• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.618-619
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• 2010

LED는 기존의 발광원에 비해 훨씬 높은 파워와 효율성으로 인해 최근 들어 각종 조명이나 교통신호 등에서 사용이 급증하고 있다. LED 재료를 위해 지금까지 여러가지가 연구되어 왔는데, 갈륨 질화물 (Gallium Nitride, GaN)에 기반한 시스템이 최근들어 가장 큰 관심을 받고 있다. GaN 방식은 열적으로 매우 안정성이 있고, 1.9 ~ 6.2 eV 범위의 넓은 밴드의 Gap, 그리고 인듐이나 알루미늄과 결합하여 청, 녹, 백색등의 다양한 빛을 발생할 수 있는 장점을 가지고 있다. 예를 들어 청색 LED는 광학 방식의 기록매체에, 백색 LED는 기존의 조명램프의 대체용으로 활용이 가능하다. 이러한 장점 덕분에 GaN기반 LED 시장은 1994년에 최초로 상용화 된 이래 최근 급격한 성장을 보여 왔다. 그러나 GaN은 다른 III~V 타입의 반도체 재료와는 달리 재료가 성장하기 위해 사파이어와 같은 별도의 기판을 필요로 하는 문제가 있다. 이것은 결국 전위발생과 같은 격자의 부조화 같은 문제를 야기하여 결국 LED의 성능을 떨어뜨리는 요인이 된다. 이러한 문제를 해결하기 위해 HVPE(Hydride Vapor Phase Epitaxy) 방법이 개발되었는데, 이 방법은 시간당 100 미크론의 매우 빠른 성장속도로 높은 두께의 레이어를 만드는 장점이 있다. 이렇게 성장된 GaN 레이어는 베이스 기판에서 쉽게 분리되어 활용이 가능하다. 그러나 HVPE 기술은 성장 공정에서 두께를 균일하게 만들도록 제어하는 것이 매우 어렵다는 문제가 있다. 따라서 HVPE 방식에서는 이러한 조건을 만족시키기 위해 반응현상에 대한 물리적 해석을 토대로 공정조건을 정밀하게 설계해야 한다. 이를 위해 최근에 실험 또는 시뮬레이션을 활용하여 이러한 공정조건을 향상시키기 위한 여러 연구가 진행되었다. 본 연구에서는 이러한 연구의 일환으로 반응로에 투입되는 여러 기체의 유량과 존별 주변온도 조건을 입력변수로 하고, 이들이 GaN 성장에 미치는 영향을 분석하였다. HVPE 시스템에서 가장 이상적인 목표는 반응기체가 층류유동을 유지하면서 대부분의 반응이 기판위에서 이뤄지며, 기판위에서 성장되는 재료의 두께가 균일하게 되는 것이다. 입력변수들이 이러한 결과에 어떠한 영향을 미치는 지 분석하기 위해 전산유체역학(CFD, Computational Fluid Dynamics)을 수행하는 상용코드 FLUENT를 사용하였다. 보다 실제에 가까운 해석을 위해서는 기체간의 화학반응을 포함해야 하나, 해석의 편의와 효율을 위해 본 연구에서는 열 및 유동해석만을 수행하였다. 한편 실제 반응로의 우수성은 성장속도와 두께분포의 균일도를 통해 평가된다. CFD 해석을 통해 이들을 분석하기 위해 기존에 수행한 실험조건을 해석하고 해석결과의 유동패턴/압력분포를 실험결과의 성장속도/두께분포와 비교하고, 이중에서 관련성이 높은 해석결과변수를 우수성 평가에 활용하였다. 기존의 실험결과를 토대로 이러한 중요 결과변수와 함께 이들에 대한 목표값이 도출되고 나면, 입력 공정조건 - 사용기체의 유량과 주변온도 조건 - 에 대해 실험계획(DOE,Design of Experiment)을 수립하고 목표성능을 구현하기 위한 최적설계를 수행할 수 있다. 일반적으로 CFD를 통해 최적의 설계나 공정조건을 탐색하는 작업은 1회의 CFD 계산시간이 매우 오래 소요되기 때문에 쉽지 않다. 그러나 본 연구에서는 CFD와 DOE의 적절한 조합을 통해 적은 수의 해석을 가지고도 원하는 결과를 효율적으로 얻는 것이 가능함을 입증하고자 한다. 본 발표에서는 아직 이러한 연구가 완성되지 않은 시점에서 제반 연구개요를 소개하고 현 시점까지의 연구 결과 및 향후 계획을 소개하고자 한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.487-495
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• 2017

