4.6 Article

Extension and validation of the particle segregation model for bubbling gas-fluidized beds of binary mixtures

期刊

CHEMICAL ENGINEERING SCIENCE
卷 97, 期 -, 页码 139-151

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ces.2013.04.012

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Fluidization; Mixing; Multiphase flow; Particulate processes; Drag force; Segregation

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The present work elaborates on the Particle Segregation Model (PSM) recently developed (Di Maio et al., 2012. Powder Technology 226, 180-188) to address the prediction of the segregation direction in fluidized beds, i.e. the flotsam/jetsam behavior of the solid components in the bubbling bed. In the original derivation, the PSM was obtained in the limit of viscous flow, i.e. for particle Reynolds' number up to 5. In the present contribution we prove that its formulation is more general, and that it can be extended without modifications to any flow regime. Starting from the force balance on one particle, the competition of mechanisms in mixtures whose components' size difference effect counteracts that of density difference is contemplated. The macroscopic result is expressed, analytically and without adjustable parameters, in terms of the size ratio, density ratio, voidage and bed composition. The knowledge of the segregation direction can be combined with a comparison of the pure components' minimum fluidization velocities yielding, although only under the complete segregation hypothesis, a prediction of the different segregation/fluidization patterns. Extensive model validation is carried out by: (i) comparison of the predicted segregation direction against many experimental observations reported in the literature (53 systems) and with tests (7 systems) carried out in the present work; (ii) visualization in a 2D rig of segregated beds predicted to exhibit a layer fluidized below the stagnant rest of the material; (iii) observation of float/sink behavior of few large spheres immersed in the bubbling bed. Agreement for nearly all the considered systems is found, with remarkable segregation reversal predictions with bed composition for three of them. (c) 2013 Elsevier Ltd. All rights reserved.

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