Skip to main content
Log in

Evolution and recent trends of particle image velocimetry for an aerodynamic experiment (review)

  • Published:
Thermophysics and Aeromechanics Aims and scope

Abstract

This review is devoted to the analysis of the history and current trends in the development of the velocimetry method based on particle images for an aerodynamic experiment. The authors consider the basics of the method, various implementations, former and current status of equipment. Special attention is paid to the methods of data processing and evaluation of various physical values in the flow from the measured velocity fields. The paper briefly analyzes some optical methods that can be used together with velocimetry based on particle images and are implemented using similar equipment. The main focus of the review is set on the works that demonstrate the potential and the current level of the anemometry method based on particle images in the context of an aerodynamic experiment.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • S.S. Abdurakipov, 2016, Features of spiral structures in swirling jets and flame [in Russian], PhD thesis Cand. Phys.-Math. Sci., Novosibirsk.

    Google Scholar 

  • C. Abram, B. Fond, A.L. Heyes, and F. Beyrau, 2013, High-speed planar thermometry and velocimetry using thermographic phosphor particles, Appl. Phys. B, Vol. 111, Iss. 2, P. 155–160.

    Article  ADS  Google Scholar 

  • R.J. Adrian, 1984, Scattering particle characteristics and their effect on pulsed laser measurements of fluid flow: speckle velocimetry vs. particle image velocimetry, Appl. Opt., Vol. 23, No. 11, P. 10–11.

    Article  Google Scholar 

  • R.J. Adrian, 1986, Multi-point optical measurements of simultaneous vectors in unsteady flow — a review, Int. J. Heat Fluid Flow, Vol. 7, No. 2, P. 127–145.

    Article  Google Scholar 

  • R.J. Adrian, 2005, Twenty years of particle image velocimetry, Exp. Fluids, Vol. 39, P. 159–169.

    Article  Google Scholar 

  • Y.K. Akhmetbekov, A.V. Bilsky, D.M. Markovich, A.A. Maslov, P.A Polivanov, I.S. Tsyryulnikov, and M.I. Yaroslavtsev, 2009, Application of “POLIS” PIV system for measurement of velocity fields in a supersonic flow of the wind tunnels, Thermophysics and Aeromechanics, Vol. 16, No. 3, P. 325–333.

    Article  ADS  Google Scholar 

  • S.V. Alekseenko, S.S. Abdurakipov, M.Y. Hrebtov, M.P. Tokarev, V.M. Dulin, and D.M. Markovich, 2018, Coherent structures in the near-field of swirling turbulent jets: a tomographic PIV study, Int. J. Heat and Fluid Flow, Vol. 70, P. 363–379.

    Article  Google Scholar 

  • S. Alekseenko, A. Bilsky, O. Heinz, B. Ilyushin, and D. Markovich, 2003, Near-wall characteristics of impinging turbulent jet, Proc. Fourth Int. Symp. on Turbulence, Heat and Mass Transfer, Antalya, Turkey, P. 12–17.

  • S.V. Alekseenko, A.V. Bilsky, and D.M. Markovich, 2004, Application of the method of particle image velocimetry for analyzing turbulent flows with a periodic component, Instruments Exp. Tech., Vol. 47, No. 5, P. 703–710.

    Article  Google Scholar 

  • I.A. Amelysuhkin, Yu.H. Ganiev, O.A. Gobyzov, Yu.M. Lipnitsky, Yu.A. Lozhkin, and S.E. Filippov, 2017, Non-equilibrium aerosol flow in supersonic wind tunnel, TsAGI Sci J., Vol. 48, No. 1, P. 53–71

    Google Scholar 

  • M.M. Ardasheva, L.B. Nevskii, and G.E. Pervushin, 1985, Measurement of pressure distribution by means of indicator coatings, J. Appl. Mech. Techn. Phys., Vol. 26, No. 4, P. 469–474.

    Article  ADS  Google Scholar 

  • M.P. Arroyo and C.A. Greated, Stereoscopic particle image velocimetry, Meas. Sci.Technol., 1991, Vol. 2, P. 1181–1186.

    Article  ADS  Google Scholar 

  • C. Atkinson and J. Soria, 2009, An efficient simultaneous reconstruction technique for tomographic particle image velocimetry, Exp. Fluids, Vol. 47, P. 553–568.

