• Atmosphere
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• v.29 no.1
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• pp.21-39
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• 2019

The conventional observations of the Korea Meteorological Administration (KMA) and National Centers for Environmental Prediction (NCEP) are compared in the numerical weather forecast system at the Korea Institute of Atmospheric Prediction Systems (KIAPS). The weather forecasting system used in this study is consists of Korea Integrated Model (KIM) as a global numerical weather prediction model, three-dimensional variational method as a data assimilation system, and KIAPS Package for Observation Processing (KPOP) as an observation pre-processing system. As a result, the forecast performance of NCEP observation was better while the number of observation is similar to the KMA observation. In addition, the sensitivity of forecast performance was investigated for each SONDE, SURFACE and AIRCRAFT observations. The differences in AIRCRAFT observation were not sensitive to forecast, but the use of NCEP SONDE and SURFACE observations have shown better forecast performance. It is found that the NCEP observations have more wind observations of the SONDE in the upper atmosphere and more surface pressure observations of the SURFACE in the ocean. The results suggest that evenly distributed observations can lead to improved forecast performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.4
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• pp.245-255
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• 2019

This paper describes on aerodynamic analysis based on the truncation rate of guided-weapon nose using computational fluid dynamics. The shape to perform the analysis is only the body of the guided weapon and the diameter to length ratio is 10.7. Three nose shapes were selected and hemisphere, 25% and 50% truncation were compared. For the accurate CFD analysis of the body, the grid method and the analytical method were selected and verified using NASA wind tunnel test data. For the three nose shapes, the drag analysis for the flight Mach number is 6~20% different. This difference was analyzed by the pressure distribution from nose to base.

• Atmosphere
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• v.32 no.4
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• pp.381-394
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• 2022

The Korea Meteorological Administration (KMA) National Typhoon Center has been officially releasing reanalyzed best tracks for the previous year's northwest Pacific typhoons since 2015. However, while most typhoon researchers are aware of the data released by other institutions, such as the Joint Typhoon Warning Center (JTWC) and the Regional Specialized Meteorological Center (RSMC) Tokyo, they are often unfamiliar with the KMA products. In this technical note, we describe the best track data released by KMA, and the algorithms that are used to generate it. We hope that this will increase the usefulness of the data to typhoon researchers, and help raise awareness of the product. The best track reanalysis process is initiated when the necessary database of observations-which includes satellite, synoptic, ocean, and radar observations-has become complete for the required year. Three categories of best track information-position (track), intensity (maximum sustained winds and central pressure), and size (radii of high-wind areas)-are estimated based on scientific processes. These estimates are then examined by typhoon forecasters and other internal and external experts, and issued as an official product when final approval has been given.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.7-13
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• 2021

This study develops an artificial intelligence prediction system for Fine particulate Matter(PM2.5) based on the deep learning algorithm GAN model. The experimental data are closely related to the changes in temperature, humidity, wind speed, and atmospheric pressure generated by the time series axis and the concentration of air pollutants such as SO2, CO, O3, NO2, and PM10. Due to the characteristics of the data, since the concentration at the current time is affected by the concentration at the previous time, a predictive model for recursive supervised learning was applied. For comparative analysis of the accuracy of the existing models, CNN and LSTM, the difference between observation value and prediction value was analyzed and visualized. As a result of performance analysis, it was confirmed that the proposed GAN improved to 15.8%, 10.9%, and 5.5% in the evaluation items RMSE, MAPE, and IOA compared to LSTM, respectively.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.1
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• pp.1-10
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• 2021

In this study, Information for the case of seawater flooding and observation data over a period of 10 years (2009~2018) was collected. Using machine learning algorithms, the characteristics of the types of seawater flooding and observations by type were classified. Information for the case of seawater flooding was collected from the reports of the Korea Hydrographic and Oceanographic Agency (KHOA) and the Korea Land and Geospatial Informatics Corporation. Observation data for ocean and meteorological were collected from the KHOA and the Korea Meteorological Agency (KMA). The classification of seawater flooding incidence types is largely categorized into four types, and into 5 development types through combination of 4 types. These types were able to distinguish the types of seawater flooding according to the marine weather environment. The main characteristics of each was classified into the following groups: tidal movement, low pressure system, strong wind, and typhoon. Besides, in consideration of the geographical characteristics of the ocean, the thresholds of ocean factors for seawater flooding by region and type were derived.

