• Journal of the Korean Solar Energy Society
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• v.30 no.2
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• pp.65-71
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• 2010

The hydrologic performance characteristics of small hydro power(SHP) sites located in four major river systems have been studied. The model, which can predict flow duration characteristic of stream, was developed to analyze the variation of inflow caused from rainfall condition. And another model to predict hydrologic performance for SHP plants is established. Monthly inflow data measured at Andong dam for 32 years were analyzed. The predicted results from the developed models in this study showed that the data were in good agreement with measured results of long term inflow at Andong dam. The results from hydrologic performance analysis for SHP sites located on five major river systems based on the models developed in this study show that the specific design flowrate and specific output of SHP site have large difference between the river systems.

• Nuclear Engineering and Technology
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• v.50 no.7
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• pp.1190-1197
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• 2018

Analysis of the GRSW-A model coupled into the FALCON code is extended by simulation of central void formation in fuel pellets due to high-temperature fuel restructuring. The extended calculation is verified against published, well-known experimental data. Good agreement with the data for a central void diameter in pellets of the rod irradiated in an Experimental Breeder Reactor is shown. The new calculation methodology is employed in comparative analysis of modern BWR fuel behavior under assumed high-power operation. The initial fuel porosity is shown to have a major effect on the predicted central void diameter during the operation in question. Discernible effects of a central void on peak fuel temperature and Pellet-Cladding Mechanical Interaction (PCMI) during a simulated power ramp are shown. A mitigating effect on PCMI is largely attributed to the additional free volume in the pellets into which the fuel can creep due to internal compressive stresses during a power ramp.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.6
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• pp.550-557
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• 2015

The Jeju Special Self-Governing Province is currently promoting the "Carbon-free Island by 2030" policy, which requires the use of renewable energy instead of fossil fuel so that the island will have no carbon gases generated by 2030. To implement this policy, the island plans to build a wind power plant capacity of 1.09 GW in 2020; this wind power plant is currently ongoing. However, when wind power output is greater than the power demand of the island, the stability of Jeju Island power system must be prepared for it because it can be a problem. Therefore, this study proposes a voltage source-type MMC-HVDC system linked to mainland Korea to expand the wind power penetration limits of Jeju Island under the stable operation of the Jeju Island power system. To verify the effectiveness of the proposed scheme, computer simulations using the PSCAD/EMTDC program are conducted, and the results are demonstrated. The scenarios of the computer simulation consist of two cases. First, the MMC-HVDC system is operated under variable wind power in the Jeju Island power system. Second, it is operated under the predicted Jeju Island power system in 2020.

• Journal of Korean Academy of Nursing Administration
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• v.8 no.4
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• pp.551-561
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• 2002

Purpose : The purpose of the present study was to examine the causal relationships among head nurses' leadership (consideration oriented leadership, structure initiated leadership), nursing unit culture (human development culture, task development culture), and nurses' organizational commitment. Method : Four large general hospitals located in and around Seoul were selected to participate. The total sample of 286 registered nurses represents a response rate of 90 percent. Data for this study was collected from August to September in 2000 by questionnaire. Path analyses with LISREL program were used to test the fit of the proposed model to the data and to examine the causal relationships among variables. Result : Both the proposed model and the modified model fit the data adequately. The model revealed relatively high explanatory power. 52% of human development culture was explained by predicted variables and 44% of task development was explained by predicted variables; 47% of the organizational commitment was explained by predicted variables. In predicting developmental (both human and task) nursing unit culture, the findings of this study clearly demonstrated that head nurses' consideration oriented leadership might be the most important variable. The result also showed that head nurses' consideration oriented leadership might be the most important variable among the predicted variables in predicting organizational commitment. Conclusion : Based on the findings of this study, it was suggested that various studies, for example, matching leadership and nursing unit culture, were needed.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2003.11a
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• pp.534-538
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• 2003

Final disposal of radioactive waste generated from Nuclear Power Plant (NPP) requires the detailed knowledge of the natures and quantities of radionuclides in waste package. Many of these radionuclides are difficult to measure and expensive to assay. Thus it is suggested to the Indirect method by which the concentrations of DTM (Difficult-to-Measure) nuclide is decided using the relation of concentrations (Scaling Factor) between Key (Easy-to-Measure) nuclide and DTM nuclide with measured concentrations of Key nuclide. In general, scaling factor is determined by using of log mean average (LMA) and regression. These methods are adequate to apply most corrosion product nuclides. But in case of fission product nuclides and some corrosion product nuclides, the predicted values aren't well matched with the original values. In this study, the models using artificial neural network (ANN) for C-14 and Sr-90 are compared with those using LMA and regression. The assessment of models is executed in the two parts divided by a training part and a validation part. For all of two nuclides in the training part, the predicted values using ANN are well matched with the measured values compared with those using LMA and regression. In the validation part, the accuracy of the predicted values using ANN is better than that using LMA and is similar to or better than that using regression. It is concluded that the predicted values using ANN model are better than those using conventional model in some nuclides and ANN model can be used as the complement of LMA and regression model.

