Issue |
EPJ Nuclear Sci. Technol.
Volume 4, 2018
Special Issue on 4th International Workshop on Nuclear Data Covariances, October 2–6, 2017, Aix en Provence, France – CW2017
|
|
---|---|---|
Article Number | 30 | |
Number of page(s) | 6 | |
Section | Covariance Evaluation Methodology | |
DOI | https://doi.org/10.1051/epjn/2018038 | |
Published online | 14 November 2018 |
- T. Bayes, Phil. Trans. Roy. Soc. 53, 370 (1763), [reprinted in E.S. Pearson and M.G. Kendall, Studies in the History of Statistics and Probability, (Hafner, Darien, Conn., 1970)] [Google Scholar]
- E.T. Jaynes, Straight Line Fitting − a Bayesian Solution, http://bayes.wustl.edu/etj/articles/leapz.pdf (1991) [Google Scholar]
- G. Schnabel, Ph.D. Thesis, Technischen Universität Wien, 2015 [Google Scholar]
- M.T. Pigni, H. Leeb, in Proceedings of the International Workshop on Nuclear Data for the Transmutation of Nuclear Waste, GSI-Darmstadt, Germany, 2003 [Google Scholar]
- H. Leeb, D. Neudecker, T. Srdinko, Consistent procedure for nuclear data evaluation based on modeling, Nucl. Data Sheets 109, 2762 (2008) [CrossRef] [Google Scholar]
- D. Neudecker, R. Capote, H. Leeb, Impact of model defect and experimental uncertainties on evaluated output, Nucl. Instrum Meth. Phys. Res. A 723, 163 (2013) [Google Scholar]
- G. Schnabel, H. Leeb, Differential cross sections and the impact of model defects in nuclear data evaluation, EPJ Web Conf. 111, 9001 (2016) [Google Scholar]
- V. Blobel, Constrained Least Squares Methods with Correlated Data and Systematic Uncertainties (2010), http://www.desy.de/blobel/apltalk.pdf [Google Scholar]
- M.L. Williams, B.L. Broadhead, M.A. Jessee, J.J. Wagschal, TSURFER: An Adjustment Code To Determine Biases and Uncertainties in Nuclear System Responses by Consolidating Differential Data and Benchmark Integral Experiments, Version 6.2.1, Vol. III, Sect. M21, ORNL/TM-2005/39 (2016) [Google Scholar]
- B.T. Rearden, M.A. Jessee, Eds., SCALE Code System, ORNL/TM-2005/39, Version 6.2.1 (Oak Ridge National Laboratory, Oak Ridge, Tennessee, 2016) Available from Radiation Safety Information Computational Center as CCC-834 [CrossRef] [Google Scholar]
- National Nuclear Data Center, Brookhaven National Laboratory, http://nndc.bnl.gov [Google Scholar]
- F. Fröhner, Evaluation and Analysis of Nuclear Resonance Data, JEFF Report 18, 2000 [Google Scholar]
- V. Blobel (DESY), APLCON downloadable from http://www.desy.de/blobel/wwwcondl.html [Google Scholar]
- N.M. Larson, Updated Users' Guide for SAMMY: Multilevel R-matrix Fits to Neutron Data Using Bayes' Equations, ORNL/TM-9179/R8 (2008) [Google Scholar]
- F. James, M. Roos, Comput. Phys. Commun. 10, 343 (1975) [NASA ADS] [CrossRef] [PubMed] [Google Scholar]
- R. Capote, D.L. Smith, An investigation of the performance of the unified Monte Carlo method of neutron cross section data evaluation, Nucl. Data Sheets 109, 2768 (2008) [CrossRef] [Google Scholar]
- L. Fiorito et al., Nuclear data uncertainty propagation to integral responses using SANDY, Ann. Nucl. Energy 101, 359 (2017) [CrossRef] [Google Scholar]
- V. Sobes, L. Leal, G. Arbanas, B. Forget, Resonance parameter adjustment based on integral experiments, Nucl. Sci. Eng. 183, 347 (2016) [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.