Open Access
Issue
EPJ Web Conf.
Volume 281, 2023
5th International Workshop on Nuclear Data Covariances (CW2022)
Article Number 00021
Number of page(s) 7
DOI https://doi.org/10.1051/epjconf/202328100021
Published online 29 March 2023
  1. M. Herman, et al., “Infrastructure for the new paradigm of nuclear reaction evaluation,” Ann. Nucl. Energy, 163, 108494 (2021). [CrossRef] [Google Scholar]
  2. J. Hutchinson, et al., “Investigation of delayed neutron sensitivities for several ICSBEP benchmarks using MCNP, ” Trans. Am. Nucl. Soc., 125, p.620 (2021). [Google Scholar]
  3. A. Gandini, “A method of correlation of burnup measurements for physics prediction of fast power-reactor life, ” Nucl. Sci. Eng., 38, p.1 (1969). [CrossRef] [Google Scholar]
  4. M. L. Williams, “Development of depletion perturbation theory for coupled neutron/nuclide field, ” Nucl. Sci. Eng., 70, p.20 (1979). [CrossRef] [Google Scholar]
  5. G. Chiba, H. Harada, “Validation of LWR fuel depletion calculation module of reactor physics code system CBZ, ” J. Nucl. Sci. Technol., (accepted). [Google Scholar]
  6. 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, p.333 (1984). [CrossRef] [Google Scholar]
  7. M. Plaschy, et al., “Importance of the MUSE experiments for emerging ADS concepts from the nuclear data viewpoint, ” Ann. Nucl. Energy, 32, p.843 (2005). [CrossRef] [Google Scholar]
  8. P.T. Krishna Kumar, et al., “Maximization of representativity factors for experimental planning of crosssection measurements: an information theoretic approach, ” Ann. Nucl. Energy, 35, p.2243 (2008). [CrossRef] [Google Scholar]
  9. J.F. Lebrat, et al., “The use of representativity theory in the depletion calculations of SFR blankets, ” Ann. Nucl. Energy, 101, p.429 (2017). [CrossRef] [Google Scholar]
  10. T. Kugo, T. Mori, T. Takeda, “Theoretical study on new bias factor methods to effectively use critical experiments for improvement of prediction accuracy of neutronics characteristics”, J. Nucl. Sci. Technol., 44, p.1509 (2007). [CrossRef] [Google Scholar]
  11. A. Gandini, “Uncertainty analysis and experimental data transposition methods based on perturbation theory, ” in Y. Ronen (Ed.) “Uncertainty Analysis”, CRC press, (1988) [Google Scholar]

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