Global and flexible models for Sodium-cooled Fast Reactors in fuel cycle simulations
| Autor: | Adrien Bidaud, Sandra Bouneau, Fanny Courtin, M. Ernoult, Abdoul-Aziz Zakari-Issoufou, Sylvain David, A. Somaini, N. Thiollière, X. Doligez, Jean-Baptiste Clavel |
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| Přispěvatelé: | Institut de Physique Nucléaire d'Orsay (IPNO), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Sud - Paris 11 (UP11), Laboratoire de physique subatomique et des technologies associées (SUBATECH), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Institut de Radioprotection et de Sûreté Nucléaire (IRSN), Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Université de Nantes - Faculté des Sciences et des Techniques, Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA) |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Artificial neural network
Computer science 020209 energy Nuclear engineering Process (computing) 02 engineering and technology [PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex] 01 natural sciences 7. Clean energy Spent nuclear fuel 010305 fluids & plasmas Sodium-cooled fast reactor Breeder (animal) Nuclear Energy and Engineering Range (aeronautics) 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Sensitivity (control systems) Scenario testing |
| Zdroj: | Annals Nucl.Energy Annals Nucl.Energy, 2019, 128, pp.69-76. ⟨10.1016/j.anucene.2018.12.037⟩ |
| Popis: | International audience; Since Sodium cooled Fast Reactors are present in many scenarios and strategies for the future of nuclear energy while not having a specific design established yet, we created a new fast and flexible model for the dynamic fuel cycle simulation tools CLASS. It includes a depletion meta-model and a fuel loading method based on artificial neural networks. It is able to represent a wide range of Sodium cooled Fast Reactor designs using oxide fuels and a wide range of fuel management strategies within fuel cycle simulation tools. A comprehensive analysis of simplification options has been made in order to choose the right level of complexity for the reference full core depletion calculations performed with the MURE code used for the training of the meta-model. The process from these reference calculations to the final meta-model is explained and a specific focus is given to the operations going from detailed full core depletion results to global results suitable for neural networks training. Details on the creation process for neural networks based predictors, one for each average cross-section, and their training on full core depletion calculations are given as well as the implementation within the CLASS code. The irradiation meta-model achieves good precision on all major and minor actinides present in spent fuel. The designs and loaded fuel covered by the model allow significant burner to strong breeder strategies. A sensitivity analysis shows that the number of fertile blankets is the primary contributor for breeding capabilities, but effects of isotopic composition are also significant. A test scenario illustrates the model capacity to simulate burner and breeder designs. |
| Databáze: | OpenAIRE |
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