1. Elementary Mechanics of Fluids Lab # 3 FLOW VISUALIZATION
Rutuparna Joshi

2. System Components Nd:YAG Laser Flume Laser Beam Nano sense Camera
Timing Hub
Chiller
Control Unit
Traverse System
Flume
Control Unit
Traverse System
Timing Hub
Chiller
Flow visualization Lab

3. PIV Measurements
PIV is a non-intrusive, whole field optical technology used for obtaining velocity information by suspending ‘seeding’ particles in a fluid in motion.
Measurement is based on particle displacement over a known time interval.
The system uses a light source (Laser) and a nano-sense camera which are synchronized.
Camera/Image Displacements
Displacement Vectors
Application of Validation Algorithms
Flow visualization Lab
Flow visualization Lab

4. PIV Processing stages Image map input Evaluation of correlation plane1
Image map input 2
Evaluation of correlation plane 3
Multiple peak detection 4
Sub-pixel Interpolation 5
Vector Output 6
Vector statistics
Scalar maps
Derivatives
Velocity, Vorticity, Deviations
Flow visualization Lab

5. Light source, sheet formation and Seeding particles
Double Cavity Nd:YAG Laser:
Pulses of short duration (5-10 ns)
Vast range of Output energy and repetition rates providing powerful light flash.
Optic components added for transformation of IR to Visible light and recombination along same optical path
Seeding Particles:
Hollow glass spheres
Diameter comparable to light source wavelength (in accordance with Lorenz Mie theory)
Light scattering sideways is of interest
Flow visualization Lab

6. Flow around a Glass Cylinder
Flow visualization Lab

7. Clip depicting particle movement
Flow visualization Lab

8. Correlations
Image is subdivided into Interrogation areas (IA), each IA has a correlation function
Different types such as Adaptive, Cross and Average correlations
Calculation of velocity vectors with initial IA, applying refinement steps and using intermediary results as input for the next IA
Application of Validation Methods and IA offset scheme
Averaging the correlation to increase the signal-to-noise-ratio significantly and generating clear correlation peaks
Cross-correlations for single frame images
Flow visualization Lab

9. Filters
Average filter used to output vector maps by arithmetic averaging, individual vectors smoothed out
Substitution of vectors with uniformly weighted average over a user defined area
To enhance the results of measurement, a coherence filter applied to the raw velocity field to modify the inconsistent vectors
Application of filters improves the acquired parent data, various vector and scalar maps can be derived
Flow visualization Lab

10. Vector Statistics Output
Flow visualization Lab

11. Scalar Map Sqrt (U2 + V2)
Note: results are processed and shown downstream of
the cylinder
Scalar Map Sqrt(U2 + V2)
Flow visualization Lab

12. Scalar Map for Vorticity
Vorticity measures the “swirl” or the “local spin” of the flow
Note: results are processed and shown downstream of
the cylinder
Flow visualization Lab

13. Typical recommendations for PIV measurements around a cylinder:
At least 5 seeding particles per IA to minimize “loss of pairs”
Use cross-correlation than auto correlation methods
Use of Guassian window function to eliminate noise due to cyclic convolution
Use of filters to optimize the effectiveness of sub-pixel interpolation
Maximum permissible displacement of particles be 25% of the IA
Minimize effects of zero velocity biasing
Flow visualization Lab

14. Conclusion
Time resolved PIV is an effective tool for fluid flow visualization, determination of velocity and related fluid properties
Non-intrusive method, high speed data processing, high degree of accuracy
Can be used fairly easily to depict the flow
characteristics around objects such as
cylinders and airfoils
Scope for more precision as regards to use of
camera and multiple cavity laser technology
Valuable for academic and research purposes
Flow visualization Lab