• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.103-103
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• 2019

본 연구에서는 Terra MODIS 위성영상과 Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) 모형을 이용하여 2012년부터 2017년까지 한반도 전국의 증발산량을 산정하고 플럭스 타워 실측 증발산량과 비교하였다. METRIC은 전 세계에 널리 적용된 바 있는 에너지 수지 기반의 Surface Energy Balance Algorithm for Land (SEBAL) 모형의 개념과 기술을 기반으로 현열(Sensible Heat Flux) 추정 모듈을 개선한 모형이다. 본 연구에서 METRIC 모형은 기존 C#으로 개발되어 있던 SEBAL 코드에서 현열 추정 모듈을 수정하였고 연산 속도 개선을 위해 Python으로 재작성하였다. METRIC 모형의 위성 자료로 Terra MODIS 위성의 MOD13A2(16day, 1km) NDVI, MOD11A1(Daily, 1km) Land Surface Temperature (LST) 및 MCD43A3(Daily, 500m) Albedo를 구축하였으며 500m 공간해상도의 Albedo는 1000m 해상도로 resample하여 활용하였다. 기상자료는 기상청 기상관측소의 풍속, 풍속측정높이, 습도, 10분 간격 이슬점 온도, 일사량 자료를 위성 자료와 같은 공간해상도로 내삽(Interpolation)하여 구축하였다. 모형결과 검증을 위해 국내 플럭스 타워 (설마천, 청미천, 덕유산) 증발산량 관측 자료와의 결정계수(Coefficient of determination, $R^2$), RMSE(Root mean square error) relative RMSE (RMSE%), Nash-Sutcliffe efficiency (NSE) 및 IOA(Index of Agreement)를 산정하고, 기존 SEBAL 모형 결과와의 비교를 통해 본 모형의 개선점을 보이고자 한다.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4022-4032
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• 2021

In this study, machine learning (ML) techniques were used to model surveillance test data of nuclear power plants from an international database of the ASTM E10.02 committee. Regression modeling was conducted using various techniques, including Cubist, XGBoost, and a support vector machine. The root mean square deviation of each ML model for the baseline dataset was less than that of the ASTM E900-15 nonlinear regression model. With respect to the interpolation, the ML methods provided excellent predictions with relatively few computations when applied to the given data range. The effect of the explanatory variables on the transition temperature shift (TTS) for the ML methods was analyzed, and the trends were slightly different from those for the ASTM E900-15 model. ML methods showed some weakness in the extrapolation of the fluence in comparison to the ASTM E900-15, while the Cubist method achieved an extrapolation to a certain extent. To achieve a more reliable prediction of the TTS, it was confirmed that advanced techniques should be considered for extrapolation when applying ML modeling.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5877-5884
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• 2014

Recently, abnormally cold weather has been reported more frequently in winter due to the climate change and abnormal weather changes. On the other hand, the heating capacity of a railcar may be not enough to warm the cabin under severe cold climatic conditions, which is one of the reasons for the passengers' complaints about heating. In this study, the effects of ambient temperature and heater power on the cabin temperature was investigated to obtain the minimum ambient temperature for the tested railcar. The test railcar was placed in a large-climatic chamber, and various ambient temperature conditions were simulated. The effects of the heater output were investigated by monitoring the cabin temperature under a range of heater output conditions. The mean cabin temperature was $14.0^{\circ}C$, which was far lower than the required minimum temperature of $18^{\circ}C$, under a $-10^{\circ}C$ ambient temperature condition with the maximum heat power. When the ambient temperature was set to $0^{\circ}C$ and $10^{\circ}C$, the maximum achievable cabin temperature was $26.1^{\circ}C$ and $34.0^{\circ}C$. Through calculations using the interpolation method, the minimum ambient temperature to maintain an $18^{\circ}C$ cabin temperature was $-6.7^{\circ}C$ for this car. The vertical temperature difference was higher with a higher power output and higher ambient temperature. The maximum vertical temperature difference was higher than $10^{\circ}C$ in some cases. However, the horizontal temperature difference vs. low temperature (< $2^{\circ}C$) was independent of the power output and ambient temperature. As a result, it is very important to reduce the vertical temperature difference to achieve good heating performance.

• Ocean and Polar Research
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• v.42 no.3
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• pp.179-194
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• 2020

The present study aims to evaluate the effects of satellite-based SST (OSTIA) assimilation on a regional ocean circulation model for the Yellow and East China Seas (YECS), using three different assimilation methods: the Ensemble Optimal Interpolation (EnOI), Ensemble Kalman Filter (EnKF), and 4-Dimensional Variational (4DVAR) techniques, which are widely used in the ocean modeling communities. The model experiments show that an improved initial condition by assimilating the SST affects the seasonal water temperature and water mass distributions of the YECS. In particular, the SST data assimilation influences the temperature structures horizontally and vertically in winter, thereby improving the behavior of the YS warm current water. This is due to the fact that during wintertime the water column is well mixed, which is directly updated by the SST assimilation. The model comparisons indicate that the SST assimilation can improve the model performance in resolving the subsurface structures in wintertime, but has a relatively small impact in summertime due to the strong stratification. The differences among the different assimilation experiments are obvious when the SST was sharply changed due to a typhoon passage. Overall, the EnKF and 4DVAR show better agreement with the observations than the EnOI. The relatively low performance of EnOI under storm conditions may be related with a limitation of EnOI method whereby an analysis is obtained from a number of climatological fields, and thus the typhoon-induced SST changes in short-time scales may not be adequately reflected in the data assimilation.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.18 no.1
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• pp.47-53
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• 1982