    Article  Google Scholar 

  • S.J. Beresh, J.F. Henfling, R.W. Spillers, and S.M. Spitzer, 2018, Postage-stamp PIV: small velocity fields at 400 kHz for turbulence spectra measurements, Meas. Sci. Technol., Vol. 29, No. 3, P. 034011–1-034011-11.

    Article  ADS  Google Scholar 

  • S.J. Beresh, S.P. Kearney, J.L. Wagner, D.R. Guildenbecher, J.F. Henfling, R.W. Spillers, B.O.M. Pruett, N. Jiang, M.N. Slipchenko, J. Mance, and S. Roy, 2015, Pulse-burst PIV in a high-speed wind tunnel, Meas. Sci. Technol., Vol. 26, No. 9, P. 09530517–1–09530517–13.

    Article  Google Scholar 

  • A.V. Bilsky, V.M. Dulin, V.A. Lozhkin, D.M. Markovich, and M.P. Tokarev, 2011, Two-dimensional correlation algorithms for tomographic PIV, Proc. 9th Int. Symp. PIV, Kobe, Japan.

  • A.V. Bilsky, V.A. Lozhkin, D.M. Markovich, and M.P. Tokarev, 2013, A maximum entropy reconstruction technique for tomographic particle image velocimetry, Meas. Sci. Technol., Vol. 24, P. 1–10.

    Article  Google Scholar 

  • A.V. Bilsky, V.A. Lozhkin, D.M. Markovich, M.P. Tokarev, and M.V. Shestakov, 2011, Optimization and testing of the tomographic method of velocity measurement in the flow volume, Thermophysics and Aeromechanics, Vol. 18, No. 4, P. 535–545.

    Article  ADS  Google Scholar 

  • D.M. Birch and N. Martin, 2013, Tracer particle momentum effects in vortex flows, J. Fluid Mech., Vol. 723, P. 665–691.

    Article  ADS  MATH  Google Scholar 

  • V.M. Boiko, A.A. Pivovarov, and S.V. Poplavski, 2013, Measurement of gas velocity in a high-gradient flow, based on velocity of tracer particles, Combustion, Explosion, and Shock Waves, Vol. 49, No. 5, P. 548–554.

    Article  Google Scholar 

  • V.M. Boiko, V.I. Zapryagaev, A.A. Pivovarov, and S.V. Poplavski, 2015, Correction of PIV data for reconstruction of the gas velocity in a supersonic underexpanded jet, Combustion, Explosion, and Shock Waves, Vol. 51, No. 5, P. 587–596.

    Article  Google Scholar 

  • J. Bosbach, M. Kuhn, and C. Wagner, 2009, Large scale particle image velocimetry with helium filled soap bubbles, Exp. Fluids, Vol. 46, P. 539–547.

    Article  Google Scholar 

  • I. Boxx, M. Stöhr, C. Carter, and W. Meier, 2010, Temporally resolved planar measurements of transient phenomena in a partially pre-mixed swirl flame in a gas turbine model combustor, Combustion and Flame, Vol. 157, P. 1510–1525.

    Article  Google Scholar 

  • Ch. Brücker, 1995, Digital-Particle-Image-Velocimetry (DPIV) in a scanning light-sheet: 3D starting flow around a short cylinder, Exp. Fluids, Vol. 19, P. 255–263.

    Article  Google Scholar 

  • K.A. Chang, E.A. Cowen, and P.L.F. Liu, 1999, A multi-pulsed PTV technique for acceleration measurement, Proc. 3rd Int. Workshop PIV, Santa Barbara, CA USA, P. 451–456.

  • L.M. Chikishev, V.M. Dulin, O.A. Gobyzov, A.S. Lobasov, and D.M. Markovich, 2017, Mixing in a model gas turbine combustor studied by panoramic optical techniques, Thermophysics and Aeromechanics, Vol. 19, No. 3, P. 351–362.

    Google Scholar 

  • L.M. Chikishev, O.A. Gobyzov, D.K. Sharaborin, Z.D. Kravtsov, V.M. Dulin, A.V. Bilsky, and D.M. Markovich, 2016, PIV characterization of high Reynolds flow in turbine test facility, AIP Conf. Proc., Vol. 1770, P. 30022–1–30022–6.

