• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1998.10a
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• pp.211-221
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• 1998

A digital image processing technique which is able to get the velocity vector distribution of a surface of the spilled oil in the ocean without contacting the flow itself. This technique is based upon the PIV(Particle Imaging Velocimetry) technique and its system mainly consists of a high sensitive camera, a CCD camera, an image grabber, and a host computer in which an image processing algorithm is adopted for velocity vector acquisition. For the acquisition of the advective velocity vector of floating matters on the ocean, a new multi-frame tracking algorithm is proposed, and for the acquisition of the diffusion velocity vector distribution of the spilt oil onto the water surface, a high sensitive gray-level cross-correlation algorithm is proposed.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.4
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• pp.34-43
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• 2001

Analysis and control of intake charge motion such as swirl and tumble are very important to improve the performance of gasoline engines. In this paper, single frame double exposure PTV(particle tracking velocimetry) is used to investigate intake flow characteristic in a steady flow test rig of gasoline engine with 2-valve and pent-roof combustion chamber. To validate this PTV method, we confirmed reliability of this PTV method using chopper, and coaxial burner experiments. The velocity Held of intake flow is measured with the intake valve lift variation. It is shown that maximum flow velocity is increased and tumble flow become stronger than inverse tumble flow as valve lift increase.

• Journal of Korean Port Research
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• v.12 no.2
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• pp.291-302
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• 1998

A digital image processing technique which is able to be used for getting the velocity vector distribution of a surface of the spilt oil in the ocean without contacting the flow itself. This technique is based upon the PIV(Particle Imaging Velocimetry) technique and its system mainly consists of a high sensitive camera, a CCD camera, an image grabber, and a host computer in which an image processing algorithm is adopted for velocity vector acquisition. For the acquisition of the advective velocity vector of floating matters on the ocean, a new multi-frame tracking algorithm is proposed, and for the acquisition of the diffusion velocity vector distribution of the spilt oil onto the water surface, a high sensitive gray-level cross-correlation algorithm is proposed.

• Journal of the Korean Society of Visualization
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• v.19 no.2
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• pp.32-40
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• 2021

Vapor-driven solutal Marangoni flow is governed by the concentration distribution of solutes on a liquid-gas interface. Typically, the flow structure is investigated by particle image velocimetry (PIV). However, to develop a theoretical model or to explain the working mechanism, the concentration distribution of solutes at the interface should be known. However, it is difficult to achieve the concentration profile theoretically and experimentally. In this paper, to find the concentration distribution of solutes around 2D droplet, the reverse tracking method with an artificial neural network based on PIV data was performed. Using the method, the concentration distribution of solutes around a 2D droplet was estimated for actual flow data from PIV experiment.

• 한국가시화정보학회:학술대회논문집
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• 2004.12a
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• pp.91-110
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• 2004

A comprehensive three-dimensional nano-particle tracking technique in micro- and nano-scale spatial resolution using the Total Internal Reflection Fluorescence Microscope (TIRFM) is discussed. Evanescent waves from the total internal reflection of a 488nm argon-ion laser are used to measure the hindered Brownian diffusion within few hundred nanometers of a glass-water interface. 200-nm fluorescence-coated polystyrene spheres are used as tracers to achieve three-dimensional tracking within the near-wall penetration depth. A novel ratiometric imaging technique coupled with a neural network model is used to tag and track the tracer particles. This technique allows for the determination of the relative depth wise locations of the particles. This analysis, to our knowledge is the first such three-dimensional ratiometric nano-particle tracking velocimetry technique to be applied for measuring Brownian diffusion close to the wall.

• Journal of Korea Water Resources Association
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• v.39 no.2 s.163
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• pp.99-108
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• 2006

To describe the behavior of suspended-sediment particles in turbulent open-channel flows, the advection-diffusion equation or its simplified form has been used. Though this equation was derived upon several assumptions, only a few studies tried to evaluate the limit of the assumptions. The reason is that it is very difficult to measure turbulence in open-channel flows and to discriminate the velocities of water and sediment particles. The present study aims to measure the velocity profiles of water and sediment particles in open-channel flows by using PTV (Particle Tracking Velocimetry), a kind of PIV (Particle Image Velocimetry). The measured results showed that sediment particles moved slower than water tracers did in the outer region. In the present study, the amount of velocity-lag reached about $5\%$ of the mom flow velocity and the position of the maximum velocity-lag was $g/h\approx0.05\;(g^{+}=30\~50)$ The main cause of the velocity-lag of sediment particles seems that the sediment particles have larger density than water has. On the other hand, in the viscous sublayer, sediment particle has a larger velocity than water tracers. The reason of the inversion of velocity-lag may be due to the no-sleep condition of water at the solid boundaries.

