory of multiple scattering, Phys. Rev. 169 (1) (1968) 201. https://doi.org/10.1103/PhysRev.169.201
  29. K. Hagiwara, K. Hikasa, K. Nakamura, et al., Review of particle physics: particle data group, Phys. Rev. D 66 (1I) (2002) 100011-10001958.
  30. Y.H. Kuo, Determination of the Angular Distribution of Cosmic Rays at Sea Level, Massachusetts Institute of Technology, 2010.
  31. C. Amsler, Particle data group, review of particle physics, Phys. Lett. B 667 (1) (2008) 1-6. https://doi.org/10.1016/j.physletb.2008.07.018
  32. S. Agostinelli, J. Allison, K. Amako, et al., GEANT4-a simulation toolkit, Nucl. Instrum. Methods Phys. Res. A 506 (3) (2003) 250-303. https://doi.org/10.1016/S0168-9002(03)01368-8
  33. J. Allison, K. Amako, J. Apostolakis, et al., Geant4 developments and applications, IEEE Trans. Nucl. Sci. 53 (1) (2006) 270-278. https://doi.org/10.1109/TNS.2006.869826
  34. C. Hagmann, D. Lange, D. Wright, Cosmic-ray shower generator (CRY) for Monte Carlo transport codes, in: 2007 IEEE Nuclear Science Symposium Conference, Honolulu, HI, USA, 26 Oct.-3 Nov, 2007.