• Journal of the Korean Institute of Gas
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• v.26 no.4
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• pp.36-40
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• 2022

Recently, the biggest topic in the industry is the area of industrial safety and health management. Since city gas is flammable gas and has a high risk of fire and explosion, much effort is required to prevent serious industrial and citizenry disasters. As part of city gas safety management, this study attempted to quantitatively predict the scope and degree of damage in the event of an explosion accident caused by city gas leakage through the Consequence Analysis. As a result, there was a difference in the accident result value according to various leakage conditions such as pressure and weather conditions. Through this study, a scenario of explosion due to city gas leakage will be prepared when performing city gas safety management work and used to prepare more effective accident prevention and emergency action plans.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.68.1-68.1
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• 2019

Turbulence plays a crucial role in controlling star formation as it produces density fluctuation as well as non-thermal pressure against gravity. Therefore, turbulence controls the mode and tempo of star formation. However, despite a plenty of previous studies, the properties of turbulence remain poorly understood. As part of the Taeduk Radio Astronomy Observatory (TRAO) Key Science Program (KSP), "mapping Turbulent properties In star-forming MolEcular clouds down to the Sonic scale (TIMES; PI: Jeong-Eun Lee)", we mapped the Orion A and the Ophiuchus clouds, in three sets of lines (13CO 1-0/C18O 1-0, HCN 1-0/HCO+ 1-0, and CS 2-1/N2H+ 1-0) with a high-velocity resolution (~0.1 km/s) using the TRAO 14-m telescope. The mean Trms for the observed maps are less than 0.25 K, and all these maps show uniform Trms values throughout the observed area. These homogeneous and high signal-to-noise ratio data provide the best chance to probe the nature of turbulence in two different star-forming clouds, the Orion A and Ophiuchus clouds. We present comparisons between the line intensities of different molecular tracers as well as the results of a Principal Component Analysis (PCA).

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.59.2-59.2
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• 2020

Disks around protostars are the birthplace of planets. The first step toward planet formation is grain growth from ㎛-sized grains to mm/cm-sized grains in a disk, particularly in dense regions. In order to study whether grains grow and segregate at the protostellar stage, we investigate the ALMA Band 3 (3.1 mm) and 7 (0.87 mm) dust continuum observations of the protostellar disk WL 17 in ρ Ophiuchus L1688 cloud. As reported in a previous study, the Band 3 image shows substructures: a narrow ring and a large central hole. On the other hand, the Band 7 image shows different substructures: a non-axisymmetric ring and an off-center hole. The two-band observations provide a mean spectral index of 2.3, which suggests the presence of mm/cm-sized large grains. Its non-axisymmetric distribution may imply dust segregation between small and large grains. We perform radiative transfer modeling to examine the size and spatial distributions of dust grains in the WL 17 disk. The best-fit model suggests that large grains (>1 cm) exist in the disk, settling down toward the midplane, whereas small grains (~10 ㎛) well mixed with gas are distributed off-center and non-axisymmetrically in a thick layer. The low spectral index and the modeling results suggest that grains rapidly grow at the protostellar stage and that grains differently distribute depending on sizes, resulting in substructures varying with observed wavelengths. To understand the differential grain distributions and substructures, we discuss the effects of the protoplanet(s) expected inside the large hole and the possibility of gravitational instability.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.279-286
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• 2013

