Out-of-focus effects on particle image visibility and correlation in microscopic particle image velocimetry

2000 ◽  
Vol 29 (7) ◽  
pp. S166-S174 ◽  
Author(s):  
M. G. Olsen ◽  
R. J. Adrian
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Microscopic Particle ◽  
Image Velocimetry

Out-of-Plane Motion Effects in Microscopic Particle Image Velocimetry

2003 ◽  
Vol 125 (5) ◽  
pp. 895-901 ◽  
Author(s):  
Michael G. Olsen ◽  
Chris J. Bourdon
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Laser Sheet ◽  
Plane Motion ◽  
Entire Volume ◽  
Measurement Volume ◽  
Microscopic Particle ◽  
Image Velocimetry ◽  
Out Of Plane ◽  
Signal Peak

In microscopic particle image velocimetry (microPIV) experiments, the entire volume of a flowfield is illuminated, resulting in all of the particles in the field of view contributing to the image. Unlike in light-sheet PIV, where the depth of the measurement volume is simply the thickness of the laser sheet, in microPIV, the measurement volume depth is a function of the image forming optics of the microscope. In a flowfield with out-of-plane motion, the measurement volume (called the depth of correlation) is also a function of the magnitude of the out-of-plane motion within the measurement volume. Equations are presented describing the depth of correlation and its dependence on out-of-plane motion. The consequences of this dependence and suggestions for limiting its significance are also presented. Another result of the out-of-plane motion is that the height of the PIV signal peak in the correlation plane will decrease. Because the height of the noise peaks will not be affected by the out-of-plane motion, this could lead to erroneous velocity measurements. An equation is introduced that describes the effect of the out-of-plane motion on the signal peak height, and its implications are discussed. Finally, the derived analytical equations are compared to results calculated using synthetic PIV images, and the agreement between the two is seen to be excellent.

Interaction of Synthetic Jet with Boundary Layer Using Microscopic Particle Image Velocimetry

2010 ◽  
Vol 47 (2) ◽  
pp. 404-422 ◽  
Author(s):  
Manikandan Ramasamy ◽  
Jacob S. Wilson ◽  
Preston B. Martin
Keyword(s):  
Boundary Layer ◽  
Particle Image Velocimetry ◽  
Particle Image ◽  
Synthetic Jet ◽  
Microscopic Particle ◽  
Image Velocimetry

Validation of Analytical Solution for Depth-of-Correlation in Microscopic Particle Image Velocimetry

2003 ◽  
Author(s):  
Christopher J. Bourdon ◽  
Michael G. Olsen ◽  
Allen D. Gorby
Keyword(s):  
Particle Image Velocimetry ◽  
Correlation Function ◽  
Analytical Model ◽  
Particle Image ◽  
Object Plane ◽  
Measured Velocity ◽  
Microscopic Particle ◽  
Relative Contribution ◽  
Physical Experiments ◽  
Image Velocimetry

Because the entire flowfield is generally illuminated in microscopic particle image velocimetry (microPIV), determining the depth over which particles will contribute to the measured velocity is more difficult than in traditional, light-sheet PIV. This paper experimentally and computationally measures the influence that volume illumination, optical parameters, and particle size have on the depth of correlation for typical microPIV system. First, it is demonstrated mathematically that the relative contribution to the measured velocity at a given distance from the object plane is proportional to the curvature of the local cross-correlation function at the distance. The depth of correlation is then determined in both the physical experiments and in computational simulations by directly measuring the relative contribution to the correlation function of particles located at a known separation from the object plane. These results are then compared with a previously derived analytical model that predicts the depth of correlation from the basic properties of the imaging sytem and seed particles used for the microPIV measurements. Excellent agreement was obtained between the analytical model and both computational and physical experiments, verifying the accuracy of the previously derived analytical model.

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