The thermal characteristics of the electrodeless lamp are one of the main factors that determine the design and performance of the lamp. The coupler changes the impedance characteristic by heat and its use temperature is usually within about $150^{\circ}C$. In this study, we observed the phenomenon when the coupler was exposed at a temperature of $150^{\circ}C$ or higher, which has not been discussed so far. Two types of coupler A and coupler B with different spacing between the inner tube and the coupler were analyzed for electrical, thermal and optical properties and deterioration characteristics with different heat and heat shielding conditions. First, the impedance of the system is obtained and used as a criterion for analyzing the electrical characteristics through it. The diameters of the two types of couplers are 1 mm, and the experimental result shows that the coupler diameter is 1 mm, which can cancel out the loss of the magnetic field strength. Therefore, based on these results, when the coupler is exposed to high temperature of about $200^{\circ}C$, the efficient design method corresponding thereto is proposed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.766-773
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• 2021

Chemicals, such as ammunition, are disposable items that cannot be reused because of their operational characteristics. The reliability of the test process and test results are important factors in evaluating the performance of guns and ammunition. The pressure after firing is a crucial value in an acceptance test of guns and ammunition performance; hence, accurate measurements are required. The pressure in the artillery is measured using the copper crusher gauge. The compression amount of copper is converted into a pressure by either a length-pressure conversion table or conversion formula. Therefore, the exact measurement of the squeeze of the copper crusher is related directly to the correct estimate of the pressure. Currently, the pressure is measured manually by the operator, which always includes some human error. In this study, the cause of the measurement error was analyzed, and the automatic measuring system for copper crusher deformation was developed to minimize the error elements. A copper crusher could be measured using the probe sensor and CCD camera, and the Jig for stable positioning was also designed. A designated SW was also developed for the system operating and measurement-analysis. This measuring system through this study may be used for an ammunition stockpile reliability test and gun/ammunition acceptance test.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.7
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• pp.507-514
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• 2022

The EO/IR targeting pod mounted on a fighter to acquire information about tactical targets is typically mounted and operated at the bottom of the aircraft fuselage. Since the aircraft equipped with such an external attachment has complexed aerodynamic and inertial characteristics compared to the aircraft flying without an external attachment, a method of system performance analyses is required to identify development risk factors in the early stages of development and reflect them in the design. In this study, a development plan was presented to provide the necessary modeling and simulation tools to develop a pod that can acquire measurement data stably in a highly maneuverable environment. The limiting operating conditions of the pods mounted on the highly maneuverable aircraft were derived, the aerodynamics and inertial loads of the mounted pods were analyzed according to the limiting operating conditions, and a flight data generation and transmission system were developed by simulating the mission of the aircraft equipped with the mounted pods.

• Composites Research
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• v.35 no.2
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• pp.93-97
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• 2022

The application of infrared heating in the hot press forming of the thermoplastic composites is conducive to productivity with high-speed heating. However, high energy, high forming temperature, and high-speed heating derived from infrared heating can cause material degradation and deteriorate properties such as re-melting performance. Therefore, this study was conducted to optimize the process conditions of the hot press forming suitable for carbon fiber reinforced polyetherketoneketone(CF/PEKK) composites that are actively researched and developed as high-performance aviation materials. Specifically, the degradation mechanisms and properties that may occur in infrared high-speed heating were evaluated through morphological and thermal characteristics analysis and mechanical performance tests. The degradation mechanism was analyzed through morphological investigation of the crystal structure of PEKK. As a result, the size of the spherulite decreased as the degradation progressed, and finally, the spherulite disappeared. In thermal characteristics, the melting temperature, crystallization temperature and heat of crystallization tend to decrease as degradation progresses, and the crystal structure disappeared under long-term exposure at 460℃. In addition, the low bonding strength was observed on the degraded surface, and the bonding surfaces of PEKK did not melt intermittently. In conclusion, it was confirmed that the CF/PEKK composite material degraded at 420℃ in the infrared high-speed heating. Furthermore, the spherulite experienced morphological changes and the re-melting properties of thermoplastic materials were degraded.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1257-1271
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• 2022

