• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.06a
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• pp.30-35
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• 2001

The morphological analysis of wear particle is a very effective means for machine condition monitoring and fault diagnosis. In order to describe morphology of various wear particle, the wear test was carried oui under friction experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing system. These descriptors to analyze shape and surface wear particle are share fractal dimension and surface fractal dimension. The boundry fractal dimension can be derived from the boundary profile and surface fractal dimension can be determined b)r sum of intensity difference of surface pixel. The morphology of wear particles can be effectively obtained by two fractal dimensions.

• Particle and aerosol research
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• v.12 no.1
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• pp.21-26
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• 2016

In order to realize In-line and convenient measurement for solid-gas two phase flows, Light Transmission Fluctuation (LTF) based on the random variation of transmitted light intensity, light scattering theory and cross-correlation method was presented for online measurement of particle size, concentration and velocity. The statistical relationship among transmitted light intensity, particle size and particle number in measurement zone was described by Beer-Lambert Law. Accordingly, the particle size and concentration were determined from the fluctuation signal of transmitted light intensity. Simultaneously, the particle velocity was calculated by cross-correlation analysis of two neighboring light beams. By considering the influence of concentration variation in industrial applications, the improved algorithm based on spectral analysis of transmitted light intensity was proposed to improve measurement accuracy and stability. Therefore, the online measurement system based on LTF was developed and applied to measure pulverized coal in power station and raw material in cement plant. The particle size, concentration and velocity of powder were monitored in real-time. It can provide important references for optimal control, energy saving and emission reduction of energy-intensive industries.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.3
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• pp.15-28
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• 2023

The compaction properties of the soil change depending on the physical properties, and are also affected by crushing of the particles. Since the particle size distribution of soil affects the engineering properties of the soil, it is necessary to analyze the material properties to understand the compaction characteristics. In this study, the size of each sieve was classified into four in the particle size analysis as a material property, and the compaction characteristics were evaluated by multiple regression and maximum dry unit weight. As a result of maximum dry unit weight prediction, multiple regression analysis showed R² of 0.70 or more, and DNN analysis showed R² of 0.80 or more. The reliability of the prediction result analyzed by DNN was evaluated higher than that of multiple regression, and the analysis result of DNN-T showed improved prediction results by 1.87% than DNN. The prediction of maximum dry unit weight using particle size distribution seems to be applied to evaluate the compacting state by identifying the material characteristics of roads and embankments. In addition, the particle size distribution can be used as a parameter for predicting maximum dry unit weight, and it is expected to be of great help in terms of time and cost of applying it to the compaction state evaluation.

• Journal of Korean Society for Atmospheric Environment
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• v.16 no.2
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• pp.165-178
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• 2000

In this study the effects of block distance have been investigated on the particle deposition efficiency in the collecting cell of two-stage electrostatic precipitator by numerical analysis. Particle trajectories have been changed by the electrostatic and inertial force of particle with the inlet velocity electrostatic number and particle diameter. The total deposition efficiency has a minimum value by the interaction between the effect of particle inertial force and electrostatic force in the collecting cell. The increase of block distance makes the total deposition efficiency decrease under the range of the particle size which has the minimum deposition efficiency. However beyond the range of particle size which has minimum deposition efficiency total deposition efficiency has no trend with the variation of block distance.

• Particle and aerosol research
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• v.14 no.2
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• pp.41-47
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• 2018

Numerical analysis was conducted to characterize particle deposition onto a heated horizontal semiconductor wafer in vacuum environment. In order to calculate the properties of gas surrounding the wafer, the gas was assumed to obey the ideal gas law. Particle transport mechanisms considered in the present study were convection, Brownian diffusion, gravitational settling and thermophoresis. Averaged particle deposition velocities on the upper surface of the wafer were calculated with respect to particle size, based on the numerical results from the particle concentration equation in the Eulerian frame of reference. The deposition velocities were obtained for system pressures of 1000 Pa~1 atm, wafer heating of 0~5 K and particle sizes of $2{\sim}10^4nm$. The present numerical results showed good agreement with the available experimental ones.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.77-82
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• 2021

