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Aerosol scavenging by drops: deriving a collection kernel from microphysical modeling

Abstract : Scavenging aerosol particles by droplets is an efficient way of removing solid particles from gases. Despite its interest for both industrial applications and occupational health, predicting realistic removal rates by means of a simple collection kernel is still a challenge (Belut (2014)). A realistic collection kernel must simultaneously take into account the aerosol dynamics and the liquid-gas interactions around a moving drop. Besides flow pattern, the capture of particles is also affected by heat transfer, phase change, electric forces, Brownian motion, and inertial effects that must be taken into account. Examining the collection kernel of Wang et al. (1978) (low inertia particles undergoing Brownian, phoretic and electrostatic scavenging) or the collection kernel of Beard et al. (1971) (inertial capture only) shows the lack of universality of scavenging kernels but also the lack of numerical or experimental reference data allowing a more general scavenging kernel to be derived. We propose to extend available reference data using numerical experiments. CFD simulations of particle-laden flows around and inside a drop at moderate Reynolds number are achieved, taking into account interfacial effects. The aerosol is modeled using Lagrangian stochastic tracking with large time steps. A global scavenging kernel is then derived from the collection efficiencies obtained in numerical simulations.
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Submitted on : Wednesday, January 25, 2017 - 10:22:35 AM
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  • HAL Id : hal-01445588, version 1



Gaël Cherrier, Emmanuel Belut, Anne Tanière, Nicolas Rimbert, Fabien Gérardin. Aerosol scavenging by drops: deriving a collection kernel from microphysical modeling. 9th International Conference on Multiphase Flow, May 2016, Firenze, Italy. ⟨hal-01445588⟩



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