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Experimental validation of material discrimination ability of muon scattering tomography at the TUMUTY facility

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Abstract

Muon scattering tomography is believed to be a promising technique for cargo container inspection, owing to the ability of natural muons to penetrate into dense materials and the absence of artificial radiation. In this work, the material discrimination ability of muon scattering tomography is evaluated based on experiments at the Tsinghua University cosmic ray muon tomography facility, with four materials: flour (as drugs substitute), aluminum, steel, and lead. The features of the different materials could be discriminated with cluster analysis and classifiers based on support vector machine. The overall discrimination precisions for these four materials could reach 70, 95, and 99% with 1-, 5-, and 10-min-long measurement, respectively.

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References

  1. K.A. Olive, K. Agashe, C. Amsler et al., Review of particle physics. Chin. Phys. C 38, 090001 (2014). https://doi.org/10.1103/PhysRevD.98.030001

    Article  Google Scholar 

  2. S. Procureur, Muon imaging: principles, technologies and applications. Nucl. Instrum. Methods A 878, 169–179 (2017). https://doi.org/10.1016/j.nima.2017.08.004

    Article  Google Scholar 

  3. V. Antonuccio, M. Bandieramonte, D.L. Bonanno et al., The muon portal project: design and construction of a scanning portal based on muon tomography. Nucl. Instrum. Methods A 845, 322–325 (2017). https://doi.org/10.1016/j.nima.2016.05.006

    Article  Google Scholar 

  4. 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 A 784, 352–358 (2015). https://doi.org/10.1016/j.nima.2014.11.027

    Article  Google Scholar 

  5. P. Baesso, D. Cussans, C. Thomay et al., Toward a RPC-based muon tomography system for cargo containers. J. Instrum. 9, C10041 (2014). https://doi.org/10.1088/1748-0221/9/10/C10041

    Article  Google Scholar 

  6. L. Frazão, J. Velthuis, C. Thomay et al., Discrimination of high-z materials in concrete-filled containers using muon scattering tomography. J. Instrum. 11, P07020 (2016). https://doi.org/10.1088/1748-0221/11/07/P07020

    Article  Google Scholar 

  7. D. Poulson, J.M. Durham, E. Guardincerri et al., Cosmic ray muon computed tomography of spent nuclear fuel in dry storage casks. Nucl. Instrum. Methods A 842, 48–53 (2017). https://doi.org/10.1016/j.nima.2016.10.040

    Article  Google Scholar 

  8. J.M. Durham, D. Poulson, J. Bacon et al., Verification of spent nuclear fuel in sealed dry storage casks via measurements of cosmic-ray muon scattering. Phys. Rev. Appl. 9, 44013 (2018). https://doi.org/10.1103/PhysRevApplied.9.044013

    Article  Google Scholar 

  9. Y. Zheng, Z. Zeng, M. Zeng et al., Discrimination of drugs and explosives in cargo inspections by applying machine learning in muon tomography. High Power Laser Part. Beams 30, 086002 (2018). https://doi.org/10.11884/HPLPB201830.180062

    Article  Google Scholar 

  10. X. Wang, M. Zeng, Z. Zeng et al., The cosmic ray muon tomography facility based on large scale MRPC detectors. Nucl. Instrum. Methods A 784, 390–393 (2015). https://doi.org/10.1016/j.nima.2015.01.024

    Article  Google Scholar 

  11. L.J. Schultz, Dissertation, Portland State University (2003)

  12. B. Yu, Z. Zhao, X. Wang et al., An MAP algorithm with edge-preserving prior for muon tomography, in IEEE Nuclear Science Symposium & Medical Imaging Conference. IEEE (2014). https://doi.org/10.1109/nssmic.2014.7431083

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Authors and Affiliations

  1. Key Laboratory of Particle and Radiation Imaging (Ministry of Education) and Department of Engineering Physics, Tsinghua University, Beijing, 100084, China

    Xing-Yu Pan, Zhi Zeng & Xue-Wu Wang

  2. Department of Nuclear Engineering, University of California, Berkeley, CA, 94709, USA

    Yi-Fan Zheng

  3. Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, 94143, USA

    Yi-Fan Zheng

  4. College of Nuclear Science and Technology, Beijing Normal University, Beijing, 100875, China

    Jian-Ping Cheng

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  1. Xing-Yu Pan
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  2. Yi-Fan Zheng
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  3. Zhi Zeng
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  4. Xue-Wu Wang
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  5. Jian-Ping Cheng
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Correspondence to Zhi Zeng.

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Pan, XY., Zheng, YF., Zeng, Z. et al. Experimental validation of material discrimination ability of muon scattering tomography at the TUMUTY facility. NUCL SCI TECH 30, 120 (2019). https://doi.org/10.1007/s41365-019-0649-4

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  • DOI: https://doi.org/10.1007/s41365-019-0649-4

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