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All issues Volume 4 (2018) EPJ Nuclear Sci. Technol., 4 (2018) 19 References
Open Access
Issue
EPJ Nuclear Sci. Technol.
Volume 4, 2018
Article Number 19
Number of page(s) 6
DOI https://doi.org/10.1051/epjn/2018046
Published online 17 October 2018
  1. V.V. Orlov, A.A. Van'kov, V.I. Voropaev, Y.A. Kazansky, V.I. Matveev, V.M. Murogov, Problems of fast reactor physics related to breeding, Energy Rev. 4, 991 (1980) [Google Scholar]
  2. A. Gandini, On transposition of experimental reactor data to reference design, Technical report, Comitato nazionale per la ricerca e per lo sviluppo dell energia nucleare e delle energie alternative, 1983 [Google Scholar]
  3. P. Blaise, E. Fort, Resonance parameter adjustement methodoloby based on integral experiment analysis, Nucl. Sci. Eng. 133, 235 (1999) [CrossRef] [Google Scholar]
  4. T. Ivanova, E. Ivanov, F. Ecrabet, Uncertainty assessment for fast reactors based on nuclear data adjustment, Nucl. Data Sheets 118, 592 (2014) [CrossRef] [Google Scholar]
  5. C. De Saint Jean et al., Evaluation of cross section uncertainties using physical constraints: focus on integral experiments, Nucl. Data Sheets 123, 178 (2015) [CrossRef] [Google Scholar]
  6. E. Privas et al., Generation of 238U covariance matrices by using the integral data assimilation technique of the CONRAD code, EPJ Web Conf. 106, 04015 (2016) [CrossRef] [Google Scholar]
  7. G. Palmiotti et al., Combined use of integral experiments and covariance data, Nucl. Data Sheets 118, 596 (2014) [CrossRef] [Google Scholar]
  8. L.N. Usachev, Yu.G. Bokkov, INDC(CCP)-19/U, International Nuclear Data Committee, Vienna, 1972 [Google Scholar]
  9. G. Palmiotti, M. Salvatores, Use of integral experiments in the assessment of large liquid-metal fast breeder reactor basic design parameters, Nucl. Sci. Eng. 87, 333 (1984) [CrossRef] [Google Scholar]
  10. C. De Saint Jean, E. Dupont, M. Ishikawa, G. Palmioti, M. Salvatores, Assessment of existing nuclear data adjustment methodologies, Nuclear Science NEA/WPEC-33, 2010 [Google Scholar]
  11. P. Archier et al., COMAC, Nuclear data covariance matrices library for reactor applications, in Physor 2014 [Google Scholar]
  12. N. Terranova et al., Covariance generation and uncertainty propagation for thermal and fast neutron induced fission yields, EPJ Web Conf. 146, 02013 (2017) [CrossRef] [Google Scholar]
  13. T. Frosio, T. Bonaccorsi, P. Blaise, Nuclear data uncertainties propagation methods in Boltzmann/Bateman coupled problem: application to reactivity in MTR, Ann. Nucl. Energy 90, 303 (2016) [CrossRef] [Google Scholar]
  14. T. Frosio, T. Bonaccorsi, P. Blaise, Fission yields and cross section uncertainty propagation in Boltzmann/Bateman coupled problems: global and local parameters analysis with a focus on MTR, Ann. Nucl. Energy 98, 43 (2016) [CrossRef] [Google Scholar]
  15. T. Frosio, T. Bonaccorsi, P. Blaise, Manufacturing data uncertainties propagation method in burn-up problems, Sci. Technol. Nucl. Ins. 2017, 7275346 (2017) [Google Scholar]
  16. Nuclear Science, Methods and issues for the combined use of integral experiments and covariance data, NEA/NSC/WPEC/DOC(2013)445, 2013 [Google Scholar]
  17. M. Salvatores et al., Needs and issues of covariance data application, Nucl. Data Sheets 109, 2725 (2008) [CrossRef] [Google Scholar]
  18. N. Dossantos, Optimisation de l'approche de représentativité et de transposition pour la conception neutronique de programmes expérimentaux dans les maquettes critiques, PHD 2013, GRENI033 [Google Scholar]
  19. W.S. Yang, T.J. Downar, Depletion perturbation theory for the constrained equilibrium cycle, Nucl. Sci. Eng. 102, 365 (1989) [CrossRef] [Google Scholar]
  20. G. Palmiotti, M. Salvatores, Developments in sensitivity methodologies and the validation of reactor physics calculations, Sci. Technol. Nucl. Ins. 2012 529623 (2012) [Google Scholar]

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