• 전기학회논문지P
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• 제63권4호
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• pp.327-332
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• 2014

In this paper, the temperature distribution according to the property change of the insulating oil of the power transformer and max temperature were predicted through the ductility interpretation which heat-flow is coupled. By using CFD (Computation Fluid Dynamics) for the interpretation, the temperature distribution of 154kV the class single phase power transformer was predicted. The power loss causing the temperature rise of the transformer was changed to the heat source and we used as the input value for the heat-flow analysis. The temperature distribution was predicted according to the change of the density, specific heat, thermal conductivity and viscosity, that is the ingredient having an effect on the temperature rise of the transformer oil. The mineral oil of 4 kinds used in domestic and international based on the interpreted result was selected and the temperature distribution according to each load and Hot Spot temperature was predicted.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제49권5호
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• pp.327-337
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• 2000

In this paper, the design sensitivity formula for the control of the transient temperature distribution is developed using the direct differentiation method, and used for the optimal design of induction heating coil position. The temperature distribution is calculated using the heat source of the induced eddy current and heat diffusion equation. The physical property variations of the workpiece depending on the temperature are considered. The eddy current distribution and the temperature distribution are calculated with the 2D finite element procedure. The adjoint variable technique is employed in expressing the design sensitivity. The goal of the design is to have the desired distribution of the temperature on a specific region of the sensitivity. The goal of the design is to have the desired distribution of the temperature on a specific region sensitivity. The goal of the design is to have the desired distribution of the temperature on a specific region of the workpiece. The numerical example shows that the proposed design sensitivity analysis for the control of the transient temperature distribution is very useful and practical in the optimal design of induction heating coils.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2008년도 하계학술발표대회 논문집
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• pp.484-492
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• 2008

Air Discharge pattern and even temperature distribution is critical for a successful lower temperature air distribution system, which would supply lower temperature air than normal HAVC system. Selection of appropriate diffuser is the most critical element in completing lower temperature system.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2000년도 추계학술대회 논문집
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• pp.387-390
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• 2000

The life of transformer is significantly dependent on the thermal behavior in windings. To analyse winding temperature rise, many transformer designer have calculated temperature distribution and hot spot point by finite element method(FEM). Recently, numerical analyses of transformer are studied for optimum design, that is electric field analysis, magnetic field, potential vibration, thermal distribution and thermal stress. Therefore design time and design cost are decreased by numerical analysis. In this paper, the temperature distribution and thermal stress analysis of 50kVA pole cast resin transformer for power distribution are investigated by FEM program. The temperature change according to load rates of transformer also have been investigated. We have carried out temperature rise test and test results are compared with simulation data.

• 한국자기학회:학술대회 개요집
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• 한국자기학회 2012년도 자성 및 자성재료 국제학술대회
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• pp.104-105
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• 2012

The temperature dependence of the effective magnetic anisotropy constant K(T) of ferrite nanoparticles is obtained based on the measurements of SQUID magnetometry. For this end, a very simple but intuitive and direct method for determining the temperature dependence of anisotropy constant K(T) in nanoparticles is introduced in this study. The anisotropy constant at a given temperature is determined by associating the particle size distribution f(r) with the anisotropy energy barrier distribution $f_A(T)$. In order to estimate the particle size distribution f(r), the first quadrant part of the hysteresis loop is fitted to the classical Langevin function weight-averaged with the log?normal distribution, slightly modified from the original Chantrell's distribution function. In order to get an anisotropy energy barrier distribution $f_A(T)$, the temperature dependence of magnetization decay $M_{TD}$ of the sample is measured. For this measurement, the sample is cooled from room temperature to 5 K in a magnetic field of 100 G. Then the applied field is turned off and the remanent magnetization is measured on stepwise increasing the temperature. And the energy barrier distribution $f_A(T)$ is obtained by differentiating the magnetization decay curve at any temperature. It decreases with increasing temperature and finally vanishes when all the particles in the sample are unblocked. As a next step, a relation between r and $T_B$ is determined from the particle size distribution f(r) and the anisotropy energy barrier distribution $f_A(T)$. Under the simple assumption that the superparamagnetic fraction of cumulative area in particle size distribution at a temperature is equal to the fraction of anisotropy energy barrier overcome at that temperature in the anisotropy energy barrier distribution, we can get a relation between r and $T_B$, from which the temperature dependence of the magnetic anisotropy constant was determined, as is represented in the inset of Fig. 1. Substituting the values of r and $T_B$ into the $N{\acute{e}}el$-Arrhenius equation with the attempt time fixed to $10^{-9}s$ and measuring time being 100 s which is suitable for conventional magnetic measurement, the anisotropy constant K(T) is estimated as a function of temperature (Fig. 1). As an example, the resultant effective magnetic anisotropy constant K(T) of manganese ferrite decreases with increasing temperature from $8.5{\times}10^4J/m^3$ at 5 K to $0.35{\times}10^4J/m^3$ at 125 K. The reported value for K in the literatures is $0.25{\times}10^4J/m^3$. The anisotropy constant at low temperature region is far more than one order of magnitude larger than that at 125 K, indicative of the effects of inter?particle interaction, which is more pronounced for smaller particles.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 2000년도 제31회 춘계학술대회
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• pp.251-257
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• 2000