• The KSFM Journal of Fluid Machinery
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• v.5 no.1 s.14
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• pp.7-12
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• 2002

As the first step to investigate the fundamental mechanism of a dispersed two-phase flow, we studied the detailed interactions between bubble or particle motion and flow around it. Experiments were carried out with a rising bubble or particle in stagnant water in a vertical pipe. Particles with different densities, and/or different shapes were used for comparison with a bubble. We adopted 3D-PTV (Three-Dimensional Particle Tracking Velocimetry) for measuring the bubble or particle motions, and PIV (Particle Image Velocimetry) for measuring the water flow simultaneously (Hybrid PIV). The experimental results showed that the oblate spheroidal solid particle rose along the longer axis direction at the point that the inclination of the longer axis reached the maximum, and the inclination direction changed after moving. The bubble moved to the direction that the spheroid's projected width grew up to the largest, and the minor axis of the oblate spheroidal body of the bubble was parallel to the moving direction. The trajectory of the center of the particle/bubble which was measured with 3D-PTV, was marked on the section (x-y) of the pipe. It exhibited the pattern of the particle/bubble motion.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.6
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• pp.603-608
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• 2011

Since PTV (particle tracking velocimetry) provides velocity vectors by tracking each particle in a fluid flow, it has significant benefits when used for nano- and bio-fluid flows. However, PTV has only been used for limited flow fields because interpolation data loss is inevitable in PTV in principle. In this paper, a hybrid particle image velocimetry (PIV) algorithm that eliminates interpolation data loss was constructed by using an affine transformation. For the evaluation of the performance of the constructed hybrid PIV algorithm, an artificial image test was performed using Green-Taylor vortex data. The constructed algorithm was tested on experimental images of the wake flow (Re = 5,300) of a rectangular body ($6cm\;{\times}3cm$), and was demonstrated to provide excellent results.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.489-497
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• 1994

The most serious problems related to the cardiovascular prothesis are thrombosis and hemolysis. It is known that the flow pattern of cardiovascular prostheses is highly correlated with thrombosis and hemolysis. Laser Doppler Anemometry (LDA) is a usual method to get flow pattern, which is difficult to operate and has narrow measure region. Particle Image Velocimetry (PIV) can solve these problems. Because the flow speed of valve is too high to catch particles by CCD camera, high-speed camera (Hyspeed : Holland-Photonics) was used. The estimated maximum flow speed was 5m/sec and maximum trackable length is 0.5 cm, so the shutter speed was determined as 1000 frames per sec. Several image processing techniques (blurring, segmentation, morphology, etc) were used for the preprocessing. Particle tracking algorithm and 2-D interpolation technique which were necessary in making gridrized velocity pronto, were applied to this PIV program. By using Single-Pulse Multi-Frame particle tracking algorithm, some problems of PIV can be solved. To eliminate particles which penetrate the sheeted plane and to determine the direction of particle paths are these solving methods. 1-D relaxation fomula is modified to interpolate 2-D field. Parachute artificial heart valve which was developed by Seoul National University and Bjork-Shiely valve was testified. For each valve, different flow pattern, velocity profile, wall shear stress and mean velocity were obtained.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.4
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• pp.559-564
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• 1999

A particle image velocimetry is the representative technique for measuring flow velocities at whole field simultaneously. The present study adopted the PTV method for velocity acquisition in a square enclosure with initially isothermal fluid by using a general lamp-based sheet light source. The enclosure was composed of hot and cold vertical wall and was confined by two horizon-tal adiabatic walls. The drift velocities were measured and the drift was visualized by PTV for a rayleigh number of 5.28{\times}10^8.$ Obtained instant simulataneous velocity vectors show flow pattern and the result of horizontal velocity profile agree well with the numerical result.