Properties’ evolution of reactors loaded with MOX-MR fuels in plutonium multi-recycling scenarios in PWR

This paper studies evolutions of reactor properties when loaded with MOX-MR fuels during dynamical fuel cycle simulations. To do so, artificial neural networks, trained on a dedicated reactor depletion database, are used to estimate reactor irradiation lengths, power factors and burn-up of each discharged assembly during the scenario simulations. The studied scenario is an academic simulation of the French historical fleet that is replaced by 30 new EPRs, a fraction of which are loaded with MOX-MR fuel to balance the plutonium production in UOX fuels. Our simulations, that integrate reactor models based on full core calculations, show that 15 EPRs loaded with 50% MOX-MR assemblies are needed to stabilize the total plutonium inventory. For MOX-MR fuel fabrication, 4 spent fuel blending options at reprocessing are proposed here. Results show that the steady-state plutonium global inventory appears to depend little on spent fuel mixing proportions, which is not the case for spent fuel stockpile, highly dependent to those mixing hypothesis. The simulations also show that some blending options at processing may ensure an acceptable isotopic composition for MOX-MR fuels. Changes in plutonium isotopic quality may occur during the scenario and lead to an approximately 13% deviation of the reactor irradiation length. Consequently, using a fixed-content model for MOX-MR fuels in fuel cycle simulations imposes to control precisely the spent fuel streams at reprocessing to recover plutonium with an acceptable given quality. Unsuitable spent fuel stream flows at reprocessing lead to a strong deviation of the plutonium isotopic vector that should be compensated by an adapted plutonium content in MOX-MR fuels. If not, deviations in reactor cycle length may happen that would question the consistency of scenario simulations. Finally, this paper demonstrates the possibilities and limitations of fixed-fraction fuel fabrication models in fuel cycle simulations. This kind of model induces limited biases when fresh fuel compositions are ensured to be constant among the scenario time. Consequently, two options are viable for fuel cycle simulations : improving fuel fabrication models by adapting the plutonium content to its isotopic composition, or improving the reprocessing modeling by adapting the spent fuel blending to ensure a constant plutonium quality during the scenario simulation.