Experiments in Fluids

, Volume 46, Issue 4, pp 617–629 | Cite as

In situ calibration of hot wire probes in turbulent flows

  • M. TutkunEmail author
  • W. K. George
  • J. M. Foucaut
  • S. Coudert
  • M. Stanislas
  • J. Delville
Research Article


A method for in situ calibration of hot-wires in a turbulent flow is presented. The method is particularly convenient (even necessary) for calibrating large probe arrays, like the 143-wire boundary layer rake of the WALLTURB experiment. It is based on polynomial expansion of the velocity statistics in terms of voltage statistics as originally described by George et al. [Exp Ther Fluid Sci 2(2):230–235, 1989]. Application of the method requires knowing reference mean velocity and higher order central moments (with the array in place) of the turbulent velocity at the probe location at only one freestream velocity. These were obtained in our experiment by a stereo PIV plane just upstream of the probe array. Both the procedure for implementing the method and sample results are presented in the article.


Particle Image Velocimetry Central Moment Calibration Coefficient Particle Image Velocimetry Data Freestream Velocity 
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.



The authors would like to thank P. B. V. Johansson and L. Jernqvist of Chalmers, F. Mehdi of University of New Hampshire, and P. Braud and C. Fourment of Laboratoire d’Etudes Aérodynamiques for their help for realization of the experiments within the Wallturb research program. This work has been performed under the WALLTURB project. WALLTURB (A European synergy for the assessment of wall turbulence) is funded by the CEC under the sixth framework program (CONTRACT No: AST4-CT-2005-516008).


  1. Breuer KS (1995) Stochastic calibration of sensors in turbulent flow fields. Exp Fluids 19(2):138–141CrossRefMathSciNetGoogle Scholar
  2. Bruun HH (1995) Hot-wire anemometry. Oxford University Press, New YorkGoogle Scholar
  3. Citriniti JH, George WK (2000) Reconstruction of the global velocity field in the axisymmetric mixing layer utilizing the proper orthogonal decomposition. J Fluid Mech 418:137–166zbMATHCrossRefGoogle Scholar
  4. Coudert S, Foucaut JM, Kostas J, Stanislas M, Braud P, Fourment C, Delville J, Tutkun M, Mehdi F, Johansson PBV, George WK (2007) Double large field stereoscopic PIV in a high Reynolds number turbulent boundary layer. Exp FluidsGoogle Scholar
  5. Delville J (1994) Characterization of the organization in shear layers via the proper orhogonal decomposition. Appl Sci Res 53:263–281CrossRefGoogle Scholar
  6. Delville J, Fourment C, Tutkun M, Johansson PBV, George WK, Kostas J, Coudert S, Foucaut JM, Stanislas M (2007) High Reynolds number flat plate turbulent boundary layer experiments using a hot-wire rake synchronized with stereo PIV. In: Fifth international symposium on turbulence and shear flow phenomena, vol 1, pp 23–28Google Scholar
  7. Delville J, Ukeiley L, Cordier L, Bonnet JP, Glauser M (1999) Examination of large-scale structures in a turbulent plane mixing layer. Part 1. Proper orthogonal decomposition. J Fluid Mech 391:91–122zbMATHCrossRefMathSciNetGoogle Scholar
  8. George WK, Beuther PD, Lumley JL (1978) Processing of random signals. In: Proceedings of the dynamic flow conference, pp 757–800Google Scholar
  9. George WK, Beuther PD, Shabbir A (1989) Polynomial calibrations for hot wires in thermally varying flows. Exp Ther Fluid Sci 2(2):230–235CrossRefGoogle Scholar
  10. Glauser MN (1987) Coherent structures in the axisymmetric turbulent jet mixing layer. Ph.D. dissertation, State University of New York, BuffaloGoogle Scholar
  11. Iqbal MO, Thomas FO (2007) Coherent structure in a turbulent jet via a vector implementation of the proper orthogonal decomposition. J Fluid Mech 571:281–326zbMATHCrossRefGoogle Scholar
  12. Johansson PBV, George WK (2006) The far downstream evloution of the high Reynolds number axisymmetric wake behind a disk. Part 1. Single point statistics. J Fluid Mech 555:363–385zbMATHCrossRefGoogle Scholar
  13. Jung D, Gamard S, George WK (2004) Downstream evolution of the most energetic modes in a turbulent axisymmetric jet at high Reynolds number. Part 1. The near-field region. J Fluid Mech 514:173–204zbMATHCrossRefGoogle Scholar
  14. Lumley JL (1970) Stochastic tools in turbulence. Academic Press, New YorkzbMATHGoogle Scholar
  15. Perry AE (1982) Hot-wire anemometry. Oxford University Press, New YorkGoogle Scholar
  16. Tutkun M (2008) Structure of zero pressure gradient high Reynolds number turbulent boundary layers. Ph.D. dissertation, Chalmers University of Technology, Göteborg, Sweden. ISBN: 978-91-7385-166-4Google Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • M. Tutkun
    • 1
    Email author
  • W. K. George
    • 2
  • J. M. Foucaut
    • 3
  • S. Coudert
    • 3
  • M. Stanislas
    • 3
  • J. Delville
    • 4
  1. 1.Norwegian Defence Research Establishment, FFIKjellerNorway
  2. 2.Department of Applied MechanicsChalmers University of TechnologyGothenburgSweden
  3. 3.Laboratoire de Mécanique de Lille, UMR CNRS 8107Villeneuve d’AscqFrance
  4. 4.Laboratoire d’Etudes Aérodynamiques, Université de Poitiers, UMR CNRS 6609, ENSMAPoitiers CedexFrance

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