• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.858-864
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• 2017

This study aims to restrain free conducting wire-type particles which are commonly and dangerously existing within DC gas-insulated transmission lines. A realistic platform of a coaxial cylindrical electrode was established by using a high-speed camera and a partial discharge (PD) monitor to observe the motion, PD, and breakdown of these particles. The probabilities of standing or bouncing, which can be affected by the length of the particles, were also quantitatively examined. The corona images of the particles were recorded, and particle-triggered PD signals were monitored and extracted. Breakdown images were also obtained. The air-gap breakdown with the particles was subjected to mechanism analysis on the basis of stream theory. Results reveal that the lifting voltage of the wire particles is almost irrelevant to their length but is proportional to the square root of their radius. Short particles correspond to high bouncing probability. The intensity and frequency of PD and the micro-discharge gap increase as the length of the particles increases. The breakdown voltage decreases as the length of the particles decreases.

• Proceedings of the KIEE Conference
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• 1998.11c
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• pp.898-900
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• 1998

This paper describes the motion characteristics and micro-discharge of the free conducting particles between plain electrodes under alternating voltage. The particles move between both electrodes due to electrostatic force by applied AC voltage. Various types and sizes of free conducting particles were used to study the motion and micro-discharge characteristics. The micro-discharge and breakdown were observed during the particle motion.

• 한국전산유체공학회:학술대회논문집
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• 2002.10a
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• pp.41-46
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• 2002

A numerical simulation was made to determine the motion of particles in the fluid. The simulation is based on the Eulerian-Lagrangian method. The fluid motion was solved using a PISO-based finite-element method and a $\kappa-\epsilon$ model of turbulence. In the Lagrangian method for the solid phase, the trajectories of particles are calculated by integrating the equations of motion of a single Particle, and the collision between particles are taken into account. The influence of particles on the fluid phase is taken into account by introducing source terms in the Eulerian equations govering the fluid flow. It is known as the particle-source-in-cell (PSIC) method. Also, the turbulent effect in the particles and fluid notion is considered. The numerical results were compared with the experiment for a two-phase flow in a vertical pipe.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.11a
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• pp.514-517
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• 2004

We have studied motion of micro-particle immersed in liquid crystal (LC) controlled by in-plane field, which is an important technology in the electro-phoretic display (EPD). In the EPD on and off states are decided by movement of these charged particles and response time is influenced by moving velocity of charged particles. In addition, the velocity can be controlled by intensity of applied voltage such that the higher the applied voltage, the faster velocity of particles become. In this study, we investigated particles's motion as functions of applied voltage, temperature of LC, rubbing direction,

• Proceedings of the KSME Conference
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• 2000.04b
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• pp.740-745
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• 2000

Effects of porous fences on the wind erosion of sand particles from a triangular pile were investigated experimentally. The porous fence and sand pile were installed in a simulated atmospheric boundary layer. The mean velocity and turbulent intensity profiles measured at the sand pile location were well fitted to the atmospheric boundary layer over the open terrain. Particle motion was visualized to see the motion of windblown sand particles qualitatively. In addition, the threshold velocity were measured using a light sensitive video camera with varying the fence porosity ${\varepsilon}$. As a result, various types of particle motion were observed according to the fence porosity. The porous wind fence having porosity ${\varepsilon}=30%$ was revealed to have the maximum threshold velocity, indicating good shelter effect for abating windblown dust particles.

• Journal of the Korea Computer Graphics Society
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• v.28 no.4
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• pp.13-22
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• 2022

In this paper, we propose a single framework based on the MPM(Material Point Method) that can represent the dynamic angular motion of the elementary particle unit. In this study, the particles can have various shapes while also describing linear and angular motion. As a result, unlike other particle-based simulations, which only represent linear movements of spherical (e.g. Circle, Sphere) particles, it is possible to express the visually dynamic motion of them. The proposed framework utilizes MPM, due to the fact that rotational motion can be decomposed and derived from large deformation. During the integration process of the presented technique, a deformation gradient tensor is decomposed by polar decomposition theory for extracting rotation tensor. By applying this together with the linear motion of each particle, as a result, it is possible to simultaneously express the angluar and linear motion of the particle itself. To verify the proposed method, we show the simulation of rotating particles scattering in the wind field, and the interaction(e.g. Collision) between a moving object and them by comparing the traditional MPM

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.2
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• pp.110-116
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• 2005

This paper deals with interaction between two bubbles or particles and flow around them, visualized by a moving object flow image analyzer(MOFIA) consisting of a three-dimensional (3D) moving object image analyzer(MOIA) and two-dimensional particle image velocimetry(PIV). The experiments were carried out for rising bubbles or particles of various densities, sizes, and/or shapes in stagnant water in a vertical pipe. In the MOFIA employed, 3D-MOIA was used to measure particles or bubbles motion and PIV was used to measure fluid flow, The experimental results showed that the interaction was characterized by the shape, size and density of two particles or bubbles.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2003.05b
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• pp.355-356
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• 2003

Coagulation is a process whereby particles collide with one another due to their relative motion, and adhere to form large particles. Coagulation caused by the random Brownian motion of particles is called Brownian coagulation. Many properties, such as light scattering, electrostatic charges, toxicity, as well as physical processes, including diffusion, condensation and thermophoresis depend strongly on their size distribution. Therefore, Brownian coagulation is substantially important in atmospheric science, combustion technology, inhalation toxicology and nuclear safety analysis. (omitted)

• Transactions of the Korean Society of Mechanical Engineers B
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• v.23 no.10
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• pp.1240-1247
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• 1999

Particle motion through a disk type critical orifice placed in a 3.0cm diameter chamber has been studied numerically. In the simulation, the velocity field is solved using Pantankar's SIMPLER algorithm for the compressible flow and convergence of the computation is confirmed if the mass source at each control volume is smaller than $10^{-7}$. The particle motion in the flow field is solved in Lagrangian method. The particle trajectories showed that the particles injected away from the center line are expanded rapidly. At lower pressures, this expansion phenomena are more dominant. At lower pressures, the clear difference in particle and air speed is showed all the way down to the exit plan. It was found that particles with Stokes number of ca.2.5 tend to focus close to the center line very well except the particles travelling near the wall. However, particles with Stokes number greater than ca.2.5 show a tendency to cross the center line.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.496-496
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• 2000

We propose a neuron computer for tracking motion of particles in multi-dimensional space. The neuron computer is constructed of neural networks and their connections, which is a simplified model of the brain. The neuron computer is assemblage of neural networks, it includes a control unit, and the actions of the unit are represented by instructions. We designed a neuron computer to recognize and predict motion of particles. The recognition unit is constructed of neuron-array, encoder, and control part. The neuron-array is a model of the retina, and particles crease an image on the array, where the image is binary. The encoder picks one particle from the array, and translates the particle's location to Cartesian coordinates, which is scaled in [0, 1] intervals. Next, the encoder picks another particle, and does same process. The ordering and reduction of complex processes are executed by instructions. The instructions are held in the control part. The prediction unit is constructed of a multi-layer neural network and a feedback loop, where real time learning is executed. The particles' future locations are forecasted by coordinate values. The neuron computer can chase maximum 100 particles that take evasions.