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Direct Measurement of Particle Behavior in the Particle-Lagrangian Reference Frame of a Turbulent Flow James A. Bickford M.S.M.E. Defense 10 August 1999 Advisor : Chris Rogers (Tufts University) Committee Members : Vincent Manno (Tufts University) Martin Maxey (Brown University)
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Outline Overview and Applications Quasi-numerical Simulation –QNS Method –Velocity autocorrelations, spectra –Integral scales –u’ –Anomalous drift Digital Particle Image Velocimetry –DPIV Method –Kolmogorov estimates –Effects of preferential concentration
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Particles and Turbulence Turbulent Fluid Fluctuations –Occur on a range of length and time scales –Suspended particles respond to these scales
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Applications Engine combustion, radiation and pollution control, volcanic erruptions Aeolian Martian processes Formation of planetary bodies and large scale structure of the universe
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Three-tiered research approach Tactical approach uses separate but complimentary methods –Microgravity flight experiments –Direct numerical simulations –Quasi-numerical simulations
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Quasi-Numerical Overview Technique –Hybrid numerical-experimental –Two-axis traverse emulates a virtual particle in a water flow –Measures turbulence statistics in the particle’s reference frame Variable Parameters –Particle time constant (size) –Drift velocity (gravity) –Reynolds number (turbulence intensity) Data Acquisition Methods –Laser Doppler Velocimetry –Digital Particle Image Velocimetry
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QNS Methodology Read Fluid Velocity Update Traverse Velocity Repeat >> T k
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Particle Response to Turbulence Time Velocity Particle Velocity Fluid Velocity (along particle path)
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Movie - “QNS in action”
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Effect of Gravity on Velocity Autocorrelations Gravity Decreases Correlation times “crossing trajectories” effect Increases relative particle energy at higher frequencies Little effect on fluid spectra Time R ii / u’ 2
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Effect of Particle Inertia on Velocity Autocorrelations Particle Inertia Increases particle correlation times Almost no effect on fluid correlations or spectra Decreases relative energy at higher frequencies Time R ii / u’ 2
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Effect of Gravity on Integral Scales Sg Gravity Fluid Scales Decrease Streamwise Streamnormal (more) Particle Scales Possible decrease (tiny) p-L fluid scales ME = pL @ Sg = 1 T 2 p-L / T 2 me
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Effect of Particle Inertia on Integral Scales T 1 p-L / T 1 me St me Inertia General increase in fluid and particle integral scales Possible local peaks Tf ~ 1 (particle) Tf ~ 0.7 (fluid) SW more prominent
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Anomalous Drift Velocities (Measured Drift - Imposed Drift) / U St me
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U’ Dependence on Gravity and Particle Inertia U’ i pl / U’ i me StreamwiseStreamnormal St me
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Mechanisms Dictating Particle Behavior Looking beyond single point statistics Vorticity as a governing force for particle motion Preferential concentration
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Digital Particle Image Velocimetry Four computers used during simultaneous QNS –Master control –Traverse control (DSP) –Frame grabber –Laser and camera pulse control 750 mW pulsed diode laser illuminates a 2-D plane of the flow Dichroic filter allows camera and LDV regions to coincide Kodak ES-1 camera grabs 1008x1018 pixel images at 30 Hz
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Image Correlations Images broken into sections (interrogation windows) Sub-images cross-correlated to produce vector field
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Bad Vector Identification Bad correlations (lighting, dirt, 3-D effects) Bad vectors are identified by comparing the velocity of a given vector to its surrounding neighbors. γ = 2 (good) γ = 8 (bad) γ = 6 (bad)
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Tagged Vector Replacement Average with surrounding vectors –iterate to fix coincident vectors –inaccurate velocities –reduced resolution Replace with higher order interpolated value –more accurate interpolation –same reduced resolution Use secondary correlation peaks –no loss of resolution or accuracy
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Estimation of the Kolmogorov Fluid Time Scale Kolmogorov Fluid Time Scale Results
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Effect of Preferential Concentration on Particle Path
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Conclusion Gravity and Inertia –Affect particle trajectory which in turns affects Integral scales Measured u’ Measured vorticity Observed Anomalies –Drift –Integral scale dependence
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Acknowledgements Committee Members –Chris Rogers * –Vincent Manno –Martin Maxey Staff –Jim Hoffmann, Vinny Maraglia –Audrey-Beth Stein, Joan Kern TUFTL –Becca Macmaster, AJ Bettencourt –Dave McAndrew, Dan Groszmann, Scott Coppen, Jon Coppeta, Merre Portsmore
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Ainley & Bickford Rii Comparisons Fluid Velocity AutocorrelationParticle Velocity Autocorrelation
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