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

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.493-510
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• 2021

Mineral wool is an insulation material commonly used in passive fire protection (PFP) systems on offshore installations. Insulation materials have only been considered functional materials for thermal analysis in the conventional offshore PFP system design method. Hence, the structural performance of insulation has yet to be considered in the design of PFP systems. However, the structural elements of offshore PFP systems are often designed with excessive dimensions to satisfy structural requirements under external loads such as wind, fire and explosive pressure. To verify the structural contribution of insulation material, it was considered a structural material in this study. A series of material tensile tests was undertaken with two types of mineral wool at room temperature and at elevated temperatures for fire conditions. The mechanical properties were then verified with modified methods, and a database was constructed for application in a series of nonlinear structural and thermal finite-element analyses of an offshore bulkhead-type PFP system. Numerical analyses were performed with a conventional model without insulation and with a new suggested model with insulation. These analyses showed the structural contribution of the insulation in the structural behaviour of the PFP panel. The results suggest the need to consider the structural strength of the insulation material in PFP systems during the structural design step for offshore installations.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.153-153
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• 2021

Storm Storm event is one of major issues in South Korea due to devastating damage at its landfall. A series of statistical study on the historical typhoon records consistently insist that the typhoon translation speed (TS) is on slowdown trend annually, and thus provides an urgent topic in assessing the extreme storm surge under future climate change. Even though TS has been regarded as a principal contributor in storm surge dynamics, only a few studies have considered its impact on the storm surge. The landfall angle (LA), another key physical factor of storm surge also needs to be further investigated along with TS. This study aims to elucidate the interaction mechanism among TS, LA, coastal geometry, and storm surge synthetically by performing a series of simulations on the idealized geometries using Delft3D FM. In the simulation, various typhoons are set up according to different combinations of TS and LA, while their trajectories are assumed to be straight with the constant wind speed and the central pressure. Then, typhoons are subjected to make landfall over a set of idealized geometries that have different depth profiles and layouts (i.e., open coasts or bays). The simulation results show that: (i) For the open coasts, the maximum surge height (MSH) increases with increasing TS. (ii) For the constant bed level, a typhoon normal to the coastline resulted in peak MSH due to the lowest effect of the coastal wave. (iii) For the continental shelf with different widths, the slow-moving typhoon will generate the peak MSH around a small LA as the shelf width becomes narrow. (iv) For the bay, MSH enlarges with the ratio of L/E (the length of main-bay axis /gate size) dropping, while the greatest MSH is at L/E=1. These findings suggest that a fast-moving typhoon perpendicular to the coastline over a broad continental shelf will likely generate the extreme storm surge hazard in the future, as well as the slow-moving typhoon will make an acute landfall over a narrow continental shelf.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.15-17
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• 2021

This paper proposes a drone flight trajectory method for accurate air pollutant emission designation detection. In areas with many factories, such as industrial complexes, there are workplaces that illegally emit air pollutants in a situation where monitoring is neglected. In the past, studies have been actively conducted to measure air pollutants in these areas using drones. The measurement method using a drone uses a method of detecting pollution by stopping around the chimney of a factory, but it has a problem in that the detection of air pollutants is inaccurate depending on environmental factors such as air pressure and wind. Therefore, this paper proposes a drone flight trajectory method for accurate air pollutant emission designation detection. This paper devises a screw orbit flight method in which a drone flies upward while rotating the chimney, and the total area of the chimney is detected and measured considering environmental factors. In the experiment, our proposal shows a higher performance than the existing method.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.5
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• pp.367-374
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• 2023

As the Fourth Industrial Revolution accelerating, countries worldwide are developing technologies to digitize and automate various industrial sectors. Building smart factories not only reduces costs through improved process productivity but also allows for preemptive identification and removal of risk factors through the practice of Health, Safety, and Environment (HSE) management, thereby reducing industrial accident risks. In this study, we visualized pressure, temperature, power, and wind speed data measured in real-time via a monitoring GUI, enabling field managers and workers to easily access related information. Through the work environment monitoring system developed in this study, it is possible to conduct economic analysis on per-unit basis, based on the digitization of production management elements and the tracking of required resources. By implementing HSE in shipyards, potential risk factors can be improved, and gas and electrical leaks can be identified, which are expected to reduce production costs.