• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.477-481
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• 2007

The purpose of this study is to provide the ideal forecasting model of cadastral survey work load through the Economeatric Analysis of Time Series, Granger Causality and VAR Model Analysis, it suggested the forecasting reference materials for the total amount of cadastral survey general work load. The main result is that the derive of the environment variables which affect cadastral survey general work load and the outcome of VAR(vector auto regression) analysis materials(impulse response function and forecast error variance decomposition analysis materials), which explain the change of general work load depending on altering the environment variables. And also, For confirming the stability of time series data, we took a unit root test, ADF(Augmented Dickey-Fuller) analysis and the time series model analysis derives the best cadastral forecasting model regarding on general cadastral survey work load. And also, it showed up the various standards that are applied the statistical method of econometric analysis so it enhanced the prior aggregate system of cadastral survey work load forecasting.

• Journal of IKEEE
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• v.4 no.2 s.7
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• pp.233-240
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• 2000

This paper presents fuzzy clustering and wavelet transform analysis based technique for the industrial hourly load forecasting fur the purpose of peak demand control. Firstly, one year of historical load data were sorted and clustered into several groups using fuzzy clustering and then wavelet transform is adopted using the Biorthogonal mother wavelet in order to forecast the peak load of one hour ahead. The 5-level decomposition of the daily industrial load curve is implemented to consider the weather sensitive component of loads effectively. The wavelet coefficients associated with certain frequency and time localization is adjusted using the conventional multiple regression method and the components are reconstructed to predict the final loads through a five-scale synthesis technique. The outcome of the study clearly indicates that the proposed composite model of fuzzy clustering and wavelet transform approach can be used as an attractive and effective means for the industrial hourly peak load forecasting.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.320-325
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• 2009

In this study, a method to estimate the suspension bridge deflection is developed using mode decomposition technique. In order to examine the suspension bridge stability against these dynamic loadings, the prediction of displacement response is very important to evaluate bridge stability. However, it is recognized that any measurement of movement for suspension bridges may be difficult for the absence of proper methods to measure the displacement response on site. This study aims at suggesting a method to estimate the displacement response from the measured strain signals in an indirect way to predict the displacement response, not a direct way to measure the displacement response. Additionally, by applying the FBG sensors with multi-point measurements not influenced by electric noise, it can be expected that the technique would be applicable to infrastructures.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.6
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• pp.605-615
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• 2017

Efficient simultaneous reduction conditions for $NO_x$ and $NH_3$-slip was investigated in SCR (Selective Catalytic Reduction) process with load variation by applying dual catalysts (SCR catalyst, $NH_3$ decomposition catalyst) system. $N_2O$ formation characteristics were analyzed to look into possible undesirable reaction pathways. In the experiments of catalyst characteristics, various operational variables were tested for the combined catalytic system, such as $NH_3/NO_x$ ratio, temperature, oxygen concentration and $H_2O$. The reaction characteristics of $NO_x$, $NH_3$ and $N_2O$ were analyzed and optimal conditions could be evaluated for the combustion facility with varied load. In terms of $NO_x/NH_3$ simultaneous reduction and $N_2O$ formation suppression, optimal condition was considered NSR 1.2 and temperature $300^{\circ}C$. At this operational condition, $NO_x$ conversion was 98%, $NH_3$ reduction efficiency was 95%, generated $N_2O$ concentration 9.5 ppm with inlet $NO_x$ concentration of 100 ppm. In $NH_3-SCR$ process with $NH_3$ decomposition catalyst, $NO_x$ and $NH_3$ can be considered to be reduced simultaneously at limited conditions. The results of this study may be utilized as basic data at facilities requiring simultaneous $NO_x$ and $NH_3$ reduction for facilities with load variation.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.301-303
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• 2000

This paper presents Kohonen neural network and wavelet transform analysis based technique for industrial peak load forecasting for the purpose of peak demand control. Firstly, one year of historical load data were sorted and clustered into several groups using Kohonen neural network and then wavelet transforms are adopted using the Biorthogonal mother wavelet in order to forecast the peak load of one hour ahead. The 5-level decomposition of the daily industrial load curve is implemented to consider the weather sensitive component of loads effectively. The wavelet coefficients associated with certain frequency and time localization is adjusted using the conventional multiple regression method and the components are reconstructed to predict the final loads through a six-scale synthesis technique.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.7
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• pp.535-540
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• 2019

The coupling between different models for MDO (Multi-disciplinary Optimization) greatly increases the complexity of the computational framework, while at the same time increasing CPU time and memory usage. To overcome these difficulties, POD (Proper Orthogonal Decomposition) and RBF (Radial Basis Function) are used to solve the optimization problem of determining the thickness of composites and sandwich cores when composite sandwich structures are used as aircraft wing skin materials. POD and RBF are used to construct surrogate models for the wing shape and the load data. Optimization is performed using the objective function and constraint function values which are obtained from the surrogate models.

