Issue
EPJ Nuclear Sci. Technol.
Volume 12, 2026
Special Issue on ‘Overview of recent advances in HPC simulation methods for nuclear applications’, edited by Andrea Zoia, Elie Saikali, Cheikh Diop and Cyrille de Saint Jean
Article Number 4
Number of page(s) 11
DOI https://doi.org/10.1051/epjn/2025068
Published online 16 January 2026
  1. F.B. Brown, T.M. Monte, Sutton Carlo fundamentals, No. KAPL-4823, Knolls Atomic Power Lab. (KAPL), New York, United States (1996) [Google Scholar]
  2. H. Rief, Generalized Monte Carlo perturbation algorithms for correlated sampling and a second-order Taylor series approach, Ann. Nucl. Energy 11, 455 (1984) [CrossRef] [Google Scholar]
  3. Y. Nagaya, T. Mori, Impact of perturbed fission source on the effective multiplication factor in Monte Carlo perturbation calculations, J. Nucl. Sci. Technol. 42, 428 (2005) [CrossRef] [Google Scholar]
  4. Y. Nagaya, T. Mori, Estimation of sample reactivity worth with differential operator sampling method, Prog. Nucl. Sci. Technol. 2, 842 (2011) [CrossRef] [Google Scholar]
  5. B.C. Kiedrowski, F.B. Brown, P.P.H. Wilson, Adjoint-weighted tallies for k-eigenvalue calculations with continuous-energy Monte Carlo, Nucl. Sci. Eng. 168, 226 (2011) [CrossRef] [Google Scholar]
  6. B.C. Kiedrowski, F.B. Brown, Comparison of the Monte Carlo adjoint-weighted and differential operator perturbation methods, Prog. Nucl. Sci. Technol. 2, 836 (2011) [CrossRef] [Google Scholar]
  7. H.J. Shim, C.H. Kim, Adjoint sensitivity and uncertainty analyses in Monte Carlo forward calculations, J. Nucl. Sci. Technol. 48, 1453 (2011) [CrossRef] [Google Scholar]
  8. H.J. Shim, C.H. Kim, Monte Carlo fuel temperature coefficient estimation by an adjoint-weighted correlated sampling method, Nucl. Sci. Eng. 177, 184 (2014) [CrossRef] [Google Scholar]
  9. N. Terranova, D. Mancusi, A. Zoia, New perturbation and sensitivity capabilities in TRIPOLI-4®, Ann. Nucl. Energy 121, 335 (2018) [CrossRef] [Google Scholar]
  10. G. Truchet, P. Leconte, J.M. Palau, P. Archier, J. Tommasi, A. Santamarina, Y. Peneliau, A. Zoia, E. Brun, Sodium void reactivity effect analysis using the newly developed exact perturbation theory in Monte-Carlo code TRIPOLI-4®, PHYSOR 2014, Kyoto, Japan (2014) [Google Scholar]
  11. G. Truchet, P. Leconte, Small sample reactivity worths calculation exact perturbation theory and monte carlo transport, M&C2019, Portland, United States (2019) [Google Scholar]
  12. D. Tuya, Y. Nagaya, Adjoint-weighted correlated sampling for k-eigenvalue perturbation in Monte Carlo calculation, Ann. Nucl. Energy 169, 108919 (2022) [CrossRef] [Google Scholar]
  13. H. Hurwitz, in Naval Reactor Physics Handbook, edited by A. Radkowsky (U.S. Atomic Energy Commission, 1964), Vol. 1, p. 864 [Google Scholar]
  14. H. Lee, W. Kim, P. Zhang, M. Lemaire, A. Khassenov, J. Yu, Y. Jo, J. Park, D. Lee, MCS–A Monte Carlo particle transport code for large-scale power reactor analysis, Ann. Nucl. Energy 139, 107276 (2020) [CrossRef] [Google Scholar]
  15. N. Horelik, B. Herman, M. Ellis, K. Smith, MIT Benchmark for Evaluation and Validation of Reactor Simulations (BEAVRS), Version 2.0.2, MIT Computational Reactor Physics Group (2018) [Google Scholar]
  16. J. Jang, W. Kim, S. Jeong, E. Jeong, J. Park, M. Lemaire, H. Lee, Y. Jo, P. Zhang, D. Lee, Validation of UNIST Monte Carlo code MCS for criticality safety analysis of PWR spent fuel pool and storage cask, Ann. Nucl. Energy 114, 495 (2018) [CrossRef] [Google Scholar]
  17. D.L. Ta, S.G. Hong, D. Lee, Validation of UNIST Monte Carlo code MCS for criticality safety calculations with burnup credit through MOX criticality benchmark problems, Nucl. Eng. Technol. 53, 19 (2021) [Google Scholar]
  18. S. Yuk, APR1400 Reactor Core Benchmark Problem Book, Technical Report RPL-INERI-CA-004, KAERI, Daejon, South Korea, (2019) [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.