Particle Tracking Velocimetry using the genetic algorithm

2009 ◽  
Vol 12 (3) ◽  
pp. 217-232 ◽  
Author(s):  
K. Ohmi ◽  
S. P. Panday
Keyword(s):  
Genetic Algorithm ◽  
Particle Tracking ◽  
Particle Tracking Velocimetry

scholarly journals Stereoscopic Correspondence of Particles for 3-Dimensional Particle Tracking Velocimetry by using Genetic Algorithm

2017 ◽  
Vol 12 (1) ◽  
pp. 10-26 ◽  
Author(s):  
Sanjeeb Prasad Panday
Keyword(s):  
Genetic Algorithm ◽  
Particle Tracking ◽  
Particle Tracking Velocimetry ◽  
Three Dimensional ◽  
Time Step ◽  
3 Dimensional ◽  
Proximity Analysis ◽  
Ga Algorithm ◽  
New Strategy ◽  
Better Than

The genetic algorithm (GA) based stereo particle-pairing algorithm has been developed and applied to the spatial particle-pairing problem of the stereoscopic three-dimensional (3-D) PTV system. In this 3 D  PTV system, particles viewed by two (or more than two) stereoscopic cameras with a parallax have to be correctly paired at every synchronized time step. This is important because the 3-D coordinates of individual particles cannot be computed without the knowledge of the correct stereo correspondence of the particles. In the present study, the GA algorithm is applied to the epipolar line proximity analysis for establishing correspondence of particles pairs between two co-instantaneous stereoscopic particles images, in order to compute the 3-D coordinates of every individual particle. The results are tested with various standard images and it’s found that the new strategy using GA works better than conventional particle pairing methods of 3-D particle tracking velocimetry for steoroscopic PTV. Journal of the Institute of Engineering, 2016, 12(1): 10-26

scholarly journals Quantifying the Response of Grass Carp Larvae to Acoustic Stimuli Using Particle-Tracking Velocimetry

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 603
Author(s):  
Hojung You ◽  
Rafael O. Tinoco
Keyword(s):  
Particle Tracking ◽  
Grass Carp ◽  
Particle Tracking Velocimetry ◽  
Quantitative Imaging ◽  
Functional Relation ◽  
Acoustic Signals ◽  
Ecological Impacts ◽  
Ctenopharyngodon Idella ◽  
Response Ratio ◽  
Larval Behavior

Acoustic deterrents are recognized as a promising method to prevent the spread of invasive grass carp, Ctenopharyngodon idella (Valenciennes, 1844) and the negative ecological impacts caused by them. As the efficacy of sound barriers depends on the hearing capabilities of carp, it is important to identify whether carps can recognize acoustic signals and alter their swimming behavior. Our study focuses on quantifying the response of grass carp larvae when exposed to out-of-water acoustic signals within the range of 100–1000 Hz, by capturing their movement using particle-tracking velocimetry (PTV), a quantitative imaging tool often used for hydrodynamic studies. The number of responsive larvae is counted to compute response ratio at each frequency, to quantify the influence of sound on larval behavior. While the highest response occurred at 700 Hz, we did not observe any clear functional relation between frequency of sound and response ratio. Overall, 20–30% of larvae were consistently reacting to sound stimuli regardless of the frequency. In this study, we emphasize that larval behaviors when exposed to acoustic signals vary by individual, and thus a sufficient number of larvae should be surveyed at the same time under identical conditions, to better quantify their sensitivity to sound rather than repeating the experiment with individual specimens. Since bulk quantification, such as mean or quantile velocities of multiple specimens, can misrepresent larval behavior, our study finds that including the response ratio can more effectively reflect the larval response.

3D real-time volumetric particle tracking velocimetry – A promising tool for studies of airflow around high-rise buildings

2020 ◽  
Vol 178 ◽  
pp. 106930
Author(s):  
Yu Zhao ◽  
Xiaojun Ma ◽  
Chengbin Zhang ◽  
Haoyu Wang ◽  
Yuanhui Zhang
Keyword(s):  
Real Time ◽  
Particle Tracking ◽  
Particle Tracking Velocimetry ◽  
High Rise ◽  
Promising Tool
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