MOX fuel enrichment prediction in PWR using polynomial models - IN2P3 - Institut national de physique nucléaire et de physique des particules Accéder directement au contenu
Article Dans Une Revue Annals of Nuclear Energy Année : 2015

MOX fuel enrichment prediction in PWR using polynomial models

Résumé

A dynamic fuel cycle simulation code models all the ingoing and outgoing material flow in all facilities of a nuclear reactor’s fleet as well as their evolutions through the different nuclear processes (irradiation, decay, chemical separation, etc.). One of the main difficulties encountered when performing such calculation comes from the fuel fabrication of reprocessed fuel such as MOX fuel. Indeed, the MOX fuel is fabricated using a plutonium base completed with depleted uranium. The amount of plutonium in the fuel will directly impact the neutron multiplication factor and its evolution through irradiation, so the duration to keep the fuel in the reactor. The present paper presents the study of different PWR MOX fuel fabrication polynomial models. Those models will allow the prediction of the amount of plutonium needed to reach a wanted burnup from the plutonium isotopics. After defining a method to generate a training sample, that is to say the set of fuel depletion calculations used to fit the polynomial models, this papers will discuss their performances on 3 different applications. On the two tested models, one linear and one quadratic, while the linear model fail to properly describe the amount of plutonium needed, the fuel fabricated, using the quadratic one, reaches the wanted burnup with a discrepancy below 2%.
Fichier non déposé

Dates et versions

in2p3-01189018 , version 1 (01-09-2015)

Identifiants

Citer

B. Mouginot, B. Leniau, Nicolas Thiollière, A. Bidaud, F. Courtin, et al.. MOX fuel enrichment prediction in PWR using polynomial models. Annals of Nuclear Energy, 2015, 85, pp.812-819. ⟨10.1016/j.anucene.2015.06.038⟩. ⟨in2p3-01189018⟩
22 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More