• Journal of the Korean Mathematical Society
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• v.32 no.2
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• pp.211-236
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• 1995

The purpose of this paper is to provide a transient diffusion approximation of queue size distribution for M/G/m/N system. The M/G/m/N system can be expressed as follows. The interarrival times of customers are exponential and the service times of customers have general distribution. The system can hold at most a total of N customers (including the customers in service) and any further arriving customers will be refused entry to the system and will depart immediately without service. The queueing system with finite capacity is more practical model than queueing system with infinite capacity. For example, in the design of a computer system one of the important problems is how much capacity is required for a buffer memory. It its capacity is too little, then overflow of customers (jobs) occurs frequently in heavy traffic and the performance of system deteriorates rapidly. On the other hand, if its capacity is too large, then most buffer memories remain unused.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.19 no.3
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• pp.233-239
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• 2006

Two different nanofluids were prepared by dispersing $Al_{2}O_3$ nanoparticles in transformer oil after hydrophobic surface modification. The agglomerated alumina nanoparticles with diameters from ${\mu}m$ to mm were ball-milled and then treated with surfactants such as lauric acid, stearic acid and oleic acid. The surface characteristics of modified nanoparticles were examined by FTIR spectroscopy. It showed that the hydrophobicity of nanoparticles was caused by esterification between hydroxyl groups on the particle surface and functional groups of surfactant. The shape and size distribution of ball-milled particles were analyzed by TEM and PSA. The results compared with the primary particles indicated that the size distributions of nanoparticles were dependant on milling times. The dispersion stability of modified nanoparticles dispersed in oil was highly dependent on the composition and amounts of surfactants.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.11a
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• pp.151-152
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• 2005

Both $Al_2O_3$ and AlN nanopowders with diameters from ${\mu}m$ to mm were bead-milled and surface-modified by stabilizing agent. The size of bead-milled nanoparticles compared with the primary powder was effectively decreased and was dependent on milling time and bead size. The results of dispersion stability analysis indicated that chemical bonding between nanoparticles and surfactant is more effective than chemical adsorption to prepare the stable transformer oils containing nanoparticles. In this study, the thermal conductivity of the transformer oils containing nanoparticles was measured by transient hot-wire and laser flash methods.

• Transactions of Materials Processing
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• v.18 no.6
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• pp.482-487
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• 2009

A finite element based microstructural modeling for the size dependent strengthening of particle reinforced aluminum composites is presented. The model accounts explicitly for the enhanced strength in a discretely defined "punched zone" around the particle in an aluminum matrix composite as a result of geometrically necessary dislocations developed through a CTE mismatch. The density of geometrically necessary dislocations is calculated considering volume fraction of the particle. Results show that predicted flow stresses with different particle size are in good agreement with experiments. It is also shown that 0.2% offset yield stresses increases with smaller particles and larger volume fractions and this length-scale effect on the enhanced strength can be observed by explicitly including GND region around the particle. The strengths predicted with the inclusion of volume fraction in the density equation are slightly lower than those without.

• Advances in materials Research
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• v.8 no.3
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• pp.237-257
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• 2019

The present article researches large-amplitude thermal free vibration characteristics of nonlocal two-phase piezo-magnetic nano-size beams having geometric imperfections by considering piezoelectric reinforcement scheme. The piezoelectric reinforcement can cause an enhanced vibration behavior of smart nanobeams under magnetic field. All previous studies on vibrations of piezoelectric-magnetic nano-size beams ignore the influences of geometric imperfections which are crucial since a nanobeam is not always ideal or perfect. Nonlinear governing equations of a smart nanobeam are derived based on classical beam theory and an analytical trend is provided to obtain nonlinear vibration frequency. This research shows that changing the volume fraction of piezoelectric phase in the material has a great influence on vibration behavior of smart nanobeam under electric and magnetic fields. Also, it can be seen that nonlinear vibration behaviors of smart nanobeam is dependent on the magnitude of exerted electric voltage, magnetic imperfection amplitude and substrate constants.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.116-118
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• 2011

일반적으로 나노입자의 크기는 나노복합체의 역학적 특성에 상당한 영향을 미친다. 이에 본 연구에서는 나노입자 크기를 고려한 나노복합체 재료 구성모델 (Kim et al., 2011)을 소개하고자 한다. Kim et al. (2011)에 의해서 나노입자 크기효과를 위한 Size-dependent Eshelby tensor가 미세역학 모델에 적용되었으며, 나노스케일 해석과 함께 다양한 수치해석을 수행하였다. 특히, 본 연구에서는 이를 활용하여 $SiO_2$/Epoxy 나노복합체의 역학적 특성을 예측해 보았다.

• International Journal of Precision Engineering and Manufacturing
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• v.9 no.4
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• pp.71-73
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• 2008

The development of polymer/inorganic nanocomposites has attracted a great deal of interest due to the improved hybrid properties derived from the two different components. Various nanoscale fillers have been used to enhance polymer mechanical and thermal properties, such as toughness, stiffness, and heat resistance. The effects of the filler on the final properties of the nanocomposites are highly dependent on the filler shape, particle size, aggregate size, surface characteristics, polymer/inorganic interactions, and degree of dispersion. In this paper, we describe the influence of different $CaCO_3$ dispersion methods on the thermal properties of polyethylene terephthalate (PET)/$CaCO_3$ composites: i.e., the adsorption of $CaCO_3$ on the modified PET surface, and the hydrophobic modification of the hydrophilic $CaCO_3$ surface. We prepared PET/$CaCO_3$ nanocomposites using a twin-screw extruder, and investigated their thermal properties and morphology.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.04a
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• pp.351-358
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• 2001

In this study, for the investigation of effects of several parameters, such as fluid mesh boundary size, cylinder or block shape, dimensions of depth, breadth and length at free suface, and fluid mesh element size to the depth direction on a reliable shock response of finite element model under underwater explosion with consideration of the bulk cavitation analysis of a simplified surface ship was carried out using the LS-DYNA3D/USA code. The shock responses were not much affected by the fluid mesh parameters. The computational time was greatly dependent on the number of DAA boundary segments. It is desirable to reduce the DAA boundary segments in the fluid mesh model, and it is not necessary to cover the fluid mesh boundary to or beyond the bulk cavitation zone just for the concerns about an initial shock wave response. It is also the better way to prefer cylinder type of the fluid mesh model to the block one.

• Journal of Magnetics
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• v.15 no.1
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• pp.21-24
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• 2010

A new synthetic method for the formation of uniform $\alpha-Fe_2O_3$ nanoparticles was reported and their magnetic properties were investigated. The sonochemical synthesis and the subsequent take-off technique resulted in spherical shaped $\alpha-Fe_2O_3$ nanoparticles with an average diameter of 60 nm. The temperature- and applied magnetic field-dependent magnetization of the $\alpha-Fe_2O_3$ nanoparticles was explained by the sum of two contributions, i.e., the Morin transition and superparamagnetism, because the critical size for superparamagnetism was within the size variation of the nanoparticles.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.3
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• pp.17-29
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• 1995

Recently, neural network models have been employed as an alternative to regression analysis for point estimation or function fitting in various field. Thus far, however, no theoretical or empirical guides seem to exist for selecting the tool which the most suitable one for a specific function-fitting problem. In this paper, we evaluate performance of three major function-fitting techniques, regression analysis and two neural network models, back-propagation and linear-Hebbian-learning neural networks. The functions to be fitted are simple linear ones of a single independent variable. The factors considered are size of noise both in dependent and independent variables, portion of outliers, and size of the data. Based on comutational results performed in this study, some guidelines are suggested to choose the best technique that can be used for a specific problem concerned.