• Journal of the Society of Naval Architects of Korea
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• v.31 no.1
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• pp.94-101
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• 1994

This paper describes a short-term prediction model for the movement of an oil slick in shallow waters. Under the assumption that the initial movement of the oil slick is governed by spreading and advection, the model has been developed and applied to Kyungki-Bay near Incheon Harbor. The initial spreading is estimated by using an empirical formula. The depth-averaged momentum equations are solved numerically for the volume transport velocities, in which the $M_2$ tide is the main driving source. A staggered grid system is adopted fur spatial discretization and the half-time method is implemented for time marching. The numerical result is visualized with the help of animation and thus the contaminated area is displayed on a monitor in time sequence. The input data are the time, the location and the volume of spill accident as well as environmental data such as md and $M_2$ tide.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.12
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• pp.987-997
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• 2019

Walk score, walkablity index of built environmental condition, has developed and used in everyday life in United States. The purpose of this study is to produce walk score in Seoul, and to develop computer-based walk score system for improving it's usage. This study covers city of Seoul, and the unit of spatial analysis is 100m × 100m grid cell. This study uses same methodology with walk score in US, the Geographic Information Systems(GIS) is used for calculating the values of walk score(N=58,062). This study implemented Java-based system that utilizes walk score dataset(latitude, longitude, and walk score). This system provided search functions including both lat/long-based and address-based options. Meanwhile, this system was designed to provide the closest value of walk score in dataset if location did not match the certain points in dataset. This study has significance to provide walk score system being easily available to all.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.227-234
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• 2019

The purpose of this study is to present a block type smart classroom model for comprehensive supply of educational contents, classroom environment and ICT technology in African countries where educational infrastructure is weak. It will provide a contextual solution that integrates learning management, power management, and classroom environment management systems, and will be a convergence model that can optimize economic and non-economic conditions for different African countries. It can be expected to enhance utilization as it is a differentiated model from existing classrooms with a single container, as well as independent research and development centered on services, content, and solutions. Through this integrated research process, we can overcome the spatial and functional limitations appearing in single container classrooms and build a flexible space for advanced e-learning technology. The depth and scope of the follow-up study can be carried by investigating the performance and models that are in line with the educational and infrastructure conditions of the various regions.

• Journal of the Korean Society of Propulsion Engineers
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• v.22 no.6
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• pp.84-93
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• 2018

Three-dimensional (3D) numerical simulations have been carried out to study how coolant injection conditions influence the cooling efficiency and projectile ejection performance in a mixture-gas ejection system (or gas-steam launch system). The 3D single-phase computational model was verified using a 1D model constructed with reference to the previous research and then a two-phase flow computation simulating coolant injection on to hot gas was performed using a DPM (Discrete Phase Model). As a result of varying the coolant flow rate and number of injection holes, cooling efficiency was improved when the number of injection holes were increased. In addition, the change of the coalescence frequency and spatial distribution of coolant droplets caused by the injection condition variation resulted in a change of the droplet diameter, affecting the evaporation rate of coolant. The evaporation was found to be a critical factor in the design optimization of the ejection system by suppressing the pressure drop while the temperature decreases inside the breech.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.1
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• pp.17-25
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• 2019

An intake of Aircraft becomes S-shaped geometry due to spatial limitation or procuring survivability. But curvature of the S-shaped geometry makes secondary flow or flow separation which is the cause of non-uniform pressure distribution. In this study, boundary layer suction is applied to RAE M 2129 S-Duct by attaching sub duct. Design variable is suction location and angle. A mass flow rate drawn out by suction at the sub duct outlet is constant over every model. A grid dependency test was conducted to verify validity of computation. The comparison among the CFD (Computation Fluid Dynamics), ARA experimental result, and ARA computation result of non-dimensional pressure distribution on the Port side and Starboard Side confirmed the validity of CFD. In this study, Distortion Coefficient was used for evaluating aerodynamic performance of S-Duct. The analysis, which was about flow separation, vortex, mass flow rate distribution, and pressure distribution were also investigated. Maximum 26.14% reduction in Distortion Coefficient was verified.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.49-57
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• 2019

The International Maritime Organization is developing a maritime safety system called eNavigation in order to effectively respond to accidents occurring on board vessels. Korea is actively participating in the development of eNavigation and is developing Korean eNavigation by adding its own concept to eNavigation of the IMO. eNavigation is designed to provide various functions for marine safety. The data required for each function is various such as spatial data, relational data, file, weather grid. Therefore, there is a need for a system that can appropriately provide heterogeneous data suitable for eNavigation to each eNavigation's service system. In this paper, we analyzed the kinds of data needed for e-Navigation and designed the architecture of heterogeneous data service system that could provide these data properly.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.2
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• pp.1-11
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• 2019