    Google Scholar 

  • C. Cierpka, B. Lütke, and C.J. Kähler, 2013, Higher order multi-frame particle tracking velocimetry, Exp. Fluids, Vol. 54, P. 1533–1545.

    Article  Google Scholar 

  • J. De Jong, L. Cao, S.H. Woodward, J.P.L.C. Salazar, L.R. Collins, and H. Meng, 2008, Dissipation rate estimation from PIV in zero-mean isotropic turbulence, Exp. Fluids, Vol. 46, No. 3, P. 499–515.

    Article  Google Scholar 

  • V. Del Campo, D. Ragni, D. Micallef, F.J. Diez, and C.S. Ferreira, 2015, Estimation of loads on a horizontal axis wind turbine operating in yawed flow conditions, Wind Energy, Vol. 18, No. 11, P. 1875–1891.

    Article  ADS  Google Scholar 

  • V.M. Dulin, D.M. Markovich, and S.V. Alekseenko, 2009, Stereo PIV measurements of fine-scale turbulence statistics in a free jet flow, Proc. 6th Int. Symp. Turbulence, Heat Mass Transfer, Begell House, Rome, Italy.

  • H. Ehlers, R. Konrath, R. Wokoeck, and R. Radespiel, 2016, Three-dimensional flow field investigations of flapping wing aerodynamics, AIAA J., Vol. 54, No. 11, P. 3434–3449.

    Article  ADS  Google Scholar 

  • G.E. Elsinga, B. Wieneke, F. Scarano, and B.W. van Oudheusden, 2006, Tomographic particle image velocimetry, Exp. Fluids, Vol. 41, P. 933–947.

    Article  Google Scholar 

  • P.J. Erbland, M.L. Baumgartner, A.P. Yalin, M.R. Etz, B. Muzas, W.R. Lempert, A.J. Smits, and R.B. Miles, 1997, Development of planar diagnostics for imaging Mach 8 flow-fields using carbon dioxide and sodium seeding, 35th AeroSciences. Meeting and Exhibit, Reno, NV, USA. AIAA Paper, No. 97-0154.

  • T. Fahringer, K. Lynch, and B. Thurow, 2015, Volumetric particle image velocimetry with a single plenoptic camera, Meas. Sci. Technol., Vol. 26, P. 115201–1–115201–25.

    Article  ADS  Google Scholar 

  • N. Fomin, W. Merzkirch, D. Vitkin, and H. Wintrich, 1996, Visualization of turbulence anisotropy by single exposure speckle photography, Exp. Fluids, Vol. 20, P. 476–479.

    Article  Google Scholar 

  • J.M. Foucaut, J. Carlier, and M. Stanislas, 2004, PIV optimization for the study of turbulent flow using spectral analysis, Meas. Sci. Technol., Vol. 15, No. 6, P. 1046–1058.

    Article  ADS  Google Scholar 

  • Q. Gao, Q. Li, S. Pan, H. Wang, R. Wei, and J. Wang, 2019, Particle reconstruction of volumetric particle image velocimetry with strategy of machine learning. ArXiv:1909.07815 [eess.IV].

  • S. Ghaemi and F. Scarano, 2011, Counter-hairpin vortices in the turbulent wake of a sharp trailing-edge, J. Fluid Mech., Vol. 689, P. 317–356.

    Article  ADS  MATH  Google Scholar 

  • O.A. Gobyzov, Yu.A. Lozhkin, Yu.Kh. Ganiev, E.P. Zakharov, and S.E. Filippov, 2014, Investigation of the flow field in the working part of a supersonic wind tunnel by anemometry using particle images [in Russian], Cosmonautics and Rocket Science, No. 4, P. 26–33.

  • Y.V. Gromyko, P.A. Polivanov, D.A. Bountin, and E.A. Merkulova, 2019, Application of optical methods to study disturbance development, AIP Conf. Proc., Vol. 2125, P. 030097–1–030097–6.