This paper introduces a new method for identification of building energy performance problems. The presented method is based on automated analysis and visualization of deviations between actual and expected energy performance of the building using EPAR (Energy Performance Augmented Reality) models. For generating EPAR models, during building inspections, energy auditors collect a large number of digital and thermal imagery using a consumer-level single thermal camera that has a built-in digital lens. Based on a pipeline of image-based 3D reconstruction algorithms built on GPU and multi-core CPU architecture, 3D geometrical and thermal point cloud models of the building under inspection are automatically generated and integrated. Then, the resulting actual 3D spatio-thermal model and the expected energy performance model simulated using computational fluid dynamics (CFD) analysis are superimposed within an augmented reality environment. Based on the resulting EPAR models which jointly visualize the actual and expected energy performance of the building under inspection, two new algorithms are introduced for quick and reliable identification of potential performance problems: 1) 3D thermal mesh modeling using k-d trees and nearest neighbor searching to automate calculation of temperature deviations; and 2) automated visualization of performance deviations using a metaphor based on traffic light colors. The proposed EPAR v2.0 modeling method is validated on several interior locations of a residential building and an instructional facility. Our empirical observations show that the automated energy performance analysis using EPAR models enables performance deviations to be rapidly and accurately identified. The visualization of performance deviations in 3D enables auditors to easily identify potential building performance problems. Rather than manually analyzing thermal imagery, auditors can focus on other important tasks such as evaluating possible remedial alternatives.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.837-847
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• 2023

In this study, we explored a method for assessing the extent of damage caused by chemical substances at an accident site through the use of a vegetation index. Data collection involved the deployment of two different drone types, and the damaged area was determined using photogrammetry technology from the 3D point cloud data. To create a vegetation index image, we utilized spectral band data from a multi-spectral sensor to generate an orthoimage. Subsequently, we conducted statistical analyses of the accident site with respect to the damaged area using a predefined threshold value. The Kappa values for the vegetation index, based on the near-infrared band and the green band, were found to be 0.79 and 0.76, respectively. These results suggest that the vegetation index-based approach for analyzing damage areas can be effectively applied in investigations of chemical accidents.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.235-241
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• 2013

$NO_2$ vertical column densities were retrieved via ground based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements for the first time for 6 months over the spring season in 2007 and 2008 in Seoul, one the megacities in the Northeast Asia. The retrieved $NO_2$ vertical column densities were compared with those obtained from space borneOzone Monitoring Instrument (OMI). Over the entire measurement period, the $NO_2$ vertical column densities measured by MAX-DOAS ranged from $1.0{\times}10^{15}molec{\cdot}cm^{-2}$ to $6.0{\times}10^{16}molec{\cdot}cm^{-2}$ while those obtained by OMI ranged $1.0{\times}10^{15}molec{\cdot}cm^{-2}$ to $7.0{\times}10^{16}molec{\cdot}cm^{-2}$. The correlation coefficient between $NO_2$ vertical column densities obtained from MAX-DOAS and OMI is 0.73 for the entire measurement period whereas the correlation coefficient of 0.85 is found for the dates under the clear sky condition. The cloudy condition is thought to play a major role in increase in uncertainty of the retrieved OMI $NO_2$ vertical column densities since air mass factor may induce high uncertainty due to the lack of cloud and aerosol vertical distribution information.

• Journal of Satellite, Information and Communications
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• v.2 no.2
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• pp.29-35
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• 2007

COMS satellite is a multipurpose satellite in the geostationary orbit, which accommodates multiple payloads of the Ka band Satellite Communication Payload, Meteorological Imager, and Geostationary Ocean Color Imager into a single spacecraft platform. In this paper, Korea's first innovative geostationary Communication, Ocean and Meteorological Satellite (COMS) program is introduced which is fully funded by Korean Government. The satellite platform is based on the Astrium EUROSTAR 3000 communication satellite, but creatively combined with MARS Express satellite platform to accommodate three different payloads efficiently for COMS. The goals of the Ka band satellite communication mission are to in-orbit verify the performances of advanced communication technologies and to experiment wide-band multi-media communication service. The Meteorological Imager mission is to continuously extract meteorological products with high resolution and multi-spectral imager, to detect special weather such as storm, flood, yellow sand, and to extract data on long-term change of sea surface temperature and cloud. The Geostationary Ocean Color Imager mission aims at monitoring of marine environments around Korean peninsula, production of fishery information (Chlorophyll, etc.), and monitoring of long-term/short-term change of marine ecosystem. The system design difficulties are in the different kinds of payload mission requirements of communication and remote sensing purposes and how to combine them into one to meet the overall satellite requirements. In this paper, Ka band communication payload system is more highlighted.

