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
|Number of page(s)||9|
|Published online||14 November 2018|
How to produce accurate inelastic cross sections from an indirect measurement method?
Université de Strasbourg CNRS,IPHC UMR
2 Horia Hulubei National Institute of Physics and Nuclear Engineering, Bucharest-Magurele, Romania
3 CEA, DAM, DIF, Arpajon, France
4 European Commission, Joint Research Centre, Geel, Belgium
* e-mail: email@example.com
Received in final form: 8 March 2018
Accepted: 14 May 2018
Published online: 14 November 2018
Inelastic reactions ((n,xn) for x ≥ 1) play a key role in reactor cores as they influence the slowing down of the neutrons. A reactor neutron energy spectrum depends thus on this process which is in strong competition with elastic scattering and fission; a nice example is the case of 238U. Inelastic scattering (x = 1) impacts keff and radial power distribution in the nuclear reactor. For several years, it has been shown that the knowledge of the inelastic cross sections in nuclear databases is not good enough to accurately simulate reactor cores and a strong demand for new measurements has emerged with very tight objectives (only a few percent) for the uncertainties on the cross section. To bypass the well-known experimental difficulty to detect neutrons, the prompt γ-ray spectroscopy method is a powerful but indirect way to obtain inelastic cross sections. Our collaboration has used this method for more than ten years and have produced a lot of (n,n′γ) cross sections for nuclei from 7Li to 238U. In this article, we will first discuss the issues of the prompt γ-ray spectroscopy regarding the control of all the uncertainties involved in the (n,n′γ) cross section estimation. Secondly, we will focus on the role of theoretical modeling which, in certain cases, is crucial to reach the objectives of a few percent uncertainty on the (n,n′) cross sections.
© M. Kerveno et al., published by EDP Sciences, 2018
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