An analysis of convection, in a fully developed laminar steady flow through the vertical square duct under the condition of variational symmetric heat flux, is considered. Finite element solution algorithm by Galerkin's method with triangular elements and linear interpolation polynominals for the temperature and velocity profiles are derived for the vertical square duct. The comparison of temperature distribution due to variational symmetric heat flux in the duct were made with available the other data when the condition of peripheral heat flux were uniform and zero. Numerical values for the dimensionless temperatures and Nusselt numbers at selected Rayleigh numbers and pressure gradient parameters were obtained at a few nodal points for the vertical square ducts and effects of corner in the duct were investigated.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.15-20
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• 2017

The main purpose of the ball valve ball is to be moved by the rotation of the stem when fully open or completely closed. In this study the heat of the initial model, which used a structure interaction analysis technique, tried to examine the structural safety of the high temperature for the ball valve. In the initial model the stress of the exiting sheet was more than the yield strength. We selected two design shapes with variables of length and thickness for the optimization of the sheet. The Kriging interpolation method was applied to a meta-model-based optimization technique. As a result, it was possible to find a thickness and length for the sheet within the yield strength. This was done by measuring the value of the capacity coefficient of the valve and evaluating the performance of the ball valve.

• Korean Journal of Optics and Photonics
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• v.29 no.2
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• pp.70-76
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• 2018

Comparison calibration equipment for infrared-radiation thermometers below $0^{\circ}C$ has been established, using a TRT2 (transfer radiation thermometer 2, HEITRONICS) as a transfer standard and an ME30 (Model: ME30, HEITRONICS) as a variabletemperature blackbody. The TRT2 was calibrated using three fixed points (Ice ($0.01^{\circ}C$), In ($156.5985^{\circ}C$), and Sn ($231.928^{\circ}C$)) and the Planckian Sakuma-Hattori equation, and including the interpolation and extrapolation errors at $-50^{\circ}C$ in the uncertainty. The pneumatic lid is installed upon opening of the ME30 and is opened for only 30 seconds for measuring the radiation temperature, which prevents formation of ice in the ME30 and also reduces the calibration time to half. The farther away from the $0{\sim}232^{\circ}C$ region, the larger the uncertainty of the comparison calibration equipment becomes. The expanded uncertainty of the comparison calibration equipment was estimated as 0.26 K at $-20^{\circ}C$.

• Spatial Information Research
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• v.22 no.2
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• pp.63-71
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• 2014

Ocean leisure sports have recently emerged as one of so-called blue ocean industries. They are sensitive to diverse environmental conditions such as current, temperature, and salinity, which can increase needs of forecasting data as well as in-situ observations for the ocean. In this context, a Web-based geovisualization system for coastal information produced by model forecasts was implemented for use in supporting various ocean activities. First, FVCOM(Finite Volume Coastal Ocean Model) was selected as a forecasting model, and its data was preprocessed by a spatial interpolation and sampling library. The interpolated raster data for water surface elevation, temperature, and salinity were stored in image files, and the vector data for currents including speed and direction were imported into a distributed DBMS(Database Management System). Web services in REST(Representational State Transfer) API(Application Programming Interface) were composed using Spring Framework and integrated with desktop and mobile applications developed on the basis of hybrid structure, which can realize a cross-platform environment for geovisualization.

• Atmosphere
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• v.30 no.2
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• pp.169-181
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• 2020

We conducted a study on the impact of observation station density; this was done in order to enable the accurate estimation of spatial meteorological variables. The purpose of this study is to help operate an efficient observation network by examining distributions of temperature, relative humidity, and wind speed in a test area of a three-dimensional meteorological observation project in the Yeongdong region in 2019. For our analysis, we grouped the observation stations as follows: 41 stations (for Step 4), 34 stations (for Step 3), 17 stations (for Step 2), and 10 stations (for Step 1). Grid values were interpolated using the kriging method. We compared the spatial accuracy of the estimated meteorological grid by using station density. The effect of increased observation network density varied and was dependent on meteorological variables and weather conditions. The temperature is sufficient for the current weather observation network (featuring an average distance about 9.30 km between stations), and the relative humidity is sufficient when the average distance between stations is about 5.04 km. However, it is recommended that all observation networks, with an average distance of approximately 4.59 km between stations, be utilized for monitoring wind speed. In addition, this also enables the operation of an effective observation network through the classification of outliers.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2104-2125
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• 2021

This paper presents the verification and validation (V&V) of a calculation module for isotope inventory prediction to control the back-end cycle of spent nuclear fuel (SNF). The calculation method presented herein was implemented in a two-step code system of a lattice code STREAM and a nodal diffusion code RAST-K. STREAM generates a cross section and provides the number density information using branch/history depletion branch calculations, whereas RAST-K supplies the power history and three history indices (boron concentration, moderator temperature, and fuel temperature). As its primary feature, this method can directly consider three-dimensional core simulation conditions using history indices of the operating conditions. Therefore, this method reduces the computation time by avoiding a recalculation of the fuel depletion. The module for isotope inventory calculates the number densities using the Lagrange interpolation method and power history correction factors, which are applied to correct the effects of the decay and fission products generated at different power levels. To assess the reliability of the developed code system for back-end cycle analysis, validation study was performed with 58 measured samples of pressurized water reactor (PWR) SNF, and code-to-code comparison was conducted with STREAM-SNF, HELIOS-1.6 and SCALE 5.1. The V&V results presented that the developed code system can provide reasonable results with comparable confidence intervals. As a result, this paper successfully demonstrates that the isotope inventory prediction code system can be used for spent nuclear fuel analysis.