4.7 Article

PR-DNS investigation on momentum and heat transfer of two interactive non-spherical particles in a fluid

Journal

POWDER TECHNOLOGY
Volume 427, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.powtec.2023.118791

Keywords

PR-DNS; Interactive particles; Porous particle; Drag coefficient; Average Nusselt number

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Particle-resolved direct numerical simulations (PR-DNS) are used to study the momentum and heat transfer of two interactive non-spherical porous particles. Various parameters of the leading particle, such as aspect ratio, orientation, and porosity, are shown to affect the drag coefficient and average Nusselt number of the trailing particle. The results reveal different trends depending on the specific conditions, such as the shape of the leading particle and the distance between the particles.
Particle-resolved direct numerical simulations (PR-DNS) are carried out to investigate the momentum (quantified by the drag coefficient, Cd) and heat (quantified by the average Nusselt number, Nu) transfer of two interactive non-spherical porous particles in a fluid. The leading particle (relevant parameters marked by a subscript 'L') is a spheroid with different shapes and porosities, and the trailing particle (relevant parameters marked by a subscript 'T') is a sphere. The numerical model is firstly well validated against previously published data and then the effects of the leading particle aspect ratio (ArL), orientation (BL), porosity (eL), distance (L) and Reynolds number (Re) are stressed, respectively, on the CdT and NuT of the trailing one. New findings from the current numerical results are: CdT increases when increasing BL for a leading oblate spheroid but decreases with BL for a leading prolate spheroid. When BL = 0 degrees, CdT increases with increasing ArL but the opposite trend is found when BL = 90 degrees. When BL = 45 degrees and the distance between the two particles is small, CdT increases with the increase of ArL. However, when the distance between the two interactive particles gets larger, CdT first decreases and then increases with ArL. When the leading particle is a spheroid and the two interactive particles are far away from each other, NuT increases first and then decreases with increasing BL. When the leading particle is a spheroid and the two interactive particles are close to each other, the changing trend of NuT with BL can be more greatly influenced by & epsilon;L. That is, when & epsilon;L = 0.9, NuT increases with & theta;L for a leading oblate spheroid but decreases with & theta;L for a leading prolate spheroid. On the contrary, when & epsilon;L = 0 and & epsilon;L = 0.5, NuT increases first and then decreases with & theta;L for both leading oblate and prolate spheroids. When & theta;L = 45 degrees and the two interactive particles are close to each other, a large & epsilon;L of the leading spheroid plays an important role in affecting NuT which makes it drop significantly. When & theta;L = 45 degrees and the two interactive particles are far away from each other, and the effects of a leading inclined spheroid on both CdT and NuT are weaker than that of a leading sphere. Generally speaking, both CdT and NuT decrease with increasing & epsilon;L. At last, a back propagation neural network (BPNN) model is established in this study for prediction purposes.

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