• Journal of The Korean Astronomical Society
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• v.43 no.4
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• pp.105-113
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• 2010

We study the dynamical evolution of the M87 globular cluster (GC) system using the most advanced and realistic Fokker-Planck (FP) model.By comparing our FP models with both mass function (MF) and radial distribution (RD) of the observed GC system, we find the best-fit initial (at M87's age of 2-3 Gyr) MF and RD for three GC groups: all GCs, blue GCs, and red GCs. We estimate the initial total mass in GCs to be $1.8^{+0.3}_{-0.2}{\times}10^{10}M_{\bigodot}$, which is about 100 times larger than that of the Milky Way GC system. We also find that the fraction of the total mass currently in GCs is 34\%. When blue and red GCs are fitted separately, blue GCs initially have a larger total mass and a shallower radial distribution than red GCs. If one assumes that most of the significant major merger events of M87 have ended by the age of 2-3 Gyr, our finding that blue (metal-poor) GCs initially had a shallower radial distribution supports the major merger scenario for the origin of metallicity bimodality.

• Smart Structures and Systems
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• v.13 no.1
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• pp.1-24
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• 2014

The present study deals with two dimensional electro-elastic analysis of a functionally graded piezoelectric (FGP) cylinder under internal pressure. Energy method and first order shear deformation theory (FSDT) are employed for this purpose. All mechanical and electrical properties except Poisson ratio are considered as a power function along the radial direction. The cylinder is subjected to uniform internal pressure. By supposing two dimensional displacement and electric potential fields along the radial and axial direction, the governing differential equations can be derived in terms of unknown electrical and mechanical functions. Homogeneous solution can be obtained by imposing the appropriate mechanical and electrical boundary conditions. This proposed solution has capability to solve the cylinder structure with arbitrary boundary conditions. The previous solutions have been proposed for the problem with simple boundary conditions (simply supported cylinder) by using the routine functions such as trigonometric functions. The axial distribution of the axial displacement, radial displacement and electric potential of the cylinder can be presented as the important results of this paper for various non homogeneous indexes. This paper evaluates the effect of a local support on the distribution of mechanical and electrical components. This investigation indicates that a support has important influence on the distribution of mechanical and electrical components rather than a cylinder with ignoring the effect of the supports. Obtained results using present method at regions that are adequate far from two ends of the cylinder can be compared with previous results (plane elasticity and one dimensional first order shear deformation theories).

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07b
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• pp.1129-1133
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• 2004

반도체공정 최적화에 소요되는 시간과 경비를 줄이기 위해 신경망 모델이 개발되고 있다. 주로 역전파 신경망을 이용하여 모델이 개발되고 있으며, 본 연구에서는 Radial Basis Function Network (RBFN)을 이용하여 플라즈마 식각공정 모델을 개발한다. 실험데이터는 유도결합형 플라즈마를 이용한 Silicon Carbide 박막의 식각공정으로부터 수집되었다. 모델개발을 위해 $2^4$ 전인자 (full factorial) 실험계획법이 적용되었으며, 모델에 이용된 식각응답은 식각률과 atomic force microscopy로 측정한 식각표면 거칠기이다. 모델검증을 위해 추가적으로 16번의 실험을 수행하였다. RBFN의 예측성능은 세 학습인자, 즉 뉴런수, width, 초기 웨이트 분포 (initial weight distribution-IWD) 크기에 의해 결정된다. 본 연구에서는 각 학습인자의 영향을 최적화하였으며, IWD의 불규칙성을 고려하여 주어진 학습인자에 대해서 100개의 모델을 발생하고, 이중 최소의 IWD를 갖는 모델을 선택하였다. 최적화한 식각률과 표면거칠기 모델의 RMSE는 각기 26 nm/min과 0.103 nm이었다. 통계적인 회귀모델과 비교하여, 식각률과 표면거칠기 모델은 각기 52%와 24%의 향상된 예측정확도를 보였다. 이로써 RBFN이 플라즈마 공정을 효과적으로 모델링 할 수 있음을 확인하였다.

• Geomechanics and Engineering
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• v.33 no.6
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• pp.567-581
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• 2023

The prediction and achievement of a proper rock fragmentation size is the main challenge of blasting operations in surface mines. This is because an optimum size distribution can optimize the overall mine/plant economics. To this end, this study attempts to develop four improved artificial intelligence models to predict rock fragmentation through cascaded forward neural network (CFNN) and radial basis function neural network (RBFNN) models. In this regards, the CFNN was trained by the Levenberg-Marquardt algorithm (LMA) and Conjugate gradient backpropagation (CGP). Further, the RBFNN was optimized by the Dragonfly Algorithm (DA) and teaching-learning-based optimization (TLBO). For developing the models, the database required was collected from the Midouk copper mine, Iran. After modeling, the statistical functions were computed to check the accuracy of the models, and the root mean square errors (RMSEs) of CFNN-LMA, CFNN-CGP, RBFNN-DA, and RBFNN-TLBO were obtained as 1.0656, 1.9698, 2.2235, and 1.6216, respectively. Accordingly, CFNN-LMA, with the lowest RMSE, was determined as the model with the best prediction results among the four examined in this study.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.2
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• pp.35.1-35.1
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• 2010

