• Transactions of Materials Processing
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• v.22 no.8
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• pp.450-455
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• 2013

In the current study, a new dynamic recrystallization model for predicting high temperature flow stress is developed based on a physical model and the mean field theory. In the model, the grain aggregate is assumed as a representative volume element to describe dynamic recrystallization. The flow stress and microstructure during dynamic recrystallization were calculated using three sub-models for work hardening, for nucleation and for growth. In the case of work hardening, a single parameter dislocation density model was used to calculate change of dislocation density and stress in the grains. For modeling nucleation, the nucleation criterion developed was based on the grain boundary bulge mechanism and a constant nucleation rate was assumed. Conventional rate theory was used for describing growth. The flow stress behavior of pure copper was investigated using the model and compared with experimental findings. Simulated results by cellular automata were used for validating the model.

• Journal of Power System Engineering
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• v.10 no.4
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• pp.133-138
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• 2006

Effective thermal conductivity of particulate reinforced composite has been predicted by Eshelby's equivalent inclusion method modified with Mori-Tanaka's mean field theory. The predicted results are compared with the experimental results from the literature. The model composite is polymer matrix filled with ceramic particles such as silica, alumina, and aluminum nitride. The preliminary examination by Eshelby type model shows that the predicted results are in good agreements with the experimental results for the composite with perfect spherical filler. As the shape of filler deviates from the perfect sphere, the predicted error increases. By using the aspect ratio of the filler deduced from the fixed filler volume fraction of 30%, the predicted results coincide well with the experimental results for filler volume fraction of 40% or less. Beyond this fraction, the predicted error increases rapidly. It can be finally concluded from the study that Eshelby type model can be applied to predict the thermal conductivity of the particulate composite with filler volume fraction less than 40%.

• Bulletin of the Korean Chemical Society
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• v.12 no.2
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• pp.170-177
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• 1991

A lattice mean field theory is developed to investigate the conformational properties of monolayer amphiphiles at the air-water interface. By generalizing Dill and Cantor's method and by extending Whittington's recurrence equation, we derive the supermatrix recurrence equation which is applied to calculation of various segment density profiles and order parameter, etc. In deriving the equation, we incorporated the chain stiffness effect and the chain connectivity which are distinguished features of linear chain molecule. Our result shows that, as the surface coverage $\sigma$ increases the chain ordering process with respect to vertical axis of the lattice system becomes dominant.

• The Korean Journal of Rheology
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• v.11 no.2
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• pp.128-134
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• 1999

Rheological characterization was examined for two different types of magenetic particle (rod-like $\gamma$-$Fe_{2}O_{3}$, $CrO_2$ )suspension in this study. The measured suspension viscosity (viscosity vs. concentration or shear rate) is used to obtain the dependence of viscous energy dissipation on the microstructural states of magnetic particle dispersions as well as the microstructural shape effects which are related to magnetic particle orientation. The empirical formulas from mean field theory and the Mooney equation are used to relate suspension viscosity to particle concentration. Intrinsic viscosities of these two different types of rod-like magnetic particle suspensions are found to exceed the prediction of hydrodynamic theory for dilute suspensions and support the existence of flocs containing significant amounts of immobilized suspending medium due to native attraction forces among particles in the microstructures.

• Composites Research
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• v.18 no.5
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• pp.21-26
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• 2005

The validity of Eshelby-type model with Mori-Tanaka's mean field theory to predict the effective material properties of composites have been investigated in terms of filler size and its arrangement. The 2-dimensional plate composites including constant volume fraction of fillers are used as the model composite for the analytical studies, where the filler size and its arrangement are considered as parameters. The exact effective material properties of the composites are computed by finite element analysis(FEA), which are compared with effective material properties from the Eshelby-type model. Although the fillers are periodically or randomly arranged, the average Young's moduli by Eshelby-type model and FEA are in good agreement, specially for the ratio of specimen size to filler size being smaller than 0.03. However, Poisson's ratio of the composite by the Eshelby-type model is overestimated by $20\%$.

• Composites Research
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• v.17 no.5
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• pp.54-60
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• 2004

A new three-dimensional model for predicting the relationship between the prestrain of the composite and the amount of phase transformation of shape memory alloy inducing shape memory effect has been proposed by using Eshelby's equivalent inclusion method with Mori-Tanaka's mean field theory. The model composite is aluminum matrix reinforced with short TiNi fiber shape memory alloy, where the matrix is work-hardening material of power-law type. The analytical results predicted by the current model show that most of the prestrain is induced by the plastic deformation of the matrix, except the small prestrain region. The strengthening mechanism of the composite by the shape memory effect should be explained by excluding its increase of yield stress due to the work-hardening effect of the matrix.

• Journal of the Korean Solar Energy Society
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• v.25 no.1
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• pp.79-86
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• 2005

The external conditions for estimating dynamic wind loads of wind turbines, such as the turbulence, the extreme wind, the mean velocity gradients and the flow angles, are simulated over GangWon Wind Energy Test Field placed in one of the most complex terrain in Korea. Reference meteorological data has been gathered at a height of 30m from 2003 to 2004 with a ultrasonic anemometer. The absolute value of the spectral energy are simulated and the verification of this prediction has been carried out with comparing to the experimental data. The most desirable place for constructing new wind turbine are resulted as Point 2 and Point 3 due to the lower value of Turbulence Intensity and the higher value of wind resource relatively.

• Computational Structural Engineering
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• v.10 no.1
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• pp.173-183
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• 1997

In this paper a method is suggested for the probabilistic analysis of impact buckling failure time of cylinder with random axisymmetric geometric imperfection under axial impact. Failure is assumed as axisymmetric radial deformation exceeds the given criteria for the first time. For the generation of random geometric initial imperfection, random field theory by mean function and autocorrelation function of geometric imperfection is used. Suggested method is useful for the treatment of the randomness of realistic geometric imperfection and can be used for the structural safety analysis of cylinder considering its effect.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.348-353
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• 2013

Recently, control theory including stochastic optimal control and various machine-learning-based artificial intelligence methods have become major tools in the field of financial engineering. In this paper, we briefly review some recent papers utilizing stochastic optimal control theory in the fields of the pair trading for mean-reverting markets and the trend-following strategy, and consider a couple of strategies utilizing both stochastic optimal control theory and machine learning methods to acquire more flexible and accessible tools. Illustrative simulations show that the considered strategies can yield encouraging results when applied to a set of real financial market data.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.6
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• pp.61-71
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• 2017

The tracer gas method has an advantage that can estimate total and local ventilation rate by tracing air flow. However, the field measurement using tracer gas has disadvantages such as danger, inefficiency, and high cost. Therefore, the aim of this study was to evaluate ventilation rate in pig house by using the thermal distribution data rather than tracer gas. Especially, LMA (Local Mean Age), which is an index based on the age of air theory, was used to evaluate the ventilation rate in pig house. Firstly, the field experiment was conducted to measure micro-climate inside pig house, such as the air temperature, $CO_2$ concentration and wind velocity. And then, LMA was calculated based on the decay of $CO_2$ concentration and air temperature, respectively. This study compared between LMA determined by $CO_2$ concentration and air temperature; the average error and root mean square error were 3.76 s and 5.34 s. From these results, it was determined that thermal distribution data could be used for estimation of LMA. Finally, CFD (Computational fluid dynamic) model was validated using LMA and wind velocity. The mesh size was designed to be 0.1 m based on the grid independence test, and the Standard $k-{\omega}$ model was eventually chosen as the proper turbulence model. The developed CFD model was highly appropriate for evaluating the ventilation rate in pig house.