• 한국태양에너지학회:학술대회논문집
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• 2008.11a
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• pp.202-207
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• 2008

Measures for coping with energy shortage are being sought all over the world. Following such a phenomenon, effort to use less energy in the design of buildings and equipment are being conducted. In particular, a program to evaluate the performance of a building comes into the spotlight. However. indispensable standard wether data to estimate the exact energy consumption of a building is currently unprepared. Thus, after appling standard weather data for four weather factors which were used in previous researches to Visual DOE 4.0, we compared it with the result of the existing data and evaluated them. For the monthly cooling and heating load of our target building, we used revised data for June, July, August, and September during which cooling load is applied. When not the existing data but the revised data was used, the research shows that an average of 14.9% increased in June, August, and September except for July. Also, in a case of heating load, the result by the revised data shows a reduction of an average of 11.9% from October to April during which heating load is applied. In particular, the heating loads of all months for which the revised data was used were more low than those of the existing data. In the maximum cooling and heating load according to load factors, the loads by residents and illumination for which the revised data was used were the same as those of the existing data, but the maximum cooling loads used by the two data have a difference in structures such as walls and roofs. Through the above results, the research cannot clearly grasp which weather data influences the cooling and heating load of a building. However, in the maximum loads by the change of weather data in four factors (dry-bulb temperature, web-bulb temperature, cloud amount, and wind speed) among 14 weather factors, the research shows that 5.95% in cooling load and 27.56% in heating load increased, and these results cannot be ignored. In order to make weather data for Performing energy performance evaluation for future buildings, the flow of weather data for the Present and past should be obviously grasped.

• Applied Chemistry for Engineering
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• v.27 no.5
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• pp.516-520
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• 2016

Concentrated liquid detergents have 2~3 times higher surfactant contents [35~45% (w/w)] compared to those of normal type detergents. In general, a single surfactant forms a lyotropic liquid crystal (LC) phase when the concentration is in the region of 30~60% (w/w). Whereas the concentrated liquid detergent at about 40% (w/w) concentration in a mixed surfactant system shows an opaque appearance of gel or LC. In order to meet consumer needs and preference for product appearance, we applied hydrotropes and various surfactants systems in concentrated liquid detergents to obtain an opaque gel-phase and also a clear transparent phase at even below zero $^{\circ}C$ temperature. The more effective hydrotropes for making concentrated liquid detergents are 1,6-hexanediol, adipic acid and dipropylene glycol (DPG) which have two hydrophilic groups in both terminated positions. In order to prepare an excellent concentrated liquid detergent, good hydrotropes alongside secondary type surfactants like LAS and SAS were used. The formation of LC phase of concentrated liquid detergents at about 40% (w/w) concentration could be prevented by the use of both hydrotropes and secondary type surfactants. The result indicate that concentrated detergents having excellent low temperature stability and controlled viscosity can be prepared.

• Nuclear Engineering and Technology
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• v.48 no.1
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• pp.274-284
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• 2016

Purpose: The purpose of this work is to describe the spectrometric analysis of gaseous cloud formation over reactor mixed uranium-and-plutonium (UP) fuel $(U_{0.8}Pu_{0.2})O_2$ samples heated to a temperature $>2,000^{\circ}C$, and thus forecast and evaluate radiation hazards threatening humans who cope with the consequences of any accident at a fission reactor loaded by UP mixed oxide $(U_{0.8}Pu_{0.2})O_2$, such as a mixture of 80% U and 20% Pu in weight. Materials and methods: The UP nuclear fuel samples were heated up to a temperature of over $2,000^{\circ}C$ in a suitable assembly (apparatus) at out-of-pile experiments' implementation, the experimental in-depth study of metabolism of active materials in living organisms by means of artificial irradiation of pigs by plutonium. Spectrometric measurements were carried out on the different exposed organs and tissues of pigs for the further estimation of human internal exposure by nuclear materials released from the core of a fission reactor fueled with UP mixed oxide. Results: The main results of the research described are the following: (1) following the research on the influence of mixed fuel fission products (radioactive isotopes being formed during reactor operation as a result of nuclear decay of elements included into the fuel composition) on living organisms, the authors determined the quantities of plutonium dioxide ($PuO_2$) that penetrated into blood and lay in the pulmonary region, liver, skeleton and other tissues; and (2) experiments confirmed that the output speed of plutonium out of the basic precipitation locations is very small. On the strength of the experimental evidence, the authors suggest that the biological output of plutonium can be disregarded in the process of evaluation of the internal irradiation doses.