• Composites Research
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• v.12 no.2
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• pp.53-61
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• 1999

A failure criterion must be considered in each failure mode and loading condition to provide easy determining strength parameters, flexibility and rational simplicity. In this study, new failure criterion was developed by introducing equivalent strength under biaxial loading of tension and torsion. The experimental results showed that the equivalent biaxial strength has a power law relation with respect to a parameter, cos($tan^{-1}R_b$). Failure strength under biaxial loadings could be predicted as a function of tensile strength, torsional strength and biaxial ratio. The scattering of experimental data could be predicted using a Weibull distribution function and the concept of equivalent biaxial strength. Also, in this study, a fatigue theory was developed based on a plane stress model which enabled the S-N curve for combined stress states to be predicted from the S-N data for uniaxial loading. The prediction models can be predicted a biaxial strength and fatigue life of general laminated composite naterials under multi-axial loadings.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.64-71
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• 2017

Considering the volatility, intermittent and random of photovoltaic (PV) generation systems, accurate forecasting of PV power output is important for the grid scheduling and energy management. In order to improve the accuracy of short-term power forecasting of PV systems, this paper proposes a prediction model based on environmental factors and support vector machine optimized by genetic algorithm (GA-SVM). In order to improve the prediction accuracy of this model, weather conditions are divided into three types, and the gray correlation coefficient algorithm is used to find out a similar day of the predicted day. To avoid parameters optimization into local optima, this paper uses genetic algorithm to optimize SVM parameters. Example verification shows that the prediction accuracy in three types of weather will remain at between 10% -15% and the short-term PV power forecasting model proposed is effective and promising.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.391-397
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• 2005

Power Flow Analysis(PFA) is used as the promising tools for the vibration and noise predictions of complex structures in medium-to-high frequency ranges. When the noise and vibration of a complex structure are analyzed, Power Flow finite Element Method combining PFA with FEM is efficient in vibration analysis, and Power Flow Boundary element Method combining PFA with BEM is usful in noise analysis. PFFEM software, PFADS has been developed for the vibration analysis of coupled system structures. Also, NASPFA, the noise analysis software based on PFBEM, has been developed. Through the several upgrades, the current version PFADS R3 and NASPFA R2 are used for the vibration and noise analysis of system structures in medium-to-high frequency ranges. In this paper, the structure and function of each software are explained, and the vibration and noise levels of vehicle structures predicted by each software are shown.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1340-1347
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• 2017

Utilization of Electric Vehicles (EVs) have been growing popularity in recent years due to increment in fuel price and lack of natural resources. Random unexpected charging by home EV charger in distribution is predicted in the future. The power quality problems such as fluctuation of power factor in a residential distribution network was explored with random EV chargers. This paper proposes a high-performance nonlinear sliding mode controller (SMC) for an EV charging system to compensate voltage distortions and to enhance the power factor against the unbalanced EV chargers. For the verification of the proposed scheme, MATLAB-Simulink simulations are performed on 22.9-kV grid. The results show that the proposed scheme can improve the power factor of a smart grid due to the EV chargers on the grid.

• Nuclear Engineering and Technology
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• v.41 no.7
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• pp.969-978
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• 2009

The ASSERT-PV subchannel code developed by AECL has been applied as a design-assist tool to the advanced $CANDU^{(R)1}$ reactor fuel bundle. Based primarily on the $CANFLEX^{(R)2}$ fuel bundle, several geometry changes (such as element sizes and pitch-circle diameters of various element rings) were examined to optimize the dryout power and pressure-drop performances of the new fuel bundle. An experiment was performed to obtain dryout power measurements for verification of the ASSERT-PV code predictions. It was carried out using an electrically heated, Refrigerant-134a cooled, fuel bundle string simulator. The axial power profile of the simulator was uniform, while the radial power profile of the element rings was varied simulating profiles in bundles with various fuel compositions and burn-ups. Dryout power measurements are predicted closely using the ASSERT-PV code, particularly at low flows and low pressures, but are overpredicted at high flows and high pressures. The majority of data shows that dryout powers are underpredicted at low inlet-fluid temperatures but overpredicted at high inlet-fluid temperatures.