• Journal of Astronomy and Space Sciences
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• v.14 no.2
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• pp.330-346
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• 1997

Korea Multi-Purpose Satellite I (KOMPSAT-I, the first multi-purpose Korean satellite) will be launched in the third quarter of 1999, which is operated on the sun-synchronous orbit for cartography, ocean color monitoring, and space environment monitoring. The main mission of Electro-Optical Camera(EOC) which is one of KOMPSAT-I sensors is to provide images for the production of scale maps of Korea. EOC collects panchromatic imagery with the ground sample distance of 6.6m at nadir through visible spectral band of 510~730nm. For determining KOMPSAT-I crossing time over Korea, this study examines the diurnal variation of solar and atmospheric variables that can exert a great influence on the EOC imagery. The results are as follows: 1) After 10:30 a.m. at the winter solstice, solar zenith angle is less than $70^{\circ}$ and expected flux of EOC spectral band over land for clear sky is greater than about $2.4mW/cm^2$. 2) For daytime the distribution of cloud cover (clear sky) shows minimum (maximum) at about 11:00 a.m. Although the occurrence frequency of poor visibility by fog decreases from early morning toward noon, its effect on the distribution of clear sky is negligible. From the above examination it is concluded that determining KOMPSAT-I crossing time over Korea between 10:30 and 11:30 a.m. is adequate.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.3 s.303
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• pp.39-52
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• 2005

In this paper, a registration method is presented to register partial 3D point clouds, acquired from a multi-view camera, for 3D reconstruction of an indoor environment. In general, conventional registration methods require a high computational complexity and much time for registration. Moreover, these methods are not robust for 3D point cloud which has comparatively low precision. To overcome these drawbacks, a projection-based registration method is proposed. First, depth images are refined based on temporal property by excluding 3D points with a large variation, and spatial property by filling up holes referring neighboring 3D points. Second, 3D point clouds acquired from two views are projected onto the same image plane, and two-step integer mapping is applied to enable modified KLT (Kanade-Lucas-Tomasi) to find correspondences. Then, fine registration is carried out through minimizing distance errors based on adaptive search range. Finally, we calculate a final color referring colors of corresponding points and reconstruct an indoor environment by applying the above procedure to consecutive scenes. The proposed method not only reduces computational complexity by searching for correspondences on a 2D image plane, but also enables effective registration even for 3D points which have low precision. Furthermore, only a few color and depth images are needed to reconstruct an indoor environment.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.311-323
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• 2023

Oil spill accidents can cause various environmental issues, so it is important to quickly assess the extent and changes in the area and location of the spilled oil. In the case of oil spill detection using satellite imagery, it is possible to detect a wide range of oil spill areas by utilizing the information collected from various sensors equipped on the satellite. Previous studies have analyzed the reflectance of oil at specific wavelengths and have developed an oil spill index using bands within the specific wavelength ranges. When analyzing multiple images before and after an oil spill for monitoring purposes, a significant amount of time and computing resources are consumed due to the large volume of data. By utilizing Google Earth Engine, which allows for the analysis of large volumes of satellite imagery through a web browser, it is possible to efficiently detect oil spills. In this study, we evaluated the applicability of four types of oil spill indices in the area of various land cover using Sentinel-2 MultiSpectral Instrument data and the cloud-based Google Earth Engine platform. We assessed the separability of oil spill areas by comparing the index values for different land covers. The results of this study demonstrated the efficient utilization of Google Earth Engine in oil spill detection research and indicated that the use of oil spill index B ((B3+B4)/B2) and oil spill index C (R: B3/B2, G: (B3+B4)/B2, B: (B6+B7)/B5) can contribute to effective oil spill monitoring in other regions with complex land covers.