Open Access
Issue |
EPJ Web Conf.
Volume 247, 2021
PHYSOR2020 – International Conference on Physics of Reactors: Transition to a Scalable Nuclear Future
|
|
---|---|---|
Article Number | 15006 | |
Number of page(s) | 10 | |
Section | Sensitivity & Uncertainty Methods | |
DOI | https://doi.org/10.1051/epjconf/202124715006 | |
Published online | 22 February 2021 |
- L. Wang, J. Guo, and F. Li, “Direct Evaluation of Nuclear Data Uncertainty Propagation in Pebble-bed HTR Core,” in PHYSOR 2016, Sun Valley, Idaho, 2016, p. 2394. [Google Scholar]
- C. HAO, Y. CHEN, J. GUO et al., “Mechanism analysis of the contribution of nuclear data to the keff uncertainty in the pebble bed HTR,” Annals of Nuclear Energy, vol. 120, pp. 857–868, 2018. [Google Scholar]
- L. Fiorito, C. J. Diez, O. Cabellos et al., “Fission yield covariance generation and uncertainty propagation through fission pulse decay heat calculation,” Annals of Nuclear Energy, vol. 69, pp. 331–343, 2014. [Google Scholar]
- O. Leray, L. Fiorito, D. Rochman et al., “Uncertainty propagation of fission product yields to nuclide composition and decay heat for a PWR UO2 fuel assembly,” Progress in Nuclear Energy, vol. 101, pp. 486–495, 2017. [Google Scholar]
- H. J. Rütten, K. A. Haas, H. Brockmann et al., “V.S.O.P. (99/05) Computer code system for reactor physics and fuel cycle simulation,” Forschungszentrum Jülich GmbH, ISR, Jül – 4189, 2005. [Google Scholar]
- Z. Zhang, Z. Wu, D. Wang et al., “Current status and technical description of Chinese 2×250MWth HTR-PM demonstration plant,” Nuclear Engineering and Design, vol. 239, no. 7, pp. 1212–1219, 2009. [Google Scholar]
- Z. Zhang, Y. Dong, F. Li et al., “The Shandong Shidao Bay 200 MW e High-Temperature Gas-Cooled Reactor Pebble-Bed Module (HTR-PM) Demonstration Power Plant: An Engineering and Technological Innovation,” Engineering, vol. 2, no. 1, pp. 112–118, 2016. [Google Scholar]
- T. R. E. a. B. F. Rider, “Evaluation and Compilation of Fission Product Yields 1993,” Los Alamos National Laboratory1994. [Google Scholar]
- D. L. Smith, Probability, statistics, and data uncertainties in nuclear science and technology. 1991. [Google Scholar]
- T. Kawano and M. B. Chadwick, “Estimation of 239Pu independent and cumulative fission product yields from the chain yield data using a Bayesian technique,” Journal of Nuclear Science and Technology, vol. 50, no. 10, pp. 1034–1042, 2013. [Google Scholar]
- M. T. Pigni, M. W. Francis, and I. C. Gauld, “Investigation of Inconsistent ENDF/B-VII.1 Independent and Cumulative Fission Product Yields with Proposed Revisions,” Nuclear Data Sheets, vol. 123, pp. 231–236, 2015. [Google Scholar]
- M. F. James, R. W. Mills, and D. R. Weaver, “A new evaluation of fission product yields and the production of a new library (UKFY2) of independent and cumulative yields,” Progress in Nuclear Energy, vol. 26, no. 1, pp. 1–29, 1991. [Google Scholar]
- D. L. Smith, D. G. Naberejnev, and L. A. Van Wormer, “Large errors and sever conditions,” Nuclear Instruments and Methods in Physics Research A, vol. 488, no. 1-2, pp. 342–361, 2002. [Google Scholar]
- F. H. Fröhner, “Assigning Uncertainties to Scientific Data,” Nuclear Science and Engineering, vol. 126, no. 1, pp. 1–18, 1997. [Google Scholar]
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