Advertisement

Experiments in Fluids

, 51:933 | Cite as

Particle relaxation and its influence on the particle image velocimetry cross-correlation function

  • Daniel Mitchell
  • Damon Honnery
  • Julio Soria
Research Article

Abstract

A study of some aspects of tracer particle responses to step changes in fluid velocity is presented. The effect of size distribution within a seed material on measured relaxation time is examined, with polydisperse particles of the same median diameter shown to possess a significantly higher relaxation time than their monodisperse counterparts when measured via a particle image velocimetry algorithm. The influence of a shock wave–induced velocity gradient within a PIV interrogation window on the correlation function is also examined using the noiseless cross-correlation function of Soria (Turbulence and coherent structures in fluids, plasmas and nonlinear media. World Scientific, Singapore, 2006). The presence of a shock is shown to introduce an artificial fluctuation into the measurement of velocity. This fluctuation is a function of the shock position, shock strength, spatial ratio and particle distribution. When the shock is located at the middle of the window, the magnitude of the fluctuation increases monotonically with increasing spatial ratio, increases asymptotically with shock strength, and decreases for increasing particle polydispersity. When the shock is located at the left-hand edge of the window, the magnitude of the artificial fluctuation is highest for intermediate spatial ratios, going to zero at infinitely high and low values. In this instance, particle polydispersity acts to increase the magnitude of fluctuations in measured velocity. In both cases, particle polydispersity serves to broaden the PDF of measured velocity. For the cases presented herein, with a shock located within the interrogation window, the root mean square of the artificial velocity fluctuations reaches values in excess of 30% of the freestream velocity.

Keywords

Particle Image Velocimetry Interrogation Window Correlation Peak Mach Disc Shock Strength 
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.

Notes

Acknowledgments

The authors would like to acknowledge the support of the Australian Research Council. The first author would also like to acknowledge the support received via the Australian Postgraduate Award.

References

  1. Elsinga GE, van Oudheusden BW, Scarano F (2005) Evaluation of aero-optical distortion effects in PIV. Exp Fluids 39:246–256CrossRefGoogle Scholar
  2. Kahler CJ (1995) Generation and control of tracer particles for optical flow investigations in air. Exp Fluids 33:736–742Google Scholar
  3. Krothapalli A, Rajkuperan E, Alvi F, Lourenco L (1999) Flow field and noise characteristics of a supersonic impinging jet. J Fluid Mech 392:155–181zbMATHCrossRefGoogle Scholar
  4. Melling A (1997) Tracer particles and seeding for particle image velocimetry. Meas Sci Technol 8:1406–1416CrossRefGoogle Scholar
  5. Meyers J (1991) Generation of particles and seeding. In: Laser velocimetry, vol 8. von Karman Institute for Fluid Dynamics, pp 1–41Google Scholar
  6. Meyers J, Feller W (1975) Development of a controllable particle generator for lv seeding in hypersonic wind tunnels. In: Minnesota Symposium on Laser AnemometryGoogle Scholar
  7. Mitchell D, Honnery D, Soria J (2007a) High resolution measurements of an underexpanded supersonic jet. In: 7th International Symposium on Particle Image Velocimetry, Rome, ItalyGoogle Scholar
  8. Mitchell D, Honnery D, Soria J (2007b) Study of underexpanded supersonic jets with optical techniques. In: 16th Australiasian Fluid Mechanics Conference, Queensland, AustraliaGoogle Scholar
  9. Mitchell D, Honnery D, Soria J (2009) The influence of shockwave induced velocity gradients on the correlation function. In: 8th International Symposium on Particle Image VelocimetryGoogle Scholar
  10. Ragni D, Schrijer F, van Oudheusden B, Scarano F (2011) Particle tracer response across shocks measured by PIV. Exp Fluids 50:53–64CrossRefGoogle Scholar
  11. Rumpf H (1990) Particle technology. Chapman and Hall, LondonGoogle Scholar
  12. Scarano F (2002) Iterative image deformation methods in PIV. Meas Sci Technol 13:R1–R19CrossRefGoogle Scholar
  13. Soria J (1996) An investigation of the near wake of a circular cylinder using a video-based digital cross-correlation particle image velocimetry technique. Exp Thermal Fluid Sci 12:221–233CrossRefGoogle Scholar
  14. Soria J (2006) Particle image velocimetry-application to turbulence studies. In: Turbulence and coherent structures in fluids, plasmas and nonlinear media. World Scientific, Singapore, pp 319–330Google Scholar
  15. Stokes G (1851) On the effect of the internal friction of fluids on the motion of pendulums. Trans Cambridge Philos Soc 9:8–27Google Scholar
  16. Tedeschi G, Gouin H (1999) Motion of tracer particles in supersonic flows. Exp Fluids 26:288–296CrossRefGoogle Scholar
  17. Urban WD, Mungal G (2001) Planar velocity measurements in compressible mixing layers. J Fluid Mech 431:189–222zbMATHCrossRefGoogle Scholar
  18. Voges M, Klinner J, Willert C, Beversdorff M, Schodl R (2007) Assessment of powder-based seeding materials for piv applications in transonic, supersonic and reacting flows. In: 7th International Symposium on Particle Image Velocimetry, Rome, ItalyGoogle Scholar
  19. Westerweel J (2007) On velocity gradients in PIV interrogation. In: 7th International Symposium on Particle Image Velocimetry, Rome, ItalyGoogle Scholar
  20. Westerweel J, Dabiri D, Gharib M (1997) The effect of a discrete window offset on the accuracy of cross-correlation analysis of digital piv recordings. Exp Fluids 23:20–28CrossRefGoogle Scholar
  21. Xu J, Lin C, Sha J, Zhang K (2006) A PIV study and numerical simulation of overexpanded supersonic impinging free jet. In: 14th AIAA/AHI International Space Planes and Hypersonics Systems Conference, Canberra, AustraliaGoogle Scholar
  22. Yao W, Guangsheng G, Fei W, Jun W (2002) Fluidization and agglomerate structure of SiO2 nanoparticles. Powder Technol 124:152–159CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  1. 1.Laboratory for Turbulence Research in Aerospace and Combustion, Department of Mechanical and Aerospace EngineeringMonash UniversityMelbourneAustralia

Personalised recommendations