Modeling of Reprocessed Uranium Enrichment for Nuclear Scenarios Simulations

Reprocessed uranium recycling in PWR is a key component of the uranium and plutonium multi-recycling strategies in PWR foreseen in the French fleet by the year 2050.Reprocessed uranium (RepU) recovered at UOX spent fuel reprocessing usually contains a significant fraction of 235 U.However, RepU enrichment process also results in an increase of the concentration of other Uranium isotopes, such as 234 U and 236 U. To acquire insights on RepU recycling strategies in PWR and their potential deployment in the French nuclear fleet, nuclear scenario simulations are performed.This paper focuses on the development of a RepU enrichment model for the nuclear scenario simulation code CLASS.This model is based on iterative bisection method calculating the 235 U enrichment in enriched reprocessed uranium (ERU) fresh fuel required to reach a discharge target burn-up in PWR depending on the RepU isotopic composition.This algorithm relies on an artificial neural network estimator of the maximum achievable burn-up depending on ERU fresh fuel composition, based on a PWR ERU depletion calculation database.This algorithm is then applied to a sample of RepU isotopic compositions from spent cooled PWR UOX fuels, highlighting the impact of 236 U fraction in RepU on the required over-enrichment in ERU fresh fuel.