• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2534-2539
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• 2007

Launch vehicles are exposed to aerodynamic heating conditions while flying at high Mach numbers in the atmosphere. In this study aerodynamic heating test for fairing nose-cone was done using ATSF(Aerodynamic Thermal Simulation Facility) and Engineering Model for fairing. ATSF is a facility that can simulate given temperature profile using about 4,000 halogen heaters on fairing model. Aerodynamic heating profile is got from result of thermal analysis using MINIVER, Thermal Desktop and SINDA/FLUINT. After aerodynamic heat test, it is found that initial temperature of fairing inner surface and thickness of BMS has important effects on temperature of fairing inner surface. Also it is confirmed that maximum temperature of fairing nose-cone inner surface during flight is lower than allowable temperature limit. Later, thermal correlation between thermal analysis and experimental results will be done using aerodynamic heating test result

• JSTS:Journal of Semiconductor Technology and Science
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• v.6 no.3
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• pp.206-209
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• 2006

This paper presents an analytical noise model for the drain thermal noise, the induced gate noise, and their correlation coefficient in deep-submicron MOSFETs, which is valid in both linear region and saturation region. The impedance field method was used to calculate the external drain thermal noise current. The effect of channel length modulation was included in the analytical equation. The noise behavior of MOSFETs with decreasing channel length was successfully predicted from our model.

• Bulletin of the Korean Chemical Society
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• v.12 no.3
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• pp.315-322
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• 1991

In a recent $paper^1$ we reported equilibrium (EMD) and non-equilibrium (NEMD) molecular dynamics simulations of liquid argon using the Green-Kubo relations and NEMD algorithms to calculate the thermal transport coefficients-the self-diffusion coefficient, shear viscosity, and thermal conductivity. The overall agreement with experimental data is quite good. In this paper the same technique is applied to calculate the thermal transport coefficients of liquid water at 298.15 K and 1 atm using TIP4P model for the interaction between water molecules. The EMD results show difficulty to apply the Green-Kubo relations since the time-correlation functions of liquid water are oscillating and not decaying rapidly enough except the velocity auto-correlation function. The NEMD results are found to be within approximately ${\pm}$30-40% error bars, which makes it possible to apply the NEMD technique to other molecular liquids.

• Nuclear Engineering and Technology
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• v.27 no.4
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• pp.518-531
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• 1995

A study has been Peformed to investigate the thermal margin increase by replacing the single-channel analysis model with a multichannel analysis model. h new critical heat flux(CHF) correlation, which is applicable to a 17$\times$17 Korean Fuel Assembly(KOFA)-loaded core, was developed on the basis of the local conditions predicted by the subchannel analysis code, TORC. The hot sub-channel analysis was carried out by using one-stage analysis methodology with a prescribed nodal layout of the core. The result of the analysis shooed that more than 5％ of the thermal margin can be recovered by introducing the TORC/KRB-1 system(multichannel analysis model) instead of the PUMA/ERB-2 system(single-channel anal)sis model). The thermal margin increase was attributed not only to the effect of the local thermal hydraulic conditions in the hot subchannel predicted by the code, but also to the effect of the characteristics of the CHF correlation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.12
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• pp.1232-1239
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• 2010

A high-resolution electro-optical camera (EOS-C Ver.3.0), the mission payload of an Earth observation satellite, is under development in Satrec Initiative. We designed this system to give improved thermal performance compared with the EOS-C Ver.2.0 which is the main payload of DubaiSat-1 by optimizing the active and passive thermal control design. We developed the Structural-Thermal Model (STM) and verified the design margin by performing the qualification level thermal vacuum test. We also conducted the verification of its Thermal Mathematical Model (TMM) through the thermal balance test. As a result, it was confirmed that TMM faithfully represents the thermal characteristics of the EOS-C Ver.3.0.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.10
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• pp.729-737
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• 2022

