EDP Sciences logo
Submit your paper
Search
Menu
All issues Volume 5 (2019) EPJ Nuclear Sci. Technol., 5 (2019) 17 References
Issue
EPJ Nuclear Sci. Technol.
Volume 5, 2019
Progress in the Science and Technology of Nuclear Reactors using Molten Salts
Article Number 17
Number of page(s) 9
Section Physics
DOI https://doi.org/10.1051/epjn/2019034
Published online 14 November 2019
  1. M.W. Rosenthal, P.R. Kasten, R.B. Briggs, Molten-salt Reactors – history, status, and potential, Nucl. Appl. Technol. 8, 107 (1970) [CrossRef] [Google Scholar]
  2. D. LeBlanc, Molten salt reactors: a new beginning for an old idea, Nucl. Eng. Des. 240, 1644 (2010) [CrossRef] [Google Scholar]
  3. H.G. MacPherson, The molten salt reactor adventure, Nucl. Sci. Eng. 90, 374 (1985) [CrossRef] [Google Scholar]
  4. R. Robertson, MSRE design and operations report. Part I. Description of reactor design, Tech. Rep. ORNL-TM-728, 1965, DOI:10.2172/4654707 [CrossRef] [Google Scholar]
  5. M.W. Rosentahl, The development status of molten-salt breeder reactors, Tech. Rep. ORNL-4812, 1972 [Google Scholar]
  6. L.G. Alexander, Molten-Salt Fast Reactors, Tech. Rep. ANL-6792, 1963 [Google Scholar]
  7. D. Holcomb, et al., Fast Spectrum Molten Salt Reactor Options, Tech. Rep. ORNL/TM-2011/105, 2011 [Google Scholar]
  8. The Generation IV International Forum (GIF), https://www.gen-4.org/gif/, Accessed: 04-10-2019 [Google Scholar]
  9. V. Ignatiev, O. Feynberg, I. Gnidoi, A. Merzlyakov, A. Surenkov, V. Uglov, A. Zagnitko, V. Subbotin, I. Sannikov, A. Toropov, et al., Molten salt actinide recycler and transforming system without and with Th-U support: fuel cycle flexibility and key material properties, Ann. Nucl. Energy 64, 408 (2014) [CrossRef] [Google Scholar]
  10. L. Mathieu, D. Heuer, E. Merle-Lucotte, R. Brissot, C. Le Brun, E. Liatard, J.-M. Loiseaux, O. Méplan, A.Nuttin, D. Lecarpentier, Possible configurations for the thorium molten salt reactor and advantages of the fast nonmoderated version, Nucl. Sci. Eng. 161, 78 (2009) [CrossRef] [Google Scholar]
  11. D. Heuer, E. Merle-Lucotte, M. Allibert, M. Brovchenko, V. Ghetta, P. Rubiolo, Towards the thorium fuel cycle with molten salt fast reactors, Ann. Nucl. Energy 64, 421 (2014) [CrossRef] [Google Scholar]
  12. EVOL (Project no249696) Final Reportr, https://cordis.europa.eu/docs/results/249/249696/final1-final-report-f.pdf, Accessed: 04-10-2019 [Google Scholar]
  13. SAMOFAR (Safety Assessment of the Molten Salt Fast Reactor), http://samofar.eu/, Accessed: 04-10-2019 [Google Scholar]
  14. MCFR Solutions: Nuclear Innovation for New Options in American Industry, https://terrapower.com/technologies/mcfr, Accessed: 04-10-2019 [Google Scholar]
  15. M. Tano-Retamales, Modélisation multi-physique multi-échelle de caloporteurs sels fondus et validation expérimentale, Ph.D. thesis, Université Grenoble-Alpes, 2018 [Google Scholar]
  16. B.S. Collins, C.A. Gentry, A.J. Wysocki, R.K. Salko, Molten salt reactor simulations using MPACT-CTF, Tech. rep., Oak Ridge National Lab.(ORNL), Oak Ridge, TN (United States), 2017 [Google Scholar]
  17. C.A. Gentry, B.R. Betzler, B.S. Collins, Initial Benchmarking of ChemTriton and MPACT MSR Modeling Capabilities, Tech. rep., Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States), 2017 [Google Scholar]
  18. M. Aufiero, A. Cammi, O. Geoffroy, M. Losa, L. Luzzi, M.E. Ricotti, H. Rouch, Development of an OpenFOAM model for the Molten Salt Fast Reactor transient analysis, Chem. Eng. Sci. 111, 390 (2014) [CrossRef] [Google Scholar]
