• 한국전산유체공학회:학술대회논문집
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• 2007.10a
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• pp.227-231
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• 2007

COMS (Communication, Ocean and Meteorological Satellite) is a geostationary satellite and has been developing by KARI for communication and ocean and meteorological observations. It will be launched by ARIANE 5. Ka-band components are installed on South panel, where single solar array wing is mounted. Radiators, embedded heat pipes, external heat pipe, insulation blankets and heaters are utilized for the thermal control of the satellite. The Ka-band payload section is divided several areas based on unit operating temperature in order to optimize radiator area and maximize heat rejection capability. Other equipment for sensors and bus are installed on North panel. The ocean and meteorological sensors are installed on optical benches on the top floor to decouple thermally from the satellite. During the transfer orbit operation, satellite will be under severe thermal environments due to low dissipation of components, satellite attitudes and LAE(Liquid Apogee Engine) firing. This paper presents temperature and heater power prediction and validation of thermal control design during transfer orbit operation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1134-1147
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• 2017

With the rise in popularity of photographic and video cameras, an increasing number of fields are now using thermal imaging cameras. One such application is in the diagnosis of breast cancer, as thermal imaging provides a low-cost and noninvasive method. Thermal imaging is particularly safe for pregnant women, and those with large, dense, or sensitive breasts. In addition, excessive doses of radiation, which may be used in traditional methods of breast cancer detection, can increase the risk of cancer. This paper presents one method of breast cancer detection. Breast images were taken using a thermal camera, with preliminary experiments conducted on Cambodian women. Then the experimental results were analyzed and compared using Shannon entropy and logistic regression.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.75-80
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• 1999

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcome limitation of accuracy in the linear regression model or the engineering judgment model. And this model is compared with the engineering judgment model. It is not necessary complex process such like multi-regression analysis of the engineering judgment model. A fuzzy model does not need to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Like a regression model, this model can be applied to any machine, but it delivers greater accuracy and robustness.

• Journal of Institute of Convergence Technology
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• v.8 no.1
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• pp.21-25
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• 2018

We developed nano-porous $TiO_2-SiO_2$ composites (commercial name : PTI, porous titania insulator) with low thermal conductivity as thermal insulating material as well as function of photocatalyst. The objectives of this paper are, firstly, to evaluate of the thermal conductivity of the PTI powder in the temperature range from -160 to $250^{\circ}C$, secondly to evaluate of thermal conductivities of insulation materials that is applied PTI powder. The structure of the PTI powder that has the pores size of 20-30 nm and the particle diameter of 2-10 nm. The PTI had a high surface area of $400m^2/g$ and a mean pore size of $45{\AA}$, which was fairly uniform. The thermal conductivity was measured by GHP(guarded hot plate) method and HFM(heat flux method). The PTI structure is a three-dimensional network nano-structures composed by a pearl-necklace that involved a precious stone in the center of the necklace. The thermal conductivities of PTI-PX powder by the GHP and HFM were 0.0366 W/m.K, 0.0314 W/m.K at $20^{\circ}C$, respectively. This is similar to values that are proportional to the square of the absolute temperature of the thermal conductivity of static air. The thermal conductivities of insulating sheets coated with PTI powder were similar results with that of the PTI powder.

• Journal of Adhesion and Interface
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• v.7 no.4
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• pp.32-38
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• 2006

A series of organic-inorganic hybrids, PCL/EP/$SiO_2$, involving epoxy resin and triethoxysilane-terminated polycaprolactone elastomer (PCL-TESi) were prepared via polymerization of diglycidyl ether of bisphenol A (DGEBA) with amine curing agent KB-2 and sol-gel process of PCL-TESi. The curing reactions were started from the initially homogeneous mixture of DGEBA, KB-2 and the PCL-TESi. The organicinorganic hybrids containing up to 4.95% (wt) of $SiO_2$ were obtained and characterized by FT-IR, transmission electron microscopy (TEM), differential scanning calorimetry (DSC) and thermogravimetry analysis (TGA). It was experimentally shown that the swelling property in toluene, morphologies and thermal properties of the resulting hybrids were quite dependent on the contents of $SiO_2$. The crosslink network density decreases with increasing of the PCL-TESi. And in TEM, the phase separated morphology of these hybrids was found, which resulted from the coagulation of Si-O-Si networks resulting from $-Si(OC_2H_5)_3$ of PCL-TESi self-curing by hydrolytic silanol condensation, with the advancement of the curing reaction in the modified epoxy resin systems. Meanwhile, the change of the $SiO_2$ content made the morphologies changed from aggregated particles of Si-O-Si in the hybrid to nanocluster of interconnected Si-O-Si particles, then to aggregated Si-O-Si dispersing in the continuous cured epoxy phase again, and last to co-continuous interpenetrating network. The glass transition behavior of the hybrid material was cooperative motion of large chain segments, which were hindered by the inorganic Si-O-Si network. And in TG analysis, the characteristic temperature at 5% of weight loss was evidently increased from $120.5^{\circ}C$ of pure cured epoxy to $277.6^{\circ}C$ of 3.84% (wt) of $SiO_2$ modified epoxy due to the existence of Si-O-Si when PCL-TESi was added in the hybrid.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.164-170
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• 2012