Melting and icing process of the PCMTCU(Phase Change Material Thermal Control Unit) installed on the NEXTSat-2, which is scheduled to be launched in the second half, was investigated through the results of satellite-level TVT(Thermal Vacuum Test). As a result of the test, it was confirmed that the latent heat of PCM contributes to the temperature stabilization of the heating components. The thermal model for numerical analysis of the PCMTCU was correlated to acquire a reasonable degree of accuracy using the collected temperature measurements during TVT. The periodic temperature variation of the PCMTCU in normal on-orbit operation was predicted with the correlated thermal model, and the quantitative contribution of the PCM on the thermal energy management was evaluated with the liquid fraction. It will receive flight telemetry from the NEXTSat-2 after the launch, and complete the space verification of the PCMTCU.

• 한국태양에너지학회:학술대회논문집
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• 2009.11a
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• pp.15-20
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• 2009

The purpose of this study is to develop of portable thermal comfort measurement tool for elderly. Using prediction expression of thermal comfort for elderly which derived at previous study, a field studies were conducted. The objects of this survey are old persons over 60 years old and total 296 (male:111 persons, female:145 persons) persons were measured. The actual thermal sensation was compared with predicted thermal sensation calculated with PMV model, and the results shows that there were no correlation between them. Also, appling cheek temperature and hand temperature were useful to predict thermal sensation of elderly people. Especially, predicted thermal sensation using cheek temperature were closely connected with actual thermal sensation of elderly and presented most similar trend to actual thermal sensation.

• Korean Journal of Food Science and Technology
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• v.17 no.6
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• pp.482-489
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• 1985

The model foods similar to Korean typical foods were propared by combining moisture, protein and starch, and their thermal conductivities were investigated. Thermal conductivity of the model foods had a close relationship with food components such as moisture, protein and starch content. The interaction between the thermal conductivity and food components was not found. Thermal conductivity was proportionally increased as the moisture content increased, and thermal conductivity of starch food was lower than that of protein foods under the same level of moisture content of the model foods. The regression equation between thermal condutivity of the model foods. The regression equation between thermal conductivity of the model foods and moisture, protein and starch content at $20^{\circ}C$ was as follows; k = 0.00421M + 0.03152P + 0.05181. Correlation coefficient between calculated by above equation and measured values showed highly significant ($r=0.8418^{\ast}{\ast}$).

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2297-2310
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• 2022

A condensation heat transfer model is essential to accurately predict the performance of the passive containment cooling system (PCCS) during an accident in an advanced light water reactor. However, most of existing models tend to predict condensation heat transfer very well for a specific range of thermal-hydraulic conditions. In this study, a new correlation for condensation heat transfer coefficient (HTC) is presented using machine learning technique. To secure sufficient training data, a large number of pseudo data were produced by using ten existing condensation models. Then, a neural network model was developed, consisting of a fully connected layer and a convolutional neural network (CNN) algorithm, DenseNet. Based on the hold-out cross-validation, the neural network was trained and validated against the pseudo data. Thereafter, it was evaluated using the experimental data, which were not used for training. The machine learning model predicted better results than the existing models. It was also confirmed through a parametric study that the machine learning model presents continuous and physical HTCs for various thermal-hydraulic conditions. By reflecting the effects of individual variables obtained from the parametric analysis, a new correlation was proposed. It yielded better results for almost all experimental conditions than the ten existing models.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.8 no.2
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• pp.135-142
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• 2010

To obtain the input data for the design and long-term performance assessment of a high-level waste repository, the thermal conductivities of several granite rocks which were taken from the rock cores from the declined borehole were measured. The thermal conductivities of granite were measured under the different conditions of water content to investigate the effects of the water content on the thermal conductivity. A simple empirical correlation was proposed to predict the thermal conductivity of granite as a function of effective porosity and water content which can be measured with relative ease while neglecting the possible effects of mineralogy, structure and anisotropy. The correlation could predict the thermal conductivity of granite with the effective porosity below 2.7% from the KURT site with an estimated error below 10%.