Open Access
Issue
EPJ Nuclear Sci. Technol.
Volume 7, 2021
Article Number 24
Number of page(s) 8
DOI https://doi.org/10.1051/epjn/2021027
Published online 21 December 2021
  1. “Thermal Scattering Law S(α, β): Measurement, Evaluation and Application”, International Evaluation Co-operation, Volume 42, OECD Nuclear Science NEA No. 7511 (2020) [Google Scholar]
  2. D.A. Brown et al., ENDF/B-VIII.0: The 8th Major Release of the Nuclear Reaction Data Library with CIELO-project Cross Sections, New Standards and Thermal Scattering Data, Nucl. Data Sheets 148, 1 (2018) [Google Scholar]
  3. A. Koning, D. Rochman, J. Sublet, N. Dzysiuk, M. Fleming, S. van der Marck, TENDL: complete nuclear data library for innovative nuclear science and technology, Nucl. Data Sheets 155, 1 (2019) [Google Scholar]
  4. J.I. Marquez Damian, J.R. Granada, D.C. Malaspina, CAB models for water: a new evaluation of the thermal neutron scattering laws for light and heavy water in ENDF-6 format, Ann. Nucl. Eng. 65, 280 (2014) [Google Scholar]
  5. A.J.M. Plompen et al., The joint evaluated fission and fusion nuclear data library, JEFF-3.3, Eur. Phys. J. A 56, 181 (2020) [Google Scholar]
  6. G. Noguere, J.P. Scotta, C. De Saint Jean, P. Archier, Covariance matrices of the hydrogen neutron cross sections bound in light water for the JEFF-3.1.1 neutron library, Ann. Nucl. Eng. 104, 132 (2017) [Google Scholar]
  7. C.W. Chapman, G. Arbanas, A.I. Kolesnikov, L. Leal, Y. Danon, C. Wendorff, K. Ramic, L. Liu, F. Rahnema, Methodology for generating covariance data of thermal neutron scattering cross sections, Nucl. Sci. Eng. 195, 13 (2021) [Google Scholar]
  8. J.C. Holmes, Monte Carlo Calculation of Thermal Neutron Inelastic Scattering Cross Section Uncertainties by Sampling Perturbed Phonon Spectra, PhD thesis, North Carolina State University, USA, UMI 3584310 (2014) [Google Scholar]
  9. L. Maul, Thermal Scattering Law Uncertainties and Propagation into Small Thermal Fission Reactors, PhD thesis, School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney, Australia (2018) [Google Scholar]
  10. A.J. Koning, D. Rochman, Towards sustainable nuclear energy: putting nuclear physics to work, Ann. Nucl. Energy 35, 2024 2008 [Google Scholar]
  11. D. Rochman, W. Zwermann, S.C. van der Marck, A.J. Koning, H. Sjöstrand, P. Helgesson, B. Krzykacz-Hausmann, Efficient use of Monte Carlo: uncertainty propagation, Nucl. Sci. Eng. 177, 337 (2014) [Google Scholar]
  12. J. Leppanen, PSG2 / Serpent - a Continuous-energy Monte Carlo Reactor Physics Burnup Calculation Code, VTT Technical Research Centre of Finland, Finland (2010), http://montecarlo.vtt.fi [Google Scholar]
  13. T. Goorley, MCNP 6.1.1 - Beta release Notes, Los Alamos National Laboratory, Report LA-UR-14-24680 (2014) [Google Scholar]
  14. J.P. Scotta, G. Noguere, D. Bernard, J.I. Marquez Damian, A. Santamarina, Impact of the thermal scattering law of H in H2O on the isothermal temperature reactivity coefficients for UOX and MOX fuel lattices in cold operating conditions, Eur. Phys. J. Nuclear Sci. Technol. 2, 28 (2016) [Google Scholar]
  15. O. Cabellos, E. Castro, C. Ahnert, C. Holgado, Propagation of nuclear data uncertainties for PWR core analysis, Nucl. Eng. Technol. 46, 299 (2014) [Google Scholar]
  16. D. Rochman, A.J. Koning, Random adjustment of the H in H2O neutron thermal scattering data, Nucl. Sci. Eng. 172, 287 (2012) [Google Scholar]
  17. “European Joint Programme on Radioactive Waste Management”, EU H2020-Euratom-1.2 program, Grant agreement ID: 847593, https://cordis.europa.eu/project/id/847593 [Google Scholar]
  18. “tsl-HinH2O”, J.I. Marquez Damian, J.R. Granada, D. Roubtsov, https://github.com/marquezj/tsl-HinH2O (2020) [Google Scholar]
