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PuO2 Agglomerate Detectability in (Th,1%Pu)O2 Fuel—A Monte Carlo Simulation Study

  • K. V. Vrinda DeviEmail author
  • K. Biju
  • K. B. Khan
Conference paper

Abstract

Advanced heavy water reactor (AHWR) is being developed for thorium utilisation and various technologies associated with this are being studied. Experimental irradiation of (Th0.99,Pu0.01)O2 MOX fuel has been carried out in AHWR conditions. Fabrication and characterisation of this fuel were carried out through conventional powder metallurgical route similar to (U,Pu)O2 MOX fuel. Homogeneity of fissile material distribution is a crucial characteristic of the fuel, and quality control procedure of the fuel incorporates inspections to ensure its conformance with specifications in this regard. Gamma autoradiography (GAR) is one of the techniques carried out for this wherein plutonium-rich agglomerates; if any, present in the matrix appear as dark spots in the gamma image of the fuel. However, it is difficult to characterise the agglomerate based on the GAR image as multiple factors such as plutonium richness and size of the agglomerate, location on the fuel pellet influence the formation of the image significantly. Hence, a theoretical simulation study was carried out to estimate the minimum detectable size of a 100% rich plutonium agglomerate located on the surface of (Th0.99,Pu0.01)O2 MOX fuel by GAR. Monte Carlo methods using FLUKA2011.2C code was applied for this. Details of the simulations and the results obtained are discussed in this paper.

Keywords

MOX Plutonium homogeneity GAR Monte Carlo 

Notes

Acknowledgements

The authors are grateful to all their colleagues at AFFF, BARC, Tarapur for their encouragement and support during this work.

References

  1. 1.
    F. Glodeanu, J. Nucl. Mater. 126, 181–183 (1984)CrossRefGoogle Scholar
  2. 2.
    N. Kumar, A.K. Hinge, N. Walinjkar, D.B. Sathe, A. Prakash, D. Mukherjee, T.R.G. Kutty, Mohd. Afzal, J.P. Panakkal, Proceedings of the National Seminar & Exhibition on Non-Destructive Evaluation NDE 2011, 8–10 December 2011, pp. 101–104Google Scholar
  3. 3.
    J.P. Panakkal, K.V. Vrinda Devi, D. Mukherjee, R.S. Wadhwani, H.S. Kamath, WCNDT’96, New Delhi, Dec 1996Google Scholar
  4. 4.
    K.V. Vrinda Devi, J.P. Panakkal, Nucl. Eng. Des. 255, 132–137 (2013)CrossRefGoogle Scholar
  5. 5.
    K.V. Vrinda Devi, K. Biju, K.B. Khan, A. Kumar, 5th ISMC-2014Google Scholar
  6. 6.
    K.V. Vrinda Devi, K. Biju, K.B. Khan, A. Kumar, 59th DAE SSSP-2014Google Scholar
  7. 7.
    A. Fasso’, A. Ferrari, J. Ranft, P.R. Sala, FLUKA: A Multi-Particle Transport Code. CERN-2005- INFN/TC_05/11, SLAC-R-773 (2005)Google Scholar
  8. 8.
    G. Battistoni, S. Muraro, P.R. Sala, F. Cerutti, A. Ferrari, S. Roesler, A. Fasso’, J. Ranft, The FLUKA code: description and benchmarking, in Proceedings of the Hadronic Shower Simulation, Workshop 2006, Fermilab, 6–8 September 2006. AIP Conference Proceeding, vol. 896, pp. 31–49 (2007)Google Scholar
  9. 9.
    E.D. Cashwell, C.J. Everett, A Practical Manual on the Monte Carlo Method for Random Walk Problems, LA-2120, Physics and Mathematics, Los Alamos Scientific Laboratory, New Mexico (1957)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Radiometallurgy DivisionBhabha Atomic Research CentreMumbaiIndia
  2. 2.Health Physics DivisionBhabha Atomic Research CentreTrombay, MumbaiIndia

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