• Journal of Soil and Groundwater Environment
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• 제19권1호
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• pp.26-33
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• 2014

Uncertainty associated with a sampling method is very high in evaluating the degree of site contamination; therefore, such uncertainty affects the reliability of precise investigation and remediation verification. In particular, in evaluating a site for a small-sized filling station, underground utilities, such as connection pipes and oil storage tanks, make grid-unit sampling impossible and the resulting increase in uncertainty is inevitable. Accordingly, this study quantified the uncertainty related to the evaluation of the degree of contamination by total petroleum hydrocarbon and by benzene, toluene, ethylene, and xylene. When planning a grid aimed at detecting a hot spot, major factors that influence the increase in uncertainty include grid interval and the size and shape of the hot spot. The current guideline for soil sampling prescribes that the grid interval increase in proportion to the area of the evaluated site, but this heightens the possibility that a hot spot will not be detected. In evaluating a site, therefore, it is crucial to estimate the size and shape of the hot spot in advance and to establish a sampling plan considering a diversity of scenarios.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 한국방사성폐기물학회 2017년도 춘계학술논문요약집
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• pp.139-140
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• 2017

• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1438-1449
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• 2018

The importance of power system stability has been emphasized with an increase of wind energy penetration in the power system. Accordingly, the guarantee on various control capabilities, including active and reactive power control of wind farms, was regarded as the most important aspect for the connection to the grid. To control the wind farm active power, the wind farm controller was introduced. The wind farm controller decides the power set points for each wind turbine generating unit and each wind turbine generating unit controls its power according to the set points from the wind farm controller. Therefore, co-relationship between wind farm controller and wind turbine controllers are significantly important. This paper proposes some control methods of wind farm active power control based on modified wind turbine control for power system stability and structures to connect wind turbine controllers to wind farm controller. Besides, this paper contributes to development of control algorithm considering not only electrical components but also mechanical components. The proposed contributions were verified by full simulation including power electronics and turbulent wind speed. The scenario refers to the active power control regulations of the Eltra and Elkraft system in Denmark.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제19권6호
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• pp.107-117
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• 2020

With the recent development of autonomous vehicles, various sensors installed in vehicles have become common, and big data generated from those sensors is increasingly being used in the transportation field. In this study, we proposed a grid index method to efficiently process real-time vehicle sensing big data and public data such as road weather. The applicability and effect of the proposed grid space division method and grid ID generation method were analyzed. We created virtual data based on DTG data and mapped to the road link based on coordinates. As a result of analyzing the data processing speed in grid index method, the data processing performance improved by more than 2,400 times compared to the existing link unit processing method. In addition, in order to analyze the efficiency of the proposed technology, the virtually generated data was mapped and visualized.

• Journal of Korea Water Resources Association
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• 제55권12호
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• pp.991-998
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• 2022

The purpose of this study is to develop GPU (Graphics Processing Unit) acceleration technique for 2-dimensional model and to assess the effectiveness for high resolution flood simulation in wide area In this study, GPU acceleration technique was implemented in the G2D (Grid based 2-Dimensional land surface flood model) model, using implicit scheme and uniform square grid, by using CUDA. The technique was applied to flood simulation in Jinju-si. The spatial resolution of the simulation domain is 10 m × 10 m, and the number of cells to calculate is 5,090,611. Flood period by typhoon Mitag, December 2019, was simulated. Rainfall radar data was applied to source term and measured discharge of Namgang-Dam (Ilryu-moon) and measured stream flow of Jinju-si (Oksan-gyo) were applied to boundary conditions. From this study, 2-dimensional flood model could be implemented to reproduce the measured water level in Nam-gang (Riv.). The results of GPU acceleration technique showed more faster flood simulation than the serial and parallel simulation using CPU (Central Processing Unit). This study can contribute to the study of developing GPU acceleration technique for 2-dimensional flood model using implicit scheme and simulating land surface flood in wide area.

• The Transactions of The Korean Institute of Electrical Engineers
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• 제67권6호
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• pp.708-714
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• 2018

Islanded operation of a microgrid can ensure the reliable operation of the system when a large accident occurs in the main grid. However, because the generation capability of a microgrid is typically limited, a microgrid operator should take islanded operation risk into account in scheduling its generation resources. To address this problem, in this paper we have proposed two unit commitment formulations based on the islanding scenario that reflect the expected and worst-case values of the islanded operation risk. An optimal resource scheduling strategy is obtained for the microgrid operator by solving these optimization problem, and the effectiveness of the proposed method is investigated by numerical simulations.