• Advances in Energy Research
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• v.1 no.2
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• pp.147-163
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• 2013

The world faces several issues of energy crisis and environmental deterioration due to over-dependence on single source of which is fossil fuel. Though, fuel is needed as ingredients for industrial development and growth of any country, however the fossil fuel which is a major source of energy for this purpose has always been terrifying thus the need for alternative and renewable energy sources. The search for alternative energy sources resulted into the acceptance of a biofuel as a reliable alternative energy source. This work presents the study of optimization of process of transesterification of vegetable oil to biodiesel using NaOH as catalyst. A $2^4$ factorial design method was employed to investigate the influence of ratio of oil to methanol, temperature, NaOH concentration, and transesterification time on the yield of biodiesel from vegetable oil. Low and high levels of the key factors considered were 4:1 and 6:1 mole ratio, 30 and $60^{\circ}C$ temperatures, 0.5 and 1.0 wt% catalyst concentration, and 30 and 60 min reaction time. Results obtained revealed that oil to methanol molar ratio of 6:1, tranesetrification temperature of $60^{\circ}C$, catalyst concentration of 1.0wt % and reaction time of 30 min are the best operating conditions for the optimum yield of biofuel from vegetable oil, with optimum yield of 95.8%. Results obtained on the characterizzation of the produced biodiesel indicate that the specific gravity, cloud point, flash point, sulphur content, viscosity, diesel index, centane number, acid value, free glycerine, total glycerine and total recovery are 0.8899, 4, 13, 0.0087%, 4.83, 25, 54.6. 0.228mgKOH/g, 0.018, 0.23% and 96% respectively. Results also indicate that the qualities of the biodiesel tested for are in conformity with the set standard. A model equation was developed based on the results obtained using a statistical tool. Analysis of variance (ANOVA) of data shows that mole ratio of ground nut oil to methanol and transesterification time have the most pronounced effect on the biodiesel yield with contributions of 55.06% and 9.22% respectively. It can be inferred from the results various conducted that vegetable oil locally produced from groundnut oil can be utilized as a feedstock for biodiesel production.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.275-285
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• 2017

National Meteorological Satellite Center(NMSC) has produced Sea Surface Temperature (SST) using Communication, Ocean, and Meteorological Satellite(COMS) data since April 2011. In this study, we have developed a new regional COMS SST algorithm optimized within the North-West Pacific Ocean area based on the Multi-Channel SST(MCSST) method and made a composite SST using polar orbit satellites as well as the COMS data. In order to retrieve the optimized SST at Northwest Pacific, we carried out a colocation process of COMS and in-situ buoy data to make coefficients of the MCSST algorithm through the new cloud masking including contaminant pixels and quality control processes of buoy data. And then, we have estimated the composite SST through the optimal interpolation method developed by National Institute of Meteorological Science(NIMS). We used four satellites SST data including COMS, NOAA-18/19(National Oceanic and Atmospheric Administration-18/19), and GCOM-W1(Global Change Observation Mission-Water 1). As a result, the root mean square error ofthe composite SST for the period of July 2012 to June 2013 was $0.95^{\circ}C$ in comparison with in-situ buoy data.

• Journal of the Korean earth science society
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• v.26 no.3
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• pp.283-296
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• 2005

The effect of ozone and surface temperature on the ozone band at $9.7{\mu}m$ has been investigated from radiative transfer theory together with observations in order to derive empirical methods for remotely sensing ground-ozone concentration. Simultaneous observations of satellite (MODIS Aqua; ECT 13:30) and ground-ozone at 79 stations have been used over the Seoul Metropolitan Area (SMA; 125.7-127.2 E, 37.2-37.7 N) during four ozone-warning days in the year 2003. Cloud effect on the band in the methods was filtered out based on synoptic observations. Upwelling radiance values at $9.6{\mu}m$ which have been estimated at the given ozone concentration of 327-391 DU depend on surface temperature (Ts) showing $5.52\~5.78Wm^{-2}sr^{-1}\;at\;Ts = 290 K,\;and\;9.00\~9.57Wm^{-2}sr^{-1}$ Ts = 325K. Thus, the partitioned contributions of ozone and temperature to intensity of ozone absorption band are $0.26Wm^{-1}sr^{-1}/64\;DU\;and\;0.31 Wm^{-2}sr^{-1}/35K$, respectively. Here the intensity which has been used to remotely detect ground-ozone concentration from infrared satellite measurement is defined as the difference in brightness temperature between $11{\mu} m\;and\;9.7{\mu}m (i.e.,\; T_{11-9.7})$. The methods in this study have been applied to estimate ground-ozone from MODIS data in cases that there are significant correlations between the band intensity and ground-ozone. The values of estimated ozone significantly correlate (0.49-0.63) with ground observations at a significance level of $1\%$. For the improved methods, further study may be required to use tropospheric ozone rather than ground-ozone, considering the variation stratospheric ozone.