• Smart Structures and Systems
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• v.20 no.2
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• pp.231-246
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• 2017

A recent work by the authors has demonstrated the feasibility of scour evaluation for Kao-Ping-Hsi Cable-Stayed Bridge simply based on ambient vibration measurements. To further attain the goal of scour monitoring, a key challenge comes from the interference of several environmental factors that may also significantly alter the pier frequencies without the change of scour depth. Consequently, this study attempts to investigate the variation in certain modal frequencies of this bridge induced by several environmental factors. Four sets of pier vibration measurements were taken either during the season of plum rains, under regular summer days without rain, or in a period of typhoon. These signals are analyzed with the stochastic subspace identification and empirical mode decomposition techniques. The variations of the identified modal frequencies are then compared with those of the corresponding traffic load, air temperature, and water level. Comparison of the analyzed results elucidates that both the traffic load and the environmental temperature are negatively correlated with the bridge frequencies. However, the traffic load is clearly a more dominant factor to alternate the identified bridge deck frequency than the environmental temperature. The pier modes are also influenced by the passing traffic on the bridge deck, even though with a weaker correlation. In addition, the variation of air temperature follows a similar tendency as that of the passing traffic, but its effect on changing the bridge frequencies is obviously not as significant. As for the effect from the alternation of water level, it is observed that the frequency baselines of the pier modes may positively correlate with the water level during the seasons of plum rains and typhoon.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2009.11a
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• pp.93-96
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• 2009

Advances in high speed flight technologies and engine efficiencies increase heat load on the aircraft. As the temperature of air flow is too high to cool the structure at hypersonic flight speeds, it is necessary to utilize the aircraft fuel as the primary coolant. By undergoing endothermic reaction, such as thermal decomposition or catalytic decomposition, aircraft fuels have heat sink potential. These fuels are called endothermic fuels. The endothermic reaction can be improved by catalysts, but limited by coke deposition. In this study the essential technologies of endothermic fuels are described, and intended to be used for basic research.

• Journal of Korean Society on Water Environment
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• v.23 no.4
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• pp.551-560
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• 2007

The present study analyzed noise reduction and long/short-term components for discharge, TOC concentration, and TOC load data in order to understand the data characteristics better. For the purpose, wavelet transform which can reduce noise from raw data and has flexible resolution in time and frequency domain was applied and the theory of nonlinear dynamics was also used to determine the last decomposition level for wavelet transform. Wavelet function of 'db10' and the 7th level for the last decomposition of wavelet transform were applied for the all data in the present study. Also the results revealed that the energy ratios of approximation components with 187-hour periodicity decomposed from 7th level of wavelet transform were 94.71% (discharge), 99.00% (TOC concentration), and 93.84% (TOC load), respectively. In addition, the energy ratios of detail components showed the range between 1.00% and 6.17%, which were extremely small comparing to the energy ratios of approximation components, therefore, the first and second detail components might be considered as noise components included in the raw data.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.4
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• pp.365-373
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• 2011

Damage of reinforced concrete panel subjected to blast load using parallel and domain decomposition is analyzed. The numerical results are sensitive to the mesh size because blast waves are generated during the extremely short term. In order to investigate the effect of mesh size on the blast wave, the analysis results from various wave mesh size using AUTODYN, the explicit finite element analysis program, were compared with existing experimental results. The smaller mesh size was, the higher accuracy was. However, in this case, the analysis was inefficient. Therefore, in order to increase numerical efficiency, the parallel analysis using decomposed method based on Euler and Lagrangian description was performed. Finally, the decomposed method using both the structure domain based on Lagrange description and the blast wave domain based on Euler description was more efficient than the decomposed method using only the Lagrange mesh on structure domain.