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 âL') is a spheroid with different shapes and porosities, and the trailing particle (relevant parameters marked by a subscript âT') 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 (ΞL), porosity (ΔL), 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 ΞL for a leading oblate spheroid but decreases with ΞL for a leading prolate spheroid. When ΞL = 0°, CdT increases with increasing ArL but the opposite trend is found when ΞL = 90°. When ΞL = 45° 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 ΞL. When the leading particle is a spheroid and the two interactive particles are close to each other, the changing trend of NuT with ΞL can be more greatly influenced by ΔL. That is, when ΔL = 0.9, NuT increases with ΞL for a leading oblate spheroid but decreases with ΞL for a leading prolate spheroid. On the contrary, when ΔL = 0 and ΔL = 0.5, NuT increases first and then decreases with ΞL for both leading oblate and prolate spheroids. When ΞL = 45°and the two interactive particles are close to each other, a large ΔL of the leading spheroid plays an important role in affecting NuT which makes it drop significantly. When ΞL = 45°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 ΔL. At last, a back propagation neural network (BPNN) model is established in this study for prediction purposes.
Read full abstract