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Nuclear waste imaging and spent fuel verification by muon tomography

  • Published:2013-03 Issue: Volume:53 Page:267-273
  • ISSN:0306-4549
  • Container-title:Annals of Nuclear Energy
  • language:en
  • Short-container-title:Annals of Nuclear Energy

Author:

Jonkmans G.,Anghel V.N.P.,Jewett C.,Thompson M.

Publisher

Elsevier BV

Subject

Nuclear Energy and Engineering

Reference29 articles.

1. GEANT4 a simulation tool kit;Agostinelli;Nucl. Instr. Meth.,2003

2. Search for hidden chambers in the pyramids using cosmic rays;Alvarez;Science,1970

3. Review of particle physics;Amsler;Phys. Lett. B,2008

4. Anghel, V.N.P., et al., 2011. Detecting High Atomic Number Materials with Cosmic Ray Muon Tomography. US Provisional Patent No. 48283-3001.

5. Radiographic imaging with cosmic ray muons;Borozdin;Nature,2003

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1. Application of machine learning methods for spent fuel characterization based on gamma spectrometry measurements;Annals of Nuclear Energy;2024-09

2. A new algorithm to improve imaging quality for muon tomography;Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment;2024-09

3. Enhanced material identification via momentum-integrated muon scattering tomography;Nuclear Science and Technology Open Research;2024-04-29

4. Momentum informed muon scattering tomography for monitoring spent nuclear fuels in dry storage cask;Scientific Reports;2024-03-20

5. Nuclear Waste Management: A Mini Review on Waste Package Characterization Approaches;Science and Technology of Nuclear Installations;2024-01
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