Open Access
| Issue |
EPJ Nuclear Sci. Technol.
Volume 1, 2015
|
|
|---|---|---|
| Article Number | 17 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/epjn/e2015-50022-3 | |
| Published online | 16 December 2015 | |
- B. Bouriquet et al., Differential influence of instruments in nuclear core activity evaluation by data assimilation, Nucl. Instrum. Methods Phys. Res. A 626-627, 97 (2011) [CrossRef] [Google Scholar]
- B. Bouriquet et al., Robustness of nuclear core activity reconstruction by data assimilation, Nucl. Instrum. Methods Phys. Res. A 629, 282 (2011) [CrossRef] [Google Scholar]
- D.G. Cacuci, M. Ionescu-Bujor, Best-estimate model calibration and prediction through experimental data assimilation - I: Mathematical framework, Nucl. Sci. Eng. 165, 18 (2010) [CrossRef] [Google Scholar]
- D. Petruzzi, G. Cacuci, F. d’Auria, Best-estimate model calibration and prediction through experimental data assimilation - II: Application to a blowdown benchmark experiment, Nucl. Sci. Eng. 165, 45 (2010) [CrossRef] [Google Scholar]
- J.P. Bouriquet, A.R. Cugnart, Optimal design of measurement network for neutronic activity field reconstruction by data assimilation, Nucl. Instrum. Methods Phys. Res. A 664, 117 (2012) [CrossRef] [Google Scholar]
- T. Clerc et al., An advanced computational scheme for the optimization of 2D radial reflectors in pressurized water reactors, Nucl. Eng. Des. 273, 560 (2014) [CrossRef] [Google Scholar]
- F. Bouttier, P. Courtier, Data assimilation concepts and methods, Meteorological training course lecture series, ECMWF, 1999 [Google Scholar]
- E. Kalnay, Atmospheric modeling, data assimilation and predictability (Cambridge University Press, 2003) [Google Scholar]
- F. Rabier et al., The ECMWF operational implementation of four-dimensional variational assimilation. Part I: Experimental results with simplified physics, Q. J. R. Meteorol. Soc. 126, 1143 (2000) [CrossRef] [Google Scholar]
- O. Talagrand, Assimilation of observations, an introduction, J. Meteorol. Soc. Japan 75, 191 (1997) [Google Scholar]
- K. Ide, P. Courtier, M. Ghil, A.C. Lorenc, United notation for data assimilation: operational, sequential and variational, J. Meteorol. Soc. Japan 75, 181 (1997) [Google Scholar]
- D.F. Parrish, J.C. Derber, The National Meteorological Center's spectral statistical interpolation analysis system, Mon. Weather Rev. 120, 1747 (1992) [CrossRef] [Google Scholar]
- R. Todling, S.E. Cohn, Suboptimal schemes for atmospheric data assimilation based on the Kalman filter, Mon. Weather Rev. 122, 530 (1994) [Google Scholar]
- S.M. Uppala et al., The ERA-40 re-analysis, Q. J. R. Meteorol. Soc. 131, 2961 (2005) [Google Scholar]
- E. Kalnay et al., The NCEP/NCAR 40-year reanalysis project, Bull. Am. Meteorol. Soc. 77, 437 (1996) [Google Scholar]
- G.J. Huffman et al., The Global Precipitation Climatology Project (GPCP) combined precipitation dataset, Bull. Am. Meteorol. Soc. 78, 5 (1997) [CrossRef] [Google Scholar]
- S. Massart, S. Buis, P. Erhard, G. Gacon, Use of 3DVAR and Kalman filter approaches for neutronic state and parameter estimation in nuclear reactors, Nucl. Sci. Eng. 155, 409 (2007) [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.