  19. A. Laureau, D. Heuer, E. Merle-Lucotte, P. Rubiolo, M. Allibert, M. Aufiero, Transient coupled calculations of the Molten Salt Fast Reactor using the transient fission matrix approach, Nucl. Eng. Des. 316, 112 (2017) [CrossRef] [Google Scholar]
  20. J. Bao, Development of the model for the multiphysics analysis of Molten Salt Reactor Experiment using GeN-Foam code, Master’s thesis, EPFL & ETH Zurich, 2016, https://www.psi.ch/fast/PublicationsEN/FB-DOC-16-014.pdf [Google Scholar]
  21. C. Fiorina, I. Clifford, M. Aufiero, K. Mikityuk, GeN-Foam: a novel OpenFOAM® based multi-physics solver for 2D/3D transient analysis of nuclear reactors, Nucl. Eng. Des. 294, 24 (2015) [CrossRef] [Google Scholar]
  22. K. Pearson, LIII. On lines and planes of closest fit to systems of points in space, Philos. Mag. 2, 559 (1901) [Google Scholar]
  23. R. Pinnau, Model reduction via proper orthogonal decomposition, in Model Order Reduction: Theory, Research Aspects and Applications (Springer, 2008), p. 95 [CrossRef] [Google Scholar]
  24. E. Merle-Lucotte, D. Heuer, M. Allibert, M. Brovchenko, N. Capellan, V. Ghetta, Launching the thorium fuel cycle with the molten salt fast reactor, in Proceedings of ICAPP (2011), p. 2 [Google Scholar]
  25. M. Allibert, M. Aufiero, M. Brovchenko, S. Delpech, V. Ghetta, D. Heuer, A. Laureau, E. Merle-Lucotte, Molten salt fast reactors, in Handbook of Generation IV Nuclear Reactors (Elsevier, 2016), p. 157 [CrossRef] [Google Scholar]
  26. A. Sartori, D. Baroli, A. Cammi, D. Chiesa, L. Luzzi, R. Ponciroli, E. Previtali, M.E. Ricotti, G. Rozza, M. Sisti, Comparison of a Modal Method and a Proper Orthogonal Decomposition approach for multi-group time-dependent reactor spatial kinetics, Ann. Nucl. Energy 71, 217 (2014) [CrossRef] [Google Scholar]
  27. D.P. Prill, A.G. Class, Semi-automated proper orthogonal decomposition reduced order model non-linear analysis for future BWR stability, Ann. Nucl. Energy 67, 70 (2014) [CrossRef] [Google Scholar]
  28. A.G. Buchan, A. Calloo, M.G. Goffin, S. Dargaville, F. Fang, C.C. Pain, I.M. Navon, A POD reduced order model for resolving angular direction in neutron/photon transport problems, J. Comput. Phys. 296, 138 (2015) [CrossRef] [Google Scholar]
  29. A. Buchan, C. Pain, F. Fang, I. Navon, A POD reduced-order model for eigenvalue problems with application to reactor physics, Int. J. Numer. Methods Eng. 95, 1011 (2013) [CrossRef] [Google Scholar]
  30. A. Sartori, A. Cammi, L. Luzzi, G. Rozza, A multi-physics reduced order model for the analysis of Lead Fast Reactor single channel, Ann. Nucl. Energy 87, 198 (2016) [CrossRef] [Google Scholar]
  31. C. Wang, H.S. Abdel-Khalik, Construction of accuracy-preserving surrogate for the eigenvalue radiation diffusion and/ortransport problem, Tech. rep., American Nuclear Society, Inc., 555 N. Kensington Avenue, La Grange Park, Illinois 60526, United States, 2012 [Google Scholar]
  32. C. Wang, H.S. Abdel-Khalik, U. Mertyurek, Crane: A new scale super-sequence for neutron transport calculations, in Proceeding of MC 2015, Nashville, TN, April 19–23, 2015 [Google Scholar]
  33. P. German, J.C. Ragusa, Reduced-order modeling of parameterized multi-group diffusion k-eigenvalue problems, Ann. Nucl. Energy 134, 144 (2019) [CrossRef] [Google Scholar]
  34. S. Chaturantabut, D.C. Sorensen, Nonlinear model reduction via discrete empirical interpolation, SIAM J. Sci. Comput. 32, 2737 (2010) [CrossRef] [MathSciNet] [Google Scholar]
