• International Journal of Naval Architecture and Ocean Engineering
• /
• v.11 no.1
• /
• pp.624-637
• /
• 2019

A semi-submersible offshore platform always operates under complex weather conditions, especially wind and waves. It is vital to analyze the structural dynamic responses of the platform in short-term sea states under the combined wind and wave loads, which touches upon three following work. Firstly, a derived relationship between wind and waves reveals a correlation of wind velocity and significant wave height. Then, an Improved Mixture Simulation (IMS) method is proposed to simulate the time series of wind/waves accurately and efficiently. Thus, a wind-wave scatter diagram is expanded from the traditional wave scatter diagram. Finally, the time series of wind/wave pressures on the platform in the short-term sea states are converted by Workbench-AQWA. The numerical results demonstrate that the proposed numerical methods are validated to be applicable for wind and wave simulations in structural analyses. The structural dynamic responses of the platform members increase with the wind and wave strength. In the up-wind and wave state, the stresses on the deck, the connections between deck and columns, and the connection between columns and pontoons are relatively larger under the vertical bending moment. These numerical methods and results are wished to provide some references for structural design and health monitoring of several offshore platforms.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.57 no.4
• /
• pp.351-364
• /
• 2021

In this study, the vertical distribution of giant jellyfish analyzed echo counting method and such survey methods as sighting and trawl were used to compare its density estimates. In May and July 2021, surveys were conducted in the East China Sea and the coastal waters of Korea. As a result, Nemopilema nomurai were evenly distributed in all water layers in East China Sea in May and July. When considered the correlation by each survey methods, it is possible to identify jellyfish in the surface area by sighting method and using sampling net; however, it has a low correlation with acoustic estimates due to marine environmental factor such as weather condition, wind and atmospheric pressure. Therefore, the result can be utilized by basic data when estimating jellyfish's distribution patterns and density estimates from each survey methods hereafter.

• Ocean Systems Engineering
• /
• v.12 no.2
• /
• pp.225-245
• /
• 2022

More and more shipping containers are falling into the sea due to bad weather. Containers lost at sea negatively affect the shipping line, the trader and the consumer, and the environment. The question of locating and recovering dropped containers is a challenging engineering problem. Model-testing of small-scaled container models is proposed as an efficient way to investigate their falling trajectories to salvage them. In this study, we first build a standard 20-ft container model in SOLIDWORKS. Then, a three-dimensional (3D) geometric model in the STL (Standard Tessellation Language) format is exported to a Stratasys F170 Fused Deposition Modeling (FDM) printer. In total, six models were made of acrylonitrile styrene acrylate (ASA) and printed for the purpose of testing. They represent three different loading conditions with different densities and center of gravity (COG). Two samples for each condition were tested. The physical models were dropped into the towing tank of University of New Orleans (UNO). From the experimental tests, it is found that the impact of the initial position after sinking can cause a certain initial rolling velocity, which may have a great impact on the lateral displacement, and subsequently affect the final landing position. This series of model tests not only provide experimental data for the study of the trajectory of box-shape objects but also provide a valuable reference for maritime salvage operations and for the pipeline layout design.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.207-207
• /
• 2021

The Vietnamese Mekong Delta(VMD) covers an area of 62,250 km² in the lowest basin of the Mekong Delta where more than half of the country's total rice production takes place. In 2016, an estimated 1.29 million tonnes of Vietnam's rice were lost to the country's biggest drought in 90 year and particularly in VMD, at least 221,000 hectares of rice paddies were hit by the drought and related saltwater intrusion from the South China Sea. In this study, 3D numerical simulations using Delft3D hydrodynamic models with calibration and validation process were performed to examine flow characteristics, climate change scenarios, water level changes, and salinity concentrations in the nine major estuaries and coastal zones of VMD during the 21^st century. The river flows and their interactions with ocean currents were modeled by Delft3D and since the water levels and saltwater intrusion in the area are sensitive to the climate conditions and upstream dam operations, the hydrodynamic models considered discharges from the dams and climate data provided by the Coupled Model Intercomparison Project Phase 6(CMIP6). The models were calibrated and verified using observational water levels, salinity distribution, and climate change data and scenarios. The results agreed well with the observed data during calibration and validation periods. The calibrated models will be used to make predictions about the future salinity intrusion events, focusing on the impacts of sea level rise due to global warming and weather elements.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2023.11a
• /
• pp.242-243
• /
• 2023