Recently, many Earth observation optical satellites have been developed, as their demands were increasing. Therefore, a rapid preprocessing of satellites became one of the most important problem for an active utilization of satellite images. Satellite image matching is a technique in which two images are transformed and represented in one specific coordinate system. This technique is used for aligning different bands or correcting of relative positions error between two satellite images. In this paper, we propose an automatic image matching method among satellite images with different ground sampling distances (GSDs). Our method is based on improved feature matching and robust estimation of transformation between satellite images. The proposed method consists of five processes: calculation of overlapping area, improved feature detection, feature matching, robust estimation of transformation, and image resampling. For feature detection, we extract overlapping areas and resample them to equalize their GSDs. For feature matching, we used Oriented FAST and rotated BRIEF (ORB) to improve matching performance. We performed image registration experiments with images KOMPSAT-3A and RapidEye. The performance verification of the proposed method was checked in qualitative and quantitative methods. The reprojection errors of image matching were in the range of 1.277 to 1.608 pixels accuracy with respect to the GSD of RapidEye images. Finally, we confirmed the possibility of satellite image matching with heterogeneous GSDs through the proposed method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.695-706
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• 2022

Medium and high-resolution optical satellites have proven their effectiveness in detecting wildfire areas. However, smoke plumes generated by wildfire scatter visible light incidents on the surface, thereby interrupting accurate monitoring of the area where wildfire occurs. Therefore, a technology to extract smoke in advance is required. Deep learning technology is expected to improve the accuracy of smoke extraction, but the lack of training datasets limits the application. However, for clouds, which have a similar property of scattering visible light, a large amount of training datasets has been accumulated. The purpose of this study is to develop a smoke extraction technique using deep learning, and the limits due to the lack of datasets were overcome by using a cloud dataset on transfer learning. To check the effectiveness of transfer learning, a small-scale smoke extraction training set was made, and the smoke extraction performance was compared before and after applying transfer learning using a public cloud dataset. As a result, not only the performance in the visible light wavelength band was enhanced but also in the near infrared (NIR) and short-wave infrared (SWIR). Through the results of this study, it is expected that the lack of datasets, which is a critical limit for using deep learning on smoke extraction, can be solved, and therefore, through the advancement of smoke extraction technology, it will be possible to present an advantage in monitoring wildfires.

• Applied Chemistry for Engineering
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• v.34 no.1
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• pp.80-85
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• 2023

New yellow quinoline-dione dye derivatives were designed and synthesized for use in image sensor color filters. The synthesized compounds have a basic chemical structure composed of quinoline and dione groups. New materials were evaluated on the basis of their optical and thermal properties under conditions mimicking those of a commercial device fabrication process. A comparison of their related performances revealed that, between the two prepared compounds, 2-(3-hydroxyquinolin-2(1H)-ylidene)-1H-indene-1,3(2H)-dione (HQIDO) exhibited the superior performance as an image sensor color filter material, including a solubility greater than 0.5 wt% in propylene glycol monomethyl ether acetate solvent and a high decomposition temperature of 298 ℃, respectively. The results suggest that HQIDO can be used as a yellow dye additive in an image sensor colorant.

• Applied Chemistry for Engineering
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• v.34 no.6
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• pp.590-595
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• 2023

Novel aromatic imine derivatives with yellow were designed and synthesized for their potential application in color filters for image sensors. The synthesized compounds possessed chemical structures using aromatic imine groups. This innovative material was evaluated thoroughly, considering its optical and thermal properties under conditions similar to commercial device manufacturing processes. Following a rigorous performance evaluation, it was found that (E)-3-methyl-4-((3-methyl-5-oxo-1-phenyl-1H-pyrazol-4(5H)-ylidene)methyl)-1-phenyl-1H-pyrazol-5(4H)-one, abbreviated as MOPMPO, exhibited an impressive solubility of 0.5 wt% in propylene glycol monomethyl ether acetate, predominantly utilized as the solvent in the industry. Furthermore, MOPMPO showed exceptional performance as a color filter material for image sensors, having a high decomposition temperature of 290 ℃. These data unequivocally establish MOPMPO as a viable yellow dye additive for coloring materials in image sensor applications.