4.6 Article

Modification of kinetic theory of granular flow for frictional spheres, Part I: Two-fluid model derivation and numerical implementation

Journal

CHEMICAL ENGINEERING SCIENCE
Volume 152, Issue -, Pages 767-782

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ces.2016.05.031

Keywords

Fluidized granular bed; Rough particles; Rotation; Two-fluid model; Kinetic theory

Funding

  1. European Research Council under its Advanced Investigator Grant scheme (Multi-scale Flows) [247298]

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We derive a kinetic theory of granular flow (KTGF) for frictional spheres in dense systems, including rotation, sliding and sticking collisions. We use the Chapman-Enskog solution procedure of successive approximations, where the single-particle velocity distribution is assumed to be nearly Maxwellian both translationally and rotationally, as assumed by McCoy et al. (1966). An expression for the first-order particle velocity distribution function is derived, which includes the effects of particle rotation and friction. Using a simple moment method, balance equations for mass, momentum and energy are derived with closure equations for viscosities, and thermal conductivities and collisional energy dissipation rates of angular and translational kinetic energy. Because the internal angular momentum changes are coupled to the flow field, the stress tensor contains anti-symmetric components which are associated with a rotational viscosity. In the resulting closure equations, the rheological properties of the particles are explicitly described in terms of the friction coefficient. The model has been incorporated into our in-house two-fluid model (TFM) code for the modeling of dense gas-solid fluidized beds. For verification, a comparison of the present model in the limit of zero friction with the original (frictionless) KTGF model is carried out. Simulation results of both models agree well. In the next part, simulation results obtained with the new model will be compared with experimental data and discrete particle model (DPM) simulations. (C) 2016 Elsevier Ltd. All rights reserved.

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