• Journal of Advanced Marine Engineering and Technology
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• v.18 no.1
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• pp.32-40
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• 1994

The radiative heat transfer analysis in particle layer has an inherent difficulty in treating the governing integro-differential equations, which are derived from the remote effects. Most of the existing analyses are limited to the one dimensional system, taking into account only absorption or isotropic scatting of solid particles. Fortunately, a new Monte Carlo Simulation method is recently developed to analyse multidimensional radiative heat transfer in particles with anisotropically scatting. By this method, the present study analyses the radiative heat transfer in dispersed particles through the numerous droplets in the liquid droplet radiator to develop a technique of liquid droplet radiator. Consequently, knows that the radiative heat flux in particle layer is influenced by exitinction coefficient, optical thickness and surface area of particles in the system.

• Proceedings of the KIEE Conference
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• 2000.11c
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• pp.540-542
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• 2000

This paper describes the particle-initiated breakdown characteristics of various spacers, which have a ribbed surface, in the presence of a metallic particle. The particle was attached on the surface of each spacer. The breakdown voltages were measured by changing the length and thickness of the rib. Also the electrical field analyses were performed. As a result, the breakdown voltage of the spacer with two ribs was highest, and it was varied by the length and the thickness of the rib. Especially, in case of the rib with round edge, the breakdown voltage was higher than that with rectangular edge, which complied with the result through the field analysis.

• Journal of Powder Materials
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• v.27 no.1
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• pp.44-51
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• 2020

Powder characteristics, such as density, size, shape, thermal properties, and surface area, are of significant importance in the powder bed fusion (PBF) process. The powder required is exclusive for an efficient PBF process. In this study, the particle size distribution suitable for the powder bed fusion process was derived by modeling the PBF product using simulation software (GeoDict). The modeling was carried out by layering sintered powder with a large particle size distribution, with 50 ㎛ being the largest particle size. The results of the simulation showed that the porosity decreased when the mean particle size of the powder was reduced or the standard deviation increased. The particle size distribution of prepared titanium powder by the atomization process was also studied. This study is expected to offer direction for studies related to powder production for additive manufacturing.

• 한국전산유체공학회:학술대회논문집
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• 2009.11a
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• pp.1-1
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• 2009

In this presentation, I talk about various fluid simulation methods that have been developed for computer graphics special effects since 1996. They are all based on CFD but sacrifice physical reality for visual plausability and time. But as the speed of computer increases rapidly and the capability of GPU (graphics processing unit) improves, methods for more physical realism have been tried. In this talk, I will focus on four aspects of fluid simulation methods for computer graphics: (1) particle level-set methods, (2) particle-based simulation, (3) methods for exact satisfaction of incompressibility constraint, and (4) GPU-based simulation. (1) Particle level-set methods evolve the surface of fluid by means of the zero-level set and a band of massless marker particles on both sides of it. The evolution of the zero-level set captures the surface in an approximate manner and the evolution of marker particles captures the fine details of the surface, and the zero-level set is modified based on the particle positions in each step of evolution. (2) Recently the particle-based Lagrangian approach to fluid simulation gains some popularity, because it automatically respects mass conservation and the difficulty of tracking the surface geometry has been somewhat addressed. (3) Until recently fluid simulation algorithm was dominated by approximate fractional step methods. They split the Navier-Stoke equation into two, so that the first one solves the equation without considering the incompressibility constraint and the second finds the pressure which satisfies the constraint. In this approach, the first step introduces error inevitably, producing numerical diffusion in solution. But recently exact fractional step methods without error have been developed by fluid mechanics scholars), and another method was introduced which satisfies the incompressibility constraint by formulating fluid in terms of vorticity field rather than velocity field (by computer graphics scholars). (4) Finally, I want to mention GPU implementation of fluid simulation, which takes advantage of the fact that discrete fluid equations can be solved in parallel.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.3
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• pp.317-325
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• 2016

This paper describes the technique for Radar Particle filter for TBD(Track Before Detect) processing. TBD technique is applied when target is difficult to detect due to low signal-to-noise ratio caused by strong clutter environments, small RCS targets and stealth targets. Particle filter is suitable for a recursive TBD algorithm and has improved estimation accuracy than Kalman filter. In this paper, we will present a new method of calculating particle weight, when observation values(including strong clutter) are received at the same time. Estimation error performance of the particle filter algorithm is analyzed by using the virtual radar observation scenario.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.95-104
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• 2017

