EPJ Nuclear Sci. Technol.
Volume 4, 2018
Special Issue on 4th International Workshop on Nuclear Data Covariances, October 2–6, 2017, Aix en Provence, France – CW2017
Article Number 45
Number of page(s) 6
Section Applied Covariances
Published online 14 November 2018
  1. D. Rochman et al., Nuclear data uncertainty propagation: total Monte Carlo vs. covariances, J. Korean Phys. Soc. 59, 1236 (2011) [CrossRef] [Google Scholar]
  2. A. Santamarina et al., Validation of th e new code package APOLLO2.8 for accurate PWR neutronics calculations in International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (SunValley, CD-ROM, 2013) [Google Scholar]
  3. J.J. Lautard et al., in Advanced Calculational Methods for Power Reactors (Cadarache, 1990), pp. 42–50 [Google Scholar]
  4. MIT Computational Reactor Physics Group, Benchmark for Evaluation And Validation of Reactor Simulations, Release rev 2.0.1, 2017 [Google Scholar]
  5. L.N. Usachev, in Perturbation Theory for the Breeding Factor and Other Ratios of Different Processes in a Reactor (Atomnaia Energiya, 1963), p. 472 [Google Scholar]
  6. M.L. Williams, Perturbation Theory for Nuclear Reactor Analysis (CRC Handbook of nuclear reactor calculations, 1986) [Google Scholar]
  7. J. Lewins, Importance, the Adjoint Function (Pergamon Press, 1965) [Google Scholar]
  8. G. Truchet et al., Computing adjoint-weighted kinetics parameters in TRIPOLI4 by the Iterated Fission Probability method, Ann. Nucl. Energy 85, 17 (2015) [CrossRef] [Google Scholar]
  9. G. Truchet et al., Implementation and validation of reference sensitivity profile calculations in TRIPOLI4, in ICNC (2015) [Google Scholar]
  10. Y. Qiu et al., Computing eigenvalue sensitivity coefficients to nuclear data based on the CLUTCH method with RMC code, Ann. Nucl. Energy 88, 237 (2016) [CrossRef] [Google Scholar]
  11. A. Santamarina et al., The JEFF3.1.1 Nuclear Data Library − JEFF Report 22: validation results from JEF-2.2 to JEFF-3.1.1 AEN data bank, 2009 [Google Scholar]
  12. N. Hfaiedh et al., Determination of the optimised SHEM mesh for neutron transport calculations, in Mathematics and Computation (2005) [Google Scholar]
  13. C. De Saint Jean et al., Uncertainty evaluation of nuclear reaction model parameters using integral and microscopic measurements with the CONRAD code, J. Korean Phys. Soc. 59, 1276 (2011) [CrossRef] [Google Scholar]
  14. C. De Saint Jean et al., Estimation of multi-group cross section covariances of 238,235U, 239Pu, 241Am, 56Fe and 23Na, in PHYSOR (2012) [Google Scholar]
  15. E. Privas et al., Generation of U238 covariances matri- ces by using the integral data assimilation technique of the CONRAD code, in EPJ Web of Conferences 106 (2016) [Google Scholar]
  16. C. Wan et al., in International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (2017) [Google Scholar]
  17. C. Wan et al., Uncertainty analysis for the assembly and core simulation of BEAVRS at the HZP conditions, Nucl. Eng. Des. 315, 2011 (2017) [Google Scholar]

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