    Google Scholar 

  • R. Gurka, A. Liberzon, D. Hefetz, D. Rubinstein, and U. Shavit, 1999, Computation of pressure distribution using PIV velocity data, Proc. 3rd Int. Workshop PIV, Santa Barbara, CA USA, P. 671–676.

  • W.C. Hinds, 1999, Aerosol technology, properties behavior, and measurement of airborne particles, 2nd ed., John Wiley and Sons, N.Y.

    Google Scholar 

  • K.D. Hinsch, 2002, Holographic particle image velocimetry, Meas. Sci. Technol., Vol. 13, P. R61–R72.

    Article  ADS  Google Scholar 

  • P. Holmes, J.L. Lumley, G. Berkooz, and C.W. Rowley, 2012, Turbulence, coherent structures, dynamical systems and symmetry, 2nd ed., Cambridge University Press.

  • S. Hosokawa, S. Moriyama, A. Tomiyama, and N. Takada, 2003, PIV measurement of pressure distributions about single bubbles, J. Nucl. Sci. Technol., Vol. 40, P. 754–762.

    Article  Google Scholar 

  • R.A. Humble, G.E. Elsinga, F. Scarano, and B.W. van Oudheusden, 2009, Three-dimensional instantaneous structure of a shock wave/turbulent boundary layer interaction, J. Fluid Mech., Vol. 622, P. 33–62.

    Article  ADS  MATH  Google Scholar 

  • M. Huntley and A.J. Smits, 2000, Transition studies on an elliptic cone in Mach 8 flow using Filtered Rayleigh Scattering, European J. Mech. B/Fluids, Vol. 19, No. 5, P. 695–706.

    Article  ADS  MATH  Google Scholar 

  • M.L. Jakobsen, T.P. Dewhirst, and C.A. Greated, 1997, Particle Image Velocimetry for predictions of acceleration fields and forces within fluid flows, Meas. Sci. Technol., Vol. 8, P. 1502–1516.

    Article  ADS  Google Scholar 

  • C.J. Kähler, T. Astarita, P.P. Vlachos, J. Sakakibara, R. Hain, S. Discetti, R. La Foy, and C. Cierpka, 2016, Main results of the 4th International PIV Challenge, Exp. Fluids, Vol. 57, No. 6, P. 1–71.

    Article  Google Scholar 

  • C.J. Kähler, B. Sammler, and J. Kompenhans, 2002, Generation and control of tracer particles for optical flow investigations in air, Exp. Fluids, Vol. 33, P. 736–742.

    Article  Google Scholar 

  • W. Kang and H.J. Sung, 2009, Large-scale structures of turbulent flows over and open cavity, J. Fluids Struct., Vol. 25, P. 1318–1333.

    Article  ADS  Google Scholar 

  • R.D. Keane and R.J. Adrian, 1992, Theory of cross-correlation analysis of PIV images, Appl. Sci. Res., Vol. 49, P. 191–215.

    Article  Google Scholar 

  • E.M. Khabakhpasheva and B.V. Perepelitsa, 1968, Velocity and turbulent fluctuation fields in water containing low concentrations of high-molecular substances, J. Engng Phys. Thermophys., Vol. 14, No. 4, P. 319–320.

    Article  Google Scholar 

  • J. Kompenhans, M. Raffel, L. Dieterle, T. Dewhirst, H. Vollmers, K. Ehrenfried, C. Willert, K. Pengel, C. Kahler, A. Schroder, and O. Ronneberger, 2000, Particle image velocimetry in aerodynamics: Technology and applications in wind tunnels, J. Visualization, Vol. 2, Nos. 3, 4, P. 229–244.

    Article  Google Scholar 

  • S.S. Kutateladze, B.P. Mironov, V.E. Nakoryakov and Ye.M. Khabakhpasheva, 1977, Effect of polymeric additives on turbulent flow of water, Fluid Mech. - Sov. Res., Vol. 6, No. 4, P. 79–102.

    ADS  Google Scholar 

  • P. Lavoie, G. Avallone, F. De Gregorio, G.P. Romano, and R.A. Antonia, 2007, Spatial resolution of PIV for the measurement of turbulence, Exp. Fluids, Vol. 43, P. 39–51.

