• 시스템엔지니어링학술지
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• 제16권1호
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• pp.58-67
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• 2020

A big data processing method to predict solar power generation using systems engineering approach is developed in this work. For developing analytical method, linear model (LM), support vector machine (SVN), and artificial neural network (ANN) technique are chosen. As evaluation indices, the cross-correlation and the mean square root of prediction error (RMSEP) are used. From multi-variable comparison test, it was found that ANN methodology provides the highest correlation and the lowest RMSEP.

• 한국안전학회지
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• 제29권5호
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• pp.136-145
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• 2014

This article has compared the level of activities of occupational safety and health in workplace among sub-sectors of manufacturing industry in order to set the priority for policy intervention. Data of manufacturing industry in the survey on the current status of occupational safety and health was used with factor analysis and radar graphic method. Authors have categorized sub-sectors of manufacturing industry into four categories, attained group, active group, neglected group, and passive group based on injury rate, level of safety and health activities. The neglected group may be the first target group for occupational safety and health policy guiding some detailed occupational safety and health activities. Limitation of this study is that cross sectional data was analyzed. The long term effect could not be analyzed.

• 한국대기환경학회지
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• 제17권2호
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• pp.223-231
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• 2001

In order to provide some insights into the influence of electric field, gas composition, and gas temperature on electron energy distribution and electron transport characteristics, the Boltzmann equation was solved by using cross section data for electron collisions, Critical electric fields for the corona development in dry air and flue gas are 150 and 80 Td, respectively. It was seen that the decrease of critical electric field in flue gas is mainly caused by the $H_2O$ addition through the comparison of ionization and attachment coefficients of gas components. Increase of $O_2$, $H_2O$, and $CO_2$ contents in gas affected discharge characteristics according to their reciprocal characteristics between lowering the ionization threshold and increasing the electro-negativity. As electric field increases, electrons with higher energies in the electron energy distribution also increase. The mean and characteristic electron energies also linearly increase with electric field. The variation of flue gas temperature did rarely affect on the electron energy distribution function and electron transport characteristics, because the gas temperature is several hundreds or thousands times lower than the electron temperature.

• Structural Engineering and Mechanics
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• 제45권1호
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• pp.33-52
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• 2013

In this study, the effects of crack depth and crack location on the in-plane free vibration of cracked frame structures have been investigated numerically by using the Finite Element Method. For the rectangular cross-section beam, a crack element is developed by using the principles of fracture mechanics. The effects of crack depth and location on the natural frequency of multi-bay and multi-store frame structures are presented in 3D graphs. The comparison between the present work and the results obtained from ANSYS shows a very good agreement.

• 오토저널
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• 제12권5호
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• pp.85-96
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• 1990

The object of this study is to develop the computer program to predict the transmission loss of a perforated tube muffler with mean flow, and to investigate the influence of porosity and mean flow on the performance of the muffler. The numerical model is made by dividing the muffler into small segments and estimating the transfer matrices for each segment. The computer program is developed for the calculation of the transmission loss of a through-or cross-flow perforated muffler. The experiment is performed for the measurement of the transmission loss and/or the pressure drop for various porosity and flow velocity. From the comparison between computation and experiment, is known that the numerical model agrees well with the experimental result. The effect of porosity and flow velocity on the acoustic performance and the flow resistance of a muffler is presented.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2004년도 전력전자학술대회 논문집(1)
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• pp.393-396
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• 2004

This paper proposed a transfer function of a frequency-controlled resonant inverter for output power control. The inverter is modeled as an equivalent circuit by using Phasor transformation. A transfer function is derived from the equivalent circuit which contains cross-coupled nonlinear parts. By simulation of the circuit, the transfer function can be approximated as a linear first-order function. The proposed transfer function is verified through comparison of experimental and simulation results.

• 대한조선학회지
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• 제22권2호
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• pp.27-34
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• 1985

In this paper, the second order time mean forces acting on the circular cylinder floating on the free surface of a finite water depth are calculated. Under the assumption that fluid is idea and the wave the linear gravity wave, the velocity potential is calculated by the source distribution method, and the second order time mean lateral and vertical drifting forces are calculated by the direct integration of fluid pressures over the immersed body surface. The comparison of the lateral drifting forces with Rhee's results by momentum theorem shows good agreements. And it is shown that the second order time sinkage forces of a floating circular cylinder cross zero for all water depths.

• Journal of Welding and Joining
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• 제19권5호
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• pp.540-547
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• 2001

This study has evaluated the wear behavior of PTA (Plasma Transferred Arc) Inconel 625 and Stellite 6 overlays on Nimonic 80A substrate. Nimonic 80A alloy was also included for comparison. In order to evaluate the wear performance, three-body abrasive wear test and pin-on-disk dry sliding wear test were performed. Microstructural development during the solidification of deposits is also discussed. Wear test results show that the wear rate of Stellite 6 deposit is lower than that of Inconel 625 deposit and Nimonic 80A. The sliding wear resistance of overlay deposits follows a similar trend to the abrasive wear resistance, but for Nimonic 80A. The main wear mechanisms were abrasive wear for Inconel 625 deposit, adhesive wear and delamination for Stellite 6 deposit in pin-on-disk dry sliding wear test and ploughing in three-body abrasive wear test. Cross sectional examinations of the worn surface of pin specimens after pin-on-disk dry sliding wear test implies that the plastic deformation near worn surface has occurred during the wear testing.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2008년도 학술발표회 논문집
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• pp.1147-1150
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• 2008

The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of the support vector machines neural networks model (SVM-NNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The SVM-NNM in time series modeling is relatively new and it is more problematic in comparison with classifications. In this study, The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training, cross validation, and testing data, respectively. From this research, we evaluate the impact of the SVM-NNM and the MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE data from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2008년도 학술발표회 논문집
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• pp.2193-2196
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• 2008

In this study, the new methodology such as support vector machines neural networks model (SVM-NNM) using the statistical learning theory is introduced to forecast flood stage in Nakdong river, Republic of Korea. The SVM-NNM in hydrologic time series forecasting is relatively new, and it is more problematic in comparison with classification. And, the multilayer perceptron neural networks model (MLP-NNM) is introduced as the reference neural networks model to compare the performance of SVM-NNM. And, for the performances of the neural networks models, they are composed of training, cross validation, and testing data, respectively. From this research, we evaluate the impact of the SVM-NNM and the MLP-NNM for the forecasting of the hydrologic time series in Nakdong river. Furthermore, we can suggest the new methodology to forecast the flood stage and construct the optimal forecasting system in Nakdong river, Republic of Korea.