scholarly journals Time-resolved particle image velocimetry measurements of a tandem jet array in a cross flow at low velocity ratios

2020 ◽  
Author(s):  
Paul Kristo ◽  
Mark L. Kimber
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Velocity Ratio ◽  
Cross Flow ◽  
Velocity Fields ◽  
Instantaneous Velocity ◽  
Low Velocity ◽  
Time Resolved ◽  
Turbulent Statistics ◽  
Image Velocimetry

Investigation of the near field dynamics of a single and tandem array of three jets are provided by 2-D time-resolved particle image velocimetry (TR-PIV) measurements. Instantaneous velocity fields are examined in the transverse and spanwise planes with jet to cross flow velocity ratios in the range from 0.9 to 1.7. Previous studies have shown that for high ratios (≥2), the leading jet provides sufficient shielding to ensure that all jets downstream exhibit nearly identical flow characteristics. The current transverse plane measurements exhibit more unique and localized features as a result of the competing effects of pressure gradients and vortex mechanisms assessed via the jet exit profiles, first and second order turbulent statistics, streamline trajectories, recirculation areas, and penetrations depths. Proper orthogonal decomposition (POD) is applied to the spanwise plane instantaneous velocity fields to determine the statistically dominant features of the single and tandem jet configurations at equivalent velocity ratios. The velocity fields are then reconstructed using the truncated POD modes to provide further insight into the shear layer and wake vortices that drive these configurations. Vortex identification algorithms are applied to the reconstructed velocity fields to determine the statistical characteristics of the vortices, including their centroids, populations, areas, and strengths, each of which exhibit largely different dependencies on jet configuration and velocity ratio. Several of the investigated metrics are found to exhibit different behaviors below and above a velocity ratio of unity, and also as a function of increasing velocity ratio between 1 and 2, implying that several transitions mechanisms are present in the low velocity ratio regime investigated herein.

Research Methodology of Cross-Flow Cylinder Pipe Hydrodynamical

2013 ◽  
Vol 8 (4) ◽  
pp. 110-117
Author(s):  
Konstantin Dobroselsky
Keyword(s):  
Particle Image Velocimetry ◽  
Flow Visualization ◽  
Turbulent Flows ◽  
Research Methodology ◽  
Particle Image ◽  
Cross Flow ◽  
Velocity Fields ◽  
Experimental Setup ◽  
Flow Around A Cylinder ◽  
Image Velocimetry

Experimental setup (hydrodynamic pipe) for the study of turbulent flows has been upgraded. Test experiments with a cross-flow around a cylinder have been carried out. Using the method of flow visualization PIV (Particle Image Velocimetry) the velocity fields around the cylinder for precavitational and cavitation regimes (Re = 2,8 · 105 ) have been obtained

scholarly journals Experimental Validation of Falling Liquid Film Models: Velocity Assumption and Velocity Field Comparison

Polymers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1205
Author(s):  
Ruiqi Wang ◽  
Riqiang Duan ◽  
Haijun Jia
Keyword(s):  
Experimental Data ◽  
Particle Image Velocimetry ◽  
Velocity Field ◽  
Experimental Validation ◽  
Particle Image ◽  
Velocity Fields ◽  
Number Range ◽  
Comparison Results ◽  
Image Velocimetry ◽  
Experimental Particle

This publication focuses on the experimental validation of film models by comparing constructed and experimental velocity fields based on model and elementary experimental data. The film experiment covers Kapitza numbers Ka = 278.8 and Ka = 4538.6, a Reynolds number range of 1.6–52, and disturbance frequencies of 0, 2, 5, and 7 Hz. Compared to previous publications, the applied methodology has boundary identification procedures that are more refined and provide additional adaptive particle image velocimetry (PIV) method access to synthetic particle images. The experimental method was validated with a comparison with experimental particle image velocimetry and planar laser induced fluorescence (PIV/PLIF) results, Nusselt’s theoretical prediction, and experimental particle tracking velocimetry (PTV) results of flat steady cases, and a good continuity equation reproduction of transient cases proves the method’s fidelity. The velocity fields are reconstructed based on different film flow model velocity profile assumptions such as experimental film thickness, flow rates, and their derivatives, providing a validation method of film model by comparison between reconstructed velocity experimental data and experimental velocity data. The comparison results show that the first-order weighted residual model (WRM) and regularized model (RM) are very similar, although they may fail to predict the velocity field in rapidly changing zones such as the front of the main hump and the first capillary wave troughs.

scholarly journals Time-resolved particle image velocimetry measurements of the turbulent Richtmyer–Meshkov instability

2021 ◽  
Vol 917 ◽  
Author(s):  
Everest G. Sewell ◽  
Kevin J. Ferguson ◽  
Vitaliy V. Krivets ◽  
Jeffrey W. Jacobs
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Time Resolved ◽  
Image Velocimetry

Abstract

Analysis of local velocity gradients in rapid mixer using particle image velocimetry technique

2002 ◽  
Vol 2 (5-6) ◽  
pp. 47-55
Author(s):  
N.-S. Park ◽  
H. Park
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Velocity Fields ◽  
Local Velocity ◽  
Mixing Condition ◽  
Particle Image Velocimetry Technique ◽  
Velocity Gradients ◽  
Image Velocimetry ◽  
Current Design ◽  
G Value

Recognizing the significance of factual velocity fields in a rapid mixer, this study focuses on analyzing local velocity gradients in various mixer geometries with particle image velocimetry (PIV) and comparing the results of the analysis with the conventional G-value, for reviewing the roles of G-value in the current design and operation practices. The results of this study clearly show that many arguments and doubts are possible about the scientific correctness of G-value, and its current use. This is because the G-value attempts to represent the turbulent and complicated factual velocity field in a jar. Also, the results suggest that it is still a good index for representing some aspects of mixing condition, at least, mixing intensity. However, it cannot represent the distribution of velocity gradients in a jar, which is an important factor for mixing. This study as a result suggests developing another index for representing the distribution to be used with the G-value.

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