12th Conference on Cloud Physics


Inertial clustering of droplets in high-reynolds-number laboratory turbulence

Ewe Wei Saw, Michigan Technological University, Houghton, MI; and R. A. Shaw, S. Ayyalasomayajula, P. Y. Chuang, A. Gylfason, and Z. Warhaft

Clustering of droplets in cloud due to turbulence is believed to have important consequences for warm rain formation, yet a detailed understanding is still lacking. To study the dependence of inertial particle clustering on turbulence parameters we have investigated the spatial distribution of particles in laboratory turbulence. The experimental facility is an active-grid wind tunnel, generating approximately homogeneous, isotropic turbulence with Reλ in the range of 300 to 900. Under statistically stationary conditions droplets are injected into the flow and downstream their diameter, speed, and time of arrival are measured at a point with a Phase Doppler Interferometer (PDI). Although some subtleties remain, the resulting particle pair correlation functions η(r) show droplet clustering increasing with decreasing spatial scale r and with increasing Stokes number as expected from theoretical and computational work. Specifically, the particle pair correlation function η(r) has a regime of negative power law dependence on r for rk ≤ r ≤ 10rk, where rk is the Kolmogorov microscale. Furthermore, the power-law exponent increases with the dimensionless droplet Stokes number, defined as St = (1/18)(ρd/ρ)(d/rk)2 for particle diameter d.

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Poster Session 2, Cloud Physics Poster Session II
Wednesday, 12 July 2006, 5:00 PM-7:00 PM, Grand Terrace

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