    Article  Google Scholar 

  • H. Lin, Y. Shi-He, T. Li-Feng, C. Zhi, and Z. Yang-Zhu, 2013, Simultaneous density and velocity measurements in a supersonic turbulent boundary layer, Chinese Phys. B, Vol. 22, No. 2, P. 024704–1–024704–7.

    Article  ADS  Google Scholar 

  • S. Liu, J. Xu, and K. Yu, 2017, MacCormack’s technique-based pressure reconstruction approach for PIV data in compressible flows with shocks, Exp. Fluids, Vol. 58, No. 6, P. 1–22.

    Article  Google Scholar 

  • L.M. Lourenco, S.P. Gogineni, and R.T. Lasalle, 1994, On-line particle-image velocimeter: an integrated approach, Appl. Opt., Vol. 33, No. 13, P. 2465–2470.

    Article  ADS  Google Scholar 

  • J.L. Lumley, 1967, The structure of inhomogeneous turbulent flows, Atmospheric Turbulence and Radio Wave Propagation, Vol. 1, P. 166–178.

    Google Scholar 

  • H.G. Maas, A. Gruen, and D. Papantoniou, 1993, Particle tracking velocimetry in three-dimensional flows, Exp. Fluids, Vol. 15, P. 133–146.

    Article  Google Scholar 

  • D.M. Markovich, S.S. Abdurakipov, L.M. Chikishev, V.M. Dulin, and K. Hanjalic, 2014, Comparative analysis of low- and high-swirl confined flames and jets by proper orthogonal and dynamic mode decompositions, Phys. Fluids, Vol. 26, No. 6, P. 065109–1–065109–22.

    Article  ADS  Google Scholar 

  • D.M. Markovich and M.P. Tokarev, 2008, Algorithms for reconstruction of the three-component velocity field in the Stereo PIV method [in Russian], Computational Methods and Programming, Vol. 9, No. 1, P. 311–326.

    Google Scholar 

  • A.I. Maximov and A.A. Pavlov, 1986, Development of the “laser sheet” method for flow visualization in ultra-sonic wind tunnels [in Russian], TsAGI Proc., Vol. 17, No. 5, P. 37–50.

    Google Scholar 

  • D. Mei, J. Ding, S. Shi, T.H. New, and J. Soria, 2019, High resolution volumetric dual-camera light-field PIV, Exp. Fluids, Vol. 60, P. 132–153.

    Article  Google Scholar 

  • R. Mei, 1996, Velocity fidelity of flow tracer particles, Exp. Fluids, Vol. 22, P. 1–13.

    Article  Google Scholar 

  • A. Melling, 1997, Tracer particles and seeding for particle image velocimetry, Meas. Sci. Technol., Vol. 8, P. 1406–1416.

    Article  ADS  Google Scholar 

  • W. Mickiewicz, 2015, Particle image velocimetry and proper orthogonal decomposition applied to aerodynamic sound source region visualization in organ flue pipe, Archives of Acoustics, Vol. 40, No. 4, P. 475–484.

    Article  Google Scholar 

  • A.V. Mikheev and V.M. Zubtsov, 2008, Enhanced particle-tracking velocimetry (EPTV) with a combined two-component pair-matching algorithm, Meas. Sci. Technol., Vol. 19, No. 8, P. 1–16.

    Article  Google Scholar 

  • N.I. Mikheev and N.S. Dushin, 2016, A method for measuring the dynamics of velocity vector fields in a turbulent flow using smoke image-visualization videos, Instruments and Experimental Techniques, Vol. 59, No. 6, P. 882–889.

    Article  Google Scholar 

  • S.C. Morris, 2011, Shear-layer instabilities: particle image velocimetry measurements and implications for acoustics, Ann. Rev. Fluid. Mech., Vol. 43, No. 1, P. 529–550.

    Article  ADS  MATH  Google Scholar 

  • V.E. Nakoryakov, B.G. Pokusaev, S.V. Alekseenko, and V.V. Orlov, 1977, Instantaneous velocity profile in a wavy fluid film, J. Engng Phys. Thermophys., Vol. 33, P. 1012–1016.

    Article  Google Scholar 

  • P.A. Polivanov, 2018, Calculating pressure fields on the basis of PIV-measurements for supersonic flows, Thermophysics and Aeromechanics, Vol. 25, No. 5, P. 789–792.

