Experiments in Fluids

, Volume 38, Issue 1, pp 90–98

Impact of hindered Brownian diffusion on the accuracy of particle-image velocimetry using evanescent-wave illumination



The “nano-particle image velocimetry” technique uses evanescent-wave illumination generated by total internal reflection at the wall to excite colloidal neutrally buoyant fluorescent tracer particles. The displacement of these particles over time as they are convected by the flow then gives the flow velocity components tangential to the wall. Since the extent of the illumination region normal to the wall is comparable to the particle diameter, a major source of error in this technique is particle “mismatch” within a pair of images due to Brownian diffusion causing a particle to move in to or out of the illuminated region. The “brightness” (proportional to the amount of imaged fluorescence) and size of individual particle images in nPIV data are discussed. A sequence of artificial nPIV images are generated for a known uniform velocity field with the particles subject to hindered Brownian diffusion. The velocity fields calculated from these artificial images are compared with the known velocity field to determine the effect of Brownian diffusion-induced particle mismatch on nPIV accuracy. A similar analysis is carried out for experimental nPIV images. The results provide design guidance for experimental measurements using the nPIV technique.


  1. Adrian RJ (1991) Particle-imaging techniques for experimental fluid mechanics. Ann Rev Fluid Mech 23:261–304Google Scholar
  2. Axelrod D (2001) Total internal reflection fluorescence microscopy in cell biology. Traffic 2:764–774CrossRefPubMedGoogle Scholar
  3. Bevan MA, Prieve DC (2000) Hindered diffusion of colloidal particles very near to a wall: revisited. J Chem Phys 113:1228–1236CrossRefGoogle Scholar
  4. Bourdon CJ, Olsen MG, Gorby AD (2004) Validation of an analytical solution for depth of correlation in microscopic particle image velocimetry. Meas Sci Technol 15:318–327CrossRefGoogle Scholar
  5. Clark AT, Lal M, Watson GM (1987) Dynamics of colloidal particles in vicinity of an interacting surface. Faraday Discuss Chem Soc 83:179–191CrossRefGoogle Scholar
  6. Einstein A (1905) Über die von der molekularkinetischen Theorie der Wärme geforderte Bewegung von in ruhenden Flüssigkeiten suspendierten Teilchen. Ann Phys 17:549Google Scholar
  7. Faxén H (1922) Der Widerstand gegen die Bewegung einer starren Kugel in einer zähen Flüssigkeit, die zwischen zwei parallelen Ebenen Wänden eingeschlossen ist. Ann Phys 4(68):89–119Google Scholar
  8. Haertig J, Havermann M, Rey C, George A (2002) Particle image velocimetry in Mach 3.5 and 4.5 shock-tunnel flow. AIAA J 40:1056–1060Google Scholar
  9. Liang DF, Jiang CB, Li YL (2002) A combination correlation-based interrogation and tracking algorithm for digital PIV evaluation. Exp Fluids 33:684–695Google Scholar
  10. Meinhart CD, Wereley ST (2003) The theory of diffraction-limited resolution in micro-particle image velocimetry. Meas Sci Technol 14:1047–1053CrossRefGoogle Scholar
  11. Meinhart CD, Wereley ST, Gray MHB (2000a) Volume illumination for two-dimensional particle image velocimetry. Meas Sci Technol 11:809–814CrossRefGoogle Scholar
  12. Meinhart CD, Wereley ST, Santiago JG (1999) PIV measurement of a microchannel flow. Exp Fluids 27:414–419CrossRefGoogle Scholar
  13. Meinhart CD, Wereley ST, Santiago JG (2000b) A PIV algorithm for estimating time-averaged velocity fields. Trans ASME: J Fluids Eng 122:285–289Google Scholar
  14. Olsen MG, Adrian RJ (2000a) Out-of-focus effects on particle image visibility and correlation in microscopic particle image velocimetry. Exp Fluids 29:S166–S174CrossRefGoogle Scholar
  15. Olsen MG, Adrian RJ (2000b) Brownian motion and correlation in particle image velocimetry. Opt Laser Technol 32:621–627CrossRefGoogle Scholar
  16. Olsen MG, Bourdon CJ (2003) Out-of-plane motion effects in microscopic particle image velocimetry. J Fluids Eng 125:895–901CrossRefGoogle Scholar
  17. Raffel M, Willert C, Kompenhans J (1998) Particle image velocimetry; a practical guide. Springer, Berlin Heidelberg New YorkGoogle Scholar
  18. Sadr R, Yoda M, Zheng Z, Conlisk AT (2004) An experimental study of electro-osmotic flow in rectangular microchannels. J Fluid Mech 506:357–367CrossRefGoogle Scholar
  19. Santiago JG, Wereley ST, Meinhart CD, Beebe DJ, Adrian RJ (1998) Particle image velocimetry system for microfluidics. Exp Fluids 25:316–319CrossRefGoogle Scholar
  20. Tretheway DC, Meinhart CD (2002) Apparent fluid slip at hydrophobic microchannel walls. Phys Fluids 14:L9–L12CrossRefGoogle Scholar
  21. Wereley ST, Gui L, Meinhart CD (2002) Advanced algorithms for microscale particle image velocimetry. AIAA J 40:1047–1055Google Scholar
  22. Westerweel J (2000) Theoretical analysis of the measurement precision in particle image velocimetry. Exp Fluids 29:S3–S12CrossRefGoogle Scholar
  23. Zettner CM, Yoda M (2003) Particle velocity field measurements in a near-wall flow using evanescent wave illumination. Exp Fluids 34:115–121Google Scholar

Copyright information

© Springer-Verlag 2004

Authors and Affiliations

  1. 1.G. Woodruff School of Mechanical EngineeringGeorgia Institute of TechnologyAtlantaUSA

Personalised recommendations