• Journal of the Korean earth science society
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• v.37 no.7
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• pp.420-433
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• 2016

The purpose of this study is to improve the calibration matrixes of 2-D and 3-D convective rainfall rates (CRR) using the brightness temperature of the infrared $10.8{\mu}m$ channel (IR), the difference of brightness temperatures between infrared $10.8{\mu}m$ and vapor $6.7{\mu}m$ channels (IR-WV), and the normalized reflectance of the visible channel (VIS) from the COMS satellite and rainfall rate from the weather radar for the period of 75 rainy days from April 22, 2011 to October 22, 2011 in Korea. Especially, the rainfall rate data of the weather radar are used to validate the new 2-D and 3-DCRR calibration matrixes suitable for the Korean peninsula for the period of 24 rainy days in 2011. The 2D and 3D calibration matrixes provide the basic and maximum CRR values ($mm\;h^{-1}$) by multiplying the rain probability matrix, which is calculated by using the number of rainy and no-rainy pixels with associated 2-D (IR, IR-WV) and 3-D (IR, IR-WV, VIS) matrixes, by the mean and maximum rainfall rate matrixes, respectively, which is calculated by dividing the accumulated rainfall rate by the number of rainy pixels and by the product of the maximum rain rate for the calibration period by the number of rain occurrences. Finally, new 2-D and 3-D CRR calibration matrixes are obtained experimentally from the regression analysis of both basic and maximum rainfall rate matrixes. As a result, an area of rainfall rate more than 10 mm/h is magnified in the new ones as well as CRR is shown in lower class ranges in matrixes between IR brightness temperature and IR-WV brightness temperature difference than the existing ones. Accuracy and categorical statistics are computed for the data of CRR events occurred during the given period. The mean error (ME), mean absolute error (MAE), and root mean squire error (RMSE) in new 2-D and 3-D CRR calibrations led to smaller than in the existing ones, where false alarm ratio had decreased, probability of detection had increased a bit, and critical success index scores had improved. To take into account the strong rainfall rate in the weather events such as thunderstorms and typhoon, a moisture correction factor is corrected. This factor is defined as the product of the total precipitable waterby the relative humidity (PW RH), a mean value between surface and 500 hPa level, obtained from a numerical model or the COMS retrieval data. In this study, when the IR cloud top brightness temperature is lower than 210 K and the relative humidity is greater than 40%, the moisture correction factor is empirically scaled from 1.0 to 2.0 basing on PW RH values. Consequently, in applying to this factor in new 2D and 2D CRR calibrations, the ME, MAE, and RMSE are smaller than the new ones.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.2
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• pp.47-61
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• 2000

Agroclimatic zoning was done for paddy rice culture in North Korea based on a simulation experiment. Daily weather data for the experiment were generated by 3 steps consisting of spatial interpolation based on topoclimatological relationships, zonal summarization of grid cell values, and conversion of monthly climate data to daily weather data. Regression models for monthly climatological temperature estimation were derived from a statistical procedure using monthly averages of 51 standard weather stations in South and North Korea (1981-1994) and their spatial variables such as latitude, altitude, distance from the coast, sloping angle, and aspect-dependent field of view (openness). Selected models (0.4 to 1.6$^{\circ}C$ RMSE) were applied to the generation of monthly temperature surface over the entire North Korean territory on 1 km$\times$l km grid spacing. Monthly precipitation data were prepared by a procedure described in Yun (2000). Solar radiation data for 27 North Korean stations were reproduced by applying a relationship found in South Korea ([Solar Radiation, MJ m$^{-2}$ day$^{-1}$ ] =0.344 + 0.4756 [Extraterrestrial Solar Irradiance) + 0.0299 [Openness toward south, 0 - 255) - 1.307 [Cloud amount, 0 - 10) - 0.01 [Relative humidity, %), $r^2$=0.92, RMSE = 0.95 ). Monthly solar irradiance data of 27 points calculated from the reproduced data set were converted to 1 km$\times$1 km grid data by inverse distance weighted interpolation. The grid cell values of monthly temperature, solar radiation, and precipitation were summed up to represent corresponding county, which will serve as a land unit for the growth simulation. Finally, we randomly generated daily maximum and minimum temperature, solar irradiance and precipitation data for 30 years from the monthly climatic data for each county based on a statistical method suggested by Pickering et a1. (1994). CERES-rice, a rice growth simulation model, was tuned to accommodate agronomic characteristics of major North Korean cultivars based on observed phenological and yield data at two sites in South Korea during 1995~1998. Daily weather data were fed into the model to simulate the crop status at 183 counties in North Korea for 30 years. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to score the suitability of the county for paddy rice culture.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.931-946
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• 2017

