Study of vortex breakdown by particle tracking velocimetry (PTV)

The spiral-type breakdown of a slender vortex was quantitatively investigated with PTV. Multiexposed pictures of the illuminated meridional midplane were processed to obtain the instantaneous 2-D velocity field and vorticity distribution. The periodic change of flow patterns with respect to time is clearly shown in a time-series of pictures. The 2-D velocity fields contained a stagnation point in the midplane located outside of the centerline. Additionally it was observed, that this point rotates around the centerline in the same way as the outer flow. A comparison with measurements of a bubble-type breakdown indicates a strong similarity to the spiral-type breakdown. The results reveal that the slope, winding and diameter of the spiral vortex-core determine the different observable forms. The first part of the deflected vortex-core near the breakdown point causes an asymmetric backflow due to induction, the strength of which depends on the slope of the deflected vortexcore. This is responsible for the radial distance between stagnation point and centerline. In case of the observed bubble-type breakdown the spiral is compressed which results in a stable stagnation point at the centerline.     

Study of vortex breakdown by particle tracking velocimetry (PTV) Part 3: Time-dependent structure and development of breakdown-modes

This third part of the study deals with the time-dependent nature of vortex breakdown. The results show the unsteady velocity and vorticity field of the initiation and development of breakdown and transition between both predominant breakdown modes, the bubble and the spiral. During the development to breakdown, the generated amount of circumferential vorticity follows the theoretical prediction by Brown and Lopez (1990). This confirms the idea of positive feedback as the key-mechanism leading to vortex breakdown. We regard the bubble-type as the fundamental breakdown type, that is stationary and nearly axisymmetric. The circumferential vorticity is distributed in a form of an elliptical vortex-ring-like structure. Starting from this stage, an increase of volume flux to a higher Reynolds number leads to the transition to the spiral-type with an initial stretching of the vortex ring-like structure and a subsequent change to an asymmetric circumferential vorticity distribution. This in combination with the inductive effect causes the front stagnation point to be deflected radially away and later to rotate around the centerline. Consequently the approaching vortex core is radially deflected in opposite direction and evolves in a spiral path. The idea of a second positive feedback-mechanism gives a possible explanation for the transition. Following this theory the asymmetry of circumferential vorticity will trigger itself at a certain degree by the interaction with the inductively affected stagnation point and its influence on the approaching vortex core. This self-enhancing process will finally lead to the spiral-type breakdown in which the radial distance between rotating stagnation point and deflected vortex core is of the order of the characteristic vortex core radius. The reversed transition from the spiral to a stable bubble-type can be regenerated by decreasing the Reynolds number down to the value that corresponds to the stable bubble state. The flow structure evolves nearly in the time-reversed way as during transition from bubble towards the spiral.     

2-Dimensional particle tracking velocimetry (PTV): Technique and image processing algorithms

An automated particle track velocimeter (PTV) was constructed to determine the fluid velocity field in a transparent test section (an engine throttle body assembly is used as an example) by analyzing images of scattered light from hollow nylon particles as they move with the flow. The light from individual particles was imaged on an SIT vidicon at video rates, digitized on an FG100CD frame buffer board and analyzed automatically in an IBMPC/AT. The essence of this technique is a novel processing algorithm which converts particle track segments to flow velocity vectors at the rate of 2–3 images/minute with this hardware. An application of the technique to a gas phase flow ( 6.5 m/s) through this throttle body assembly is presented.     

A vision-based hybrid particle tracking velocimetry (PTV) technique using a modified cascade correlation peak-finding method

A novel technique for particle tracking velocimetry is presented in this paper to overcome the issue of overlapping particle images encountered in the flows with high particle density or under volumetric illumination conditions. To achieve this goal, algorithms for particle identification and tracking are developed based on current methods and validated with both synthetic and experimental image sets. The results from synthetic image tests show that the particle identification algorithm is able to resolve overlapped particle images up to 50?% under noisy conditions, while keeping the root mean square peak location error under 0.07?pixels. The algorithm is also robust to the size changes up to a size ratio of 5. The tracking method developed from a classic computer vision matching algorithm is capable of capturing a velocity gradient up to 0.3 while maintaining the error under 0.2?pixels. Sensitivity tests were performed to describe the optimum conditions for the technique in terms of particle image density, particle image sizes and velocity gradients, also its sensitivity to errors of the PIV results that guide the tracking process. The comparison with other existing tracking techniques demonstrates that this technique is able to resolve more vectors out of a dense particle image field.     

