2009 Annual Meeting
(515c) CFD Prediction of Uranium Tetrafluoride Particle Fluorination in Fluidized Bed Pilot
Authors
Neau, H. - Presenter, CNRS
Simonin, O. - Presenter, Institut de Mécanique des Fluides de Toulouse
Dupoizat, M. - Presenter, Areva NC
Le Goaziou, T. - Presenter, Areva NC
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Sustainability of the welfare of the societies requires adequate sources of energy. Nuclear energy represents the main support with respect to the other alternative and renewable energies. However, isotope 235 of uranium (U-235) commonly used for the manufacturing of the fuel of nuclear reactors is only about
within the natural uranium mainly comprised of U-238 (
). U-235 enrichment process usually performed by using gaseous uranium hexafluoride (
) is then needed. Among the several available processes for the production of uranium hexafluoride, the oxidation of uranium tetrafluoride (
) with fluorine (
) in fluidized bed turns out the best way (Janov & LePage (1981)), despite the limitation of gas/solid contact due to the presence of gas pockets in the bed. Advantages are excellent mass transfer, efficiency of heat transfers between phases in the bed and better control of the temperature. Simulation of such a system encompassing several complex phenomena necessitates an accurate insight of the main interactions in the bed. Basically as the reaction proceeds in the bed, mass transfer continuously arises from uranium particles towards the gas and induces momentum transfer in the same time. Moreover the accuracy of the reaction in the bed depends, in addition to the heat transfers between phases and with wall, on the correct prediction of the hydrodynamics mainly controlled by the dispersion mechanisms, the agitation of the particles and the forces ensuring the suspension of the particles. The main chemical reaction assumed in the bed is the exothermic fluorination reaction of
with
that yields
, although
may react with
to yield some intermediate products such as
,
and
in absence of fluorine and at low temperatures.
Next: Multiphase Flow Modeling Approach
KONAN Ndri Arthur 2009-05-11
![$0.7\%$](https://proceedings.aiche.org/sites/default/files/aiche-proceedings/conferences/27178/papers/160257/160257-3.gif)
![$99.3\%$](https://proceedings.aiche.org/sites/default/files/aiche-proceedings/conferences/27178/papers/160257/160257-4.gif)
![$UF_{6}$](https://proceedings.aiche.org/sites/default/files/aiche-proceedings/conferences/27178/papers/160257/160257-5.gif)
![$UF_{4}$](https://proceedings.aiche.org/sites/default/files/aiche-proceedings/conferences/27178/papers/160257/160257-6.gif)
![$F_{2}$](https://proceedings.aiche.org/sites/default/files/aiche-proceedings/conferences/27178/papers/160257/160257-7.gif)
![$UF_{4}$](https://proceedings.aiche.org/sites/default/files/aiche-proceedings/conferences/27178/papers/160257/160257-6.gif)
![$F_{2}$](https://proceedings.aiche.org/sites/default/files/aiche-proceedings/conferences/27178/papers/160257/160257-7.gif)
![$UF_{6}$](https://proceedings.aiche.org/sites/default/files/aiche-proceedings/conferences/27178/papers/160257/160257-5.gif)
![$UF_{6}$](https://proceedings.aiche.org/sites/default/files/aiche-proceedings/conferences/27178/papers/160257/160257-5.gif)
![$UF_{4}$](https://proceedings.aiche.org/sites/default/files/aiche-proceedings/conferences/27178/papers/160257/160257-6.gif)
![$U_{4}F_{17}$](https://proceedings.aiche.org/sites/default/files/aiche-proceedings/conferences/27178/papers/160257/160257-13.gif)
![$U_{2}F_{9}$](https://proceedings.aiche.org/sites/default/files/aiche-proceedings/conferences/27178/papers/160257/160257-14.gif)
![$UF_{5}$](https://proceedings.aiche.org/sites/default/files/aiche-proceedings/conferences/27178/papers/160257/160257-15.gif)
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KONAN Ndri Arthur 2009-05-11