Experiments in Fluids

, 47:569 | Cite as

Volumetric correlation PIV: a new technique for 3D velocity vector field measurement

  • Andreas FourasEmail author
  • David Lo Jacono
  • Chuong Vinh Nguyen
  • Kerry Hourigan
Research Article


A method is proposed that allows three-dimensional (3D) two-component measurements to be made by means of particle image velocimetry (PIV) in any volume illuminated over a finite thickness. The method is based on decomposing the cross-correlation function into various contributions at different depths. Because the technique is based on 3D decomposition of the correlation function and not reconstruction of particle images, there is no limit to particle seeding density as experienced by 3D particle tracking algorithms such as defocusing PIV and tomographic PIV. Correlations from different depths are differentiated by the variation in point spread function of the lens used to image the measurement volume over that range of depths. A number of examples are demonstrated by use of synthetic images which simulate micro-PIV (μPIV) experiments. These examples vary from the trivial case of Couette flow (linear variation of one velocity component over depth) to a general case where both velocity components vary by different complex functions over the depth. A final validation—the measurement of a parabolic velocity profile over the depth of a microchannel flow—is presented. The same method could also be applied using a thick light sheet in macro-scale PIV and in a stereo configuration for 3D three-component PIV.


Particle Image Velocimetry Focal Plane Point Spread Function Couette Flow Particle Tracking Velocimetry 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Adrian R, Yao C (1985) Pulsed laser technique application to liquid and gaseous flows and the scattering power of seed materials. Appl Optics 24:42–52Google Scholar
  2. Arroyo M, Greated C (1991) Stereoscopic particle image velocimetry. Meas Sci Technol 2:1181–1186CrossRefGoogle Scholar
  3. Barnhart D, Adrian R, Papen G (1994) Phase-conjugate holographic system for high-resolution particle image velocimetry. Appl Opt 33:7159–7170CrossRefGoogle Scholar
  4. Bourdon C, Olsen M, Gorby A (2004) Validation of an analytical solution for depth of correlation in microscopic particle image velocimetry. Meas Sci Technol 15:318–327CrossRefGoogle Scholar
  5. Elsinga G, Scarano F, Wieneke B, van Oudheusen B (2006) Tomographic particle image velocimetry. Exp Fluid 41:933–947CrossRefGoogle Scholar
  6. Forouhar A, Liebling M, Hickerson A, Nasiraei-Moghaddam A, Tsai HJ, Hove J, Fraser S, Dickinson M, Gharib M (2006) The embryonic vertebrate heart tube is a dynamic suction pump. Science 312(5774):751–753CrossRefGoogle Scholar
  7. Fouras A, Dusting J, Hourigan K (2007a) A simple calibration technique for stereoscopic particle image velocimetry. Exp Fluid 42:799–810CrossRefGoogle Scholar
  8. Fouras A, Dusting J, Lewis R, Hourigan K (2007b) Three-dimensional synchrotron X-ray particle image velocimetry. J Appl Phys 102:064,916–064,922CrossRefGoogle Scholar
  9. Fouras A, Lo Jacono D, Hourigan K (2008) Target-free Stereo PIV: a novel technique with inherent error estimation and improved accuracy. Exp Fluid 44:317–329CrossRefGoogle Scholar
  10. Kahler C (2004) Investigation of spatio-temporal flow structure in the buffer region of a turbulent boundary layer by means of multiplane stereo PIV. Exp Fluid 36:114–130CrossRefGoogle Scholar
  11. Lo Jacono D, Plouraboué F, Bergeon A (2005) Weak-inertial flow between two rough surfaces. Phys Fluid 17:63,602CrossRefGoogle Scholar
  12. Meinhart C, Wereley S, Gray M (2000a) Volume illumination for two-dimensional particle image velocimetry. Meas Sci Technol 11:809–814CrossRefGoogle Scholar
  13. Meinhart CD, Werely ST, Santiago JS (2000b) A PIV algorithm for estimating time-averaged velocity fields. J Fluid Eng 122:285–289CrossRefGoogle Scholar
  14. Olsen M, Adrian R (2000a) Brownian motion and correlation in particle image velocimetry. Opt Laser Technol 32:621–627CrossRefGoogle Scholar
  15. Olsen M, Adrian R (2000b) Out-of-focus effects on particle image visibility and correlation in microscopic particle image velocimetry. Exp Fluid 29:S166–S174CrossRefGoogle Scholar
  16. Olsen M, Bourdon C (2003) Out-of-plane motion effects in microscopic particle image velocimetry. J Fluid Eng 125:895–901CrossRefGoogle Scholar
  17. Park J, Kihm K (2006) Three-dimensional micro-PTV using deconvolution microscopy. Exp Fluid 40:491–499CrossRefGoogle Scholar
  18. Pereira F, Gharib M, Dabiri D, Modarress M (2000) Defocusing DPIV: A 3-component 3-D DPIV measurement technique application to bubbly flows. Exp Fluid 29:S78–S84CrossRefGoogle Scholar
  19. Schlichting H, Gersten K (2003) Boundary-layer theory, 8th edn. Springer, New YorkGoogle Scholar
  20. Schroder A, Kompenhans J (2004) Investigation of a turbulent spot using multi-plane stereo particle image velocimetry. Exp Fluid 36:82–90CrossRefGoogle Scholar
  21. Willert C, Gharib M (1992) Three-dimensional particle imaging with a single camera. Exp Fluid 12:353–358CrossRefGoogle Scholar
  22. Zhang J, Tao B, Katz J (1997) Turbulent flow measurement in a square duct with hybrid holographic PIV. Exp Fluid 23:373–381CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Andreas Fouras
    • 1
    • 2
    Email author
  • David Lo Jacono
    • 2
  • Chuong Vinh Nguyen
    • 2
  • Kerry Hourigan
    • 1
    • 2
  1. 1.Division of Biological EngineeringMonash UniversityMelbourneAustralia
  2. 2.Fluids Laboratory for Aeronautical and Industrial Research (FLAIR)Monash UniversityMelbourneAustralia

Personalised recommendations