  19. A. Hébert, DRAGON5: designing computational schemes dedicated to fission nuclear reactors for space, Int. Conf. on Nuclear and Emerging Technologies for Space, Albuquerque, NM, February 25-28 (2013) [Google Scholar]
  20. R.E. MacFarlane, A.C. Kahler, Methods for processing ENDF/B-VII with NJOY, Nucl. Data Sheets 111, 2739 (2010) [Google Scholar]
  21. M. Pecchia, D. Wicaksono, P. Grimm, A. Vasiliev, G. Perret, H. Ferroukhi, A. Pautz, Validation of Monte Carlo based burnup codes against LWR-PROTEUS Phase-II experimental data, Ann. Nucl. Eng. 97, 153 (2016) [Google Scholar]
  22. E. Kolbe, P. Grimm, A. Vasiliev, H. Ferroukhi, Assessment of MCNPX/CINDER for burnup calculations, Proc. of the Int. Conf. on Nuclear Criticality ICNC 2011, Edinburgh, Scotland, September 19-22, 2011 [Google Scholar]
  23. WIMS Library Update, https://www-nds.iaea.org/wimsd/, information obtainedon August 2021. [Google Scholar]
  24. W. Wieselquist, M. Williams, D. Wiarda, M. Pigni, U. Mertyurek, “Overview of Nuclear Data Uncertainty in Scale and Application to Light Water Reactor Uncertainty Analysis”, Oak Ridge National Laboratory report, ORNL/TM-2017/706, ORNL/TM-2017/706, December 2018 [Google Scholar]
  25. C. Wan, L. Cao, H. Wu, T. Zu, W. Shen, Propagation of nuclear data uncertainties for PWR burnup calculation, in Proceedings of The 20th Pacific Basin Nuclear Conference. PBNC 2016. Springer, Singapore [Google Scholar]
  26. M. Hursin, D. Rochman, A. Vasiliev, H. Ferroukhi, A. Pautz, Impact of various source of covariance information on integral parameters uncertainty during depletion calculations with CASMO-5, in Proceedings of the PHYSOR conference: PHYSOR 2020: Transition to a Scalable Nuclear Future, Cambridge, United Kingdom, March 29th-April 2nd, 2020 [Google Scholar]
  27. J. Park, W. Kim, M. Hursin, G. Perret, A. Vasiliev, D. Rochman, A. Pautz, H. Ferroukhi, D. Lee, Uncertainty quantification of LWR-PROTEUS Phase II experiments using CASMO-5, Ann. Nucl. Eng. 131, 9 (2019) [Google Scholar]
  28. D. Rochman, O. Leray, M. Hursin, H. Ferroukhi, A. Vasiliev, A. Aures, F. Bostelmann, W. Zwermann, O. Cabellos, C.J. Diez, J. Dyrda, N. Garcia-Herranz, E. Castro, S. van der Marcke, H. Sjöstrand, A. Hernandez, M. Fleming, J.-Ch. Sublet, L. Fiorito, NLWR fuel assemblies and a simple reactor core, Nucl. Data Sheets 139, 1 (2017) [Google Scholar]
  29. O. Leray, L. Fiorito, D. Rochman, H. Ferroukhi, A. Stankovsky, G. van den Eynde, Uncertainty propagation of fission product yields to nuclide composition and decay heat for a PWR UO2 fuel assembly, Prog. Nucl. Eng. 101, 486 (2017) [Google Scholar]
  30. D.F. da Cruz, D. Rochman, A.J. Koning, Uncertainty analysis on reactivity and discharged inventory for a Pressurized Water Reactor fuel assembly due to 235,238U nuclear data uncertainties, in Proceedings of the ICAPP conference, International Congress on Advances in National Power Plants - ICAPP 12, Chicago, USA, June 24-28 (2012) 12093 [Google Scholar]
  31. D. Rochman, A. Vasiliev, H. Ferroukhi, A. Dokhane, A. Koning, How inelastic scattering stimulates nonlinear reactor core parameter behaviour, Ann. Nucl. Eng. 112, 236 (2018) [Google Scholar]
  32. K. Shibata et al., JENDL-4.0: a new library for nuclear science and engineering, J. Nucl. Sci. Technol. 48, 1 (2011) [Google Scholar]
  33. D. Rochman, A. Vasiliev, H. Ferroukhi, M. Hursin, Analysis for the ARIANE GU1 sample: nuclide inventory and decay heat, Ann. Nucl. Eng. 160, 108359 (2021) [Google Scholar]
  34. D. Rochman, A. Vasiliev, A. Dokhane, H. Ferroukhi, Uncertainties for Swiss LWR spent nuclear fuels due to nuclear data, Eur. Phys. J. Nuclear Sci. Technol. 4, 6 (2018) [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.