1. 1 Imaging Techniques for Flow and Motion Measurement Lecture 6 Lichuan Gui University of Mississippi 2011 PIV Recording Evaluation

2. 2 Evaluation methods Frequently used evaluation methods

3. 3 Evaluation methods Particle trajectory identification PIV recording - Single frame - Single long time exposure - LID mode - Film or digital recording Evaluation - Read film recordings with a microscope system - Identify particle trajectories in digital recording yy xx

4. 4 Young’s fringes evaluation system laser PC 2D traverse system CCD camera frosted glass Evaluation methods Young’s fringes method PIV recording -Positive film -Single frame -Double/multiple exposed -HID & LS mode Young’s fringes system

5. 5 Evaluation methods Particle image tracking PIV recording - Minimum 2 frames - Single exposure - LID mode - Film or digital recording Evaluation - Identify particle images & determine position of each particle image center - Pairing particles in two frames (many algorithms) - Velocity determined by position difference of paired particles &  t t1t1 t2t2 ox y ox y (x 2, y 2 ) (x 1, y 1 )

6. 6 Evaluation methods Particle image tracking algorithm Nearest point method - Two frame - Distance between particle images >> particle image displacement 2 nd frame1 st fame1 st fame & 2 nd frame

7. 7 Evaluation methods Particle image tracking algorithm Two frame particle tracking algorithms - Distance between particle images >> particle image displacement - Neighborhood particle images used to help pairing particles - Different algorithms, e.g. “Spring model” by Okamoto 2 nd frame1 st fame1 st fame & 2 nd frame

8. 8 Evaluation methods Particle image tracking algorithm Multi frame particle tracking algorithms - Time history of particle images used to help pairing particles - Velocity variation small enough in several consecutive frames 1 st fame2 nd fame3 rd fame4 th fame

9. 9 m n  (m, n) -S S o Auto- correlation Cross-correlation Evaluation methods Correlation-based interrogation (m’,n’)

10. 10 Evaluation methods Ensemble particle image pattern tracking 1 st recording 2 nd recording Sample image pattern Image pattern at (m,n)

11. 11 Evaluation methods Ensemble particle image pattern tracking M  N dimensional vectors Difference of the vectors Double exposureSingle exposures Image pattern difference as function of (m,n) (m’,n’)

12. 12 Evaluation with large window Evaluation at identified particles LID recordings with small interrogation window Evaluation methods Individual particle image pattern tracking

13. 13 1.Read EDPIV help manual pages: “PIV recording simulation settings” 2.Create a synthetic PIV recording pair of LID mode Particle number density: 1 / 32x32 pixels Random noise: intensity=0, mean value=80 4-roll-mill flow, Ax=500, Ay=500 In start window: menu choice “ File \ New image” and “Processing” button; In “Image processing” window: menu “Tools \ Simulation settings \ Particle” menu “Tools \ Simulation settings \ Noise” menu “Tools \ Simulation settings \ Flow” menu “Tools \ One pair” Press button “I” to switch images View overlapped image in “Evaluation window” Homework