• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.483-490
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• 2022

Floating LiDAR is a system that provides a new paradigm for wind condition observation, which is essential when creating an offshore wind farm. As it can save time and money, minimize environmental impact, and even reduce backlash from local communities, it is emerging as the industry standard. However, the design and verification of a stable platform is very important, as disturbance factors caused by fluctuations of the buoy affect the reliability of observation data. In Korea, due to the nation's late entry into the technology, a number of foreign equipment manufacturers are dominating the domestic market. The west coast of Korea is a shallow sea environment with a very large tidal difference, so strong currents repeatedly appear depending on the region, and waves of strong energy that differ by season are formed. This paper conducted a study examining buoys suitable for LiDAR operation in the waters of Korea, which have such complex environmental characteristics. In this paper, we will introduce examples of optimized design and verification of ship-type buoys, which were applied first, and derive important concepts that will serve as the basis for the development of various platforms in the future.

• Journal of the Korean Society for Marine Environment & Energy
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• v.7 no.1
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• pp.22-29
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• 2004

An international project, known as Argo, for collecting data on temperature, salinity and velocity of currents in the world's oceans, has been started in the year 2000 and the full Argo array of approximately 3000 floats will be deployed by 2006. 18 countries deployed 1,023 floats, which are operating in the ocean of the world as of December 2003. In the present study, we tried to predict float distribution and a rate of drifting ashore of the floats after their termination based upon a product of the ocean general circulation model of JAMSTEC (Japan Marine Science and Technology Center). We first evaluated reliability of the model prodilct quantitatively by comparing trajectories of surface buoys of WOCE Surface Velocity Program (SVP) and those predicted by the model surface current field. It is found that the model is acceptable for practical application to deploy floats and to estimate those trajectories. 653 particles at 3-degree spacing are used to investigate the ratio of floats drifted ashore, given that during the first 4 years floats cycle between the surface and 2000m for 10 days and then floats are on just the surface for 100 years. The simulation indicates that about 29% of deployed floats will be drifted ashore within 100-year.

• Journal of Environmental Science International
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• v.19 no.11
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• pp.1397-1405
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• 2010

Mass mortalities of cultivated organisms have occurred frequently in Korean coastal waters causing enormous losses to cultivating industry. The preventive measures require continuous observation of farm environment and real-time provision of data. However, line hanging aquaculture farm are generally located far from monitoring buoys and has limitations on installation of heavy equipments. Substituting battery pack for solar panels and miniaturizing size of buoy, newly developed system can be attached to long line hanging aquaculture farm. This system could deliver measured data to users in real-time and contribute to damage mitigation and prevention from mass mortalities as well as finding their causes. The system was installed off Gijang and Yeongdeck in Korea, measuring and transmitting seawater temperature at the sea surface every 30 minutes. Short term variation of seawater temperature, less than one day, in Gijang from June to July 2009 corresponded tidal period of about 12 hours and long term variation seemed to be caused by cold water southeast coast of Korea, particularly northeast of Gijang. Seawater temperature differences between Gijang station and the other station that is about 500 m away from Gijang station were $1^{\circ}C$ on average. This fact indicates that it is need to be pay attention to use substitute data even if it is close to the station. Daily range of seawater temperature, one of crucial information to aquaculture, can be obtained from this system because temperature were measured every 30 minutes. Averages of daily range of temperature off Gijang and Yeongdeok during each observation periods were about $2.9^{\circ}C$ and $4.7^{\circ}C$ respectively. Dominant period of seawater temperature variation off Yeongdeok was one day with the lowest peak at 5 a.m. and the highest one at 5 p.m. generally, resulting from solar radiation.

