Measuring Tollmien–Schlichting waves using phase-averaged particle image velocimetry

This article addresses the direct experimental measurement of Tollmien?CSchlichting waves on a flat plate, when the laminar boundary layer is excited by velocity perturbations; the free stream velocity was 16?m/s, the excitation frequency 250?Hz. The two-dimensional velocity field in proximity of the flat plate was captured using a conventional PIV system; however, the image recording was phase locked with the disturbance source and ensemble averaging was used to obtain characteristics of the Tollmien?CSchichting waves. In particular, after subtraction of the mean velocity, the characteristics of the excited waves in terms of streamlines were extracted, revealing that the investigated waves represented velocity deviations with an order of magnitude of 1?% of the undisturbed free stream flow. This study is a prelude to the use of the same technique to visualize the effect of dielectric barrier discharge plasma actuators on the suppression of such Tollmien?CSchlichting waves, which is difficult using other measurement techniques.     

Stereoscopic particle image velocimetry

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. Received: 15 April 1999/Accepted: 1 February 2000     

Tomographic particle image velocimetry

This paper describes the principles of a novel 3D PIV system based on the illumination, recording and reconstruction of tracer particles within a 3D measurement volume. The technique makes use of several simultaneous views of the illuminated particles and their 3D reconstruction as a light intensity distribution by means of optical tomography. The technique is therefore referred to as tomographic particle image velocimetry (tomographic-PIV). The reconstruction is performed with the MART algorithm, yielding a 3D array of light intensity discretized over voxels. The reconstructed tomogram pair is then analyzed by means of 3D cross-correlation with an iterative multigrid volume deformation technique, returning the three-component velocity vector distribution over the measurement volume. The principles and details of the tomographic algorithm are discussed and a parametric study is carried out by means of a computer-simulated tomographic-PIV procedure. The study focuses on the accuracy of the light intensity field reconstruction process. The simulation also identifies the most important parameters governing the experimental method and the tomographic algorithm parameters, showing their effect on the reconstruction accuracy. A computer simulated experiment of a 3D particle motion field describing a vortex ring demonstrates the capability and potential of the proposed system with four cameras. The capability of the technique in real experimental conditions is assessed with the measurement of the turbulent flow in the near wake of a circular cylinder at Reynolds 2,700.     

Digital particle image velocimetry

Digital particle image velocimetry (DPIV) is the digital counterpart of conventional laser speckle velocitmetry (LSV) and particle image velocimetry (PIV) techniques. In this novel, two-dimensional technique, digitally recorded video images are analyzed computationally, removing both the photographic and opto-mechanical processing steps inherent to PIV and LSV. The directional ambiguity generally associated with PIV and LSV is resolved by implementing local spatial cross-correlations between two sequential single-exposed particle images. The images are recorded at video rate (30 Hz or slower) which currently limits the application of the technique to low speed flows until digital, high resolution video systems with higher framing rates become more economically feasible. Sequential imaging makes it possible to study unsteady phenomena like the temporal evolution of a vortex ring described in this paper. The spatial velocity measurements are compared with data obtained by direct measurement of the separation of individual particle pairs. Recovered velocity data are used to compute the spatial and temporal vorticity distribution and the circulation of the vortex ring.     

Investigation of thermal convection in water columns using particle image velocimetry

Particle image velocity measurements were applied on thermally driven convection at low Rayleigh numbers. In a model experiment using a water column heated from bottom and cooled from above, the velocity field was studied at different vertical temperature gradients. In the testing facility with high aspect ratio (about 19) representing a 1-m-long column with 5?cm diameter, occurrence of free convection was verified for destabilizing temperature gradients of 0.1–2?K/m. The PIV results revealed that significant flow exists already at low vertical temperature gradients. The velocity of the stable large-scale circulations increased linearly with temperature gradient (<1?K/m) from 8?×?10^?5 to 1?×?10^?3?m/s. At higher temperature gradients (1–2?K/m), a transition from quasi-stationary into time-dependent flow was observed, where convection cells changed position, number, and form temporarily. The motivation of this research was to gain more insight into density-driven convection in boreholes and groundwater monitoring wells.     