Different incident angles concerning ocean conditions and weather greatly influence small vessel navigation. Particularly for small vessels, different incident angles result in distinct motion characteristics closely related to stability. Based on actual coastal wave data, this study conducted simulations and experiments to analyze the motion characteristics of small vessels navigating in irregular waves. The analysis revealed that significant motions primarily occurred at lower speeds from the bow sea. In contrast, as the speed increased, the roll motions due to the bow sea decreased, but those due to the stern seas increased. Consequently, adjusting the incident wave angles according to vessel speed can enhance stability and navigational efficiency for small vessels.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.19 no.3
• /
• pp.93-101
• /
• 2017

The distribution of inter-annual variation in temperature would help evaluate the likelihood of a climatic risk and assess suitable zones of crops under climate change. In this study, we evaluated two methods to estimate the standard deviation of temperature in the areas where weather information is limited. We calculated the monthly standard deviation of temperature by collecting temperature at 0600 and 1500 local standard time from 10 automated weather stations (AWS). These weather stations were installed in the range of 8 to 1,073m above sea level within a mountainous catchment for 2011-2015. The observed values were compared with estimates, which were calculated using a geospatial correction scheme to derive the site-specific temperature. Those estimates explained 88 and 86% of the temperature variations at 0600 and 1500 LST, respectively. However, it often underestimated the temperatures. In the spring and fall, it tended to had different variance (e.g., increasing or decreasing pattern) from lower to higher elevation with the observed values. A regression analysis was also conducted to quantify the relationship between the standard deviation in temperature and the topography. The regression equation explained a relatively large variation of the monthly standard deviation when lapse-rate corrected temperature, basic topographical variables (e.g., slope, and aspect) and topographical variables related to temperature (e.g., thermal belt, cold air drainage, and brightness index) were used. The coefficient of determination for the regression analysis ranged between 0.46 and 0.98. It was expected that the regression model could account for 70% of the spatial variation of the standard deviation when the monthly standard deviation was predicted by using the minimum-maximum effective range of topographical variables for the area.

• Fire Science and Engineering
• /
• v.28 no.6
• /
• pp.13-21
• /
• 2014

Forest fire has a number of variables and since the effects of wind fields are bigger than any other variables, it is essential to know wind direction and velocity for the forest fire extinguishing techniques and the prediction of fire spread. With regards to the local area that has a high chance of forest fire, the data from meteorological observatory in the area is used for the estimation of wind velocity. It is relatively easy to obtain automatic weather station (AWS) data which are available for the whole nation. There is a chance that the data from the weather station may be different with the actual data at the mountain areas. In this study simply shaped hills (Sae-byeol hill of Jeju Island and port Ma-geum in An-myeon Island in the sea side) were selected as the experimental locations to minimize the distortion of the wind field by the adjacent geographic features. Spot measurements and analysis of computational fluid dynamics (CFD) for the given geographic features were conducted to examine and compare their consistency. As a conclusion It is possible to predict wind patterns in these simple locations.

• Korean Journal of Remote Sensing
• /
• v.38 no.3
• /
• pp.265-282
• /
• 2022

Sea surface temperature (SST) is a factor that greatly influences ocean circulation and ecosystems in the Earth system. As global warming causes changes in the SST near the Korean Peninsula, abnormal water temperature phenomena (high water temperature, low water temperature) occurs, causing continuous damage to the marine ecosystem and the fishery industry. Therefore, this study proposes a methodology to predict the SST near the Korean Peninsula and prevent damage by predicting abnormal water temperature phenomena. The study area was set near the Korean Peninsula, and ERA5 data from the European Center for Medium-Range Weather Forecasts (ECMWF) was used to utilize SST data at the same time period. As a research method, Long Short-Term Memory (LSTM) algorithm specialized for time series data prediction among deep learning models was used in consideration of the time series characteristics of SST data. The prediction model predicts the SST near the Korean Peninsula after 1- to 7-days and predicts the high water temperature or low water temperature phenomenon. To evaluate the accuracy of SST prediction, Coefficient of determination (R²), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) indicators were used. The summer (JAS) 1-day prediction result of the prediction model, R²=0.996, RMSE=0.119℃, MAPE=0.352% and the winter (JFM) 1-day prediction result is R²=0.999, RMSE=0.063℃, MAPE=0.646%. Using the predicted SST, the accuracy of abnormal sea surface temperature prediction was evaluated with an F1 Score (F1 Score=0.98 for high water temperature prediction in summer (2021/08/05), F1 Score=1.0 for low water temperature prediction in winter (2021/02/19)). As the prediction period increased, the prediction model showed a tendency to underestimate the SST, which also reduced the accuracy of the abnormal water temperature prediction. Therefore, it is judged that it is necessary to analyze the cause of underestimation of the predictive model in the future and study to improve the prediction accuracy.

