• Journal of Ship and Ocean Technology
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• 제11권4호
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• pp.29-54
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• 2007

Systematic sensitivity analysis of smoothed particle hydrodynamics method (SPH), a gridless Lagrangian particle method, was carried out in this study. Unlike traditional grid-based numerical schemes, systematic sensitivity study for computational parameters is very limited for SPH. In this study, the effect of computational parameters in SPH simulation is explored through two-dimensional dam-breaking and sloshing problem. The parameters to be considered are the speed of sound, the type of kernel function, the frequency of density re-initialization, particle number, smoothing length and pressure extraction method. Through a series of numerical test, detailed information was obtained about how SPH solution can be more stabilized and improved by adjusting computational parameters.

• Journal of Information Processing Systems
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• 제15권1호
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• pp.116-126
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• 2019

In this paper, an improved one-against-one support vector machine algorithm is used to classify multiple power quality disturbances. To solve the problem of parameter selection, an improved particle swarm optimization algorithm is proposed to optimize the parameters of the support vector machine. By proposing a new inertia weight expression, the particle swarm optimization algorithm can effectively conduct a global search at the outset and effectively search locally later in a study, which improves the overall classification accuracy. The experimental results show that the improved particle swarm optimization method is more accurate than a grid search algorithm optimization and other improved particle swarm optimizations with regard to its classification of multiple power quality disturbances. Furthermore, the number of support vectors is reduced.

• 한국전기전자재료학회논문지
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• 제20권8호
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• pp.742-747
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• 2007

In 2-dimensional SCBF (Spherically Convergent Beam Fusion) device, the effect on neutron production rate of the grid cathode geometry was simulated. The motion of Particles was tracked using Monte Carlo Method including the atomic and molecular collision processes and potential distribution was calculated by Finite Element Method, Main processes of the discharge were the ionization of $D_2$ by fast $D_2^+\;ion$. As the number of cathode rings was small and the size of grid cathode decreased, the ion current increased and neutron production rate will also increase. The star mode discharge which is a very important characteristic in SCBF device, was confirmed by the ionization position.

• Journal of Power Electronics
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• 제19권5호
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• pp.1248-1258
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• 2019

This paper presents a moth-flame optimization (MFO)-based maximum power point tracking (MPPT) method for photovoltaic (PV) systems. The MFO algorithm is a new optimization method that exhibits satisfactory performance in terms of exploration, exploitation, local optima avoidance, and convergence. Therefore, the MFO algorithm is quite suitable for solving multiple peaks of PV systems under partial shading conditions (PSCs). The proposed MFO-MPPT is compared with four MPPT algorithms, namely the perturb and observe (P&O)-MPPT, incremental conductance (INC)-MPPT, particle swarm optimization (PSO)-MPPT and whale optimization algorithm (WOA)-MPPT. Simulation and experiment results demonstrate that the proposed algorithm can extract the global maximum power point (MPP) with greater tracking speed and accuracy under various conditions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권4호
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• pp.247-253
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• 2011

A sustainability of electricity supply has emerged as a critical issue for low carbon green growth in South Korea. Wind power is the fastest growing source of renewable energy. However, due to its own intermittency and volatility, the power supply generated from wind energy has variability in nature. Hence, accurate forecasting of wind speed and power plays a key role in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. This paper presents a short-term wind speed prediction method based on support vector regression. Moreover, particle swarm optimization is adopted to find an optimum setting of hyper-parameters in support vector regression. An illustration is given by real-world data and the effect of model regularization by particle swarm optimization is discussed as well.

• 한국멀티미디어학회논문지
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• 제21권1호
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• pp.51-60
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• 2018

We present a real-time interactive particle-art with human motion based on computer vision techniques. We used computer vision techniques to reduce the number of equipments that required for media art appreciations. We analyze pros and cons of various computer vision methods that can adapted to interactive digital media art. In our system, background subtraction is applied to search an audience. The audience image is changed into particles with grid cells. Optical flow is used to detect the motion of the audience and create particle effects. Also we define a virtual button for interaction. This paper introduces a series of computer vision modules to build the interactive digital media art contents which can be easily configurated with a camera sensor.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2006년도 PARALLEL CFD 2006
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• pp.27-34
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• 2006

In this paper, a recently proposed parallel hybrid particle-continuum (DSMC-NS) scheme employing 3D unstructured grid for solving steady-state gas flows involving continuum and rarefied regions is described [1]. Substitution of a density-based NS solver to a pressure-based one that greatly enhances the capability of the proposed hybrid scheme and several practical experiences of implementation learned from the development and verifications are highlighted. At the end, we present some simulation results of a realistic RCS nozzle plume, which is considered very challenging using either a continuum or particle solver alone, to demonstrate the capability of the proposed hybrid DSMC-NS method.

• Bulletin of the Korean Chemical Society
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• 제25권12호
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• pp.1893-1897
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• 2004

Hydrodynamic simulations of mesoscopic solvent have been performed by multi-particle collision algorithm in a real dimensional system without and with the random shifting of the grid. A systematic conversion of the dimensionless units to a real dimensional system was confirmed by jump rates of solvent particles. Speed distributions of solvent particles obtained from the simulations agreed very well with the Maxwell-Boltzmann distributions. Solvent viscosities obtained from the simulations and from the conversion of units are exactly the same which confirmed the correct conversion of the units once again. The calculation of the friction coefficient of a massive Brownian particle in a mesoscopic solvent as a function of Brownian particle diameter was examined as an example.

• 한국대기환경학회지
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• 제15권6호
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• pp.757-765
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• 1999

Lagrangian particle dispersion model(LPDM) is an effective tool to calculate the dispersion from a point source since it dose not induce numerical diffusion errors in solving the pollutant dispersion equation. Fictitious particles are released to the atmosphere from the emission source and they are then transported by the mean velocity and diffused by the turbulent eddy motion in the LPDM. The concentration distribution from the dispersed particles in the calculation domain are finally estimated by applying a particle count method or a Gaussian kernel method. The two methods for calculating concentration profiles were compared each other and tested against the analytic solution and the tracer experiment to find the strength and weakness of each method and to choose computationally time saving method for the LPDM. The calculated concentrations from the particle count method was heavily dependent on the number of the particles released at the emission source. It requires lots fo particle emission to reach the converged concentration field. And resulting concentrations were also dependent on the size of numerical grid. The concentration field by the Gaussian kernel method, however, converged with a low particle emission rate at the source and was in good agreement with the analytic solution and the tracer experiment. The results showed that Gaussian kernel method was more effective method to calculate the concentrations in the LPDM.

• Journal of Advanced Marine Engineering and Technology
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• 제20권4호
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• pp.90-100
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• 1996

To maintain high spacial accuracy and rapid CPU time in interpolating data from grid to random position or inversely in PIV, proposed many technuques are compared and discussed mainly in terms of interpolating error and computing time. And artificial PIV atmosphere data is furnished by CFD result. First, for interpolation from grid to random position, multiquadric method gives the highest accuracy with the longest CPU time and Taylor series expansion methods give reasonable accuracy with less calculating load. Secondly, the sub-pixel resolution analysis in estimating the coordinates of the maximum correlation coefficients essential in the grey level correlation PIV reveal that 8-neighbours 2nd-order least square interpolation gives utmost accuracy in terms of the real flow conditions.