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Experimental and numerical investigation of inertial particle clustering in isotropic turbulence

Published online by Cambridge University Press:  26 March 2008

JUAN P. L. C. SALAZAR
Affiliation:
Sibley School of Mechanical & Aerospace Engineering, Cornell University, Ithaca, NY 14853–7501, USA
JEREMY DE JONG
Affiliation:
Mechanical & Aerospace Engineering, State University of New York at Buffalo, Buffalo, NY 14260–4400, USA
LUJIE CAO
Affiliation:
Mechanical & Aerospace Engineering, State University of New York at Buffalo, Buffalo, NY 14260–4400, USA
SCOTT H. WOODWARD
Affiliation:
Mechanical & Aerospace Engineering, State University of New York at Buffalo, Buffalo, NY 14260–4400, USA
HUI MENG
Affiliation:
Mechanical & Aerospace Engineering, State University of New York at Buffalo, Buffalo, NY 14260–4400, USA
LANCE R. COLLINS*
Affiliation:
Sibley School of Mechanical & Aerospace Engineering, Cornell University, Ithaca, NY 14853–7501, USA
*
Author to whom correspondence should be addressed: LC246@cornell.edu

Abstract

This paper presents the first detailed comparisons between experiments and direct numerical simulations (DNS) of inertial particle clustering in nearly isotropic ‘box turbulence’. The experimental system consists of a box 38cm in each dimension with fans in the eight corners that sustain nearly isotropic turbulence in the centre of the box. We inject hollow glass spheres with a mean diameter of 6 μm and measure the locations of several hundred particles in a 1 cm3 volume in the centre of the box using three-dimensional digital holographic particle imaging. We observe particle concentration fluctuations that result from inertial clustering (sometimes called ‘preferential concentration’). The radial distribution function (RDF), a statistical measure of clustering, has been calculated from the particle position field. We select this measure because of its relevance to the collision kernel for particles. DNS of the equivalent system, with nearly perfect parameter overlap, have also been performed. We observe good agreement between the RDF predictions of the DNS and the experimental observations, despite some challenges in the interpretation of the experiments. The results provide important guidance on ways to improve the measurement.

Type
Papers
Copyright
Copyright © Cambridge University Press 2008

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