Near-ground tornado-like vortex structure resolved by particle image velocimetry (PIV)

The near-ground flow structure of tornadoes is of utmost interest because it determines how and to what extent civil structures could get damaged in tornado events. We simulated tornado-like vortex flow at the swirl ratios of S = 0.03–0.3 (vane angle θ_v = 15°–60°), using a laboratory tornado simulator and investigated the near-ground-vortex structure by particle imaging velocimetry. Complicated near-ground flow was measured in two orthogonal views: horizontal planes at various elevations (z = 11, 26 and 53 mm above the ground) and the meridian plane. We observed two distinct vortex structures: a single-celled vortex at the lowest swirl ratio (S = 0.03, θ_v = 15°) and multiple suction vortices rotating around the primary vortex (two-celled vortex) at higher swirl ratios (S = 0.1–0.3, θ_v = 30°–60°). We quantified the effects of vortex wandering on the mean flow and found that vortex wandering was important and should be taken into account in the low swirl ratio case. The tangential velocity, as the dominant velocity component, has the peak value about three times that of the maximum radial velocity regardless of the swirl ratio. The maximum velocity variance is about twice at the high swirl ratio (θ_v = 45°) that at the low swirl ratio (θ_v = 15°), which is contributed significantly by the multiple small-scale secondary vortices. Here, the results show that not only the intensified mean flow but greatly enhanced turbulence occurs near the surface in the tornado-like vortex flow. The intensified mean flow and enhanced turbulence at the ground level, correlated with the ground-vortex interaction, may cause dramatic damage of the civil structures in tornadoes. This work provides detailed characterization of the tornado-like vortex structure, which has not been fully revealed in previous field studies and laboratory simulations. It would be helpful in improving the understanding of the interaction between the tornado-like vortex structure and the ground surface, ultimately leading to better predictions of tornado-induced wind loads on civil structures.     

3D scanning particle tracking velocimetry

In this article, we present an experimental setup and data processing schemes for 3D scanning particle tracking velocimetry (SPTV), which expands on the classical 3D particle tracking velocimetry (PTV) through changes in the illumination, image acquisition and analysis. 3D PTV is a flexible flow measurement technique based on the processing of stereoscopic images of flow tracer particles. The technique allows obtaining Lagrangian flow information directly from measured 3D trajectories of individual particles. While for a classical PTV the entire region of interest is simultaneously illuminated and recorded, in SPTV the flow field is recorded by sequential tomographic high-speed imaging of the region of interest. The advantage of the presented method is a considerable increase in maximum feasible seeding density. Results are shown for an experiment in homogenous turbulence and compared with PTV. SPTV yielded an average 3,500 tracked particles per time step, which implies a significant enhancement of the spatial resolution for Lagrangian flow measurements.     

Study of the intake tumble motion by flow visualization and particle tracking velocimetry

The purpose of this work is to characterize the in-cylinder tumbling flow generated by an engine head during the induction process using flow visualization and particle tracking velocimetry (PTV). The study was carried out for a 4-valve engine head with shrouded intake valves in a special single cylinder transient water analog. This shrouded intake valve configuration was used to obtain a prototypical pure tumble flow suitable for fundamental combustion studies. The results revealed that the shrouded intake valves generate a strong, well-behaved tumble vortex on the axial plane between the cylinder head and the piston face. This vortex dominates the entire flow field and seems to be highly repeatable from cycle to cycle. The effect of engine speed on this tumbling flow was studied. An equivalent tumble ratio was defined and evaluated using the measured velocity fields at BDC (bottom dead center).List of symbols ABDC after bottom dead Center - ATDC after top dead center - BBDC before bottom dead center - BDC bottom dead center - BTDC before top dead center - dm mass of the volume element - M total angular momentum - PTV particle tracking velocimetry - r radial distance from the reference point - t total pulse duration - TDC top dead center - U instantaneous velocity - v velocity of the center point of the element - X streak length     

Real-time image processing for particle tracking velocimetry

We present a novel high-speed particle tracking velocimetry (PTV) experimental system. Its novelty is due to the FPGA-based, real-time image processing “on camera”. Instead of an image, the camera transfers to the computer using a network card, only the relevant information of the identified flow tracers. Therefore, the system is ideal for the remote particle tracking systems in research and industrial applications, while the camera can be controlled and data can be transferred over any high-bandwidth network. We present the hardware and the open source software aspects of the PTV experiments. The tracking results of the new experimental system has been compared to the flow visualization and particle image velocimetry measurements. The canonical flow in the central cross section of a a cubic cavity (1:1:1 aspect ratio) in our lid-driven cavity apparatus is used for validation purposes. The downstream secondary eddy (DSE) is the sensitive portion of this flow and its size was measured with increasing Reynolds number (via increasing belt velocity). The size of DSE estimated from the flow visualization, PIV and compressed PTV is shown to agree within the experimental uncertainty of the methods applied.     

