Thanks to the technological progress, 3D velocimetry techniques are becoming more popular. In particular, the time-resolved flow analysis by means of particle tracking is very attractive. Compared to double-frame recordings, higher seeding concentrations are feasible, yielding high spatial resolution results without bias errors due to strong velocity gradients. However, hardware restrictions still limit time-resolved measurements to rather small flow velocities and low magnifications. In aerodynamics, especially, this is a drawback, since often higher flow velocities are of interest. To conduct reliable 3D-PTV measurements from double-frame recordings, the well-established techniques tomographic particle imaging and 3D-PTV are employed for a novel processing approach. In this combined approach, the tomographic reconstruction is used as a predictor for the sensor locations of the corresponding particle images of the reconstructed particles. Furthermore, the reconstruction helps to identify and reject non-corresponding sets of particle images, reducing the amount of ghost particles to a minimum. A probabilistic tracking algorithm is then applied to estimate the flow field.
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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
Elsinga GE, Tokgoz S (2014) Ghost hunting—an assessment of ghost particle detection and removal methods for tomographic-PIV. Meas Sci Technol 25:084004
Elsinga GE, Westerweel J, Scarano F, Novara M (2011) On the velocity of ghost particles and the bias errors in tomographic-PIV. Exp Fluids 50:825–838
Hartley RI, Sturm P (1997) Triangulation. Comput Vis Image Underst 68:146–157
Kähler CJ, Scharnowski S, Cierpka C (2012) On the uncertainty of digital PIV and PTV near walls. Exp Fluids 52:1641–1656
Reuther N, Scharnowski S, Hain R, Schanz D, Schröder A, Kähler CJ (2015) Experimental investigation of adverse pressure gradient turbulent boundary layers by means of large-scale PIV. In: 11th International symposium on particle image velocimetry, Santa Barbara
Schanz D, Gesemann S, Schröder A (2016) Shake-The-Box: Lagrangian particle tracking at high particle image densities. Exp Fluids 57:70
Schröder A, Geisler R, Staack K, Elsinga GE, Scarano F, Wieneke B, Henning A, Poelma C, Westerweel J (2011) Eulerian and Lagrangian views of a turbulent boundary layer flow using time-resolved tomographic PIV. Exp Fluids 50:1071–1091
Wieneke B (2008) Volume self-calibration for 3D particle image velocimetry. Exp Fluids 45:549–556
Wieneke B (2013) Iterative reconstruction of volumetric particle distribution. Meas Sci Technol 24:024008
The investigations were conducted as part of the joint research programme AG Turbo 2020 in the frame of AG Turbo. The work was supported by the Bundesministerium für Wirtschaft und Technologie (BMWi) as per resolution of the German Federal Parliament under Grant No. 03ET2013M. The authors gratefully acknowledge AG Turbo and MTU Aero Engines AG for their support and permission to publish this paper. The responsibility for the content lies solely with its authors.
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Fuchs, T., Hain, R. & Kähler, C.J. Double-frame 3D-PTV using a tomographic predictor. Exp Fluids 57, 174 (2016). https://doi.org/10.1007/s00348-016-2247-0
- Particle Image Velocimetry
- Particle Image
- Tomographic Reconstruction
- Particle Tracking Velocimetry
- Ghost Particle