Implementation of a cross section evaluation methodology for safety margins analysis: Post processing and data analysis for the capture cross section measurements of odd Gadolinium isotopes

The second and third generation Light Water Reactors (LWRs) are often equipped with fuel with gadolinium-enriched pins with the aim of extending the in-pile fuel life cycle without introducing any new safety issues at the Beginning Of Life (BOL). Gadolinium odd isotopes cross sections are crucial in assessing the neutron budget which constraints the economic performance and the safety features of a reactor core. This technical report follows two previous Reports, the first one discusses the need of a new evaluation of the neutron capture cross-sections of 155Gd and 157Gd using new experimental data, and the second one which describes the methodologies used and the experimental campaign carried out at the European Organization for Nuclear Research (CERN) neutron time-of-flight facility n_TOF during 2016. In this last work, we report the final results of the measurements on 157Gd and 155Gd, together with a resonance analysis above the resolved resonance region. The capture cross sections of 155Gd and 157Gd at neutron kinetic energy of 0.0253 eV have been estimated to be 62.2±2.2 kb and 239.8±9.8 kb respectively, thus up to 6% different relative to the ones reported in the nuclear data libraries. A resonance shape analysis has been performed in the resolved resonance region up to 180 eV and 300 eV, respectively, and average resonance parameters have been found in good agreement with evaluations. Above these energies the observed resonance-like structures in the cross section have been tentatively characterised in terms of resonance energy and area up to 1 keV. The collaboration of the National Institute for Nuclear Physics (INFN) and the contribution of Cristian Massimi, Gianni Vannini and Alice Manna at the Department of Physics and Astronomy of the University of Bologna is aknowledged. In addition, the authors aknowledge the contribution of Mario Mastromarco (CERN), Annamaria Mazzone (CNR and INFN/Bari) and Giulia Clai (ENEA) for their contribution to the data analysis.