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Experimental and numerical investigations of particle clustering in isotropic turbulence

Workshop on Stirring and Mixing: The Lagrangian Approach Lorentz Center Leiden, The Netherlands August 21-30, 2006. Experimental and numerical investigations of particle clustering in isotropic turbulence. International Collaboration for Turbulence Research (ICTR).

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Experimental and numerical investigations of particle clustering in isotropic turbulence

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  1. Workshop on Stirring and Mixing: The Lagrangian Approach Lorentz Center Leiden, The Netherlands August 21-30, 2006 Experimental and numerical investigations of particle clustering in isotropic turbulence International Collaboration for Turbulence Research (ICTR)

  2. Particle Clustering in Turbulence Vortices Strain Region • Maxey (1987); Squires & Eaton (1991); Wang & Maxey (1993) • Shaw, Reade, Verlinde & Collins (1997) • Falkovich, Fouxon & Stepanov (2002); Zaichik & Alipchenkov (2003); Chun, Koch, Rani, Ahluwalia & Collins (2005)

  3. Turbulence in Clouds Buoyancy Cloud Condensation Nuclei (CCN)

  4. d2 Law mass energy • Current microphysical models predict • too slow “condensational” growth • too narrow cloud droplet distributions Shaw (2003)

  5. Beard & Ochs (1993) “… At this rate, we are quite a way off from being able to predict, on firm micro-physical grounds, whether it will rain.” 0.1 mm 1 mm 10 mm

  6. Clouds in Climate Models Visible Wavelengths Infra Red High, cold clouds Low, warm clouds Distribution of cloud cover profoundly influences global energy balance Raymond Shaw

  7. Collision Kernel Particle clustering impacts the RDF Sundaram & Collins (1997); Wang, Wexler & Zhou (1998)

  8. Monodisperse clustering: drift Chun, Koch, Sarma, Ahluwalia & Collins, JFM 2005

  9. Monodisperse clustering: diffusion Chun, Koch, Sarma, Ahluwalia & Collins, JFM 2005

  10. Monodisperse clustering: RDF St = 0.7 Chun, Koch, Sarma, Ahluwalia & Collins, JFM 2005

  11. Bidisperse clustering Chun, Koch, Sarma, Ahluwalia & Collins, JFM 2005

  12. Bidisperse clustering Chun, Koch, Sarma, Ahluwalia & Collins, JFM 2005

  13. Bidisperse clustering: stationary Chun, Koch, Sarma, Ahluwalia & Collins, JFM 2005

  14. Experiments and Simulations RDF Measurements Direct Numerical Simulations

  15. Turbulence Chamber

  16. Flow Characterization Conditions at 6 Fan Speeds (MKS)

  17. Metal-Coated Hollow Glass Spheres Mean = 6 microns STD = 3.8 microns 1-10 particles/cm3 FV = 10-7

  18. Measurements of RDF Wind Tunnel Turbulence Box Saw, Shaw, Ayyalasomayajula, Chuang Gylfason, Warhaft (2006) Wood, Hwang & Eaton (2005)

  19. Why 3D? 2D Sampling 1D Sampling Relations Holtzer & Collins (2002)

  20. 3D Particle Position Measurement Techniques • Particle Tracking Velocimetry (PTV) • Advantages – Lagrangian particle information • Disadvantages – Limited particle number density. • Holographic Particle Image Velocimetry (HPIV) • Advantages – Better particle number density than PTV, larger 3D volume than Stereo PIV • Disadvantages – Cannot resolve time evolution of particles.

  21. Hybrid Digital HPIV Nd:Yag Laser 532 nm Numerical Reconstruction Intensity-Based Particle Extraction Variable Beam Attenuator Beam Expander Reference Beam • n • F • a • a • F • n 40 cm • Z 1k x 1k CCD • n • a • F (4 cm)3 Volume • Optical Window

  22. Particle Concentration and Phase Averaging

  23. Size Distribution Evolution

  24. Time Dependence of RDF

  25. Direct Numerical Simulations • 1283 Grid Points • Rl = 80 • 1.2 Million Particles (one way coupling) • Experimental Particle Size Distribution Keswani & Collins (2004)

  26. Filtering by camera Metal-coated hollow glass spheres Mean = 6 microns STD = 3.8 microns

  27. Filtering by camera Metal-coated hollow glass spheres Mean = 6 microns STD = 3.8 microns

  28. Comparison at Rl = 130

  29. Comparison at Rl = 161

  30. Summary • Clustering results from a competition between inward drift and outward diffusion • Radial Distribution Function (RDF) is the measure for collision kernel • Analysis of RDF involves Lagrangian statistics along inertial particle trajectories • RDF mainly found in direct numerical simulation • 3D measurements of RDF using holographic imaging • Reasonable agreement between experiments and DNS • Challenges for the measurement • Characterizing flow (dissipation rate, e) • Particle size distribution (will separate particles) • Increasing resolution of experiment (smaller separations) International Collaboration for Turbulence Research (ICTR)

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