• Journal of the Korean earth science society
• /
• v.45 no.1
• /
• pp.1-18
• /
• 2024

This study analyzed the effect of warming on PM_2.5 aerosol production in mid-latitude East Asia during June 2020 using PM_2.5 aerosol anomalies, which were identified by incorporating meteorological and climate data into the Weather Research Forecasting model coupled with Chemistry (WRF-Chem) model. The decadal temperature change trend over a 30-year period (1991-2020) in East Asia showed that recent warming has been greater in summer than in winter. Summer warming in East Asia generated low and high pressure in the lower and upper troposphere, respectively, over China. The boundary between the lower tropospheric low and upper tropospheric high pressure sloped along the terrain from the Tibetan Plateau to Korea. The eastern China, Yellow Sea, and Korean regions experienced a convergence of warm and humid southwesterly airflows originating from the East China Sea with the development of a northwesterly Pacific high pressure. In June 2020, the highest temperatures were observed since 1973 in Korea. Meanwhile, enhanced warming in East Asia increased the production of PM_2.5 aerosols that travelled long distances from eastern China to Korea. PM_2.5 anomalies, which were derived solely by inputting meteorological and climatic data (1991-2020) into the WRF-Chem model and excluding emission variations, showed a positive distribution extending from eastern China to South Korea across the Yellow Sea as well as over the Pacific Northwest. Thus, the contribution of warming to PM_2.5 aerosols in East Asia during June 2020 was more than 50%. In particular, PM_2.5 aerosols were transported from eastern China to Korea through the Yellow Sea, where the warm and humid southwesterly airflows implied wet scavenging of sulfate but promoted nitrate production.

• Journal of the Korean earth science society
• /
• v.26 no.5
• /
• pp.395-403
• /
• 2005

This study is focused on the relationship between snowfall and the Bowen’s Ratio (sensible heat flux/latent heat flux) through calculation of heat exchange between air and sea for snowfall events in Jeju Island from 1993 to 2003. The four weather stations for this study are located at Jeju, Seoguipo, Seongsanpo and Gosan in Jeju Island. In order to improve the reliability of snowfall forecast, the Bowen’s Ratio for snowfall, which includes influences from the atmosphere such as wind, is compared with the temperature difference between air and sea for snowfall. As a results, in the case for fresh snowfall, the minimum temperature differences between air and sea were 10, 12.3, 11.5, and $14.3^{\circ}C$ at Jeju, Seoguipo, Seongsanpo and Gosan, respectively. The probabilities of fresh snowfall were 26, 29, 13, and $23\%$, respectively, when the temperature differences were higher than the previous values. On the other hand, the minimum Bowen ratios were 0.59, 0.60, 0.65 and 0.65 at Jeju, Seoguipo, Seongsanpo and Gosan, respectively. The probabilities of fresh snowfall were 33, 70, 31 and $58\%$ respectively, when the Bowen ratio is higher than those. The reason for this is because the probability of fresh snowfall with the Bowen ratio was higher than the probability with temperature difference between air and sea. This result occurred because heat exchange by wind increased the probability of snowfall, along with the temperature difference between air and sea, and the Bowen ratio. Therefore, snowfall forecast of Jeju Island is significantly influenced by the sea, whereas forecast with Bowen ratio seems to have higher reliability than that with the temperature difference between air and sea. The data analysis for the ten-year period $(1993\~2002)$ showed that when each fresh snowfall was within 0.0 to 0.9cm, the average Bowen’s ratio was 0.63 to 0.67, and when each fresh snowfall was 1.0 to 4.9 cm, the average Bowen’s ratio was over 0.72. Therefore, fresh snowfall shows a proportional relationship with the Bowen’s ratio during snowfall.