• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.247-248
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• 2012

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.2
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• pp.181-194
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• 2015

Spatial-temporal meteorological features of the Ulsan metropolitan region (UMR) were analyzed using observations and high-resolution numerical modeling. Long-term trend analysis (1970~2013) showed a significant increase of $0.033^{\circ}Cyr^{-1}$ in the 5-year moving average temperature, although detailed short-term features varied, whereas wind speed and relative humidity over the same period displayed clear decreases of $-0.007ms^{-1}$ and $-0.29%yr^{-1}$, respectively. These trends indicate the effects of regional climate change and urbanization in the UMR. Seasonal variations averaged for the most recent three years, 2011~2013, showed that temperatures in three different regions (urban/industrial, suburban, coastal areas) of the UMR had similar seasonality, but significant differences among them were observed for a certain season. Urban and industrial complex regions were characterized by relatively higher temperatures with large differences (max.: $3.6^{\circ}C$) from that in the coastal area in summer. For wind speed, strong values in the range from 3.3 to $3.9ms^{-1}$ occurred in the coastal areas, with large differences clearly shown between the three regions in September and October. Diurnal variations of temperature were characterized by pronounced differences during the daytime (in summer) or nighttime (in winter) between the three regions. Results from the WRF modeling performed for four months of 2012 showed large variations in gridaverage temperature and winds in the UMR, which displayed significant changes by season. Especially, a clear temperature rise in the urban center was identified in July ($0.6^{\circ}C$ higher than nearby urban areas), and overall, relatively weak winds were simulated over urban and inland suburban regions in all seasons.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.12
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• pp.24-29
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• 2009

In order to model the high temperature dependence of the cutoff frequency $f_T$ in $0.18{\mu}m$ deep n-well isolated bulk NMOSFET, high temperature data of electron velocity of bulk MOSFETs from $30^{\circ}C$ to $250^{\circ}C$ are obtained by an accurate RF extraction method using measured S-parameters. From these data, an improved temperature-dependent electron velocity equation is developed and implemented in a BSIM3v3 SPICE model to eliminate modeling error of a conventional one in the high temperature range. Better agreement with measured $f_T$ data from $30^{\circ}C$ to $250^{\circ}C$ are achieved by using the SPICE model with the improved equation rather than the conventional one, verifying its accuracy of the improved one.

• The Korean Journal of Ceramics
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• v.4 no.2
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• pp.136-140
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• 1998

This work demonstrates a method for modeling of electrical conductivity in high-temperature proton-conducting oxides. Total conductivity was calculated assuming that it comprises partial conductivities contributed by protons, oxygen ions and electron holes. From the polt $\sigma_{tot}$ vs. $po_2\;{1/4}$ in wet atmosphere, thermodynamic and kinetic parameters were obtained representing transport properties such as concentration and mobility of the charge-carrying defects. The formulas for the calculation of partial conduction were derived based on the defect structure of HTPCs. Illustrative calculation were made for $SrCe_{0.95}Yb_{0.05}O_{2.975}$ system.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.37-39
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• 2003

This paper Presents an effective modeling scheme of high temperature superconducting transformer. So far there were numerical modeling and designs for conventional transformers for various applications. Recently, the interest and the R&D in superconducting technology and devices such as superconducting generator, motor, cable, fault current limiter and transformer have been increased gradually. With those interests, this paper proposes a simulation model of high temperature superconducting transformer using PSCAD/EMTDC, which can be applied to the utility network simulation readily under various system conditions.

• Journal of Environmental Science International
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• v.9 no.1
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• pp.57-64
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• 2000

The sensitivity analysis of two short-term models (ISCST3, INPUFF2.5) is performed to improve the model accuracy. It appears that the sensitivities on the changes of wind speed, stack height and stack inner diameter in the near distance from source, stability and mixing height in the remote distance form source, are significant. Also the gas exit velocity, stack inner diameter, gas temperature and air temperature which affect the plume rise have some effects on the concentration values of each model within the downwind distance where final plume rise is determined. And in modeling for the atmospheric dispersion of point pollutant source INPUFF2.5 can calculate amount, trajectory of puff and concentration versus time at each receptors. So, it is compatible to analyze distribution of point pollutants concentration at modeling area.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.473-473
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• 2011

Group method of data handling neural networks model (GMDH-NNM) is used to estimate daily reference evapotranspiration (ETo) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$), mean relative humidity ($RH_{mean}$) and sunshine duration (SD). And, for the performances of GMDH-NNM, it consists of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of GMDH-NNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily ETo data using GMDH-NNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as ETo modeling can be generalized using GMDH-NNM.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.600-601
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• 2010

This paper presents the superheater dynamic modeling and parameter estimation for the thermal plant boiler. The temperature control is closely related to the power plant efficiency and boiler life. The dynamic modeling of the superheater and desuperheater is essentially needed and developed by using the heat balance principle. The simulated model outputs are well matched with the actual ones. It is expected that the proposed model is useful for the temperature controller design.

• Journal of the Microelectronics and Packaging Society
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• v.20 no.3
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• pp.7-10
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• 2013

This study presents an approach to predict insulation resistance failure of multilayer ceramic capacitors (MLCCs) using non-linear modeling. A capacitance aging model created by non-linear modeling allowed for the prediction of insulation resistance failure. The MLCC data tested under temperature-humidity-bias testing conditions showed that a change in capacitance, when measured against a capacitance aging model, was able to provide a prediction of insulation resistance failure.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.1
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• pp.20-27
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• 2013

Numerical modeling of $CO_2$ water heater was conducted prior to optimal design of medium and large sized $CO_2$ water heater, and the experimental test with small sized $CO_2$ water heater having heat capacity of 4 kW was completed to verify the present numerical model. The present model estimated the experimental data of COP(coefficient of performance), heating capacity, and the hot water outlet temperature within the range of 3% to 8% of mean deviation. As increase of EEV(electric expansion valve) opening area, decreasing of heating capacity and the hot water outlet temperature, and increasing of COP were found in both experimental and numerical investigation.