Effects of axial inclined guide vanes on a turbo air classifier

摘要

For a turbo air classifier, the upward axial velocity in the annular region will cause the negative influence on the stability of flow field, and it is also detrimental to material dispersion. As a result, the classification accuracy will be reduced. In order to decrease the upward axial velocity, a downward force must be introduced to offset it. According to the guiding principle of guide vanes, the axial direction of airflow will be changed when the guide vanes are inclined. In this paper an axial inclined guide vane model was designed. Four models (T-0, T-2.5, T-5, T-7.5) were established with axial inclined angles of 0 degrees, 2.5 degrees, 5 degrees and 7.5 degrees. Fluent software was used to simulate the inner flow field of different structures. The simulation results show that axial inclined guide vanes can decrease the upward axial velocity in the annular region. Especially, when the inclined angle is 2.5 degrees, the upward axial velocity is decreased and the tangential velocity is increased. This is favorable to keep the flow field stable. At the same time the classification force field is enhanced to improve the dispersion of the powders. Discrete phase simulation results reveal that particle residence time in the annular region of structure T-2.5 is shorter than it is in the annular region of structure T-0. This can reduce the collision probability of particles and the energy cost is reduced. The partial classification efficiencies of T-2.5 are higher than that of T-0. From the numerical Tromp curves, it is observed that the cut size of T-2.5 is smaller than that of T-0. The classification accuracy of T-2.5 is 90.7%, while that of T-0 is 88.5%. That means that the classification performance is improved with the new structure. Calcium carbonate classification experiment results also show that the cut size decreases by 0.97-8.42 mu m and the accuracy increases by 6%-9% for the structure T-2.5, compared to the structure T-0. Therefore, the structure T-2.5 is more favorable for classification than the structure T-0. These actual experimental results are in good agreement with the simulation results and the significance of this optimization is proved. (C) 2015 Elsevier B.V. All rights reserved.