  35. A. Hochman, B.N. Bond, J.K. White, A stabilized discrete empirical interpolation method for model reduction of electrical, thermal, and microelectromechanical systems, in 2011 48th ACM/EDAC/IEEE Design Automation Conference (DAC), IEEE 2011, p. 540 [Google Scholar]
  36. A. Radermacher, S. Reese, POD-based model reduction with empirical interpolation applied to nonlinear elasticity, Int. J. Numer. Methods Eng. 107, 477 (2016) [CrossRef] [Google Scholar]
  37. W. Yao, S. Marques, Nonlinear aerodynamic and aeroelastic model reduction using a discrete empirical interpolation method, AIAA J. 55, 624 (2017) [CrossRef] [Google Scholar]
  38. S. Gugercin, A.C. Antoulas, A survey of model reduction by balanced truncation and some new results, Int. J. Control 77, 748 (2004) [CrossRef] [Google Scholar]
  39. Z. Bai, Krylov subspace techniques for reduced-order modeling of large-scale dynamical systems, Appl. Numer. Math. 43, 9 (2002) [CrossRef] [MathSciNet] [Google Scholar]
  40. S. Lorenzi, An adjoint proper orthogonal decomposition method for a neutronics reduced order model, Ann. Nucl. Energy 114, 245 (2018) [CrossRef] [Google Scholar]
  41. M. Rathinam, L.R. Petzold, A new look at proper orthogonal decomposition, SIAM J. Numer. Anal. 41, 1893 (2003) [Google Scholar]
  42. Y. Liang, H. Lee, S. Lim, W. Lin, K. Lee, C. Wu, Proper orthogonal decomposition and its applications–part I: theory, J. Sound Vib. 252, 527 (2002) [Google Scholar]
  43. B. Peherstorfer, D. Butnaru, K. Willcox, H. Bungartz, Localized discrete empirical interpolation method, SIAM J. Sci. Comput. 36, A168 (2014) [Google Scholar]
  44. S. Lorenzi, A. Cammi, L. Luzzi, G. Rozza, POD-Galerkin method for finite volume approximation of Navier–Stokes and RANS equations, Comput. Methods Appl. Mech. Eng. 311, 151 (2016) [CrossRef] [Google Scholar]
  45. S. Hijazi, G. Stabile, A. Mola, G. Rozza, Data-driven POD-Galerkin reduced order model for turbulent flows, arXiv:1907.09909 [Google Scholar]
  46. J.J. Duderstadt, L.J. Hamilton, in Nuclear reactor analysis (Wiley-Interscience, Ann Arbor, Michigan, 1976), p. 650 [Google Scholar]
  47. M. Aufiero, A. Cammi, C. Fiorina, L. Luzzi, A. Sartori, A multi-physics time-dependent model for the Lead Fast Reactor single-channel analysis, Nucl. Eng. Des. 256, 14 (2013) [CrossRef] [Google Scholar]
  48. C. Fiorina, D. Lathouwers, M. Aufiero, A. Cammi, C.Guerrieri, J.L. Kloosterman, L. Luzzi, M.E. Ricotti, Modelling and analysis of the MSFR transient behaviour, Ann. Nucl. Energy 64, 485 (2014) [CrossRef] [Google Scholar]
  49. E. Merle, Concept of Molten Salt Fast Reactor, in Molten Salt Reactor Workshow, PSI, 2017 [Google Scholar]
  50. SALOME, http://www.salome-platform.org, Accessed: 04-10-2019 [Google Scholar]
  51. J. Leppänen, M. Pusa, T. Viitanen, V. Valtavirta, T.Kaltiaisenaho, The serpent monte carlo code: Status, development and applicationsin 2013, in SNA+ MC 2013-Joint International Conference on Supercomputing in Nuclear Applications+ Monte Carlo (2014), p. 6 [Google Scholar]
  52. C. Fiorina, The Molten Salt Fast Reactor as a Fast-Spectrum Candidate for Thorium Implementation, Ph.D. thesis, Politecnico di Milano, https://www.politesi.polimi.it/bitstream/10589/74324/1/2013_03_PhD_Fiorina.pdf, 2013 [Google Scholar]
  53. B. Beachkofski, R. Grandhi, Improved distributed hypercube sampling, in 43rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (2002), p. 1274 [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.