• 한국전산구조공학회논문집
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• 제22권1호
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• pp.35-44
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• 2009

본 논문에서는 대규모 3차원 구조해석에 필요한 병렬 유한요소해석을 위한 영역분할법의 적용에 대해 묘사하였다. 영역분할법을 사용한 병렬 유한요소법 시스템을 개발하였다. 절점 생성시, 절점들간의 거리가 특정절점에서의 공간함수와 같아지면 절점이 생성되어 진다. 이 절점공간함수는 퍼지지식처리에 의해 조절되어 진다. 기본적인 요소생성은 데로우니 삼각화 기법을 적용하였다. 자동요소생성 시스템을 이용한 영역분할법은 3차원 해석에 큰 도움이 된다. 공간함수와 유사하게 절점들간의 유한요소해석을 위한 병렬 수치 알고리즘으로서 영역분할법을 전체의 해석영역을 완전히 여러 개의 작은 영역으로 겹치지 않게 나누는 공역구배인 반복적 솔버와 결합시켰다. 개발된 시스템의 효용성에 대한 성능을 몇 가지 예를 통해 제시하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.49-50
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• 2011

본 논문에서는 WT(Wavelet Transform)와 SVD(Singular Value Decomposition)를 함께 사용한 WSVD(Wavelet Singular Value Decomposition)를 이용하여 발전기 탈락 시의 전압 변동 특성을 분석하였다. WSVD 특성 분석을 위해 부산 지역의 345kV급 송전계통을 EMTP-RV로 모델링하였으며, 이 계통모델에서 발전기 탈락을 모의하였다. MATLAB을 통해 이 때 측정된 전압의 WSVD를 계산하여 발전기 탈락에 따른 특성을 분석하였다.

• 대한수학회보
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• 제55권4호
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• pp.1221-1230
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• 2018

We derive a sharp decomposition formula for the state polytope of the Hilbert point and the Hilbert-Mumford index of reducible varieties by using the decomposition of characters and basic convex geometry. This proof captures the essence of the decomposition of the state polytopes in general, and considerably simplifies an earlier proof by the authors which uses a careful analysis of initial ideals of reducible varieties.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제18권3호
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• pp.209-224
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• 2014

In this paper, the solution of time fractional telegraph equation is obtained by using Adomain decomposition method and compared with various other method to determine the efficiency of Adomain decomposition method. These methods are used to obtain the series solutions. Finally, results are analysed by plotting the solutions for various fractional orders.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1997년도 추계학술대회 논문집
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• pp.389-392
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• 1997

Glutaronitrile(GN) was introduced to diglycidyl ether of bisphenol A(DGEBA)/ 4,4'-methylene dianiline(MDA) system to improve toughness. Effects of GN contents on thermal decomposition of epoxy resin system were investigated. To study the characteristics of thermal decomposition, thermo-gravimetric analysis(TGA) and Kissinger equation were used. Thermal degradation temperatures were about 365$^{\circ}C$ regardless of GN contents. Activation energies of thermal decomposition in epoxy resin system were almost constant below 10 phr and decreased above 15 phr.

• KEPCO Journal on Electric Power and Energy
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• 제8권2호
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• pp.119-126
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• 2022

A growing number of gas-insulated transformers in underground power substations in urban areas are approaching 20 years of operation, the time when failures begin to occur. It is thus essential to prevent failure through accurate condition diagnosis of the given facility. Various solid insulation materials exist inside of the transformers, and the generated decomposition gas may differ for each gas-insulated equipment. In this study, a simulation system was designed to analyze the deterioration characteristics of SF₆ decomposition gas and insulation materials under the conditions of partial discharge and thermal fault for diagnosis of gas-insulated transformers. Degradation characteristics of the insulation materials was determined using an automatic viscometer and FT-IR. The analysis results showed that the pattern of decomposition gas generation under partial discharge and thermal fault was different. In particular, acetaldehyde was detected under a thermal fault in all types of insulation, but not under partial discharge or an arc condition. In addition, in the case of insulation materials, deterioration of the insulation itself rapidly progressed as the experimental temperature increased. It was confirmed that it was possible to diagnose the internal discharge or thermal fault occurrence of the transformer through the ratio and type of decomposition gas generated in the gas-insulated transformer.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2006년도 제26회 춘계학술대회논문집
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• pp.45-49
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• 2006