This numerical study focuses on the analysis of fume particle dispersion characteristics over the surface of target workpiece in laser micro-hole machining process. The effects of oblique stagnation flow over fume generating machining point are examined by carrying out a series of three-dimensional random particle simulations along with probabilistic particle generation model and particle drag correlation of low Reynolds number. Present computational model of fume particle dispersion is found to be capable of assessing and quantifying the fume particle contamination in precision hole machining which may influenced by different types of air flow patterns and their flow intensity. The particle size dependence on dispersion distance of fume particles from laser machining point is significant and the effects of increasing flow oblique angle are shown quite differently when slot blowing or slot suction flows are applied in micro-hole machining.

• Journal of Korean Society of Water and Wastewater
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• v.23 no.1
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• pp.97-105
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• 2009

Analysis was done on the particle size distribution of sediments flown into Saemangeum from the Mankyung and Dongjin River. The organic pollutants and heavy metal existing in the sediments were analyzed, which was further used to study the properties of pollution in the sediments according to the particle size distribution. Conclusions shown below were made from these analyses. The particle size distribution showed a big difference between the upriver areas of Mankyung and Dongjin River. Particles under $75{\mu}m$ showed to be around 85% at Dongjin River, while it showed to be around 70% at Mankyung River. This kind of distribution in particle size concluded in greatly affecting the contamination density of the sediments. From the analysis done on the soil type of sediments, deposition in Mankyung River categorized into Silty loam and Sandy loam, where Silty loam covered most of area and deposition in Dongjin River categorized into Sand, Loamy sand, Silty loam, Sandy loam. Considering the weight ratio, the density of contamination of the sediments by particle size at Dongjin and Mankyung River has been analyzed to show that organic pollutants and heavy metals occupy more than 70% of the whole contamination in the range under the particle size of $75{\mu}m$.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2511-2519
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• 2009

In this paper, we introduce the methodological system design via feature selection using Principal Component Analysis and Particle Swarm Optimization algorithms. The overall methodological system design comes from three kinds of modules such as preprocessing module, feature extraction module, and recognition module. First, Histogram equalization enhance the quality of image by exploiting contrast effect based on the normalized function generated from histogram distribution values of 2D face image. Secondly, PCA extracts feature vectors to be used for face recognition by using eigenvalues and eigenvectors obtained from covariance matrix. Finally the feature selection for face recognition among the entire feature vectors is considered by means of the Particle Swarm Optimization. The optimized Polynomial-based Radial Basis Function Neural Networks are used to evaluate the face recognition performance. This study shows that the proposed methodological system design is effective to the analysis of preferred face recognition.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.5
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• pp.424-432
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• 2002

Numerical analysis has been conducted to characterize deposition rates of aerosol particles onto a heated, rotating disk with electrostatic effect under the laminar flow field. The particle transport mechanisms considered were convection, Brownian diffusion, gravitational settling, thermophoresis and electrophoresis. The aerosol particles were assumed to have a Boltzmann charge distribution. The electric potential distribution needed to calculate local electric fields around the disk was calculated from the Laplace equation. The Coulomb, the image, the dielectrophoretic and the dipole-dipole forces acting on a charged particle near the conducting rotating disk were included in the analysis. The averaged particle deposition vetocities and their radial distributions on the upper surface of the disk were calculated from the particle concentration equation in a Eulerian frame of reference, along with a rotation speed of 0∼1,000rpm, a temperature difference of 0∼5K and a charged disk voltage of 0∼1000V.Finally, an approximate deposition velocity model for the rotating disk was suggested. The present numerical results showed relatively good agreement with the results of the present approximate model and the available experimental data.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.6
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• pp.365-370
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• 2023

This paper presents a particle-structure collision model for topology optimization, which requires sensitivity analysis. Therefore, a new model that incorporates sensitivity analysis is needed. The proposed particle-structure collision model conducts sensitivity analysis for topology optimization. To evaluate the accuracy of the proposed model, it was applied to a simplified one-dimensional collision problem. Optimization of the final positions of particles using topology optimization through this model confirmed the suitability of the proposed approach. These results demonstrate that it is possible to consider particle-structure collision in topology optimization.