This paper deals with solution methods for discrete and multi-valued optimization problems. The objective function of the problem incorporates noise effects generated in case that fitness evaluation is accomplished by computer based experiments such as Monte Carlo simulation or discrete event simulation. Meta heuristics including Genetic Algorithm (GA) and Discrete Particle Swarm Optimization (DPSO) can be used to solve these simulation based multi-valued optimization problems. In applying these population based meta heuristics to simulation based optimization problem, samples size to estimate the expected fitness value of a solution and population (particle) size in a generation (step) should be carefully determined to obtain reliable solutions. Under realistic environment with restriction on available computation time, there exists trade-off between these values. In this paper, the effects of sample and population sizes are analyzed under well-known multi-modal and multi-dimensional test functions with randomly generated noise effects. From the experimental results, it is shown that the performance of DPSO is superior to that of GA. While appropriate determination of population sizes is more important than sample size in GA, appropriate determination of sample size is more important than particle size in DPSO. Especially in DPSO, the solution quality under increasing sample sizes with steps is inferior to constant or decreasing sample sizes with steps. Furthermore, the performance of DPSO is improved when OCBA (Optimal Computing Budget Allocation) is incorporated in selecting the best particle in each step. In applying OCBA in DPSO, smaller value of incremental sample size is preferred to obtain better solutions.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.1-9
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• 2017

Innovations from current researches on cloud computing such as applying bio-inspired computing techniques have brought new level solutions in offloading mechanisms. With the growing trend of mobile devices, mobile cloud computing can also benefit from applying bio-inspired techniques. Energy-efficient offloading mechanisms on mobile cloud systems are needed to reduce the total energy consumption but previous works did not consider energy consumption in the decision-making of task distribution. This paper proposes the Particle Swarm Optimization (PSO) as an offloading strategy of cloudlet to data centers where each task is represented as a particle during the process. The collected tasks are classified using K-means clustering on the cloudlet before applying PSO in order to minimize the number of particles and to locate the best data center for a specific task, instead of considering all tasks during the PSO process. Simulation results show that the proposed PSO excels in choosing data centers with respect to energy consumption, while it has accumulated a little more processing time compared to the other approaches.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.4
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• pp.390-395
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• 2009

Design and optimization of a broadband meander-line twist reflector was performed for X-band application. Based on the equivalent transmission line model, the polarization twist performance was evaluated. Genetic analysis, particles swarm, and hybrid swarm optimizations were employed to obtain the optimized geometrical parameters. The optimized design exhibits low cross-polarization level below - 25 dB between 8.45 and 11.38 GHz. The polarization twist loss was below 0.2 dB. Comparison between computed and simulated results was also discussed.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.549-557
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• 2014

Recently, analysis of bargaining game using evolutionary computation is essential issues in field of game theory. In this paper, we observe a bargaining game using co-evolution between two heterogenous artificial agents. In oder to model two artificial agents, we use a particle swarm optimization and a differential evolution. We investigate algorithm parameters for the best performance and observe that which strategy is better in the bargaining game under the co-evolution between two heterogenous artificial agents. Experimental simulation results show that particle swarm optimization outperforms differential evolution in the bargaining game.

• Journal of the Korean Society of Visualization
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• v.15 no.1
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• pp.32-40
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• 2017

Interaction between fluid and a rigid object is frequently observed in everyday life. However, it is difficult to simulate their interaction as the medium and the object have different representations. One of the challenging issues arises especially in handling deformation of the object visually as well as rendering haptic feedback. In this paper, we propose a real-time simulation technique for multimodal interaction between particle-based fluids and soluble solids. We have developed the dissolution behavior model of solids, which is discretized based on the idea of smoothed particle hydrodynamics, and the changes in physical properties accompanying dissolution is immediately reflected to the object. The user is allowed to intervene in the simulation environment anytime by manipulating the solid object, where both visual and haptic feedback are delivered to the user on the fly. For immersive visualization, we also adopt the screen space fluid rendering technique which can balance realism and performance.