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What can we learn from (n,xnγ) cross sections about reaction mechanism and nuclear structure?

Authors: Kerveno, Maëlle; Dupuis, Marc; Borcea, Catalin; Boromiza, Marian; Capote, Roberto; Dessagne, Philippe; Henning, Greg; +9 Authors

What can we learn from (n,xnγ) cross sections about reaction mechanism and nuclear structure?

Abstract

Inelastic (n,n') cross section is a key quantity to accurately simulate reactor cores, and its precision was shown to need significant improvements. To bypass the experimental difficulties to detect neutrons from (n,xn) reaction and to discriminate inelastically scattered neutrons from those following the fission process in case of fissile targets, an indirect but yet powerful method is used: the prompt γ-ray spectroscopy. Along this line, our collaboration has developed the GRAPhEME setup, optimized for actinides, at the GELINA facility to measure partial (n,xn γ) cross sections, from which the total (n,xn) cross section can be inferred. (n,xn γ) experiments with actinides are still particularly challenging, as their structure presents a high level density at low energy, and the competing neutron-induced fission reaction contaminates the γ-energy distribution. New precise measurements of the partial (n,xn γ) cross sections provide a stringent test to theoretical model and offer a way to improve them. This is a path to a better determination of the total inelastic scattering cross sections. In this contribution we discuss modeling aspects of the 238U and 182W (n,n' γ) reactions, also measured with GRAPhEME, using the three codes TALYS, EMPIRE and CoH. We will highlight the needed/expected improvements on reaction modeling and nuclear structure input.

Country
France
Keywords

[PHYS]Physics [physics], Physics, QC1-999, [PHYS] Physics [physics]

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    6
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Average
Green
gold
Related to Research communities
Energy Research