Elementary Mechanics of Fluids Lab # 3 FLOW VISUALIZATION Rutuparna Joshi

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

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

PIV Processing stages Image map input Evaluation of correlation plane 1 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

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

Flow around a Glass Cylinder Flow visualization Lab

Clip depicting particle movement Flow visualization Lab

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

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

Vector Statistics Output Flow visualization Lab

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

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

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

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