A PIV Algorithm for Estimating Time-Averaged Velocity Fields

By C. Meinhart, Steven Wereley, Juan G. Santiago. 2000

586 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computational Mechanics, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/de1f997db20e6a9195c660729433dc4a322412bc

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In Aerospace Engineering

In Computational Mechanics

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Citations in the corpus

Particle imaging techniques for volumetric three-component (3D3C) velocity measurements in microfluidics (2011, methodology): “The averaging or summation of the correlation maps is an effective technique to deal with low seeding concentrations and low signal-to-noise ratios, especially for the processing of PIV data (Meinhart et al. 2000).”
Single-pixel resolution ensemble correlation for micro-PIV applications (2004, methodology): “This implies that the spatial correlation is computed in identical positions for a set of 10–20 consecutive image pairs, and then ensemble averaged (Delnoij et al. 1999, Meinhart et al. 2000; Wereley et al. 2002).”
On the resolution limit of digital particle image velocimetry (2012, methodology): “The evaluation of the data was performed using a sumof-correlation approach proposed by Meinhart et al. (2000) without any window weighting using 16 9 16 px interrogation windows with 87% overlap.”
Recent Advances in Micro-Particle Image Velocimetry (2010, unknown): “The average correlation method outperformed the other two methods and produced fewer than 0.5 to 1% erroneous measurements after averaging eight realizations (Meinhart et al. 2000).”
Particle tracer response across shocks measured by PIV (2011, methodology): “The recorded images are evaluated with the ensemble auto-correlation technique (Meinhart et al. 2000) available in DaVis7.”
Time-resolved reconstruction of the full velocity field around a dynamically-scaled flapping wing (2006, methodology): “A detailed description of this technique can be found in Meinhart et al. (2000).”
Stereo-PIV using self-calibration on particle images (2005, methodology): “In this case, it is required to perform a calibration outside in the water basin for each z scan position separately by adjusting the distance between the cameras and the front side of the water basin accordingly.”
Particle imaging techniques for microfabricated fluidic systems (2003, methodology): “Improvements on PIV correlation signal-to-noise ratio (and subsequently spatial resolution) can be obtained for time-averaged or phase-averaged velocity data by averaging a series of correlation functions prior to locating the signal peak in the correlation domain (Meinhart et al. 2000a).”
Multi-frame pyramid correlation for time-resolved PIV (2012, methodology): “The method practically corresponds to that of Meinhart et al. (2000), with the only difference that the ensemble average is not made on a long sequence, but rather on a short kernel according to the discussion made in Sect.”
On the uncertainty of digital PIV and PTV near walls (2012, methodology): “…are well-established: The first one is the window-correlation method that can be used to evaluate single image pairs in order to investigate instantaneous flow phenomena (Adrian and Westerweel 2010; Raffel et al. 2007) or to estimate mean flow properties as discussed in Meinhart et al. (2000).”