Abstract
Expanded graphite particle is characterized by the low density in comparison with those of bead glass and copper particles. Hydrodynamics of the irregular-shaped graphite particle swirling flows in a coaxial chamber are investigated via an improved kinetic frictional stress model. A drag force coefficient considering the effects of irregular shapes based on the artificial neural network algorithm is adopted to describe the momentum transfer between nonspherical particles and gas phases. The proposed model, algorithm, and source code for modeling and simulation are validated by measurement using spherical glass beads, and acceptable agreement is obtained. Lower sphericity particles enhance the anisotropic particle dispersions and induces the redistributions of the Reynolds stresses of the two-phase flow. Irregular-shaped particles are more sensitive to the gas followability instead of own inertia, whereas spherical particles are easier to be affected by the inlet effects. The interlock force between nonspherical particles takes great effect on particle flow than the spherical particle. The axial-axial normal stresses of sphericities of 0.63 and 0.72 are approximately 3.4 times larger than those of shear stress of spherical particle, and their axial velocities locating at near central regions are 3.0 times larger than those of sphericities.