• Korean Journal of Ichthyology
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• v.22 no.2
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• pp.105-114
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• 2010

A taxonomic review of the family Sillaginidae was carried out based on two species (Sillago japonica and S. parvisquamis) collected in the coastal waters of Korea from 2008 to 2009 and three species (S. parvisquamis, S. aeolus and S. sihama) kept in the museum. Sillago japonica was easily distinguished from S. parvisquamis and S. sihama by lateral line scales (70~73 in S. japonica vs. 77~81 in S. parvisquamis vs. 67~70 in S. sihama) and scales above lateral line (3~4 vs. 7 vs. 5~6, respectively). Sillago aeolus differed from the other three species in having dark brown blotches on the side of body. We newly found morphological differences in some measurements (snout length, pectoral fin length and $2^{nd}$ anal spine length) and the number of vertebrae between Korean and Japanese S. parvisquamis, suggesting the two may be different populations. Although four sillaginid species are known from Korea, only two species (S. japonica and S. parvisquamis) were found in this study; accordingly, the distribution of the remaining two species (S. sihama and S. aeolus) may be restricted to subtropical waters.

• Atmosphere
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• v.32 no.1
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• pp.27-37
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• 2022

The Korean Integrated Model (KIM) forecast system was extended to assimilate Horizontal Line-Of-Sight (HLOS) wind observations from the Atmospheric Laser Doppler Instrument (ALADIN) on board the Atmospheric Dynamic Mission (ADM)-Aeolus satellite. Quality control procedures were developed to assess the HLOS wind data quality, and observation operators added to the KIM three-dimensional variational data assimilation system to support the new observed variables. In a global cycling experiment, assimilation of ALADIN observations led to reductions in average root-mean-square error of 2.1% and 1.3% for the zonal and meridional wind analyses when compared against European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) analyses. Even though the observable variable is wind, the assimilation of ALADIN observation had an overall positive impact on the analyses of other variables, such as temperature and specific humidity. As a result, the KIM 72-hour wind forecast fields were improved in the Southern Hemisphere poleward of 30 degrees.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2702-2713
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• 2022

A steam generator tube rupture accompanying a core damage may cause the fission product to be released to environment bypassing the containment. In such an accident, the steam generator is the major path of the radioactive aerosol release. AEOLUS facility, the scaled-down model of Korean type steam generator, was built to examine the aerosol removal in the steam generator during the steam generator tube rupture accident. Integral and separate effect tests were performed with the facility for the dry and flooded conditions, and the decontamination factors were presented for different tube configurations and submergences. The dry test results were compared with the existing test results and with the analyses to investigate the aerosol retention physics by the tube bundle, with respect to the particle size and the bundle geometry. In the flooded tests, the effect of submergence were shown and the retention in the jet injection region were presented with respect to the Stokes number. The test results are planned to be used to constitute the aerosol retention model, specifically applicable for the analysis of the steam generator tube rupture accident in Korean nuclear power plants to evaluate realistic fission product behavior.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1631-1645
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• 2021

This research aims to provide the characteristics of the world's first active lidar sensor Atmospheric Laser Doppler Instrument (ALADIN) wind data and Geostationary Korea Multi Purpose Satellite 2A (GK2A) Atmospheric Motion Vector (AMV) data by comparing two wind data. As a result of comparing the data from September 2019 to August 1, 2020, The total number of collocated data for the AMV (using IR channel) and Mie channel ALADIN data is 177,681 which gives the Root Mean Square Error (RMSE) of 3.73 m/s and the correlation coefficient is 0.98. For a more detailed analysis, Comparison result considering altitude and latitude, the Normalized Root Mean Squared Error (NRMSE) is 0.2-0.3 at most latitude bands. However, the upper and middle layers in the lower latitudes and the lower layer in the southern hemispheric are larger than 0.4 at specific latitudes. These results are the same for the water vapor channel and the visible channel regardless of the season, and the channel-specific and seasonal characteristics do not appear prominently. Furthermore, as a result of analyzing the distribution of clouds in the latitude band with a large difference between the two wind data, Cirrus or cumulus clouds, which can lower the accuracy of height assignment of AMV, are distributed more than at other latitude bands. Accordingly, it is suggested that ALADIN wind data in the southern hemisphere and low latitude band, where the error of the AMV is large, can have a positive effect on the numerical forecast model.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.186-192
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• 2014

Recently wind energy penetration into power systems has increased. Wind power, as a renewable energy source, plays a different role in the power system compared to conventional power generation units. As long as only single and small wind power units are installed in the power system, wind power does not influence power system operation and can easily be integrated. However, when wind power penetration reaches a significantly high level and conventional power production units are substituted, the impact of wind power on the power system becomes noticeable and must be handled. The connection of large wind turbines and wind farms to the grid has a large impact on grid stability. The electrical power system becomes more vulnerable to and dependent on wind energy production, and therefore there is an increased concern about the large wind turbines impact on grid stability. In this work, a new type of fuzzy logic controller for the frequency control of wind farms is proposed and its performance is verified using SimWindFarm toolbox which was developed as part of the Aeolus FP7 project.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.237-240
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• 2005

Calibration and Validation are major element of any space borne Earth Observation Mission. These activities are the major objective of the commissioning phases but routine activities shall be maintained during the whole mission in order to maintain the quality of the product delivered to the users or at least to fully characterise the evolution with time of the product quality. With the launch of ERS-l in 1991, the European Space Agency decided to put in place a group dedicated to these activities, along with the daily monitoring of the product quality for anomaly detection and algorithm evolution. These four elements are all strongly linked together. Today this group is fully responsible for the monitoring of two ESA missions, ERS-2 and Envisat, for a total of 12 instruments of various types, preparing itself for the Earth Explorer series of five. other satellites (Cryosat, Goce, SMOS, ADM-Aeolus, Swarm) and at various levels in past and future Third Party Missions such as Landsat, J-ERS, ALOS and KOMPSAT. The Joint proposal by the European Union and the European Space Agency for a 'Global Monitoring for Environment and Security' project (GMES), triggers a review of the scope of these activities in a much wider framework than the handling of single missions with specific tools, methods and activities. Because of the global objective of this proposal, it is necessary to put in place Multi-Mission Calibration and Validation systems and procedures. GMES Calibration and Validation activities will rely on multi source data access, interoperability, long-term data preservation, and definition standards to facilitate the above objectives. The scope of this presentation is to give an overview of the current Calibration and Validation activities at ESA, and the planned evolution in the context of GMES.