• Proceedings of the Korean Society of Crop Science Conference
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• 한국작물학회 2017년도 9th Asian Crop Science Association conference
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• pp.303-303
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• 2017

Japanese agriculture has faced to several threats: aging and decrease of farmer population, global competition, and the risk of climate change as well as harsh and variable weather. On the other hands, the number of large scale farms is increasing, because farm lands have been being aggregated to fewer numbers of farms. Cost cutting, development of efficient ways to manage complicatedly scattered farm lands, maintaining yield and quality under variable weather conditions, are required to adapt to changing environments. Information and communications technology (ICT) would contribute to solve such problems and to create innovative technologies. Thus we have been developing an early warning and decision support system to reduce weather and climate risks for rice, wheat and soybean production in Japan. The concept and prototype of the system will be shown. The system consists of a weather data system (Agro-Meteorological Grid Square Data System, AMGSDS), decision support contents where information is automatically created by crop models and delivers information to users via internet. AMGSDS combines JMA's Automated Meteorological Data Acquisition System (AMeDAS) data, numerical weather forecast data and normal values, for all of Japan with about 1km Grid Square throughout years. Our climate-smart system provides information on the prediction of crop phenology, created with weather forecast data and crop phenology models, as an important function. The system also makes recommendations for crop management, such as nitrogen-topdressing, suitable harvest time, water control, pesticide spray. We are also developing methods to perform risk analysis on weather-related damage to crop production. For example, we have developed an algorism to determine the best transplanting date in rice under a given environment, using the results of multi-year simulation, in order to answer the question "when is the best transplanting date to minimize yield loss, to avoid low temperature damage and to avoid high temperature damage?".

• Korean Journal of Agricultural and Forest Meteorology
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• 제7권1호
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• pp.115-123
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• 2005

Quantitative understanding of spatial characteristics of the study site is a prerequisite to investigate water and carbon cycles in agricultural and forest ecosystems, particularly with complex, heterogeneous landscapes. The spatial characteristics of variables related with topography, vegetation and soil in Gwangneung forest watershed are quantified in this study. To characterize topography, information on elevation, slope and aspect extracted from DEM is analyzed. For vegetation and soil, a land-cover map classified from LANDSAT TM images is used. Four satellite images are selected to represent different seasons (30 June 1999, 4 September 2000, 23 September 2001 and 14 February 2002). As a flux index for CO₂ and water vapor, normalized difference vegetation index (NDVI) is calculated from satellite images for three different grid sizes: MODIS grid (7km x 7km), intensive observation grid (3km x 3km), and unit grid (1km x 1km). Then, these data are analyzed to quantify the spatial scale of heterogeneity based on semivariogram analysis. As expected, the scale of heterogeneity decreases as the grid size decreases and are sensitive to seasonal changes in vegetation. For the two unit grids where the two 40 m flux towers are located, the spatial scale of heterogeneity ranges from 200 to 1,000m, which correspond well to the climatology of the computed tower flux footprint.

• The KIPS Transactions:PartD
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• 제14D권7호
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• pp.733-742
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• 2007

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Due to this reason, memory usage for data stream analysis should be confined finitely although new data elements are continuously generated in a data stream. To satisfy this requirement, data stream processing sacrifices the correctness of its analysis result by allowing some errors. The old distribution statistics are diminished by a predefined decay rate as time goes by, so that the effect of the obsolete information on the current result of clustering can be eliminated without maintaining any data element physically. This paper proposes a grid based clustering algorithm for a data stream. Given a set of initial grid cells, the dense range of a grid cell is recursively partitioned into a smaller cell based on the distribution statistics of data elements by a top down manner until the smallest cell, called a unit cell, is identified. Since only the distribution statistics of data elements are maintained by dynamically partitioned grid cells, the clusters of a data stream can be effectively found without maintaining the data elements physically. Furthermore, the memory usage of the proposed algorithm is adjusted adaptively to the size of confined memory space by flexibly resizing the size of a unit cell. As a result, the confined memory space can be fully utilized to generate the result of clustering as accurately as possible. The proposed algorithm is analyzed by a series of experiments to identify its various characteristics

• Atmosphere
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• 제25권3호
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• pp.529-541
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• 2015

Korea Institute of Atmospheric Prediction System (KIAPS) has been developing a global numerial prediction model and data assimilation system. We has implemented LETKF (Local Ensemble Transform Kalman Filter, Hunt et al., 2007) data assimilation system to NCAR CAM-SE (National Center for Atmospheric Research Community Atmosphere Model with Spectral Element dynamical core, Dennis et al., 2012) that has cubed-sphere grid, known as the same grid system of KIAPS Integrated Model (KIM) now developing. In this study, we have assimilated Global Positioning System Radio Occultation (GPS-RO) bending angle measurements in addition to conventional data within ensemble-based data assimilation system. Before assimilating bending angle data, we performed a vertical unit conversion. The information of vertical localization for GPS-RO data is given by the unit of meter, but the vertical localization method in the LETKF system is based on pressure unit. Therefore, with a clever conversion of the vertical information, we have conducted experiments to search for the best vertical localization scale on GPS-RO data under the Observing System Simulation Experiments (OSSEs). As a result, we found the optimal setting of vertical localization for the GPS-RO bending angle data assimilation. We plan to apply the selected localization strategy to the LETKF system implemented to KIM which is expected to give better analysis of GPS-RO data assimilation due to much higher model top.