Experiments in Fluids

, Volume 53, Issue 1, pp 91–103

Large-scale tomographic PIV in forced and mixed convection using a parallel SMART version

  • Matthias Kühn
  • Klaus Ehrenfried
  • Johannes Bosbach
  • Claus Wagner
Research Article

Abstract

Large-scale tomographic particle image velocimetry (tomographic PIV) was used to study large-scale flow structures of turbulent convective air flow in an elongated rectangular convection cell. Three flow cases have been investigated, that is, pure forced convection and mixed convection at two different Archimedes numbers. The Reynolds number was constant at Re = 1.04 × 104 for all cases, while the Archimedes numbers were Ar = 2.1 and 3.6 for the mixed convection cases, corresponding to Rayleigh numbers of Ra = 1.6 × 108 and 2.8 × 108, respectively. In these investigations, the size of the measurement volume was as large as 840 mm × 500 mm × 240 mm. To allow for statistical analysis of the measured instantaneous flow fields, a large number of samples needed to be evaluated. Therefore, an efficient parallel implementation of the tomographic PIV algorithm was developed, which is based on a version of the simultaneous multiplicative reconstruction technique (SMART). Our algorithm distinguishes itself amongst other features by the fact that it does not store any weighting coefficients. The measurement of forced convection reveals an almost two-dimensional roll structure, which is orientated in the longitudinal cell direction. Its mean velocity field exhibits a core line with a wavy shape and a wavelength, which corresponds to the height and depth of the cell. In the instantaneous fields, the core line oscillates around its mean position. Under the influence of thermal buoyancy forces, the global structure of the flow field changes significantly. At lower Archimedes numbers, the resulting roll-like structure is shifted and deformed as compared to pure forced convection. Additionally, the core line oscillates much more strongly around its mean position due to the interaction of the roll structure with the rising hot air. If the Archimedes number is further increased, the roll-like structure breaks up into four counter-rotating convection rolls as a result of the increased influence of buoyancy forces. Moreover, large-scale tomographic PIV reveals that the orientation of these rolls reflects a ‘W’-like shape in the horizontal XZ-plane of the convection cell.