    Article  ADS  Google Scholar 

  • K. Nishino, N. Kasagi, and M. Hirata, 1989, Three-dimensional particle tracking velocimetry based on automated digital image processing, Trans. ASME, Vol. 111, P. 384–391.

    Article  Google Scholar 

  • F. Pereira, M. Gharib, D. Dabiri, and D. Modarress, 2000, Defocusing digital particle image velocimetry: a 3-component 3-dimensional DPIV measurement technique. Application to bubbly flows, Exp. Fluids, Vol. 29, P. S78–S84.

    Article  Google Scholar 

  • A.K. Prasad and K. Jensen, 1995, Sheimpflug stereocamera for particle image velocimetry in liquid flows, Appl. Opt., Vol. 34, No. 30, P. 7092–7099.

    Article  ADS  Google Scholar 

  • S. Probsting, M. Tuinstra, and F. Scarano, 2015, Trailing edge noise estimation by tomographic particle image velocimetry, J. Sound Vib., Vol. 346, P. 117–138.

    Article  ADS  Google Scholar 

  • M. Raffel, C.E. Willert, F. Scarano, C. Kähler, S.T. Wereley, and J. Kompenhans, 2018, Particle Image Velocimetry, A Practical Guide, 3rd ed., Springer Int. Publishing.

  • D. Ragni, A. Ashok, B.W. van Oudheusden, and F. Scarano, 2009, Surface pressure and aerodynamic loads determination of a transonic airfoil based on particle image velocimetry, Meas. Sci. Technol., Vol. 20, No. 7, P. 074005–1–074005–14.

    Article  ADS  Google Scholar 

  • D.A. Rothamer and J. Jordan, 2011, Planar imaging thermometry in gaseous flows using upconversion excitation of thermographic phosphors, Applied Phys. B, Vol. 106, No. 2, P. 435–444.

    Article  ADS  Google Scholar 

  • F. Scarano, 2012, Tomographic PIV: principles and practice, Meas. Sci. Technol., Vol. 24, No. 1, P. 012001–1-012001-28.

    Article  ADS  Google Scholar 

  • F. Scarano and M.L. Riethmuller, 1999, Iterative multigrid approach in PIV image processing with discrete window offset, Exp. Fluids, Vol. 26, P. 513–523.

    Article  Google Scholar 

  • D. Schanz, S. Gesemann, and A. Schröder, 2016, Shake-The-Box: Lagrangian particle tracking at high particle image densities, Exp. Fluids, Vol. 57, No. 5, P. 1–27.

    Article  Google Scholar 

  • P.J. Schmid, 2010, Dynamic mode decomposition of numerical and experimental data, J. Fluid Mech., Vol. 656, P. 5–28.

    Article  ADS  MathSciNet  MATH  Google Scholar 

  • A. Sciacchitano, F. Scarano, and B. Wieneke, 2012, Multi-frame pyramid correlation for time-resolved PIV, Exp. Fluids, Vol. 53, No. 4, P. 1087–1105.

    Article  Google Scholar 

  • A. Segalini, G. Bellani, G. Sardina, L. Brandt, and E.A. Variano, 2014, Corrections for one- and two-point statistics measured with coarse-resolution particle image velocimetry, Exp. Fluids., Vol. 55, P. 1739–1757.

    Article  Google Scholar 

  • M.V. Shestakov, M.P. Tokarev, and D.M. Markovich, 2014, 3D Flow dynamics in a turbulent slot jet: time-resolved tomographic PIV measurements, Proc. 17-th Int. Symp. on Appl. of Laser Techniques to Fluid Mech., Lisbon, Portugal, P. 1–7.

  • S. Shi, J. Wang, J. Ding, Z. Zhao, and T.H. New, 2016, Parametric study on light-field volumetric particle image velocimetry, Flow. Meas. Instrum., Vol. 49, P. 70–88.

    Article  Google Scholar 

  • M.N. Slipchenko, J.D. Miller, S. Roy, J.R. Gord, S.A. Danczyk, and T.R. Meyer, 2012, Quasi-continuous burst-mode laser for high-speed planar imaging, Optics Letters, Vol. 37, No. 8, P. 1346–1348.

