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 | 21 | |
Number of page(s) | 9 | |
Section | Experimental Uncertainties | |
DOI | https://doi.org/10.1051/epjn/2018026 | |
Published online | 14 November 2018 |
https://doi.org/10.1051/epjn/2018026
Regular Article
Template for estimating uncertainties of measured neutron-induced fission cross-sections
1
Los Alamos National Laboratory,
Los Alamos,
NM
87545, USA
2
Argonne National Laboratory,
Coronado,
CA
92118, USA (retired)
3
NAPC-Nuclear Data Section, International Atomic Energy Agency,
Vienna
1400, Austria
* e-mail: dneudecker@lanl.gov
Received:
31
October
2017
Received in final form:
29
January
2018
Accepted:
14
May
2018
Published online: 14 November 2018
A template for estimating uncertainties (unc.) of measured neutron-induced fission, (n,f), cross-sections (cs) is presented. This preliminary template not only lists all expected unc. sources but also supplies ranges of unc., estimates for correlations between unc. of the same and different experiments which can be used if the information is nonexistent. If this template is applied systematically when estimating experimental covariances for an evaluation, it may help in pinpointing missing unc. for individual datasets, identifying unreasonably low unc., and estimating correlations between different experimental datasets. Thus, a detailed unc. estimate – usually, a time-intensive procedure – can be undertaken more consistently and efficiently. As an example, it is shown that unc. and correlations of 239Pu(n,f) by Merla et al. [Proceedings of the Conference on Nuclear Data for Science and Technology 1991 Jülich (Springer-Verlag, Berlin, 1992) pp. 510–513], which are questionably low in the GMA database underlying the neutron cs standards evaluations, are distinctly larger at 14.7 MeV and more strongly correlated if this template is used for reestimating the associated covariances.
© D. Neudecker et al., published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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