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)||7|
|Published online||14 November 2018|
From fission yield measurements to evaluation: status on statistical methodology for the covariance question
LPSC, Université Grenoble-Alpes, CNRS/IN2P3,
Grenoble Cedex, France
2 CEA, DEN, DER, SPRC, LEPh, Cadarache Center, 13108 Saint Paul lez Durance, France
* e-mail: email@example.com
Received in final form: 21 March 2018
Accepted: 14 May 2018
Published online: 14 November 2018
Studies on fission yields have a major impact on the characterization and the understanding of the fission process and are mandatory for reactor applications. Fission yield evaluation represents the synthesis of experimental and theoretical knowledge to perform the best estimation of mass, isotopic and isomeric yields. Today, the output of fission yield evaluation is available as a function of isotopic yields. Without the explicitness of evaluation covariance data, mass yield uncertainties are greater than those of isotopic yields. This is in contradiction with experimental knowledge where the abundance of mass yield measurements is dominant. These last years, different covariance matrices have been suggested but the experimental part of those are neglected. The collaboration between the LPSC Grenoble and the CEA Cadarache starts a new program in the field of the evaluation of fission products in addition to the current experimental program at Institut Laue-Langevin. The goal is to define a new methodology of evaluation based on statistical tests to define the different experimental sets in agreement, giving different solutions for different analysis choices. This study deals with the thermal neutron induced fission of 235U. The mix of data is non-unique and this topic will be discussed using the Shannon entropy criterion in the framework of the statistical methodology proposed.
© B. Voirin et al., published by EDP Sciences, 2018
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