탄소/페놀릭 복합재료가 높은 온도에서 열분해 되는 현상을 연구하기 위하여 열중량분석기(TGA)가 이용되었다. 높은 온도와 다양한 하중조건에서 운용되는 고체 추진기관의 열방호 시스템으로 적합한 재료를 분석하고 개발하는데 연구목적이 있다. 실제 연소조건과 유사한 온도 상승속도를 고려하기 위하여 열분해 특성상수 값은 1000 K/min인 경우로 예측된 값을 FEM 해석코드 자료로 활용하였다. 온도 분포는 실험 결과 값과 같은 거동을 보였으며 열분해 깊이는 ${\pm}1mm$ 이내에서 해석 결과와 잘 일치 하였다.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2005년도 제25회 추계학술대회논문집
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• pp.22-25
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• 2005

열용량분석기(TGA)를 사용하여 고온에서의 탄소/페놀릭 복합재료의 열분해를 연구하였다. 온도상승 속도는 5, 10, 15, 30 그리고 $50^{\circ}C/min$ 이었으며 온도 상승속도가 증가할수록 최대 열분해 반응의 온도도 상승하였다. 열분해반응에서 얻어진 자료를 근간으로 물리-수학적인 모델을 제시하였으며 모델의 실효성을 판단하기 위하여 고체 추진기관 노즐의 연소시험을 통하여 내부 온도 분포 및 밀도 분포 자료를 해석 모델과 비교하였다. 향후 연구를 통하여 이러한 열분해 인자는 고체 추진기관의 열 및 구조 해석의 입력 자료로 활용이 될 것이다.

• 한국공간구조학회논문집
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• 제19권2호
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• pp.101-108
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• 2019

In this paper, the characteristic of intrinsic mode function(IMF) and its orthogonalization of ensemble empirical mode decomposition(EEMD), which is often used in the analysis of the non-linear or non-stationary signal, has been studied. In the decomposition process, the orthogonal IMF of EEMD was obtained by applying the Gram-Schmidt(G-S) orthogonalization method, and was compared with the IMF of orthogonal EMD(OEMD). Two signals for comparison analysis are adopted as the analytical test function and El Centro seismic wave. These target signals were compared by calculating the index of orthogonality(IO) and the spectral energy of the IMF. As a result of the analysis, an IMF with a high IO was obtained by GSO method, and the orthogonal EEMD using white noise was decomposed into orthogonal IMF with energy closer to the original signal than conventional OEMD.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.150-150
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• 2022

This study investigates the roles of decomposition methods on high accuracy in daily rainfall prediction from light gradient boosting machine (LightGBM) algorithm. Here, empirical mode decomposition (EMD) and singular spectrum analysis (SSA) methods were considered to decompose and reconstruct input time series into trend terms, fluctuating terms, and noise components. The decomposed time series from EMD and SSA methods were used as input data for LightGBM algorithm in two hybrid models, including empirical mode-based light gradient boosting machine (EMDGBM) and singular spectrum analysis-based light gradient boosting machine (SSAGBM), respectively. A total of four parameters (i.e., temperature, humidity, wind speed, and rainfall) at a daily scale from 2003 to 2017 is used as input data for daily rainfall prediction. As results from statistical performance indicators, it indicates that the SSAGBM model shows a better performance than the EMDGBM model and the original LightGBM algorithm with no decomposition methods. It represents that the accuracy of LightGBM algorithm in rainfall prediction was improved with the SSA method when using multivariate dataset.