• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.1
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• pp.35-44
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• 2009

This paper describes an application of domain decomposition method for parallel finite element analysis which is required to large scale 3D structural analysis. A parallel finite element method system which adopts a domain decomposition method is developed. Node is generated if its distance from existing node points is similar to the node spacing function at the point. The node spacing function is well controlled by the fuzzy knowledge processing. The Delaunay triangulation method is introduced as a basic tool for element generation. Domain decomposition method using automatic mesh generation system holds great benefits for 3D analyses. Aa parallel numerical algorithm for the finite element analyses, domain decomposition method was combined with an iterative solver, i.e. the conjugate gradient(CG) method where a whole analysis domain is fictitiously divided into a number of subdomains without overlapping. Practical performance of the present system are demonstrated through several examples.

• Proceedings of the KIEE Conference
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• 2011.07a
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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.

• Bulletin of the Korean Mathematical Society
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• v.55 no.4
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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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• v.18 no.3
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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.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1997.11a
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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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• v.8 no.2
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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.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.05a
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• pp.45-49
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• 2006

The thermal degradation of carbon fiber reinforced phenolic composites have been studied at high temperature by using thermogravimetry analysis (TGA). The aim is that ultimately it can be used to predict the service temperature during solid rocket firing for any level and type of mechanical loading and to recommend protection systems required. To simulate the high heating rate in firing condition, the modified thermal decomposition constant (1000 K/min) was used for FEM analysis. The temperature distribution and the thickness of thermal decomposition were estimated well and we could predict the thickness of thermal decomposition within ${\pm}1mm$.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2005.11a
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• pp.22-25
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• 2005

The thermal degradation of carbon/phenolic composite have been studied at high temperature by using thermogravimetric (TGA). A heating .ate of 5, 10, 15, 30 and $50^{\circ}C/min$ was used for the determination of thermal decomposition parameters of composite materials at high-temperature service. It has been shown that as the heating rates is increased, the peak decomposition rates are occur at higher temperature. Based on results of thermogravimetric analysis, the pyrolysis process is analyzed and physical and mathematical models for the process are proposed. The thermal analysis also has been conducted using transient heat conduction and the in-depth temperature distribution and the density profile were evaluated along the solid rocket nozzle. As a future effort the thermal decomposition parameter determined in this investigation will be used as input to thermal and mechanical analysis when subjected to solid rocket propulsion environment.

• Journal of Korean Association for Spatial Structures
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• v.19 no.2
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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.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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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.