• The Journal of the Acoustical Society of Korea
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• v.41 no.4
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• pp.426-434
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• 2022

Bubbles generated by various causes in the ocean are known to persist for long periods of time. Although the volume occupied by bubbles in the ocean is small, the presence of bubbles in ocean due to resonance and attenuation greatly affects the acoustic properties. Accordingly, bistatic reverberation experiment was performed in the ocean where artificial bubbles exist. A number of transducers and receivers were installed on 6 buoys arranged in a hexagonal shape, and blowing agents were dropped in the center of the buoy to generate bubbles. For reverberation modeling that reflects acoustic characteristics changed by bubbles, the spatial distribution of bubbles was estimated using video data and received signals. A measurement-based bubble spectral shape was used, and it was assumed that the bubble density within the spatial distribution of the estimated bubble was the same. As a result, it was confirmed that the bubble reverberation was simulated in a time similar to the measured data regardless of the bubble density, and the bubble reverberation level similar to the measured data was simulated at a void fraction of about 10^-7 ~ 10^-6.8.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.303-314
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• 2022

The persistence analysis of marine physical environment factors is a basic analysis that must precede the use of sea areas as an analysis required in the coastal engineering such as downtime and design. In this study, the persistence analysis was implemented for wind speed and significant wave height data from four observation points of Deokjeokdo, Oeyeondo, Geomundo, and Geojedo among the marine meteorological observation buoys of the Korea Meteorological Administration. The persistence time means the consecutive time of observation data beyond specific level. The threshold wind speed and significant wave height were set in the range of 1~15 m/s and the range of 0.25~3.0 m, respectively. Then, the persistence time was extracted. As a result of the analysis, the persistence time of wind speed and significant wave height decreased rapidly as the reference value increased. The median persistence times under the maximum reference thresholds were assessed as a maximum of 5 hours for wind speed and a maximum of 8 hours for significant wave height. When the reference wind speed and significant wave height were 15 m/s and 3 m, respectively, the persistence time that could occur with a 1% probability were 52 and 56 hours. This study can be expanded to all coastal areas in Korea, and it is expected that various engineering applications by performing a persistence analysis of the metocean data.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.5
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• pp.456-461
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• 2023

The Korea Maritime Environment Corporation is conducting a comprehensive survey of the national marine ecosystem under the commission of the Ministry of Oceans and Fisheries (MOF) to ensure continuous use of the ocean, preserve and manage the marine ecosystem. The survey has set major peaks to investigate changes in the marine ecosystem around the Korean Peninsula. However as the peak has been set around the coast, it is necessary to expand the scope of investigation to encompass offshore areas. Meanwhile, the Aids to Navigation Division of the MOF supports a comprehensive national marine ecosystem survey providing photographs of fouling organisms during the Aids to Navigation lifting inspection, however, the photographs are provided only in consultation with the Korea Maritime Environment Corporation. Therefore, a study was conducted to generate information on fouling organisms using deep learning-based image processing algorithms by the lifting Aids to Navigation and dorsal buoys so that Aids to Navigation could be used as the major component of a comprehensive national marine ecosystem. If the Aids to Navigation are used as the peak of the survey, they could serve as fundamental data to enhance their own value as well as analyze abnormal marine conditions and ecosystem changes in Korea.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.20 no.1
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• pp.1-15
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• 2015

Impacts of Sea Surface Temperature (SST) assimilation to the prediction of upper ocean temperature is investigated by using a regional ocean forecasting system, in which 3-dimensional optimal interpolation is applied. In the present study, Sea Surface Temperature and Sea Ice Analysis (OSTIA) dataset is adopted for the daily SST assimilation. This study mainly compares two experimental results with (Exp. DA) and without data assimilation (Exp. NoDA). When comparing both results with OSTIA SST data during Sept. 2011, Exp. NoDA shows Root Mean Square Error (RMSE) of about $1.5^{\circ}C$ at 24, 48, 72 forecast hour. On the other hand, Exp. DA yields the relatively lower RMSE of below $0.8^{\circ}C$ at all forecast hour. In particular, RMSE from Exp. DA reaches $0.57^{\circ}C$ at 24 forecast hour, indicating that the assimilation of daily SST (i.e., OSTIA) improves the performance in the early SST prediction. Furthermore, reduction ratio of RMSE in the Exp. DA reaches over 60% in the Yellow and East seas. In order to examine impacts in the shallow costal region, the SST measured by eight moored buoys around Korean peninsula is compared with both experiments. Exp. DA reveals reduction ratio of RMSE over 70% in all season except for summer, showing the contribution of OSTIA assimilation to the short-range prediction in the coastal region. In addition, the effect of SST assimilation in the upper ocean temperature is examined by the comparison with Argo data in the East Sea. The comparison shows that RMSE from Exp. DA is reduced by $1.5^{\circ}C$ up to 100 m depth in winter where vertical mixing is strong. Thus, SST assimilation is found to be efficient also in the upper ocean prediction. However, the temperature below the mixed layer in winter reveals larger difference in Exp. DA, implying that SST assimilation has still a limitation to the prediction of ocean interior.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.2
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• pp.109-117
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• 2022

