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Particle image velocimetry

About: Particle image velocimetry is a research topic. Over the lifetime, 14343 publications have been published within this topic receiving 271700 citations.


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TL;DR: In this paper, the proper orthogonal decomposition (POD) is combined with two new vortex identification functions, Γ1 and Γ2, to identify the locations of the center and boundary of the vortex on the basis of the velocity field.
Abstract: Particle image velocimetry (PIV) measurements are made in a highly turbulent swirling flow. In this flow, we observe a coexistence of turbulent fluctuations and an unsteady swirling motion. The proper orthogonal decomposition (POD) is used to separate these two contributions to the total energy. POD is combined with two new vortex identification functions, Γ1 and Γ2. These functions identify the locations of the centre and boundary of the vortex on the basis of the velocity field. The POD computed for the measured velocity fields shows that two spatial modes are responsible for most of the fluctuations observed in the vicinity of the location of the mean vortex centre. These two modes are also responsible for the large-scale coherence of the fluctuations. The POD computed from the Γ2 scalar field shows that the displacement and deformation of the large-scale vortex are correlated to these modes. We suggest the use of such a method to separate pseudo-fluctuations due to the unsteady nature of the large-scale vortices from fluctuations due to small-scale turbulence.

796 citations

Journal ArticleDOI
TL;DR: In this paper, an iterative method for particle image velocimetry (PIV) was proposed to enhance the precision and spatial resolution of numerical interrogation schemes by taking into account the local velocity derivatives in order to increase the interrogation spatial density and a refinement of the local interrogation window size.
Abstract: Image processing methods for particle image velocimetry (PIV) are reviewed. The discussion focuses on iterative methods aimed at enhancing the precision and spatial resolution of numerical interrogation schemes. Emphasis is placed on the efforts made to overcome the limitations of the correlation interrogation method with respect to typical problems such as in-plane loss of pairs, velocity gradient compensation and correlation peak locking. The discussion shows how the correlation signal benefits from simple operations such as the window-offset technique, or the continuous window deformation, which compensates for the in-plane velocity gradient. The image interrogation process is presented within the discussion of the image matching problem and several algorithms and implementations currently in use are classified depending on the choice made about the particle image pattern matching scheme. Several methods that differ in their implementations are found to be substantially similar. Iterative image deformation methods that account for the continuous particle image pattern transformation are analysed and the effect of crucial choices such as image interpolation method, displacement prediction correction and correlation peak fit scheme are discussed. The quantitative performance assessment made through synthetic PIV images yields order-of-magnitude improvement on the precision of the particle image displacement at a sub-pixel level when the image deformation is applied. Moreover, the issue of spatial resolution is addressed and the limiting factors of the specific interrogation methods are discussed. Finally, an attempt for a flow-adaptive spatial resolution method is proposed. The method takes into account the local velocity derivatives in order to perform a local increase of the interrogation spatial density and a refinement of the local interrogation window size. The resulting spatial resolution is selectively enhanced. The method's performance is analysed and compared with some precursor techniques, namely the conventional cross-correlation analysis with and without the effect of a window discrete offset and deformation. The suitability of the method for the measurement in turbulent flows is illustrated with the application to a turbulent backward facing step flow.

776 citations

Journal ArticleDOI
TL;DR: This review article presents the theory and practice of these techniques using a tutorial approach and compares the relative merits of the scanning and full-field approaches to velocity map imaging and concludes with a review of reported applications ofThese techniques to blood perfusion mapping and imaging.
Abstract: Laser Doppler velocimetry uses the frequency shift produced by the Doppler effect to measure velocity. It can be used to monitor blood flow or other tissue movement in the body. Laser speckle is a random interference effect that gives a grainy appearance to objects illuminated by laser light. If the object consists of individual moving scatterers (such as blood cells), the speckle pattern fluctuates. These fluctuations provide information about the velocity distribution of the scatterers. It can be shown that the speckle and Doppler approaches are different ways of looking at the same phenomenon. Both these techniques measure at a single point. If a map of the velocity distribution is required, some form of scanning must be introduced. This has been done for both time-varying speckle and laser Doppler. However, with the speckle technique it is also possible to devise a full-field technique that gives an instantaneous map of velocities in real time. This review article presents the theory and practice of these techniques using a tutorial approach and compares the relative merits of the scanning and full-field approaches to velocity map imaging. The article concludes with a review of reported applications of these techniques to blood perfusion mapping and imaging.

706 citations

Journal ArticleDOI
TL;DR: The principle of stereoscopic PIV, the different stereoscopic configurations that have been used, the relative error in the out-of-plane to the in-plane measurement, and the relative merits of calibration-based methods for reconstructing the three-dimensional displacement vector in comparison to geometric reconstruction are discussed.
Abstract: Stereoscopic particle image velocimetry (PIV) employs two cameras to record simultaneous but distinct off-axis views of the same region of interest (illuminated plane within a flow seeded with tracer particles). Sufficient information is contained in the two views to extract the out-of-plane motion of particles, and also to eliminate perspective error which can contaminate the in-plane measurement. This review discusses the principle of stereoscopic PIV, the different stereoscopic configurations that have been used, the relative error in the out-of-plane to the in-plane measurement, and the relative merits of calibration-based methods for reconstructing the three-dimensional displacement vector in comparison to geometric reconstruction. It appears that the current trend amongst practitioners of stereoscopic PIV is to use digital cameras to record the two views in the angular displacement configuration while incorporating the Scheimpflug condition. The use of calibration methods has also gained prominence over geometric reconstruction.

644 citations

Journal ArticleDOI
TL;DR: An image-processing technique that performs iterative interrogation of particle image velocimetry (PIV) recordings based on cross-correlation enhances the matching performances by means of a relative transformation between the interrogation areas, showing that a remarkable improvement can be obtained in terms of precision and dynamic range.
Abstract: An image-processing technique is proposed, which performs iterative interrogation of particle image velocimetry (PIV) recordings. The method is based on cross-correlation, enhancing the matching performances by means of a relative transformation between the interrogation areas. On the basis of an iterative prediction of the tracers motion, window offset and deformation are applied, accounting for the local deformation of the fluid continuum. In addition, progressive grid refinement is applied in order to maximise the spatial resolution. The performances of the method are analysed and compared with the conventional cross correlation with and without the effect of a window discrete offset. The assessment of performance through synthetic PIV images shows that a remarkable improvement can be obtained in terms of precision and dynamic range. Moreover, peak-locking effects do not affect the method in practice. The velocity gradient range accessed with the application of a relative window deformation (linear approximation) is significantly enlarged, as confirmed in the experimental results.

640 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20241
2023533
20221,116
2021615
2020645
2019723