References

  1. Ahlers G, Grossmann S, Lohse D (2009) Heat transfer and large scale dynamics in turbulent Rayleigh-Bénard convection. Rev Mod Phys 81:503–537CrossRefGoogle Scholar
  2. Andersen AH, Kak AC (1984) Simultaneous algebraic reconstruction technique (SART): a superior implementation of the ART algorithm. Ultrason Img 6:81–94CrossRefGoogle Scholar
  3. Atkinson C, Soria J (2009) An efficient simultaneous reconstruction technique for tomographic particle image velocimetry. Exp Fluids 47:553–568CrossRefGoogle Scholar
  4. Atkinson C, Coudert S, Foucaut JM, Stanislas M, Soria J (2011) The accuracy of tomographic particle image velocimetry for measurements of a turbulent boundary layer. Exp Fluids 50:1031–1056CrossRefGoogle Scholar
  5. Bosbach J, Penneçot J, Wagner C, Raffel M, Lerche T, Repp S (2006) Experimental and numerical simulations of turbulent ventilation in aircraft cabins. Energy 31:694–705CrossRefGoogle Scholar
  6. Bosbach J, Kühn M, Wagner C (2009) Large scale particle image velocimetry with helium filled soap bubbles. Exp Fluids 46:539–547CrossRefGoogle Scholar
  7. Buchmann NA, Atkinson C, Jeremy MC, Soria J (2011) Tomographic particle image velocimetry investigation of the flow in a modelled human carotid artery bifurcation. Exp Fluids 50:1131–1151CrossRefGoogle Scholar
  8. Chapman B, Jost G, van der Pas R (2007) Using OpenMP—portable shared memory parallel programming. The MIT Press, CambridgeGoogle Scholar
  9. Discetti S, Astarita T (2012) A fast multi-resolution approach to tomographic PIV. Exp Fluids 52:765–777CrossRefGoogle Scholar
  10. Elsinga GE, Scarano F, Wieneke B, Oudheusden BW (2006) Tomographic particle image velocimetry. Exp Fluids 41:933–947CrossRefGoogle Scholar
  11. Graftieaux L, Michard M, Grosjean N (2001) Combining PIV, POD and vortex identification algorithm for the study of unsteady turbulent swirling flows. Meas Sci Technol 12:1422–1429CrossRefGoogle Scholar
  12. Gropp W, Lusk E, Skjellum A (1999) Using MPI—portable parallel programming with the message-passing interface, 2nd edn. The MIT Press, CambridgeGoogle Scholar
  13. Herman GT, Lent A (1976) Iterative reconstruction algorithms. Comp Biol Med 6:273–294CrossRefGoogle Scholar
  14. Kaczorowski M, Wagner C (2009) Analysis of the thermal plumes in turbulent Rayleigh-Bénard convection based on well-resolved numerical simulations. J Fluid Mech 618:89–112MATHCrossRefGoogle Scholar
  15. Kühn M, Ehrenfried K, Bosbach J, Wagner C (2008) Feasibility study of tomographic particle image velocimetry for large scale convective air flow. In: 14th international symposium on applications of laser techniques to fluid mechanics, Lisbon, PortugalGoogle Scholar
  16. Kühn M, Bosbach J, Wagner C (2009) Experimental parametric study of forced and mixed convection in a passenger aircraft cabin mock-up. Build Environ 44:961–970CrossRefGoogle Scholar
  17. Kühn M, Ehrenfried K, Bosbach J, Wagner C (2010) Characteristics of large volume tomographic particle image velocimetry using helium filled soap bubbles in forced and thermal convection. In: 15th International symposium on applications of laser techniques to fluid mechanics, Lisbon, PortugalGoogle Scholar
  18. Kühn M, Ehrenfried K, Bosbach J, Wagner C (2011) Large-scale tomographic particle image velocimetry using helium-filled soap bubbles. Exp Fluids 50:929–948CrossRefGoogle Scholar
  19. Mishra D, Muralidhar K, Munshi P (1999) A robust MART algorithm for tomographic applications. Numer Heat Transfer B 35:485–506CrossRefGoogle Scholar
  20. Mueller K (1998) Fast and accurate three-dimensional reconstruction from cone-beam projection data using algebraic methods. PhD thesis, The Ohio State University, Columbus, OH, USAGoogle Scholar
  21. Raffel M, Willert CE, Wereley ST, Kompenhans J (2007) Particle image velocimetry—a practical guide, 2nd edn. Springer, BerlinGoogle Scholar
  22. Scarano F (2002) Iterative image deformation methods in PIV. Meas Sci Technol 13:R1–R19CrossRefGoogle Scholar
  23. Scarano F, Poelma C (2009) Three-dimensional vorticity patterns of cylinder wakes. Exp Fluids 47:69–83CrossRefGoogle Scholar
  24. Schanz D, Gesemann S, Schröder A, Wienecke B, Michaelis D (2010) Tomographic reconstruction with non-uniform optical transfer functions (OTF) In: 15th international symposium on applications of laser techniques to fluid mechanics, Lisbon, PortugalGoogle Scholar
  25. Schmeling D, Westhoff A, Kühn M, Bosbach J, Wagner C (2010) Flow structure formation of turbulent mixed convection in a closed rectangular cavity. In: Dillmann A, Heller G, Klaas M, Kreplin HP, Nitsche W, Schröder W (eds) New results in numerical and experimental fluid mechanics VII. Notes on numerical fluid mechanics and multidisciplinary design (NNFM), vol 112. Springer, Berlin, pp 571–578Google Scholar
  26. Schmeling D, Westhoff A, Kühn M, Bosbach J, Wagner C (2011) Large-scale flow structures and heat transport of turbulent forced and mixed convection in a closed rectangular cavity. Int J Heat Fluid Flow 32:889–900CrossRefGoogle Scholar
  27. Westhoff A, Bosbach J, Schmeling D, Wagner C (2010) Experimental study of low-frequency oscillations and large-scale circulations in turbulent mixed convection. Int J Heat Fluid Flow 31:794–804CrossRefGoogle Scholar
  28. Wieneke B (2008) Volume self-calibration for 3D particle image velocimetry. Exp Fluids 45:549–556CrossRefGoogle Scholar
  29. Worth NA, Nickels TB (2008) Acceleration of Tomo-PIV by estimating the initial volume intensity distribution. Exp Fluids 45:847–856CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Matthias Kühn
    • 1
  • Klaus Ehrenfried
    • 1
  • Johannes Bosbach
    • 1
  • Claus Wagner
    • 1
  1. 1.Institute of Aerodynamics and Flow TechnologyGerman Aerospace Center (DLR)GöttingenGermany

Personalised recommendations