PIV Technique for the Simultaneous Measurement of Dilute Two-Phase Flows

Kiger, Ken; Pan, Chunhui

doi:10.1115/1.1314864

Cited by 147 publications

(78 citation statements)

References 11 publications

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“…Therefore, a particle tracking velocimetry (PTV) algorithm is most suitable for these images (Raffel, Willert & Kompenhans 1998). For these images, the 'particle mask correlation' algorithm was found to be the most suitable (Kiger & Pan 2000;Poelma 2004). In this algorithm, particles are detected by cross-correlating the images with a 'mask' or model particle.…”

Section: Measurement Techniquesmentioning

confidence: 99%

Particle–fluid interactions in grid-generated turbulence

Poelma¹,

Westerweel²,

Ooms³

2007

J. Fluid Mech.

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The effect of small particles on decaying grid-generated turbulence is studied experimentally. Using a two-camera system, instantaneous fluid-phase and particlephase measurements can be obtained simultaneously. The data obtained with this system are used to study the decay behaviour of the turbulent flow. The role of particle size, particle density and volume load is studied in a number of different cases. These cases are chosen so that the individual role of these parameters can systematically be evaluated. Addition of particles to the flow has significant effects on the decaying turbulence: first, the onset of the turbulent decay appears to shift upstream; second, the flow becomes anisotropic as it develops downstream. The latter is observed as an increase in integral length scale in the vertical direction. The rate at which the flow becomes anisotropic can be predicted using a new parameter: the product of the non-dimensional number density and the Stokes number (referred to as the 'Stokes load'). This parameter, combining the relevant fluid and particle characteristics, is a measure for the energy redistribution leading to anisotropy. In addition to redistributing energy, the particles also produce turbulence. However, this only becomes evident when the grid-generated turbulence has decayed sufficiently, relatively far downstream of the grid. The turbulence production by particles can also account for the observed decrease in slope of the power spectrum, which leads to a 'cross-over' effect. The production of turbulence by the particles can be predicted using a model for the momentum deficit of the particle wakes. The validity of this approach is confirmed using conditional sampling of the fluid velocity field around the particles.

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Section: Measurement Techniquesmentioning

confidence: 99%

Particle–fluid interactions in grid-generated turbulence

Poelma¹,

Westerweel²,

Ooms³

2007

J. Fluid Mech.

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“…In pre-processing, the timeaveraged intensity was subtracted from each image to remove spatial variation in laser illumination. To mask the larvae, we first removed seeding particle images and enhanced the larval images by applying a median filter (Kiger and Pan, 2000). The images were then binarized to identify particles with area >100 pixels as larvae, and these larval images were subtracted from the original images to leave only the seeding particles.…”

Section: Image Processing and Analysismentioning

confidence: 99%

“…Kiger and Pan, 2000;Khalitov and Longmire, 2002;Cheng et al, 2010). Fluid velocities were estimated from pre-processed images of the seeding particles with larvae masked out.…”

Section: Image Processing and Analysismentioning

confidence: 99%

Hydrodynamic sensing and behavior by oyster larvae in turbulence and waves

Fuchs

Gerbi

Hunter

et al. 2015

Journal of Experimental Biology

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Hydrodynamic signals from turbulence and waves may provide marine invertebrate larvae with behavioral cues that affect the pathways and energetic costs of larval delivery to adult habitats. Oysters (Crassostrea virginica) live in sheltered estuaries with strong turbulence and small waves, but their larvae can be transported into coastal waters with large waves. These contrasting environments have different ranges of hydrodynamic signals, because turbulence generally produces higher spatial velocity gradients, whereas waves can produce higher temporal velocity gradients. To understand how physical processes affect oyster larval behavior, transport and energetics, we exposed larvae to different combinations of turbulence and waves in flow tanks with (1) wavy turbulence, (2) a seiche and (3) rectilinear accelerations. We quantified behavioral responses of individual larvae to local instantaneous flows using twophase, infrared particle-image velocimetry. Both high dissipation rates and high wave-generated accelerations induced most larvae to swim faster upward. High dissipation rates also induced some rapid, active dives, whereas high accelerations induced only weak active dives. In both turbulence and waves, faster swimming and active diving were achieved through an increase in propulsive force and power output that would carry a high energetic cost. Swimming costs could be offset if larvae reaching surface waters had a higher probability of being transported shoreward by Stokes drift, whereas diving costs could be offset by enhanced settlement or predator avoidance. These complex behaviors suggest that larvae integrate multiple hydrodynamic signals to manage dispersal tradeoffs, spending more energy to raise the probability of successful transport to suitable locations.

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“…Dual-phase PIV allows for simultaneous, quantitative measurements of the carrier-phase velocity field (in this case water), as well as the locations and trajectories of suspended sediment particles [65]. This approach provides for a quantification of sediment mobilization and suspension.…”

Section: Further Piv Measurementsmentioning

confidence: 99%

Effects of Model Scaling on Sediment Transport in Brownout

Glucksman-Glaser

2012

30th AIAA Applied Aerodynamics Conference

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The phenomenon of "brownout" is characterized by a large cloud of sediment or dust that is formed around a rotorcraft when it takes off or lands in arid or dusty environments. To further understand the physics of brownout, a laboratory-scale rotor hovering in water was tested over a ground plane covered with a mobile sediment bed. The sensitivity of the dual-phase flow environment to changes in the values of the similarity parameters that potentially govern the fluid dynamics of the rotor flow and the transport of sediment was explored. First, dye flow visualization was performed to study the general evolution of the rotor flow and its interaction with the ground plane. Then, dual-phase flow visualization was used to expose the details of the processes that mobilize and uplift loose particles from the sediment bed. It was shown using the flow visualization that the trailed vortices from the rotor blades were a primary contributor to the mobilization and suspension of sediment. Particle image velocimetry (PIV) was also used to obtain quantitative measurements of the flow velocities found in the rotor wake and near the ground plane. It is then discussed as to why the steady flow assumptions used in the usual definitions of the classical similarity parameters governing sediment transport are not as applicable to the dual-phase flows produced by a rotor operating over a mobile sediment bed. A Buckingham-Π analysis was performed to determine a set of new similarity parameters that potentially better reflect the dual-phase flow characteristics relevant to sediment mobilization and suspension by a rotor wake, including the characteristics of the tip vortices. Sixteen new similarity parameters were initially determined, five of which selected as having particular relevance. Specifically, these new similarity parameters were: 1. The mobile inertia ratio; 2. The stationary inertia ratio, 3. The terminal-swirl velocity ratio; 4. The threshold-swirl velocity ratio; 5. The terminal/threshold-swirl velocity ratio. The values of these similarity parameters were determined using the PIV measurements, and were all found to correlate to the quantity of sediment mobilized and uplifted by the rotor. The terminal/threshold-swirl velocity ratio is proposed as the potentially most important similarity parameter for further characterizing the brownout phenomenon.

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PIV Technique for the Simultaneous Measurement of Dilute Two-Phase Flows

Cited by 147 publications

References 11 publications

Particle–fluid interactions in grid-generated turbulence

Particle–fluid interactions in grid-generated turbulence

Hydrodynamic sensing and behavior by oyster larvae in turbulence and waves

Effects of Model Scaling on Sediment Transport in Brownout

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