A Virtual Reality Modeling Language (VRML) database access in remote virtual reality control platform for dyeing enterprise $MiWi^{TM}$ thermal sensor network is presented in this paper. The VRML-ASP framework is introduced for 3D real-time data plotting in this application. The activities of thermal sensor nodes and sensor area are analyzed. The database access framework is optimized for $MiWi^{TM}$ wireless sensor networks. The experimental results show that VRML-ASP database access framework could be a reliable and competitive data-manage candidate for targeted virtual reality remote industrial visualization application.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.502-508
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• 2012

Heliostat, as a concentrator to reflect the incident solar energy to the receiver, is the most important system in the tower-type solar thermal power plant since it determines the efficiency and ultimately the overall performance of solar thermal power plant. Thus, a good sun tracking ability as well as a good optical property of it are required. Heliostat sun tracking system uses usually an open loop control system. Thus the sun tracking error caused by heliostat's geometrical error, optical error and computational error cannot be compensated. Recently use of sun tracking error model to compensate the sun tracking error has been proposed, where the error model is obtained from the measured ones. This work is a development of heliostat sun tracking error measurement and compensation method using BCS (Beam Characterization System). We first developed an image processing system to measure the sun tracking error optically. Then the measured error is modeled in linear polynomial form and neural network form trained by the extended Kalman filter respectively. Finally error models are used to compensate the sun tracking error. We also developed the necessary image processing algorithms so that the heliostat optical properties such as maximum heat flux intensity, heat flux distribution and total reflected heat energy could be analyzed. Experimentally obtained data shows that the heliostat sun tracking accuracy could be dramatically improved using either linear polynomial type error model or neural network type error model. Neural network type error model is somewhat better in improving the sun tracking performance. Nevertheless, since the difference between two error models in compensation of sun tracking error is small, a linear error model is preferred in actual implementation due to its simplicity.

• Journal of the Korea Society for Simulation
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• v.29 no.3
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• pp.9-18
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• 2020

The development of a large-scale thermal power plant control simulator consists of water/steam systems, air/combustion systems, pulverizer systems and turbine/generator systems. Modeling is possible for all systems except mechanical turbines/generators. Currently, there have been attempts to develop neural network simulators for some systems of a boiler, but the development of simulator for the whole system has never been completed. In particular, autoTuning, one of the key technology developments of all power generation companies, is a technology that can be achieved only when modeling for all systems with high accuracy is completed. The simulation results show accuracy of 95 to 99% or more of the actual boiler system, so if the field PID controller is fitted to this simulator, it will be available for fault diagnosis or auto-tuning.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1302-1309
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• 2021

Recently, the Korean Government announced the Korean New Deal as a national development strategy to overcome the economic recession from the pandemic crisis and lead the global action against structural changes. In the Korean New Deal, the Green New Deal related with the energy aims to achieve net-zero emissions and accelerates the transition towards a low-carbon and green economy. To this end, the government plans to promote an increased use of renewable energy in the society at large. This paper introduces a binary power generation using unused low-grade thermal energy to accelerate the transition towards a low-carbon and green economy and examines a control system based on Neural Network which is capable maintenance at low-cost by an unmanned automated operation in actual power generation environment. It is expected that the realization of binary power generation accelerates introduction of renewable energy along with solar and wind power.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.557-560
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• 2021

In the face of the COVID-19 pandemic, the Korean Government announced the Korean New Deal as a national development strategy to overcome the economic recession from the pandemic crisis and lead the global action aginst sturctural changes. The Green New Deal related with the energy aims to achieve net-zero emissions and accelerates the transition towards a low-carbon and green economy. To this end, the government plans to promete an increased use of renewable energy in the the society at large. This paper introduces a compact-binary power plant using unused thermal energy and a control system based on Neural Network in order to accelerate the transition towards a low-carbon and green economy. It is expected that he compact-binary power plant accelerate introduction of renewable energy along with solar and wind power.