Nuclear data correlation between different isotopes via integral information

Abstract : This paper presents a Bayesian approach based on integral experiments to create correlations between different isotopes which do not appear with differential data. A simple Bayesian set of equations is presented with random nuclear data, similarly to the usual methods applied with differential data. As a consequence, updated nuclear data (cross sections, $\bar \nu$, fission neutron spectra and covariance matrices) are obtained, leading to better integral results. An example for $^{235}$U and $^{238}$U is proposed taking into account the Bigten criticality benchmark.
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Dimitri Rochman, Eric Baugé, Alexander Vasiliev, Hakim Ferroukhi, Gregory Perret. Nuclear data correlation between different isotopes via integral information. EPJ N - Nuclear Sciences & Technologies, EDP Sciences, 2018, 4, pp.7. ⟨10.1051/epjn/2018006⟩. ⟨cea-01794006⟩

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