EPJ Nuclear Sci. Technol.
Volume 7, 2021
Fuel Cycle Simulation TWoFCS 2021
Article Number 20
Number of page(s) 15
Published online 15 November 2021
  1. Office parlementaire d’évaluation des choix scientifiques et technologiques (France), The 2006 Programme Act on the Sustainable Management of Radioactive Materials and Wastes (OPECST, 2006) [Google Scholar]
  2. CEA/DEN, La Gestion Durable des Matières Radioactives avec les Réacteurs de 4e Génération (CEA, 2012) [Google Scholar]
  3. E. Mbala Malambu et al., Transition Towards a Sustainable Nuclear Fuel Cycle (NEA-OECD, 2013) [Google Scholar]
  4. CEA/DEN, Inventaire prospectifentre 2016 et 2100 des matières et des déchets radioactifs produits par le parc français selon différents scénarios d’évolution (CEA, 2018) [Google Scholar]
  5. L. Tillard, J.B. Clavel, X. Doligez, É. Dumonteil, M. Ernoult, J. Liang, N. Thiollière, Analysis of Transition Scenario from a PWR to a SFR Fleet Simulated with the CLASS code, in International Nuclear Fuel Cycle Conference (GLOBAL 2019), Seattle, Washington, USA (2019) [Google Scholar]
  6. M. Tiphine, C. Coquelet-Pascal, G. Krivtchik, R. Eschbach, C. Chabert, B. Carlier, M. Caron-Charles, G. Senentz, L. Durpel, C. Garzenne, F. Laugier, Simulations of Progressive Potential Scenarios of Pu Multirecycling in SFR and Associated Phase-out in the French Nuclear Power Fleet, in GLOBAL 2015 – 21st International Conference and Exhibition “Nuclear Fuel Cycle for a Low-Carbon Future”, Paris, France 2015 [Google Scholar]
  7. G. Martin, C. Coquelet-Pascal, Symbiotic equilibrium between sodium fast reactors and pressurized water reactors supplied with MOX fuel, Ann. Nucl. Energy 103, 356–362 (2017) [Google Scholar]
  8. D. Freynet, C. Coquelet-Pascal, R. Eschbach, G. Krivtchik, E. Merle-Lucotte, Multiobjective optimization for nuclear fleet evolution scenarios using COSI, EPJ Nuclear Sci. Technol. 2, 9 (2016) [Google Scholar]
  9. J. Whan Bae, C.E. Singer, K.D. Huf, Synergistic spent nuclear fuel dynamics within the European Union, Progr. Nucl. Energy 114, 1–12 (2019) [Google Scholar]
  10. P.L. Joskow, J.E. Parsons, The future of nuclear power after Fukushima, Econ. Energy Environ. Policy 1, 2 (2012) [Google Scholar]
  11. R. Mendelevitch, T.T. Dang, Nuclear Power and the Uranium Market: Are Reserves and Resources Sufficient? No. 98 (2016) DIW Roundup: Politik im Fokus [Google Scholar]
  12. S. Tillement, F. Garcias, ASTRID, back to the future: bridging scales in the development of nuclear infrastructures, Nucl. Technol. 207-9, 1291–1311 (2021) [Google Scholar]
  13. Ministère de la transition écologique et solidaire (France), Programmation Pluriannuelle de l’Energie: 2019-2023, 2024-2028 2020 [Google Scholar]
  14. N. Thiollière, J.B. Clavel, F. Courtin, X. Doligez, M. Ernoult, Z. Issoufou, G. Krivtchik, B. Leniau, B. Mouginot, A. Bidaud, S. David, V. Lebrin, C. Perigois, Y. Richet, A. Somaini, A methodology for performing sensitivity analysis in dynamic fuel cycle simulation studies applied to a PWR fleet simulated with the CLASS tool, EPJ Nuclear Sci. Technol. 4, 13 (2018) [Google Scholar]
  15. A.V. Skarbeli, F. Álvarez-Velarde, Uncertainty quantification on advanced fuel cycle scenario simulations applying local and global methods, Ann. Nucl. Energy 124, 349–356 (2019) [Google Scholar]
  16. B. Feng, S. Richards, J. Bae, E. Davidson, A. Worrall, R. Hays, Sensitivity and Uncertainty Quantification of Transition Scenario Simulations, Argonne National Lab. (ANL) ANL/NSE-20/38 (2020) [Google Scholar]
  17. W. Zhou, G. Krivtchik, P. Blaise, Resilience of nuclear fuel cycle scenarios: Definition, method and application to a fleet with uncertain power decrease, Int. J. Energy Res. 45-8, 12173–12194 (2020) [Google Scholar]
  18. J. Liang, M. Ernoult, X. Doligez, S. David, S. Bouneau, N. Thiollière, G. Krivtchik, F. Courtin, W. Zhou, S. Tillement, Assessment of strategy robustness under disruption of objective in dynamic fuel cycle studies, Ann. Nucl. Energy 154, 108131 (2021) [Google Scholar]
  19. G. Youinou, A. Vasile, Plutonium multirecycling in standard PWRs loaded with evoutionary fuels, Nucl. Sci. Eng. 151, 25–45 (2005) [Google Scholar]
  20. G. Martin, M. Guyot, F. Laugier, G. Senentz, G. Krivtchik, B. Carlier, D. Lecarpentier, F. Descamps, C. Chabert, R. Eschbach, French Scenarios Toward Fast Plutonium Multi-recycling in PWR, in ICAPP 2018 (Charlotte, United States, 2018), 103-112 [Google Scholar]
  21. F. Courtin, N. Thiollière, X. Doligez, M. Ernoult, B. Leniau, J. Liang, B. Mouginot, A.-A. Zakari-Issoufou, Assessment of plutonium inventory management in the French nuclear fleet with the fuel cycle simulator CLASS, Nucl. Eng. Des. 377, 111042 (2021) [Google Scholar]
  22. J.A. Nelder, R. Mead, A simplex method for function minimization, Comput. J. 7, 308–313 (1965) [Google Scholar]
  23. S. Singer, S. Singer, Efficient implementation of the Nelder-Mead search algorithm, Appl. Numer. Anal. Comput. Math. 1, 524–534 (2004) [Google Scholar]
  24. B. Leniau, B. Mouginot, N. Thiollière, X. Doligez, A. Bidaud, F. Courtin, M. Ernoult, S. David, A neural network approach for burn-up calculation and its application to the dynamic fuel cycle code CLASS, Ann. Nucl. Energy 81, 125–133. (2015). [Google Scholar]
  25. A.-A. Zakari-Issoufou, M. Ernoult, X. Doligez, Consequences on using macro power reactors in nuclear scenarios, in 3rd Technical Workshop On Fuel Cycle Simulation (2018) [Google Scholar]
  26. F. Courtin, Etude de l’incinération du plutonium en REP MOX sur support d’uranium enrichi avec le code de simulation dynamique du cycle CLASS, PhD thesis, Ecole nationale supérieure Mines-Télécom Atlantique, 2017, French [Google Scholar]
  27. M. Ernoult, X. Doligez, N. Thiollière, A.A. Zakari-Issoufou, A. Bidaud, S. Bouneau, J.B. Clavel, F. Courtin, S. David, A. Somaini, Global and flexible models for sodium-cooled fast reactors in fuel cycle simulations, in PHYSOR 2018: Reactor Physics paving the way towards more efficient systems, Cancun, Mexico 2018 [Google Scholar]

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