Particle Image Velocimetry Part - 4huhui/teaching/2016Fx/AerE545/lecture-notes/... · 200 300 400...
Transcript of Particle Image Velocimetry Part - 4huhui/teaching/2016Fx/AerE545/lecture-notes/... · 200 300 400...
Copyright Copyright ©© by Dr. Hui Hu @ Iowa State University. All Rights Reserved!by Dr. Hui Hu @ Iowa State University. All Rights Reserved!
HHui Huui HuDepartment of Aerospace Engineering, Iowa State University Department of Aerospace Engineering, Iowa State University
Ames, Iowa 50011, U.S.AAmes, Iowa 50011, U.S.A
Particle Image Particle Image VelocimetryVelocimetryPart Part -- 44
AerEAerE 545 class notes #28545 class notes #28
Copyright Copyright ©© by Dr. Hui Hu @ Iowa State University. All Rights Reserved!by Dr. Hui Hu @ Iowa State University. All Rights Reserved!
Advanced algorithm for PIV image processAdvanced algorithm for PIV image process
•• Particle Tracking Particle Tracking VelocimetryVelocimetry::•• Tracking individual particleTracking individual particle•• Limited to low particle image density caseLimited to low particle image density case•• Velocity vector at random points where tracer Velocity vector at random points where tracer
particles exist.particles exist.•• Spatial resolution of PTV results is usually Spatial resolution of PTV results is usually
limited by the number of the tracer particleslimited by the number of the tracer particles
•• CorrelationCorrelation--based PIV:based PIV:•• Tracking a group of particlesTracking a group of particles•• Applicable to high particle image density caseApplicable to high particle image density case•• Spatial resolution of PIV results is usually Spatial resolution of PIV results is usually
limited by the size of the interrogation window limited by the size of the interrogation window sizesize
•• Velocity vector can be at regular grid points.Velocity vector can be at regular grid points.
PIV
Copyright Copyright ©© by Dr. Hui Hu @ Iowa State University. All Rights Reserved!by Dr. Hui Hu @ Iowa State University. All Rights Reserved!
),(2),(1),( * qpqpqp RRR =
R1(p,q)R1(p,q)R2(p,q)R2(p,q)
The ideal of correlation error correction techniqueThe ideal of correlation error correction technique(multiple(multiple--correlation validation technique)correlation validation technique)
•• Since the noise peak in the correlation space may be randomly, cSince the noise peak in the correlation space may be randomly, causing the multiplied value to ausing the multiplied value to be reduced to zero. Thus, the correct peak can be easily identifbe reduced to zero. Thus, the correct peak can be easily identified. ied.
•• The location of the correct peak in the correlation space is corThe location of the correct peak in the correlation space is corresponding to the averaged responding to the averaged movement of the overlap regionmovement of the overlap region
Copyright Copyright ©© by Dr. Hui Hu @ Iowa State University. All Rights Reserved!by Dr. Hui Hu @ Iowa State University. All Rights Reserved!
Correlation error correction technique
Interrogation window BInterrogation window A
Overlap region of Interrogation window A and B
Hart method (1998)
Interrogation window BInterrogation window A
Overlap region of Interrogation window A and B
Hu et al. (1999) methodthe spatial resolution in X and Y direction is different
the spatial resolution in X and Y direction is same
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The comparison of various PIV methodsThe comparison of various PIV methods
X pixel
Ypi
xel
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a. FFT-CC method(interrogation window size 32 by 32 pixel)
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xel
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b. D-CC method(interrogation window size 32 by 32 pixel)
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c. D-CC methodwith correlation error correction treatment (interrogation window size 32 by 32 pixel)
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The Effect of the Size of the Interrogation WindowThe Effect of the Size of the Interrogation Window
Imageprocessing
Interrogationwindow
Real flow field
PIV finalresult
Vortical structure
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Hierarchical Recursive PIV AlgorithmHierarchical Recursive PIV Algorithm
Velocity vector at coarse grid level Offset velocity vector Velocity vector at refined gridVector obtained at new calculation loop
Copyright Copyright ©© by Dr. Hui Hu @ Iowa State University. All Rights Reserved!by Dr. Hui Hu @ Iowa State University. All Rights Reserved!
Results from Hierarchical PIV algorithmResults from Hierarchical PIV algorithm
X pixel
Ypi
xel
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Vorticity15.0012.00
9.006.003.000.00
-3.00-6.00-9.00
-12.00-15.00
interrogation windowsize 32 by 32 pixel
X pixel
Ypi
xel
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Vorticity10.00
8.006.004.002.000.00
-2.00-4.00-6.00-8.00
-10.00
interrogation windowsize 64 by 64 pixel
X pixel
Ypi
xel
250 500 750 1000 1250
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Vorticity30.0024.0018.0012.00
6.000.00
-6.00-12.00-18.00-24.00-30.00
interrogation windowsize 16 by 16 pixel
X pixel
Ypi
xel
250 500 750 1000 1250
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Vorticity70.0056.0042.0028.0014.00
0.00-14.00-28.00-42.00-56.00-70.00
interrogation windowsize 8 by 8 pixel