Stereoscopic micro particle image velocimetry

A stereoscopic micro-PIV (stereo-μPIV) system for the simultaneous measurement of all three components of the velocity vector in a measurement plane (2D–3C) in a closed microchannel has been developed and first test measurements were performed on the 3D laminar flow in a T-shaped micromixer. Stereomicroscopy is used to capture PIV images of the flow in a microchannel from two different angles. Stereoscopic viewing is achieved by the use of a large diameter stereo objective lens with two off-axis beam paths. Additional floating lenses in the beam paths in the microscope body allow a magnification up to 23×. The stereo-PIV images are captured simultaneously by two CCD cameras. Due to the very small confinement, a standard calibration procedure for the stereoscopic imaging by means of a calibration target is not feasible, and therefore stereo-μPIV measurements in closed microchannels require a calibration based on the self-calibration of the tracer particle images. In order to include the effects of different refractive indices (of the fluid in the microchannel, the entrance window and the surrounding air) a three-media-model is included in the triangulation procedure of the self-calibration. Test measurement in both an aligned and a tilted channel serve as an accuracy assessment of the proposed method. This shows that the stereo-μPIV results have an RMS error of less than 10% of the expected value of the in-plane velocity component. First measurements in the mixing region of a T-shaped micromixer at Re = 120 show that 3D flow in a microchannel with dimensions of 800 × 200 μm² can be measured with a spatial resolution of 44 × 44 × 15 μm³. The stationary flow in the 200 μm deep channel was scanned in multiple planes at 22 μm separation, providing a full 3D measurement of the averaged velocity distribution in the mixing region of the T-mixer. A limitation is that this approach requires a stereo-objective that typically has a low NA (0.14–0.28) and large depth-of-focus as opposed to high NA lenses (up to 0.95 without immersion) for standard μPIV.     

Experimental observation using particle image velocimetry of inertial waves in a rotating fluid

Inertial waves generated by a small oscillating disk in a rotating water filled cylinder are observed by means of a corotating particle image velocimetry system. The wave takes place in a stationary conical wavepacket, whose angle aperture depends on the oscillation frequency. Direct visualisation of the velocity and vorticity fields in a plane normal to the rotation axis are presented. The characteristic wavelength is found to be approximately equal to the disk diameter. The classical dispersion relation for plane waves is verified from the radial location of the wavepacket, and from the ellipticity of the projected velocity diagram. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.

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Hybrid stereoscopic particle image velocimetry

 The technical aspects of a photographic stereo camera for three-dimensional particle image velocimetry are described herein. The hybrid concept of the camera combines advantages of the angular displacement and the translation method. The camera uses two CCD sensors in order to adjust the lens distances and angles to meet the Scheimpflug criterion and two coupled rotating mirrors for image shifting. An application to a jet flow with an exit velocity of 33 m/s demonstrates the succesfull optimization of the recording process. Received: 27 September 1996/Accepted: 6 March 1997     

Second-order accurate particle image velocimetry

 An adaptive, second-order accurate particle image velocimetry (PIV) technique is presented. The technique uses two singly exposed images that are interrogated using a modified cross-correlation algorithm. Consequently, any of the equipment commonly available for conventional PIV (such as dual head Nd: YAG lasers, interline transfer CCD cameras, etc.) can be used with this more accurate algorithm. At the heart of the algorithm is a central difference approximation to the flow velocity (accurate to order Δt ²) versus the forward difference approximation (accurate to order Δt) common in PIV. An adaptive interrogation region-shifting algorithm is used to implement the central difference approximation. Adaptive shifting algorithms have been gaining popularity in recent years because they allow the spatial resolution of the PIV technique to be maximized. Adaptive shifting algorithms also have the virtue of helping to eliminate velocity bias errors. The second- order accuracy resulting from the central difference approximation can be obtained with relatively little additional computational effort compared to that required for a standard first-order accurate forward difference approximation. The adaptive central difference interrogation (CDI) algorithm has two main advantages over adaptive forward difference interrogation (FDI) algorithms: it is more accurate, especially at large time delays between camera exposures; and it provides a temporally symmetric view of the flow. By comparing measurements of flow around a single red blood cell made using both algorithms, the CDI technique is shown to perform better than conventional FDI-PIV interrogation algorithms near flow boundaries. Cylindrical Taylor–Couette flow images, both experimental and simulated, are used to demonstrate that the CDI algorithm is significantly more accurate than conventional PIV algorithms, especially as the time delay between exposures is increased. The results of the interrogations are shown to agree quite well with analytical predictions and confirm that the CDI algorithm is indeed second-order accurate while the conventional FDI algorithm is only first-order accurate. Received: 15 June 2000/Accepted: 2 February 2001     