Tomographic particle tracking velocimetry using telecentric imaging

The goal of this article is to discuss 3D Particle Tracking Velocimetry (PTV) in a tomographic reconstructed voxel space with at least doubling the spatial resolution compared to classical 3D PTV. For this purpose, a new tomographic reconstruction technique based on telecentric imaging in combination with the epipolar geometry is presented. The method overcomes the need for memory intensive weighting matrices or cost intensive iterations, which are necessary in iterative algebraic reconstruction techniques. A characteristic of tomographic reconstruction is the reconstruction of ghost particles. As the aim of PTV is the reconstruction of true particle paths, this article focuses on the removal of ghost particles and ghost trajectories. The method is validated via a synthetic turbulent flow field and via the benchmark experiment of a vortex ring.     

New tracking algorithm for particle image velocimetry

The cross correlation tracking technique is widely used to analyze image data, in Particle Image Velocimetry (PIV). The technique assumes that the fluid motion, within small regions of the flow field, is parallel over short time intervals. However, actual flow fields may have some distorted motion, such as rotation, shear and expansion. Therefore, if the distortion of the flow field is not negligible, the fluid motion can not be tracked well using the cross correlation technique. In this study, a new algorithm for particle tracking, called the Spring Model technique, has been proposed. The algorithm can be applied to flow fields which exhibit characteristics such as rotation, shear and expansion.The algorithm is based on pattern matching of particle clusters between the first and second image. A particle cluster is composed of particles which are assumed to be connected by invisible elastic springs. Depending on the deformation of the cluster pattern (i.e., the particle positions), the invisible springs have some forces. The smallest force pattern in the second image is the most probable pattern match to the correspondent original pattern in the first image. Therefore, by finding the best matches, particle movements can be tracked between the two images. Three-dimensional flow fields can also be reconstructed with this technique.The effectiveness of the Spring Model technique was verified with synthetic data from both a two-dimensional flow and three-dimensional flow. It showed a high degree of accuracy, even for the three-dimensional calculation. The experimental data from a vortex flow field in a cylinder wake was also measured by the Spring model technique.     

A hybrid digital particle tracking velocimetry technique

A novel approach to digital particle tracking velocimetry (DPTV) based on cross-correlation digital particle image velocimetry (DPIV) is presented that eliminates the need to interpolate the randomly located velocity vectors (typical of tracking techniques) and results in significantly improved resolution and accuracy. In particular, this approach allows for the direct measurement of mean squared fluctuating gradients, and thus several important components of the turbulent dissipation. The effect of various parameters (seeding density, particle diameter, dynamic range, out-of-plane motion, and gradient strength) on accuracy for both DPTV and DPIV are investigated using a Monte Carlo simulation and optimal values are reported. Validation results are presented from the comparison of measurements by the DPTV technique in a turbulent flat plate boundary layer to laser Doppler anemometer (LDA) measurements in the same flow as well as direct numerical simulation (DNS) data. The DPIV analysis of the images used for the DPTV validation is included for comparison. Received: 29 August 1994/Accepted: 31 May 1996     

Algorithms for fully automated three-dimensional particle tracking velocimetry

A three-dimensional Particle Tracking Velocimetry (3-D PTV) technique has been developed to provide time-resolved, three-dimensional velocity field measurements throughout a finite volume. This technique offers many advantages for fundamental research in turbulence and applied research in areas such as mixing and combustion. The data acquired in 3-D PTV is a time sequence of stereo images of flow tracer particles suspended in the fluid. In this paper, the implementation of the technique is discussed in detail, as well as the results of an extensive statistical investigation of the performance of the algorithms. The technique has been optimized to allow fully automatic processing of long sequences of image pairs in a computationally efficient manner, hereby providing a viable, practical tool for the study of complex flows.List of symbols x, y, z Particle position - u, v, w Particle velocity This work was supported by a grant from Ford Motor Company, Powertrain Research Department. Their support is gratefully acknowledged.     

Two-dimensional Gaussian regression for sub-pixel displacement estimation in particle image velocimetry or particle position estimation in particle tracking velocimetry

An explicit solution of two-dimensional Gaussian regression for the estimation of particle displacement from the correlation function in particle image velocimetry (PIV) or particle position from the images in particle tracking velocimetry (PTV) with sub-pixel accuracy is introduced. The accuracy and the ability of the methods to avoid pixel locking due to non-axially orientated, elliptically shaped particle images or correlation peaks are investigated using simulated and experimentally obtained images.     

