Spatial clustering of polydisperse inertial particles in turbulence: II. Comparing simulation with experiment

Particles that are heavy compared to the fluid in which they are embedded (inertial particles) tend to cluster in turbulent flow, with the degree of clustering depending on the particle Stokes number. The phenomenon is relevant to a variety of multiphase flows, including atmospheric clouds; in most realistic systems, particles have a continuous distribution of sizes and therefore the clustering of 'polydisperse' particle populations is of special relevance. In this part of the study, measurements of spatial correlations of particles in high-Reynolds-number turbulence are compared with the results of a direct numerical simulation of particle-laden turbulence. The experimentally derived radial distribution functions (RDFs) exhibit a pronounced scale break at approximately 10-30 times the Kolmogorov scale, with large-scale clustering arising from 'scalar mixing' of the droplet field, and smaller-scale clustering depending on the particle Stokes numbers. A procedure is outlined for isolating the RDF due to inertial clustering from that resulting from large-scale mixing. Reasonable agreement between the experiment and the direct numerical simulations (DNS) is obtained for St less than or similar to 0.3 when particle Stokes number distributions in the DNS match those existing in the experiments. The experimental RDFs are consistent with the flattening or saturation scale appearing for bidisperse particles, but as in the companion paper, also support the 'saturation' effect in the asymmetric response of the power-law slope. The evidence for a universal scale break, as observed in both the DNS and the experiments, suggests that the pre-factor in the theoretical expression for the RDF is inherently tied to the power-law exponent, and an empirical form for this is given. Finally, no strong influence of the turbulence Reynolds number was observed for the clustering phenomenon. The consistency between the carefully analyzed DNS and experiments, in terms of St dependence, dissipation-range scale break and saturation of clustering for polydisperse particles, provides an indirect confirmation of the diffusion-drift theory of Chun et al (2005 J. Fluid Mech. 536 219-51).