Treatment of interfaces in particle image velocimetry

A first-order accurate method of extending the capability of image velocimetry to interfaces is presented. In this method, the image fields are locally extended across interfaces using fields from the other image of an image pair. During this image parity exchange, the extension of the image fields amounts to locally reversing and reflecting the relative velocity field across the interface. Numerous experimental examples are given to demonstrate and validate the accuracy of the method. These are the plane Couette flow and the laminar pipe flow demonstrating straight rigid boundaries; uniform flow past a sphere and a sphere moving in a stagnant fluid demonstrating curved rigid surfaces; and a free-surface flow and a liquid–liquid interface flow demonstrating compliant interfaces. Received: 3 November 1998/Accepted: 18 August 1999     

Twenty years of particle image velocimetry

The development of the method of particle image velocimetry (PIV) is traced by describing some of the milestones that have enabled new and/or better measurements to be made. The current status of PIV is summarized, and some goals for future advances are addressed.     

High-precision sub-pixel interpolation in particle image velocimetry image processing

The task of image interpolation and re-sampling for particle image velocimetry (PIV) is investigated, which is used for window shifting with sub-pixel accuracy and image or window deformation. A new interpolation scheme based on a Gaussian filter is introduced and compared with commonly used and widely accepted interpolation techniques in terms of the achievable root mean square deviation of the displacement estimates.     

Optimal subpixel interpolation in particle image velocimetry

It is shown that among the different techniques for particle image velocimetry subpixel interpolation, only the "sinc"-kernel creates an optimal result in that it completely suppresses spurious spectral sidelobes. An efficient method is introduced for the computation of the subpixel-accurate correlation peak position without any systematic errors. A connection is made with the kernel-dependent observation of the peak-locking phenomenon.     

Estimation of complex air–water interfaces from particle image velocimetry images

This paper describes a method for the estimation of the instantaneous air–water interface directly from particle image velocimetry (PIV) images of a laboratory generated air entraining turbulent hydraulic jump. Image processing methods such as texture segmentation based on gray level co-occurrence matrices are used to obtain a first approximation for the discrete location of the free surface. Active contours based on energy minimization principles are then implemented to get a more accurate estimate of the calculated interface and draw it closer to the real surface. Results are presented for two sets of images with varying degrees of image information and surface deformation. Comparisons with visually-interpreted surfaces show good agreement. In the absence of in-situ measurements, several verification tests based on physical reasoning show that the free surface is calculated to acceptable levels of accuracy. Aside from a single image used to tune the set of parameters, the algorithm is completely automated to process an ensemble of images representative of typical PIV applications. The method is computationally efficient and can be used to track fluid-interfaces undergoing non-rigid deformations.     

Statistical investigation of errors in particle image velocimetry

The accuracy of the particle image velocimetry technique was investigated using synthetic images having known characteristics. Algorithms were developed to extract two-dimensional velocity information by tracking particles between successive frames of a movie automatically without operator assistance. This allowed to parametrically investigate the influence of the various parameters (image contrast, image noise, particle density, distribution of sizes of particles and particle displacement between frames) on the accuracy of the technique. It was found that as long as the images have a good contrast, particle locations can be determined with sub-pixel accuracy and particle velocities can be determined within a few percent.     

Quantum nanospheres for sub-micron particle image velocimetry

Quantum Nanospheres™ (QNs) have been developed as a new type of flow-tracing particle for micron resolution particle image velocimetry (PIV). The 70 nm diameter QNs were created by conjugating quantum dots to polystyrene beads. The fluorescent QNs have a large Stokes’ shift and are impervious to photobleaching. The use of QNs as flow-tracing particles for micro-PIV was demonstrated by measuring fluid motion in a 30 × 300 μm channel. Using an interrogation region of 1 × 1,024 pixels and ensemble averaging 1,800 image pairs, the physical volume of the interrogation region was 117 μm × 117 μm × 2 μm.