A numerical simulation of the temperature rise for sliding surface in dry contact is based on Jaeger's formula combined with a calculated heat input. A gear tooth temperature analysis was performed. The pressure distribution has the Hertzian pressure distribution on the heat source. The heat partition factor is calculated along line of action. A Temperature distribution of tooth surface is calculated about before and after profile modification. A Temperature of addendum and deddendum in modified gear have reduced.

• 한국자동차공학회논문집
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• 제10권4호
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• pp.69-76
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• 2002

The aim of this study is to provide fundamental informations that make it possible to use a cool stream and a hot stream simultaneously. We changed the pressure of compressed air that flows into a tube, the inner diameter of orifice that a cold stream exits, and the mass flow rate ratio. And in each case, we measured the temperature of a cold stream and a hot stream in each exit of a tube. Also we measured the axial and the radial temperature distribution in internal spare of a tube. From the study, fellowing conclusive remarks 7an be made. First, As the number of nozzles increase, separation point move into the hot exit. Second, When we use guide vane type nozzle, the axial temperature distribution constant over the 0.75 of air mass flow rate radio. Third, When we use Spiral type nozzle, axial and radial temperature distribution in the inner space is higher than another nozzle. Fourth, Axial and radial temperature distribution in the inner space vortex-tube is determined by separation point. And separation point is moved by changing of air mass flow rate ratio. At last, A heating apparatus is possible far vortex-tube to use.

• 전기학회논문지P
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• 제62권1호
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• pp.6-11
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• 2013

In this paper, the temperature characteristics of mold transformer for the distribution power system have been analyzed by using computational fluid dynamics(CFD). The model has been modeled by coil, cores, insulating materials and frames about 3MVA grade mold transformer and analyzed the temperature distribution of the structure with a heat fluid. The fluid, which is incompressible ideal gas, is analyzed as a turbulent flow phenomenon on the assumption that it is natural cooling of transformer cooling system. Through this study, by examining the temperature distribution and hot-spot of the structure field of the mold transformer, cooling design and temperature distribution information, which are demanded for designing are estimated.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.147-150
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• 1996

This paper describes controller design and implementation method for controlling the temperature distribution in a thermal stratified wind tunnel(TSWT) by using a neural network algorithm. It is impossible to derive a mathematical model of the relation between heat inputs and temperature outputs in the test section of the TSWT governed by a nonlinear turbulent flow. Thus inverse neural network models with a multi layer perceptron structure are used in a feedforward control loop and feedback control loop to generate an arbitrary temperature distribution in the test section of the TSWT.

• 산업기술연구
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• 제20권B호
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• pp.63-70
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• 2000

One aims to find out how the operation condition of secondary inlet angle effects the temperature distribution inside a small incinerator. A finite volume commercial code, PHONICS, is used to simulate the temperature field in an incinerator. The computational grid system is constructed by Multi-Block technique. The governing equations based on the curvilinear coordinates are used. Numerical experiments are done with the five variations of secondary air inlet. The temperature distribution is quantified by the statistical deviation of temperature in an incinerator. The computational analysis says that the certain angle of secondary air inlet could improve the uniformity of temperature distribution in an incinerator.