Particle Image Velocimetry: A Practical Guide

By Markus Raffel. 2002

4,595 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/62a045e50f8eeb3011e6c7e0673f78c48ab7159f

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Citations in the corpus

Flow over an espresso cup: inferring 3-D velocity and pressure fields from tomographic background oriented Schlieren via physics-informed neural networks (2021, methodology): “Compared to other flow visualization technologies, such as particle image velocimetry (PIV) (Raffel et al. 2018) and laser induced”
PIV-based pressure measurement (2013, methodology): “…and versatile technique for flow field measurement, capable of delivering a detailed experimental characterization of the flow in terms of (large) ensembles of instantaneous velocity fields, in an efficient and non-intrusive manner (Adrian 2005, Raffel et al. 2007, Adrian and Westerweel 2011).”
Spectral proper orthogonal decomposition (2015, methodology): “The PIV data were processed with PIVview (PIVTEC GmbH) using standard digital PIV processing (Willert & Gharib 1991) enhanced by iterative multi-grid interrogation (Soria 1996) with image deformation (Huang, Fiedler & Wang 1993; Raffel et al. 2007, pp. 146–158).”
Multi-frame pyramid correlation for time-resolved PIV (2012, background): “In the conventional image–pair correlation algorithm, two main error sources are responsible for the low accuracy of the temporal derivatives (Fincham and Delerce 2000; Raffel et al. 2007): 1.”
Optically sliced micro-PIV using confocal laser scanning microscopy (CLSM) (2004, methodology): “The idea is that CLSM can accommodate the use of particle image velocimetry (Raffel et al. 1998) to provide optically sliced micro-fluidic velocity field mapping.”
Structure of the airflow above surface waves (2016, background): “01), which yielded a RMS tracking error below 1% (Raffel et al., 2007).”
A synthetic Schlieren method for the measurement of the topography of a liquid interface (2009, methodology): “In fluid mechanics, apart from synthetic Schlieren applications, DIC algorithms are mostly used in particle image velocimetry (PIV) applications, where the velocity field is given by the displacement field of tracer particles per unit of sampling time (Adrian 1991; Raffel et al. 1998).”