Remote sensing products have long been used to monitor and forecast natural disasters. Satellite-derived rainfall products are becoming more accurate as space and time resolution improve, and are widely used in areas where measurement is difficult because of the periodic accumulation of images in large areas. In the case of North Korea, there is a limit to the estimation of precipitation for unmeasured areas due to the limited accessibility and quality of statistical data. CHIRPS (Climate Hazards Group InfraRed Precipitation with Stations) is global satellite-derived rainfall data of 0.05 degree grid resolution. It has been available since 1981 from USAID (U.S. Agency for International Development), NASA (National Aeronautics and Space Administration), NOAA (National Oceanic and Atmospheric Administration). This study evaluates the applicability of CHIRPS rainfall products for South Korea and North Korea by comparing CHIRPS data with ground observation data, and analyzing temporal and spatial drought trends using the Standardized Precipitation Index (SPI), a meteorological drought index available through CHIRPS. The results indicate that the data set performed well in assessing drought years (1994, 2000, 2015 and 2017). Overall, this study concludes that CHIRPS is a valuable tool for using data to estimate precipitation and drought monitoring in Korea.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.161-161
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• 2023

Bias correction of values is a necessary step in downscaling coarse and systematically biased global climate models for use in local climate change impact studies. In addition to univariate bias correction methods, many multivariate methods which correct multiple variables jointly - each with their own mathematical designs - have been developed recently. While some literature have focused on the inter-comparison of these multivariate bias correction methods, none have focused extensively on the effect of diverse configurations (i.e., different combinations of input variables to be corrected) of climate variables, particularly high-dimensional ones, on the ability of the different methods to remove biases in uni- and multivariate statistics. This study evaluates the impact of three configurations (inter-variable, inter-spatial, and full dimensional dependence configurations) on four state-of-the-art multivariate bias correction methods in a national-scale domain over South Korea using a gridded approach. An inter-comparison framework evaluating the performance of the different combinations of configurations and bias correction methods in adjusting various climate variable statistics was created. Precipitation, maximum, and minimum temperatures were corrected across 306 high-resolution (0.2°) grid cells and were evaluated. Results show improvements in most methods in correcting various statistics when implementing high-dimensional configurations. However, some instabilities were observed, likely tied to the mathematical designs of the methods, informing that some multivariate bias correction methods are incompatible with high-dimensional configurations highlighting the potential for further improvements in the field, as well as the importance of proper selection of the correction method specific to the needs of the user.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.65-76
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• 2023

This paper identifies the aspects of living environment elements (PM^2.5, PM¹⁰, Noise) throughout Seoul and the urban characteristics that affect them by utilizing the big data of the S-Dot sensors in Seoul, which has recently become a hot topic. In other words, it proposes a big data based urban computing research methodology and research direction to confirm the relationship between urban characteristics and living environments that directly affect citizens. The temporal range is from 2020 to 2021, which is the available range of time series data for S-Dot sensors, and the spatial range is throughout Seoul by 500mX500m GRID. First of all, as part of analyzing specific living environment patterns, simple trends through EDA are identified, and cluster analysis is conducted based on the trends. After that, in order to derive specific urban planning factors of each cluster, basic statistical analysis such as ANOVA, OLS and MNL analysis were conducted to confirm more specific characteristics. As a result of this study, cluster patterns of environment elements(PM^2.5, PM¹⁰, Noise) and urban factors that affect them are identified, and there are areas with relatively high or low long-term living environment values compared to other regions. The results of this study are believed to be a reference for urban planning management measures for vulnerable areas of living environment, and it is expected to be an exploratory study that can provide directions to urban computing field, especially related to environmental data in the future.

• Atmosphere
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• v.33 no.1
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• pp.61-72
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• 2023

Accurate estimation of forest carbon stocks is important in establishing greenhouse gas reduction plans. In this study, we estimate the spatial distribution of forest carbon stocks using machine learning techniques based on high-resolution remote sensing data and detailed field survey data. The high-resolution remote sensing data used in this study are Landsat indices (EVI, NDVI, NDII) for monitoring vegetation vitality and Shuttle Radar Topography Mission (SRTM) data for describing topography. We also used the forest growing stock data from the National Forest Inventory (NFI) for estimating forest biomass. Based on these data, we built a model based on machine learning methods and optimized for Korean forest types to calculate the forest carbon stocks per grid unit. With the newly developed estimation model, we created forest carbon stocks maps and estimated the forest carbon stocks in South Korea. As a result, forest carbon stock in South Korea was estimated to be 432,214,520 tC in 2020. Furthermore, we estimated the loss of forest carbon stocks due to the Donghae-Uljin forest fire in 2022 using the forest carbon stock map in this study. The surrounding forest destroyed around the fire area was estimated to be about 24,835 ha and the loss of forest carbon stocks was estimated to be 1,396,457 tC. Our model serves as a tool to estimate spatially distributed local forest carbon stocks and facilitates accounting of real-time changes in the carbon balance as well as managing the LULUCF part of greenhouse gas inventories.