Performance assessment of adjusted nuclear data along with their covariances on the basis of fast reactor experiments

摘要

In view of fast reactor analyses, it is shown that efficient nuclear data adjustments can be obtained on a limited assimilation database consisting of just six well documented integral parameters, i.e. the central spectral indices measured in Godiva and ZPPR-9. This study uses a Generalized Linear Least-Squares (GLLS) based data assimilation method by means of Asymptotic Progressing Incremental nuclear data Adjustment (APIA) simulations with two incremental steps, one involving Godiva; the other one ZPPR-9. Consistent JEFF-3.3 and TENDL based prior data including their covariances are used; correspondingly, the assimilation leads to posterior JEFF-3.3 and TENDL data. 34 target experiments are then investigated by means of both prior and posterior data. These experiments consist of spectral indices as well as multiplication factors which pertain to 11 fast spectrum configurations including the six integral parameters which are part of the assimilation.