Open Access
EPJ Web Conf.
Volume 247, 2021
PHYSOR2020 – International Conference on Physics of Reactors: Transition to a Scalable Nuclear Future
Article Number 15011
Number of page(s) 8
Section Sensitivity & Uncertainty Methods
Published online 22 February 2021
  1. G. Rimpault, D. Plisson, J. Tommasi, R. Jacqmin, D. Verrier, and D. Biron. The ERANOS Code and Data System for Fast Reactor Neutronic Analyses. Physor 2002, (November), 2002. [Google Scholar]
  2. J. Leppänen, M. Pusa, T. Viitanen, V. Valtavirta, and Toni Kaltiaisenaho. The Serpent Monte Carlo code: Status, development and applications in 2013. Annals of Nuclear Energy, 82:142–150, 2015. [Google Scholar]
  3. M. Aufiero, M. Martin, and M. Fratoni. xGPT: Extending Monte Carlo Generalized Perturbation Theory capabilities to continuous-energy sensitivity functions. Annals of Nuclear Energy, 96:295–306, 2016. [Google Scholar]
  4. N. Abrate, M. Aufiero, S. Dulla, and L. Fiorito. Nuclear Data Uncertainty Quantification in Molten Salt Reactors with xGPT. In Proceedings of the ANS International Conference M&C2019, Portland, OR, August 25-29 2019. [Google Scholar]
  5. R. Bonifetto, S. Dulla, P. Ravetto, L. Savoldi Richard, and R. Zanino. A full-core coupled neutronic/thermalhydraulic code for the modeling of lead-cooled nuclear fast reactors. Nuclear Engineering and Design, 261:85–94, aug 2013. [Google Scholar]
  6. G. Grasso, C. Petrovich, D. Mattioli, C. Artioli, P. Sciora, D. Gugiu, G. Bandini, E. Bubelis, and K. Mikityuk. The core design of ALFRED, a demonstrator for the European lead-cooled reactors. Nuclear Engineering and Design, 278:287–301, 2014. [CrossRef] [Google Scholar]
  7. D. Rochman, A. J. Koning, S. C. Van Der Marck, A. Hogenbirk, and C. M. Sciolla. Nuclear data uncertainty propagation: Perturbation vs. Monte Carlo. Annals of Nuclear Energy, 38(5):942–952, 2011. [Google Scholar]
  8. Dan G Cacuci. Sensitivity & Uncertainty Analysis, Volume I: Theory. CRC Press, Boca Raton, 2003. [Google Scholar]
  9. R E Macfarlane, Contributing Authors, D W Muir, R M Boicourt, A C Kahler, J L Conlin, and W Haeck. The NJOY Nuclear Data Processing System, Version 2016. Technical report, 2018. [Google Scholar]
  10. D. Rochman, A.J. Koning, J.Ch. Sublet, M. Fleming, E. Bauge, S. Hilaire, P. Romain, B. Morillon, H. Duarte, S. Goriely, S.C. van der Marck, H. Sjöstrand, S. Pomp, N. Dzysiuk, O. Cabellos, H. Ferroukhi, and A. Vasiliev. The TENDL library: Hope, reality and future. EPJ Web of Conferences, 146:02006, 2017. [EDP Sciences] [Google Scholar]
  11. L. Fiorito, G. Žerovnik, A. Stankovskiy, G. Van den Eynde, and P. E. Labeau. Nuclear data uncertainty propagation to integral responses using SANDY. Annals of Nuclear Energy, 101:359–366, 2017. [Google Scholar]
  12. G F Nallo, N Abrate, S Dulla, Ravetto P., and Valerio D. Neutronic benchmark of the FRENETIC code for the multiphysics analysis of lead fast reactors. The European Physical Journal Plus, 123, 2020. [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.