• Journal of Korea Multimedia Society
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• v.18 no.1
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• pp.65-70
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• 2015

Particle accelerator has mainly used in nuclear field only because of the large scale of the facility. However, since laser-plasma particle accelerator which has smaller size and spends less cost developed, the availability of this accelerator is expended to various research fields such as industrial and medical. This paper suggests a visualization system to control the laser-plasma particle accelerator efficiently. This system offers real-time 3D images via convert HDF file comes from plasma data obtained from PIC simulation into OpenGL texture type to analyse and modify plasma data. After that, it stores high-resolution rendering images of the data with external renderer hereafter.

• Journal of the Korean Society of Visualization
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• v.21 no.1
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• pp.119-126
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• 2023

Acquiring experimental data for PIV verification or machine learning training data is resource-demanding, leading to an increasing interest in synthetic particle images as simulation data. Conventional synthetic particle image generation algorithms do not follow physical laws, and the use of CFD is time-consuming and requires computing resources. In this study, we propose a new method for synthetic particle image generation, based on a Physics-Informed Neural Networks(PINN). The PINN is utilized to infer the flow fields, enabling the generation of synthetic particle images that follow physical laws with reduced computation time and have no constraints on spatial resolution compared to CFD. The proposed method is expected to contribute to the verification of PIV algorithms.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.45-50
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• 2005

Characteristics of flows at T-junction duct with and without orifices are investigated in this paper. Experiments and PIV visualization were carried out for several flow rates. Two-dimensional PIV experimental apparatus was decided by numerical analysis. PIV visualization was also coded to visualize flow fields at junctions for two-dimensional case. For the PIV visualization system, Grey-Level Cross-Correlation particle tracking algorithm was used to calculate the flow fields. Vinyl chloride polymer particles of $100{\sim}150{\mu}m$ of diameter are used in this visualization. The PIV visualization results showed relatively good agreement with Experimental data.

• Journal of Ocean Engineering and Technology
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• v.18 no.3
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• pp.1-7
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• 2004

Flaw visualization and velocity field measurement methods have practical applications in the various fluid engineering fields, such as mechanics, ships, and heat fluids. In this study, the basic principles and theoretical methods are used to establish an application technique of Particle Imae Velocimetry(abbreviated to PIV below). Accordingly, the measured results of velocity field distribution of a section inside the Circulating Water Channel (abbreviated to CWC below) are computed using the PIV is presented. The uniformity of velocity distribution of the section in CWC is confirmed, by comparing this PIV data with the existing current meter data. Also, in order to measure the flaw fields of surroundings of 2-dimensional cylinder in the CWC, the flaw visualization technique using the PIV is applied.

• Journal of the Korean Society of Visualization
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• v.16 no.2
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• pp.23-30
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• 2018

The present study compares flow fields reconstructed by data assimilation method with different combinations of parameters. As a data assimilation method, Vortex-in-Cell-sharp (VIC#), which supplements additional constraints and multigrid approximation to Vortex-in-Cell-plus (VIC+), is used to reconstruct flow fields from scattered particle tracks. Two parameters, standard deviation of Gaussian radial basis function (RBF) and grid spacing, are mainly tested using artificial data sets which contain few particle tracks. Consequent flow fields are analyzed in terms of flow structure sizes. It is demonstrated that sizes of the flow structures are proportional to an actual scale of the standard deviation of RBF. It implies that a combination of larger grid spacing and smaller standard deviation which preserves the actual standard deviation is able to save computational resources in case of a low track density. In addition, a simple comparison using an experimental data filled with dense particle tracks is conducted.

• 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.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.53-59
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• 2020

Initial response is important in marine oil spills, such as the Hebei Spirit oil spill, but it is very difficult to predict the movement of oil out of the ocean, where there are many variables. In order to solve this problem, the forecasting of oil spill has been carried out by expanding the particle prediction, which is an existing study that studies the movement of floats on the sea using the data of the float. In the ocean data format HDF5, the current and wind velocity data at a specific location were extracted using bilinear interpolation, and then the movement of numerous points was predicted by particles and the results were visualized using polygons and heat maps. In addition, we propose a spill oil particle matching algorithm to compensate for the lack of data and the difference between the spilled oil and movement. The spilled oil particle matching algorithm is an algorithm that tracks the movement of particles by granulating the appearance of surface oil spilled oil. The problem was segmented using principal component analysis and matched using genetic algorithm to the point where the variance of travel distance of effluent oil is minimized. As a result of verifying the effluent oil visualization data, it was confirmed that the particle matching algorithm using principal component analysis and genetic algorithm showed the best performance, and the mean data error was 3.2%.

• Journal of the Korean housing association
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• v.26 no.4
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• pp.55-62
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• 2015

The international concern on the inhalable fine dust is continuing to increase. In addition to the toxic properties of the fine dust itself, it can be more dangerous than other environmental factors since the dust pollution is hard to be detected by human sense. Although the information on outdoor air condition can be acquired easily, the indoor dust concentration is another problem because the indoor air condition is influenced by the architectural environment and human activity. It means occupants may be exposed to indoor dust pollution over a long period without being aware. Therefore the indoor dust concentration should be measured separately and visualized as an intuitive information. By visualizing, the indoor dust concentration in each space can be recognized practically in compare with the degree of pollution in adjacent spaces. Besides the visualization outcome can be used as base data for related research such as an analysis of the relation between indoor dust concentration and architectural environment. Meanwhile, with the development of network and micro sensing devices, it became possible to collect wide range of indoor environment data. In this regards, this paper suggests a system for visualization of indoor dust concentration and demonstrates it on an actual space.

• Journal of the Korean Society of Visualization
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• v.19 no.3
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• pp.115-122
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• 2021

Oral cancer surgery typically consists of resection of lesion, neck dissection and reconstruction, and it has an impact on the position of hyoid bone. Therefore, morphological change of airway can occur since the geometric parameter of airway is correlated with the hyoid bone. Airflow is affected by geometry of the airway. In this study, flow characteristics were compared between pre- and post-surgery models by both particle image velocimetry (PIV) and numerical simulation. 3D model of upper airway was reconstructed based on CT data. Velocity is accelerated by the reduced channel area, and vortex and recirculation region are observed in pre- and post-surgery models. For the post-surgery model, high pressure distribution is developed by significantly decreased hydraulic diameter, and the longitudinal flow stream is also interrupted.

• Journal of the Korean Society of Visualization
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• v.9 no.4
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• pp.47-53
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• 2011

A water driven ejector loop was designed and constructed for air absorption. The used ejector was horizontally installed in the loop and annular water jet at the throat entrained air through the circular pipe placed at the center of the ejector. Wide range of water flow rate was provided using two kinds of pumps in the loop. The tested range of water flow rate was 100${\ell}$ /min to 1,000 ${\ell}$/min. Two-phase flow inside the ejector loop was simulated by CFD analysis. Homogeneous particle model was used for void fraction prediction. Water and air flow rates and pressure drop through the ejector were automatically recorded by using the LabView based data acquisition system. Flow characteristics and air bubble velocity field downstream of the ejector were investigated by two-phase flow visualization and PIV measurement based on bubble shadow images. Overall performance of the two-phase ejector predicted by the CFD simulation agrees well with that of the experiment.