Effect of interpolation kernels and grid refinement on two way--coupled point-particle simulations

Many practical applications use an Euler-Lagrange point-particle model for simulations of the dispersed phase in complex turbulent flows, such as sprays and sediment transport. For direct or large-eddy simulations of these flows, the particle size can be comparable to or larger than the grid size used to capture the smallest resolved scale of the flow, wherein the standard point-particle model is not strictly valid. This talk presents the assessment of the predictive capability of the two-way--coupled point-particle model under such conditions. The model is systematically evaluated in its ability to accurately capture particle-flow interactions, kinetic energy evolution, dissipation rate, and particle acceleration statistics for different interpolation kernels and grid resolutions. It is shown that the interpolation kernels whose width scales with the particle size perform significantly better under grid refinement than kernels whose width scales with the grid size. Convergence and predictive capability are analyzed in detail for two cases: (i) uniform flow over a stationary particle, and (ii) decaying isotropic turbulence laden with Kolmogorov-scale particles.