Unlike the initial mass function, the initial size distribution of globular cluster (GC) systems is not well known. We calculate the evolution of the mass function (MF), radial distribution (RD), and size distribution (SD) of the Galactic GC system. By comparing the results from this calculation and the present-day MF, RD, and SD of the Galactic GC system, we infer the initial SD of the GC system. We find that a Gaussian distribution of the half-mass radius and a Gaussian distribution of the half-mass to Jacobi radius ratio are the best-fit initial SDs of the Galactic GC system.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.3
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• pp.380-391
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• 1997

A numerical study has been done on the evolution of particle size distribution in particle laden high temperature jet flows undergoing convection, diffusion, thermophoresis and coagulation. The dynamic behavior of these particles have been modelled by approximating the particle size distribution by a lognormal function throughout the process and the moments of the particle size distribution have been used to solve the general dynamic equation. The size distributions of spherical particles in the radial and axial direction have been obtained including the effect of buoyancy. Of particular interests are the variations of geometric mean diameter, number concentration and polydispersity. Results show that buoyancy significantly alters the size distribution in both axial and radial direction. One dimensional analysis for non-spherical particles has also been done and the results have been compared with the existing experimental data.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.4
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• pp.82-86
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• 1999

Electron Energy Distribution Function(EEDF) were treasured In Radio-Frequency Inductively Coupled Plasma(RFlCP) using a probe rrethocl Measurerrents were conducted in argon discharge for pressure from 10[mTorr] to 4O[mTorr] and input rf power from 100[W] to 600[W] and flow rate from 3[sccm] to 12[sccm]. Spatial distribution of electron energy distribution function were measured for discharge with same aspoct ratio (R/L=2). Electron energy distribution function strongly depended on both pressure and power. Electron energy distribution function increased with increasing flow rate. Radial distribution of the electron energy distribution function were peaked in the plasma center. Normal distribution of the electron energy distribution function were peaked in the center between quartz plate and substrate. From the results, we can find out the generation mechanism of Radio Frequency Inductively Coupled Plasma. And these results contribute the application of a simple Inductively Coupled Plasma(ICP).a(ICP).

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2511-2520
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• 2018

In this study, Multi-Radial Basis Function Support Vector Machine (Multi-RBF SVM) classifier is introduced based on a composite kernel function. In the proposed multi-RBF support vector machine classifier, the input space is divided into several local subsets considered for extremely nonlinear classification tasks. Each local subset is expressed as nonlinear classification subspace and mapped into feature space by using kernel function. The composite kernel function employs the dual RBF structure. By capturing the nonlinear distribution knowledge of local subsets, the training data is mapped into higher feature space, then Multi-SVM classifier is realized by using the composite kernel function through optimization procedure similar to conventional SVM classifier. The original training data set is partitioned by using some unsupervised learning methods such as clustering methods. In this study, three types of clustering method are considered such as Affinity propagation (AP), Hard C-Mean (HCM) and Iterative Self-Organizing Data Analysis Technique Algorithm (ISODATA). Experimental results on benchmark machine learning datasets show that the proposed method improves the classification performance efficiently.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.22 no.1
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• pp.51-56
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• 2012

In the present study, we investigated the effect of mechanical alloying (MA) on the formation of amorphous VCo system through solid state reaction during ball milling. Two types of powder samples, ${\sigma}$-VCo intermetallic compound and $V_{50}Co_{50}$ powder mixture, were applied as a starting materials. With increasing milling time, a structural characteristics into the amorphous state is distinctly observed from the structural factor and radial distribution by X-ray diffraction. Amorphization has been observed in all two types of samples after the milling for 120 hrs. DSC spectrum of $V_{50}Co_{50}$ powder sample milled for 60 hrs indicates a sharp exothermic peak from the crystallization at $600^{\circ}C$. The structure factor, S(Q) and radial distribution function, RDF(r), observed by X-ray diffraction gradually change into a structure characteristic of an amorphous state with increasing MA time.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.3
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• pp.48-55
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• 1999

Ths paper presents an optimization method which determines locations and size of capacitors simultaneously while minimizing power losses and improving voltage profile in radial distribution systems. Especially, the cost function associated with capacitor pla.cerrent is considered as step function due to banks of standard discrete capacities. Genetic algorithms(GA) are used to obtain efficiently the solution of the cost function associated with capacitors which is non-continuous and non-differentiable function. The strings in GA consist of the node nwnber index and size of capacitors to be installed. The length mutation operator, which is able to change the length of strings in each generation, is used. The proposed Jrethod which determines locations and size of capacitors simultaneously can reduce power losses and improve voltage proftle with capacitors of minimum size. Its efficiency is proved through the arolication in radial distribution systems.ystems.