    Article  ADS  Google Scholar 

  • S.M. Soloff, R.J. Adrian, and Z.-C. Liu, 1997, Distortion compensation for generalized stereoscopic particle image velocimetry, Meas. Sci. Technol., Vol. 8, P. 1441–1454.

    Article  ADS  Google Scholar 

  • M. Stanislas and K. Okamoto, 2003, Main results of the First International PIV Challenge, Meas. Sci. Technol., Vol. 14, P. R63–R89.

    Article  Google Scholar 

  • M. Stanislas, K. Okamoto, C.J. Kähler, and J. Westerweel, 2005, Main results of the Second International PIV Challenge, Exp. Fluids, Vol. 39, No. 2, P. 170–191.

    Article  Google Scholar 

  • L.K. Su and M.G. Mungal, 2004, Simultaneous measurements of scalar and velocity field evolution in turbulent crossflowing jets, J. Fluid Mech., Vol. 513, P. 1–45.

    Article  ADS  MATH  Google Scholar 

  • K. Taira, S.L. Brunton, S.T.M. Dawson, C.W. Rowley, T. Colonius, B.J. McKeon, O.T. Schmidt, S. Gordeyev, V. Theofilis, and L.S. Ukeiley, 2017, Modal analysis of fluid flows: an overview, AIAA J., Vol. 55, P. 4013–4041.

    Article  ADS  Google Scholar 

  • G. Tedeschi, H. Gouin, and M. Elena, 1999, Motion of tracer particles in supersonic flows, Exp. Fluids, Vol. 26, No. 4, P. 288–296.

    Article  Google Scholar 

  • W. Terra, A. Sciacchitano, and Y.H. Shah, 2019, Aerodynamic drag determination of a full-scale cyclist mannequin from large-scale PTV measurements, Exp. Fluids, Vol. 60, No. 2, P. 29–40.

    Article  Google Scholar 

  • B.H. Timmerman, 1997, Holographic interferometric tomography for unsteady compressible flow, PhD thesis, Delft University of Technology.

  • M.P. Tokarev, D.M. Markovich, and A.V. Bilsky, 2007, Adaptive algorithms for PIV image processing [in Russian], Comput. Technol., Vol. 12, No. 3, P. 109–131.

    MATH  Google Scholar 

  • M.P. Tokarev, 2010, Development of algorithms and software for processing images in digital tracer visualization methods [in Russian], PhD thesis: Cand. Tech. Sci., Novosibirsk.

    Google Scholar 

  • C. Tropea, A.L. Yarin, and J.F. Foss, 2007, Springer Handbook of Experimental Fluid Mechanics, Springer, Berlin Heidelberg.

    Book  Google Scholar 

  • B.W. Van Oudheusden, F. Scarano, E.W. Roosenboom, E.W. Casimiri, and L.J. Souverein, 2007, Evaluation of integral forces and pressure fields from planar velocimetry data for incompressible and compressible flows, Exp. Fluids, Vol. 43, No. 2–3, P. 153–162.

    Article  Google Scholar 

  • V.A. Vlasov, G.G. Gadzhimagomedov, V.M. Lutovinov, and D.S. Sboev, 2013, Aerodynamic loads measurements on an airfoil using PIV system, TsAGI Sci J., Vol. 44, No. 3, P. 355–370.

    Article  Google Scholar 

  • C.E. Willert and M. Gharib, 1991, Digital particle image velocimetry, Exp. Fluids, Vol. 10, P. 181–193.

    Article  Google Scholar 

  • Y. Wu, S. Yi, He L., Z. Chen, and X. Wang, 2016, Experimental investigations of supersonic flow over a compression ramp based on nanoparticle-tracer-based planar laser scattering technique, Experimental Techniques, Vol. 40, No. 2, P. 651–660.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to O. A. Gobyzov.

Additional information

The work was carried out within the framework of State contract with Kutateladze Institute of Thermophysics SB RAS.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bilsky, A.V., Gobyzov, O.A. & Markovich, D.M. Evolution and recent trends of particle image velocimetry for an aerodynamic experiment (review). Thermophys. Aeromech. 27, 1–22 (2020). https://doi.org/10.1134/S0869864320010011

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0869864320010011

Keywords

Navigation