Advances in iterative multigrid PIV image processing

Scarano, Fulvio; Riethmuller, M. L.

doi:10.1007/s003480070007

Cited by 501 publications

(284 citation statements)

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“…Image deformation is applied to each correlation window 32 whilst outlier detection and recursive replacement by the average of admissible neighbor vectors over a 3 × 3 × 3 vector region is performed after each correlation pass. 33 The resulting vector field contains approximately 1 ×10 6 vectors in an ellipsoidal region at an equal spacing of 0.825 mm.…”

Section: Tomographic Reconstruction and Vector Calculationmentioning

confidence: 99%

Scanning tomographic particle image velocimetry applied to a turbulent jet

2013

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We introduce a modified tomographic PIV technique using four high-speed video cameras and a scanning pulsed laser-volume. By rapidly illuminating adjacent subvolumes onto separate video frames, we can resolve a larger total volume of velocity vectors, while retaining good spatial resolution. We demonstrate this technique by performing time-resolved measurements of the turbulent structure of a round jet, using up to 9 adjacent volume slices. In essence this technique resolves more velocity planes in the depth direction by maintaining optimal particle image density and limiting the number of ghost particles. The total measurement volumes contain between 1 ×106 and 3 ×106 velocity vectors calculated from up to 1500 reconstructed depthwise image planes, showing time-resolved evolution of the large-scale vortical structures for a turbulent jet of Re up to 10 000.

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Section: Tomographic Reconstruction and Vector Calculationmentioning

confidence: 99%

Scanning tomographic particle image velocimetry applied to a turbulent jet

2013

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“…The reconstructed volume dimensions in streamwise (x), wall-normal (y) and spanwise direction (z) were 70 × 6.5 × 35 mm 3 , which was discretized at 20 3 voxels mm −3 . The particle motion analysis was performed by cross-correlation adopting a multi-grid method including volume deformation (Scarano & Riethmuller 2000). The measurement spatial resolution was dictated by the final interrogation box size of 40 3 voxels (2.0 × 2.0 × 2.0 mm 3 ) each including approximately 24 tracers.…”

Section: Tomographic Pivmentioning

confidence: 99%

Three-dimensional vortex organization in a high-Reynolds-number supersonic turbulent boundary layer

et al. 2010

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Tomographic particle image velocimetry was used to quantitatively visualize the three-dimensional coherent structures in a supersonic (Mach 2) turbulent boundary layer in the region between y/δ = 0.15 and 0.89. The Reynolds number based on momentum thickness Re θ = 34 000. The instantaneous velocity fields give evidence of hairpin vortices aligned in the streamwise direction forming very long zones of lowspeed fluid, consistent with Tomkins & Adrian (J. Fluid Mech., vol. 490, 2003, p. 37). The observed hairpin structure is also a statistically relevant structure as is shown by the conditional average flow field associated to spanwise swirling motion. Spatial low-pass filtering of the velocity field reveals streamwise vortices and signatures of large-scale hairpins (height > 0.5δ), which are weaker than the smaller scale hairpins in the unfiltered velocity field. The large-scale hairpin structures in the instantaneous velocity fields are observed to be aligned in the streamwise direction and spanwise organized along diagonal lines. Additionally the autocorrelation function of the wallnormal swirling motion representing the large-scale hairpin structure returns positive correlation peaks in the streamwise direction (at 1.5δ distance from the DC peak) and along the 45 • diagonals, which also suggest a periodic arrangement in those directions. This is evidence for the existence of a spanwise-streamwise organization of the coherent structures in a fully turbulent boundary layer.

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“…The most common choice for the displacement interpolation is bi-linear (Huang et al 1993;Jambunathan et al 1995;Scarano and Riethmuller 2000a) which is also used in the current investigation. Higher order functions have also been considered (Fincham and Delerce 2000;Lecordier and Trinité 2003), which may in principle improve the accuracy of image deformation.…”

Section: Iterative Interrogation With Image Deformationmentioning

confidence: 99%

“…The iterative window deformation method (Huang et al 1993;Jambunathan et al 1995) opened the way to the development of more sophisticated algorithms able to cope with flows exhibiting a large velocity gradient minimizing correlation peak broadening. The most important improvement brought to the technique was in terms of the velocity gradient dynamic range (Fincham and Delerce 2000;Scarano and Riethmuller 2000a). However, the properties of the iterative interrogation process, expressed as the stability and the spatial resolution of the converged results were not well understood.…”

Section: Introductionmentioning

confidence: 99%

Effect of predictor–corrector filtering on the stability and spatial resolution of iterative PIV interrogation

2008

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The stability and resolution of iterative PIV image analysis methods is investigated. The study focuses on the effects of stabilization by means of spatial filtering when implemented into the iterative process. Two filtering approaches are studied: predictor and corrector filtering respectively. A family of convolution filters is proposed, which allows to vary the filtering strength in a systematic way and primarily affects the system stability and to a smaller extent its spatial response. A critical value for the filter parameter is identified which guarantees the stability of the iterative process. A theoretical analysis is provided that determines the asymptotic properties of the iterative method with varying filter parameters. The study is completed with a numerical assessment and concludes with an application to real experiments, showing the consequence of an incorrect implementation of the iterative scheme under experimental conditions.

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Advances in iterative multigrid PIV image processing

Cited by 501 publications

References 0 publications

Scanning tomographic particle image velocimetry applied to a turbulent jet

Scanning tomographic particle image velocimetry applied to a turbulent jet

Three-dimensional vortex organization in a high-Reynolds-number supersonic turbulent boundary layer

Effect of predictor–corrector filtering on the stability and spatial resolution of iterative PIV interrogation

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