EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 239 (2020) EPJ Web Conf., 239 (2020) 11001 References
Open Access
Issue
EPJ Web Conf.
Volume 239, 2020
ND 2019: International Conference on Nuclear Data for Science and Technology
Article Number 11001
Number of page(s) 8
Section Evaluation Methodology
DOI https://doi.org/10.1051/epjconf/202023911001
Published online 30 September 2020
  1. Working Party on International Nuclear Data Evaluation Co-operation (WPEC), https://www.oecd-nea.org/science/wpec/ [Google Scholar]
  2. C.W. Reich and M.S. Moore, “Multilevel Formula for the Fission Process", Phys. Rev. 111 929 (1958). [Google Scholar]
  3. A.M. Lane and R.G. Thomas, “R-matrix theory of nuclear reactions", Rev. Mod. Phys. 30 257 (1958). [Google Scholar]
  4. M. Herman, S. Hoblit, G.P.A. Nobre, A. Palumbo, M.T. Pigni, G. Palmiotti, H. Hiruta, M. Salvatores, “Use of Covariances in a Consistent Data Assimilation for Improvement of Basic Nuclear Parameters in Nuclear Reactor Applications: From Meters to Femtometers", BNL Report BNL-99142-2013-IR, https://www.bnl.gov/isd/documents/79809.pdf [Google Scholar]
  5. M. Herman, R. Capote, B. Carlson, P. Obložinský, M. Sin, A. Trkov, W. H., and V. Zerkin, “EMPIRE: Nuclear Reaction Model Code System for Data Evaluation,” Nuclear Data Sheets, 108, 2655 (2007). [CrossRef] [Google Scholar]
  6. P. Grechanuk, M.E. Rising and T.S. Palmer, “Using Machine Learning Methods to Predict Bias in Nuclear Criticality Safety", Jour. of Computational and Theoretical Transport, 47, NOS. 4-6, 552 (2018), https://doi.org./10.1080/23324309.2019.1585877 [CrossRef] [Google Scholar]
  7. P. Grechanuk, M.E. Rising and T.S. Palmer, “Identifying Sources of Bias from Nuclear Data in MCNP6 Calculations using Machine Learning Algorithms", M&C 2019, International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, 2019-08-25, Portland, Oregon, United States. [Google Scholar]
  8. https://lansce.lanl.gov/facilities/wnr/flight-paths/chi-nu/index.php [Google Scholar]
  9. https://lansce.lanl.gov/facilities/wnr/flight-paths/fp-15R/index.php [Google Scholar]
  10. https://lansce.lanl.gov/facilities/wnr/flight-paths/fp-90L/index.php [Google Scholar]
  11. B. Becker, P. Talou, T. Kawano et al. , “ Monte Carlo Hauser-Feshbach Predictions of Prompt Fission γ Rays: Application to nth+235U, nth+239Pu, and 252Cf (sf)", Phys. Rev. C 87, 014617 (2013). [Google Scholar]
  12. L. Leal and R. Sayer, “CSEWG-2014: Resonance Evaluations for 16O for the CIELO Project.” [Google Scholar]
  13. R. Vogt, J. Randrup, J. Pruet et al. , “Event-by-event Study of Prompt Neutrons from 239Pu(n, f),” Phys. Rev. C 80, 044611 (2009). [Google Scholar]
  14. O. Litaize and O. Serot, “Investigation of Phe-nomenological Models for the Monte Carlo Simulation of the Prompt Fission Neutron and γ Emission,” Phys. Rev.C 82, 054616 (2010). [CrossRef] [Google Scholar]
  15. D.G. Madland and J.R. Nix, “New Calculation of Prompt Fission Neutron-Spectra and Average Prompt Neutron Multiplicities,” Nucl. Sci. and Eng., 81, 213-271 (1982). [CrossRef] [Google Scholar]
  16. D. Rochman and M. Herman, “WPEC-SG-49 Reproducibility in Nuclear Data Evaluation,” https://www.oecd-nea.org/science/wpec/sg49/ [Google Scholar]
  17. M. White and D. Bernard, “WPEC-SG-45 Validation of Nuclear Data Libraries (VaNDaL) Project,” https://www.oecd-nea.org/science/wpec/sg45/ [Google Scholar]
  18. I. Kodeli, “WPEC-SG-47 Use of Shielding Integral Benchmark Archive and Database for Nuclear Data Validation,” https://www.oecd-nea.org/science/wpec/sg47/index.html [Google Scholar]
  19. M. Salvatores and G. Palmiotti, “WPEC-SG-46 Efficient and Effective Use of Integral Experiments for Nuclear Data Validation.,” https://www.oecd-nea.org/science/wpec/sg46/ [Google Scholar]
  20. G. Palmiotti and M. Salvatores, “WPEC-SG-39 Methods and Approaches to Provide Feedback from Nuclear and Covariance Data Adjustment for Improvement of Nuclear Data Files,” https://www.oecd-nea.org/science/wpec/sg39/ [Google Scholar]
  21. G. Palmiotti and M. Salvatores, “WPEC-SG-33 Methods and Issues for the Combined Use of Integral Experiments and Covariance Data,” https://www.oecd-nea.org/science/wpec/sg33/ [Google Scholar]
  22. M. Salvatores, G. Palmiotti, G.A. Aliberti et al. , “Methods and Issues for the Combined Use of Integral Experiments and Covariance Data" A report by the Working Party on International Nuclear Data Evaluation Co-operation of the NEA Nuclear Science Committee NEA/NSC/WPEC/DOC(2013)445, Nuclear Energy Agency (2013). [Google Scholar]
  23. M. Salvatores, G. Aliberti, M.D. Dunn et al. , “WPEC-SG-26 Uncertainty and Target Accuracy Assessment for Innovative Systems Using Recent Covari-ance Data Evaluations,” International Evaluation Cooperation 26 ISBN 978-92-64-99053-1, OECD Nuclear Energy Agency (2008). [Google Scholar]
  24. M.B. Chadwick, R. Capote, A. Trkov et al. , “CIELO Collaboration Summary Results: International Evaluations of Neutron Reactions on Uranium, Plutonium, Iron, Oxygen and Hydrogen”, Nuclear Data Sheets, 148, 189-213 (2018). [CrossRef] [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.