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PIV and PTV in Multiphase Flows Gustavo A. Zarruk
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At IFE we have DPIV and Time-Resolved DPIV What is it? • Non-intrusive measurement
technique • Excellent temporal and spatial
resolution • High repetition laser • High speed camera • Digital image processing • Fancy mathematics and statistics
Frame rate vs Resolution Typical 5400 @ 1024x1024 pixels Maximum 675,000 @ 64x16 pixels
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Time Resolved Particle Image Velocimetry (TRPIV)
Fundamentals of Digital Particle Image Velocimetry - Westerweel (1997)
• Fluid Velocity inferred from ideal tracer particles • Velocity measured indirectly from particle displacement • Tracer particles are described in terms of a pattern • 2D – TRPIV
• Cross section of the flow is illuminated with a thin light sheet (Dual pulsed laser)
• Tracer particles in the light sheet are projected onto a recording medium ~ CCD or CMOS high speed camera - TRPIV
• Image pair acquired in a short period of time dt~Ο (1µs) • FFT-based cross-correlation performed on small interrogation
windows • Correlation peak ~ particle pattern displacement, ds
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PIV Schematic
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How does it look?
Bad PIV but good for explaining
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PIV Velocity Estimation
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Partickle Tracking A hybrid digital particle tracking velocimetry technique – Cowen & Monismith (1997)
DPIV results
Particle Tracking Algorithm
I1(t) I2(t+dt)
New particle Tracked particle
Out of field of view
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Results sample Fluid Velocity and Vorticity
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PIV @ IFE: Particle flow in pipelines Raw Images Fluid Velocity
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Final result
Poelma et. al. (2006)
Fluid and Particle Velocity Information
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PIV and PTV in Slug Flow
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Sample Image : Challenges Gas Pocket
Small Bubbles
Tracer particles
Small bubbles in out of focus
Background illumination
Sample Image
Enlarged view
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Uncertainty: Density of tracer particles and bubbles
BIAS RMS
Zarruk et.al (2011)
PIV
PTV
PIV
PTV
Bubble concentration Bubble concentration
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Uncertainty: Slip velocity and angle
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THE LESSON PTV offers better results in multiphase flows
THE PROBLEM PTV data distribution is not uniform. For some statistical analyses, interpolation of data is necessary
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Slug front: Large eddy
o Large eddy observed at
beginning of slug front.
o Ls= 0.6D
o Large eddy: cause for
gas entrainment and
acceleration of stratified
liquid layer
Velocity distribution
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Evolution of liquid phase velocity in slug zone
8 7 6 5 1 3 4 2 9 10 11
5
3 2
7 6
1
8
4
9 10
11
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Costs Operational • Measurement time
Depends on: • Camera characteristics • Frames per second • Image resolution • Inboard camera memory
• Examples: 4GB memory with 1000 fps @ 1024 x1024 pixels = 3 s 4GB memory with 3000 fps @ 512 x 512 pixels = 4 s 4GB memory with 250 fps @ 256 x 256 pixels = 192 s
• Data processing • 24 hours with an optimal processing algorithm • Days – months for large data sets
Financial • State of the art system 2-3 MNOK • Startup system MNOK 0.6