Improving the dynamic range of particle tracking velocimetry systems

In applying a video-based particle image velocimetry (PTV) system in a complex fluid flow, it is common to find both regions of fast and slow moving flow intermixing-particularly in highly turbulent or reversing flows. When one attempts to track the movement of particles in such a flow with a wide velocity range (and hence, separation distance between particle images), resolution problems are encountered. Inability to cover a wide range of velocities is actually a limitation of PTV. A method is introduced here that extends the dynamic range of PTV when implemented on a video-based system. It combines the use of multiple frames and multiple exposures on a single frame. The method is subsequently verified by tracking dots painted on a spinning flat disc.     

Stereo particle image velocimetry applied to a vortex pipe flow

Stereo particle image velocimetry (PIV) has been employed to study a vortex generated via tangential injection of water in a 2.25 inch (57 mm) diameter pipe for Reynolds numbers ranging from 1,118 to 63,367. Methods of decreasing pipe-induced optical distortion and the PIV calibration technique are addressed. The mean velocity field analyses have shown spatial similarity and revealed four distinct flow regions starting from the central axis of rotation to the pipe wall in the vortex flows. Turbulence statistical data and vortex core location data suggest that velocity fluctuations are due to the axis of the in-line vortex distorting in the shape of a spiral.     

Integrating cross-correlation and relaxation algorithms for particle tracking velocimetry

An integrated cross-correlation/relaxation algorithm for particle tracking velocimetry is presented. The aim of this integration is to provide a flexible methodology able to analyze images with different seeding and flow conditions. The method is based on the improvement of the individual performance of both matching methods by combining their characteristics in a two-stage process. Analogous to the hybrid particle image velocimetry method, the combined algorithm starts with a solution obtained by the cross-correlation algorithm, which is further refined by the application of the relaxation algorithm in the zones where the cross-correlation method shows low reliability. The performance of the three algorithms, cross-correlation, relaxation method and the integrated cross-correlation/relaxation algorithm, is compared and analyzed using synthetic and large-scale experimental images. The results show that in case of high velocity gradients and heterogeneous seeding, the integrated algorithm improves the overall performance of the individual algorithms on which it is based, in terms of number of valid recovered vectors, with a lower sensitivity to the individual control parameters.     

Estimation of particle dynamics in 2-D fluidized beds using particle tracking velocimetry

The experimental characterization of particle dynamics in fluidized beds is of great importance in fostering an understanding of solid phase motion and its effect on particle properties in granulation processes.Commonly used techniques such as particle image velocimetry rely on the cross-correlation of illumination intensity and averaging procedures.It is not possible to obtain single particle velocities with such techniques.Moreover,the estimated velocities may not accurately represent the local particle velocities in regions with high velocity gradients.Consequently,there is a need for devices and methods that are capable of acquiring individual particle velocities.This paper describes how particle tracking velocimetry can be adapted to dense particulate flows.The approach presented in this paper couples high-speed imaging with an innovative segmentation algorithm for particle detection,and employs the Voronoi method to solve the assignment problem usually encountered in densely seeded flows.Lagrangian particle tracks are obtained as primary information,and these serve as the basis for calculating sophisticated quantities such as the solid-phase flow field,granular temperature,and solid volume fraction.We show that the consistency of individual trajectories is sufficient to recognize collision events.     

Time-resolved volumetric particle tracking velocimetry of large-scale vortex structures from the reattachment region of a laminar separation bubble to the wake

The present paper presents time-resolved volumetric Particle Tracking Velocimetry measurements in a water towing tank on a SD7003 airfoil, performed at a Reynolds number of 60,000 and a 4° angle of attack. The SD7003 airfoil was chosen because of its long mid-chord and stable laminar separation bubble (LSB), occurring on the suction side of the airfoil at low Reynolds numbers. The present study focuses on the temporal resolution of unsteady large-scale vortex structures emitted from the LSB. In contrast to other studies, where only the observation of the flow in the transition region was examined, the entire flow from the leading edge to the far wake of the airfoil was investigated here.     

Study of the phenomena affecting the accuracy of a video- based particle tracking velocimetry technique

 The development of a video-based Particle Tracking Velocimetry (PTV) technique has focused on the problem of the accuracy of this method. The PTV-method can be decomposed into three parts: the recording of the experiment, the image processing and the evaluation of the velocities. The accuracy of each stage has been studied. Inaccuracies due to resolution, length scale, light intensity and distortion of the x and y direction are analysed. One of the main factors influencing the accuracy is the selection of the time difference between frames. During the evaluation of velocities, incorrect identifications of particles may occur. The relation between the time-step of the frames and the percentage of incorrect identifications has been shown. The percentage of false identifications increases with the size of the time-step. The resolution accuracy is however improved when the time-step is increased. An adequate selection of the time-step has to be made to obtain a high resolution accuracy and a limited number of incorrect identifications. Received: 22 April 1996 / Accepted: 17 November 1996