The purpose of this study is to observe and analyze soil moisture conditions with high resolution and to evaluate its application feasibility to agriculture. For this purpose, we used three Landsat-8 OLI (Operational Land Imager)/TIRS (Thermal Infrared Sensor) optical and thermal infrared satellite images taken from May to June 2015, 2016, and 2017, including the rural areas of Jeollabuk-do, where 46% of agricultural areas are located. The soil moisture conditions at each date in the study area can be effectively obtained through the SPI (Standardized Precipitation Index)3 drought index, and each image has near normal, moderately wet, and moderately dry soil moisture conditions. The temperature vegetation dryness index (TVDI) was calculated to observe the soil moisture status from the Landsat-8 OLI/TIRS images with different soil moisture conditions and to compare and analyze the soil moisture conditions obtained from the SPI3 drought index. TVDI is estimated from the relationship between LST (Land Surface Temperature) and NDVI (Normalized Difference Vegetation Index) calculated from Landsat-8 OLI/TIRS satellite images. The maximum/minimum values of LST according to NDVI are extracted from the distribution of pixels in the feature space of LST-NDVI, and the Dry/Wet edges of LST according to NDVI can be determined by linear regression analysis. The TVDI value is obtained by calculating the ratio of the LST value between the two edges. We classified the relative soil moisture conditions from the TVDI values into five stages: very wet, wet, normal, dry, and very dry and compared to the soil moisture conditions obtained from SPI3. Due to the rice-planing season from May to June, 62% of the whole images were classified as wet and very wet due to paddy field areas which are the largest proportions in the image. Also, the pixels classified as normal were analyzed because of the influence of the field area in the image. The TVDI classification results for the whole image roughly corresponded to the SPI3 soil moisture condition, but they did not correspond to the subdivision results which are very dry, wet, and very wet. In addition, after extracting and classifying agricultural areas of paddy field and field, the paddy field area did not correspond to the SPI3 drought index in the very dry, normal and very wet classification results, and the field area did not correspond to the SPI3 drought index in the normal classification. This is considered to be a problem in Dry/Wet edge estimation due to outlier such as extremely dry bare soil and very wet paddy field area, water, cloud and mountain topography effects (shadow). However, in the agricultural area, especially the field area, in May to June, it was possible to effectively observe the soil moisture conditions as a subdivision. It is expected that the application of this method will be possible by observing the temporal and spatial changes of the soil moisture status in the agricultural area using the optical satellite with high spatial resolution and forecasting the agricultural production.

• Journal of the Korean earth science society
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• v.27 no.4
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• pp.450-463
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• 2006

Seasonal threshold values for fog detection over the ten airport areas within the Korean Peninsula have been derived from the data of polar-orbit Aqua/Terra MODIS and geostationary GOES-9 during a two years. The values are obtained from reflectance at $0.65{\mu}m\;(R_{0.65})$ and the difference in brightness temperature between $3.7{\mu}m\;and\;11{\mu}m\;(T_{3.7-11})$. In order to examine the discrepancy between the threshold values of two kinds of satellites, the following four parameters have been analyzed under the condition of daytime/nighttime and fog/clear-sky, utilizing their simultaneous observations over the Seoul metropolitan area: brightness temperature at $3.7{\mu}m$, the temperature at $11{\mu}m,\;the\;T_{3.7-11}$ for day and night, and the $R_{0.65}$ for daytime. The parameters show significant correlations (r<0.5) in spatial distribution between the two kinds of satellites. The discrepancy between their infrared thresholds is mainly due to the disagreement in their spatial resolutions and spectral bands, particularly at $3.7{\mu}m$. Fog detection from GOES-9 over the nine airport areas except the Cheongju airport has revealed accuracy of 60% in the daytime and 70% in the nighttime, based on statistical verification. The accuracy decreases in foggy cases with twilight, precipitation, short persistence, or the higher cloud above fog. The sensitivity of radiance and reflectance with wavelength has been analyzed in numerical experiments with respect to various meteorological conditions to investigate optical characteristics of the three channels.