There has been an increasing number of studies on photovoltaic energy generation system in an offshore site with the largest energy generation efficiency, as increasing the researches and developments of renewable energies for use of offshore space and resources to replace existing fossil fuels and resolve environmental challenges. For installation and operation of floating photovoltaic systems in an offshore site with harsher environmental conditions, a stiffness of structural members comprising the total system must be reinforced to inland water spaces as dams, reservoirs etc., which have relatively weak condition. However, there are various limitations for the reinforcement of structural stiffness of the system, including producible size, total mass of the system, economic efficiency, etc. Thus, in this study, a floating breakwater is considered for reducing wave loads on the system and minimizing the reinforcement of the structural members. Wave reduction performances of floating breakwaters are evaluated, considering size and distance to the system. The wave loads on the system are evaluated using the higher-order boundary element method (HOBEM), considering the multi-body effect of buoys. Stresses on structural members are assessed by coupled analyses using the finite element method (FEM), considering the wave loads and hydrodynamic characteristics. As the maximum stresses on each of the cases are reviewed and compared, the effect of floating breakwater for floating photovoltaic system is checked, and it is confirmed that the size of breakwater has a significant effect on structural responses of the system.

• Journal of the Korean earth science society
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• v.41 no.5
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• pp.469-477
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• 2020

Salinity is not only an important variable that determines the density of the ocean but also one of the main parameters representing the global water cycle. Ocean salinity observations have been mainly conducted using ships, Argo floats, and buoys. Since the first satellite salinity was launched in 2009, it is also possible to observe sea surface salinity in the global ocean using satellite salinity data. However, the satellite salinity data contain various errors, it is necessary to validate its accuracy before applying it as research data. In this study, the salinity accuracy between the Soil Moisture Active Passive (SMAP) satellite salinity data and the in-situ salinity data provided by the Ieodo ocean research station was evaluated, and the error characteristics were analyzed from April 2015 to August 2020. As a result, a total of 314 match-up points were produced, and the root mean square error (RMSE) and mean bias of salinity were 1.79 and 0.91 psu, respectively. Overall, the satellite salinity was overestimated compare to the in-situ salinity. Satellite salinity is dependent on various marine environmental factors such as season, sea surface temperature (SST), and wind speed. In summer, the difference between the satellite salinity and the in-situ salinity was less than 0.18 psu. This means that the accuracy of satellite salinity increases at high SST rather than at low SST. This accuracy was affected by the sensitivity of the sensor. Likewise, the error was reduced at wind speeds greater than 5 m s^-1. This study suggests that satellite-derived salinity data should be used in coastal areas for limited use by checking if they are suitable for specific research purposes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.186-197
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• 2023

In this study, we focus on the improvement of data quality transmitted from a weather buoy that guides a route of ships. The buoy has an Internet-of-Thing (IoT) including sensors to collect meteorological data and the buoy's status, and it also has a wireless communication device to send them to the central database in a ground control center and ships nearby. The time interval of data collected by the sensor is irregular, and fault data is often detected. Therefore, this study provides a framework to improve data quality using machine learning models. The normal data pattern is trained by machine learning models, and the trained models detect the fault data from the collected data set of the sensor and adjust them. For determining fault data, interquartile range (IQR) removes the value outside the outlier, and an NGBoost algorithm removes the data above the upper bound and below the lower bound. The removed data is interpolated using NGBoost or long-short term memory (LSTM) algorithm. The performance of the suggested process is evaluated by actual weather buoy data from Korea to improve the quality of 'AIR_TEMPERATURE' data by using other data from the same buoy. The performance of our proposed framework has been validated through computational experiments based on real-world data, confirming its suitability for practical applications in real-world scenarios.