Abstract
We propose a novel robust 3D particle tracking technique based on a scanning laser setup. The method yields Lagrangian statistics in densely seeded turbulent flows with good spatial and temporal resolution, overcoming some of the inherent difficulty with line-of-sight-based volumetric methods. To do this, we have developed an effective triangulation method greatly reducing ghost particle reconstruction using images from two cameras. A laser sheet is rapidly traversed (‘scanned’) across a measurement volume illuminating only a thin slice of the flow at a time. Particle images are taken at closely spaced, overlapping nominal laser sheet locations giving multiple intensity recordings for each individual particle. The laser-sheet intensity varies as a Gaussian across its thickness, which is here exploited to deduce the particle’s probable location along the scan direction to sub-sheet number resolution by fitting a similar Gaussian profile to the particle’s multiple intensity recordings. The method is presently verified via numerical experiment using a DNS database. Following successful reconstruction of a time series of 3D particle fields, particle tracks are formed from which all components of Lagrangian velocity and acceleration are calculated.
Graphic abstract
Similar content being viewed by others
References
Adrian RJ (1991) Particle-imaging techniques for experimental fluid mechanics. Ann Rev Fluid Mech 23:261–304
Brücker C (1995) Digital-particle-image-velocimetry (DPIV) in a scanning light-sheet: 3D starting flow around a short cylinder. Exp Fluids 19:255–263
Cierpka C, Lütke B, Kähler CJ (2013) Higher order multi-frame particle tracking velocimetry. Exp Fluids 54:1533
Elsinga GE, Scarano F, Wieneke B, Van Oudheusden BW (2006) Tomographic particle image velocimetry. Exp Fluids 41:933–947
Garcia V, Debreuve E, Nielsen F, Barlaud M (2010) K-nearest neighbor search: fast GPU-based implementations and application to high-dimensional feature matching. In: 17th IEEE international conference on image processing (ICIP), Hong Kong
Gesemann S, Huhn F, Schanz D, Schröder A (2016) From noisy particle tracks to velocity, acceleration and pressure fields using B-splines and penalties. In: 18th international symposium on the application of laser and imaging techniques to fluid mechanics, Lisbon, Portugal
Hartley R, Zisserman A (2003) Multiple view geometry in computer vision. Cambridge University Press, Cambridge
Hoyer K, Holzner M, Lüthi B, Guala M, Liberzon A, Kinzelbach W (2005) 3D scanning particle tracking velocimetry. Exp Fluids 39:923
Knutsen AN, Lawson JM, Dawson JR, Worth NA (2017) A laser sheet self-calibration method for scanning PIV. Exp Fluids 58:145
Lawson JM, Dawson JR (2014) A scanning PIV method for fine-scale turbulence measurements. Exp Fluids 55:1857
Lawson JM, Dawson JR (2015) On velocity gradient dynamics and turbulent structure. J Fluid Mech 780:60–98
Lawson JM, Bodenschatz E, Knutsen AN, Dawson JR, Worth NA (2019) Direct assessment of Kolmogorov’s first refined similarity hypothesis. Phys Rev Fluids 4:022,601
Lecordier B, Westerweel J (2004) The EUROPIV synthetic image generator (SIG). In: Particle image velocimetry: recent improvements, Springer, New York, pp 145–161
Li Y, Perlman E, Wan M, Yang Y, Meneveau C, Burns R, Chen S, Szalay A, Eyink G (2008) A public turbulence database cluster and applications to study Lagrangian evolution of velocity increments in turbulence. J Turbul 9:1–29
Lüthi B, Tsinober A, Kinzelbach W (2005) Lagrangian measurement of vorticity dynamics in turbulent flow. J Fluid Mech 528:87–118
Lynch KP, Scarano F (2015) An efficient and accurate approach to MTE-MART for time-resolved tomographic PIV. Exp Fluids 56:66
Maas HG, Gruen A, Papantoniou D (1993) Particle tracking velocimetry in three-dimensional flows. Exp Fluids 15:133–146
Malik NA, Dracos T, Papantoniou DA (1993) Particle tracking velocimetry in three-dimensional flows. Exp Fluids 15:279–294
Nishino K, Kasagi N, Hirata M (1989) Three-dimensional particle tracking velocimetry based on automated digital image processing. Trans ASME J Fluid Eng 111:384–391
Novara M, Scarano F (2013) A particle-tracking approach for accurate material derivative measurements with tomographic PIV. Exp Fluids 54:1584
Ouellette NT, Xu H, Bodenschatz E (2006) A quantitative study of three-dimensional lagrangian particle tracking algorithms. Exp Fluids 40:301–313
Schanz D, Gesemann S, Schröder A, Wieneke B, Novara M (2013) Non-uniform optical transfer functions in particle imaging: calibration and application to tomographic reconstruction. Meas Sci Technol 24:024009
Schanz D, Gesemann S, Schröder A (2016) Shake-The-Box: Lagrangian particle tracking at high particle image densities. Exp Fluids 57:70
Scharnowski S, Kähler CJ (2016) Estimation and optimization of loss-of-pair uncertainties based on PIV correlation functions. Exp Fluids 57:23
Schneiders JFG, Scarano F (2016) Dense velocity reconstruction from tomographic PTV with material derivatives. Exp Fluids 57:139
Virant M, Dracos T (1997) 3D PTV and its application on lagrangian motion. Meas Sci Technol 8:1539
Voth GA, La Porta A, Crawford AM, Alexander J, Bodenschatz E (2002) Measurement of particle accelerations in fully developed turbulence. J Fluid Mech 469:121–160
Wieneke B (2013) Iterative reconstruction of volumetric particle distribution. Meas Sci Technol 24:024,008
Yu H, Kanov K, Perlman E, Graham J, Frederix E, Burns R, Szalay A, Eyink G, Meneveau C (2012) Studying lagrangian dynamics of turbulence using on-demand fluid particle tracking in a public turbulence database. J Turbul 13:1–29
Zhang W, Hain R, Kähler CJ (2008) Scanning PIV investigation of the laminar separation bubble on a SD7003 airfoil. Exp Fluids 45:725–743
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Kozul, M., Koothur, V., Worth, N.A. et al. A scanning particle tracking velocimetry technique for high-Reynolds number turbulent flows. Exp Fluids 60, 137 (2019). https://doi.org/10.1007/s00348-019-2777-3
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1007/s00348-019-2777-3