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Laser Velocimetry
Published in Richard J. Goldstein, Fluid Mechanics Measurements, 2017
One method of measuring particle displacements in the PIV technique is particle tracking velocimetry (PTV), in which each particle image is analyzed to locate its center, and the centers of (possibly multiple pulse) image tracks are connected to determine the particle’s trajectory and velocity [125–127. PTV is usually applied to low-image-density fields in which the number of images is not so large as to make image-by-image analysis prohibitively time consuming, or to introduce ambiguities due to crossing trajectories. If the image density increases, simple tracking methods fail because they are unable to successfully associate images with the correct particles. Hence, PTV and low-image-density PIV are often used synonymously, whereas in fact, one is a measurement method and the other is a type of image. The distinction becomes crucial in certain advanced analysis techniques.
Velocity
Published in Jochen Aberle, Colin D. Rennie, David M. Admiraal, Marian Muste, Experimental Hydraulics: Methods, Instrumentation, Data Processing and Management, 2017
Jochen Aberle, Colin D. Rennie, David M. Admiraal, Marian Muste
Particle Tracking Velocimetry (PTV) and Particle Image Velocimetry (PIV) are closely related, both belonging to the more general classification of particle-imaging techniques. Both methods analyze pairs or sequences of images of a tracer particle field, using the tracer particles as surrogates to measure fluid displacements in the flow field. Knowing the time between images, the image-to-image displacements are then used to determine the velocity field. The key difference between PTV and PIV is that in PTV, velocities are determined from discretely tracked particles, whereas in PIV, velocities are determined from the motions of groups of particles. This difference between PTV and PIV has implications for seeding concentrations, spatial resolution, and field averaging of results.
Laser velocimetry
Published in Stefano Discetti, Andrea Ianiro, Experimental Aerodynamics, 2017
Although recently it is more common in the fluid dynamics community to track the motion of groups of particles statistically using PIV, methods that evaluate the velocity field by studying the motion of individual particles have a long history, dating perhaps as far back as Leonardo da Vinci [42]. Today, quantitative versions of these techniques are usually referred to as particle tracking velocimetry, or PTV. Practically, these methods can typically be applied interchangeably with PIV on the same set of images, and the principles of designing and setting up an experiment are essentially identical, though often with a lower seeding density to aid in matching and preventing overlap of particle images.
Design and characterization of a dust dispenser for tungsten dust injection experiments in the STOR-M tokamak
Published in Radiation Effects and Defects in Solids, 2022
N. Nelson, L. Couëdel, C. Xiao
In order to reconstruct the trajectory of a particle, its position and velocity have to be determined at the time when it appears in the view of the camera and a force model has to be implemented. The time evolution of the spatial distribution of a large number of dispensed particles can then be reconstructed [26,27]. A particle tracking velocimetry (PTV) algorithm [26–28] is used to identify particles in each of the consecutive frames and to obtain positions and velocities of particles at the time of measurement. For successful identification and tracking of individual particles, raw image data must be processed in order to reduce noise. This is done by applying a smoothing Gaussian filter and then subsequently selecting an appropriate threshold to produce a binary image [26,27]. Figure 6(a,b) shows a raw image as captured by the camera and the corresponding processed binary image, respectively. The circles in Figure 6(b) mark the particles identified. Tracking performance of particles between successive video frames is significantly enhanced when using such processed binary images [26,27].
An experimental study on the motion of buoyant particles in the free-surface vortex flow
Published in Journal of Hydraulic Research, 2021
Alex Duinmeijer, Francois Clemens
The experimental setup consists of an acrylic tank with an inside diameter of 0.610 m and a height of 1 m. The experimental particles are released on the water surface at variable or fixed position. The 3D motion is determined by a 3D particle tracking velocimetry (PTV) set-up. For a more detailed description of the set-up, the reader is referred to Duinmeijer, Moreno-Rodenas, et al. (2019). In several experiments, the particle only showed a 2D motion at the free-surface. For these combinations of characteristics, additional 2D-PTV experiments were done. The 2D-PTV set-up consists of an IO Industries Flare 2M280CCX high speed camera placed above the water surface. The experimental particles are produced using 3D-printing technology and come in three shapes: sphere, ovoid and cube (Table 1). The particles were designed with different density ρpto quantify the effect of this parameter on the particle’s dynamics. The uncertainty in ρp is determined to be in a range of 1–5 kg m−3.
Particle image velocimetry validation for quantifying bedload movement
Published in Journal of Applied Water Engineering and Research, 2019
Muhammed T. Mustafa, Amanda L. Cox, Kyle Mitchell
For the low-density case, particles can be dealt with individually. Different images from different sources corresponding to the same particle can be identified and tracked for evaluation, this method is called Particle Tracking Velocimetry (PTV). For high-density cases, detection of individual particles within images is very difficult as the concentration of scattered particles is so large that the particle images (i.e. the projection of a particle onto an image plane) overlap in the image plane and form speckle patterns. Correlation for high-density cases is evaluated based on particle speckles, and this process is called Laser Speckle Velocimetry (LSV). For medium-density cases, when concentrations lie between those of PTV and LSV, images for individual particles can also be identified, but visual identification of the image pair is no longer possible. Therefore, for medium-density cases, the standard method of PIV is used for the evaluation process, which is based on the correlation between particle groups in different images, known as correlation-based PIV (Prasad 2000).