Application of data assimilation in searching better lattice-physics parameters of fuel assembly

Abstract

This study aims to apply the data assimilation technique to adjust the fuel enrichment to find a better performance of the fuel assembly lattice-physics parameters. In this study, the STARU data assimilation, which can deal with the highly non-linear system behaviors and many parameters, was implemented; and MCNP6 was used to evaluate the lattice-physics parameters of the fuel assembly. Furthermore, restriction and non-restriction sampling algorithms were employed to efficiently find the enhanced candidates for the NuScale fuel assembly. We found that the improvements were up to 0.1 w/o, and the fuel depletion of the optimal candidate was compared well with the equivalenced enrichment of the typical fuel assembly. Eventually, the conceptual design configuration was proposed using the alpha and theta requirements for adjusting the fuel rod dimensions and enrichments, methodically. Consequently, the proposed conceptual design illustrated an excellent performance of the lattice-physics parameters such as high k∞-value and low PPPF. Nevertheless, the burn-up performance of the proposed conceptual design was slightly poor compared with the NFAC-01. Future studies should examine the application of neutron absorber materials to overcome this limitation.