Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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Optimization study of a clustering algorithm for cosmic-ray muon scattering tomography used in fast inspection

  • Received : 2020.01.07
  • Accepted : 2020.06.02
  • Published : 2021.01.25
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Abstract

Cosmic-ray muon scattering tomography (MST) technology is a new radiation imaging technology with unique advantages. As the performance of its image reconstruction algorithm has a crucial influence on the imaging quality, researches on this algorithm are of great significance to the development and application of this technology. In this paper, a fast inspection algorithm based on clustering analysis for the identification of the existence of nuclear materials is studied and optimized. Firstly, the principles of MST technology and a binned clustering algorithm were introduced, and then several simulation experiments were carried out using Geant4 toolkit to test the effects of exposure time, algorithm parameter, the size and structure of object on the performance of the algorithm. Based on these, we proposed two optimization methods for the clustering algorithm: the optimization of vertical distance coefficient and the displacement of sub-volumes. Finally, several sets of experiments were designed to validate the optimization effect, and the results showed that these two optimization methods could significantly enhance the distinguishing ability of the algorithm for different materials, help to obtain more details in practical applications, and was therefore of great importance to the development and application of the MST technology.

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References

  1. K.A. Olive, K. Agashe, C. Amsler, et al., Review of particle physics, Chin. Phys. C 38 (9) (2014), 090001. https://doi.org/10.1088/1674-1137/38/9/090001
  2. K.N. Borozdin, T.J. Asaki, R. Chartrand, et al., Information extraction from muon radiography data, Los Alamos Natl. Lab. (2004). LA-UR-04-3985.
  3. K.N. Borozdin, G.E. Hogan, C. Morris, et al., Surveillance: radiographic imaging with cosmic-ray muons, Nature 422 (2003) 277-278.
  4. J.M. Durham, E. Guardincerri, C.L. Morris, et al., Tests of cosmic ray radiography for power industry applications, AIP Adv. 5 (2015), 067111. https://doi.org/10.1063/1.4922006
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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.
  11. 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
  12. 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
  13. 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
  14. 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.