• Proceedings of the Korea Concrete Institute Conference
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• 1999.04a
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• pp.727-732
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• 1999

In this research, we made an experiment on the 10 specimen beams that we made. The specimen beams consist of 4 steel plate strengthening beams and 5 carbon fiber sheet strengthening beams. We applied the methods of notch, rounding off a edge, anchor bolt and side shear strengening to the steel plate and for the case of carbon fiber sheet, we applied the methods of anchor bolt, line anchor and shear strengthening. After all the cases were applied, the beams was measured and analyzed about the behavior property of strengthened beams, th ability of strengthening method, the relation between load and the shape of failure, the crack load, the yield load, the shape of crack pattern, the increasing rate from yield load and maximum load and the strain of rebar. All the strengthening methods resulted in almost same value until the yield load, and it wasn't quite different from the theoretical value. In comparison with existing method, the SER, SEAS for the steel plate and the CEA, CESS, CCESS for carbon fiber sheet showed the increasement of ductility with big displacement.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1276-1280
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• 2015

Among the various statistical factors for South Korea, the population has been steadily decreased by lower birthrate. Nevertheless, the number of household is constantly increasing amid population aging and single life style. In general, residential electricity use is more the result of the number of household than the population. Therefore, residential electricity consumption is expected to be far higher for decades to come. The existing long-term load forecasting, however, do not necessarily reflect the growth of single and two-member households. In this respect, this paper proposes the long-term load forecasting for residential users considering the effect of changes of the housing type, and in the case study the changes of the residential load pattern is analyzed for accurate long-term load forecasting.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.790-793
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• 2001

The characteristics of smart skin for wireless LAN system under compression load are investigated. The smart skin structure is composed of 3 layers of face material and 2 layers of core material. Theoretical formula for determining buckling load is derived by Rayleigh-Ritz method and compared with experimental result. The maximum length of specimen that buckling does not occur is determined by assuming that the compression load is sustained by only face material. In the experiment, if buckling occurs obviously then it follows the theoretical result well. In the process of buckling, the load supporting capability and the antenna property such as radiation pattern and reflection coefficient were examined.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.2
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• pp.217-223
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• 2014

Recently, various researches and projects about electric vehicles are in progress vigorously and continuously and it is expected to penetrate rapidly with the next a few years. This deployment will cause the change of load composition rate affecting on power system planning and operations. Therefore, a new load model should be developed integrating with electric vehicle loads. In this paper, the load composition rate of residential sectors is analyzed considering the deployment of this mobility load such as electric vehicles and a new diffusion model is proposed based on the classification of the replacement patterns. Additionally, electric vehicle charging loads are basically modeled by some individual load experiments to develop new load models for smart place and some new conceptual power systems such as micro grids.

• Structural Engineering and Mechanics
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• v.14 no.3
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• pp.331-343
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• 2002

Because of the increasing span of arch bridges, ultimate capacity analysis recently becomes more focused both on design and construction. This paper investigates the static and ultimate behavior of a long-span steel arch bridge up to failure and evaluates the overall safety of the bridge. The example bridge is a long-span steel arch bridge with a 550 m-long central span under construction in Shanghai, China. This will be the longest central span of any arch bridge in the world. Ultimate behavior of the example bridge is investigated using three methods. Comparisons of the accuracy and reliability of the three methods are given. The effects of material nonlinearity of individual bridge element and distribution pattern of live load and initial lateral deflection of main arch ribs as well as yield stresses of material and changes of temperature on the ultimate load-carrying capacity of the bridge have been studied. The results show that the distribution pattern of live load and yield stresses of material have important effects on bridge behavior. The critical load analyses based on the linear buckling method and geometrically nonlinear buckling method considerably overestimate the load-carrying capacity of the bridge. The ultimate load-carrying capacity analysis and overall safety evaluation of a long-span steel arch bridge should be based on the geometrically and materially nonlinear buckling method. Finally, the in-plane failure mechanism of long-span steel arch bridges is explained by tracing the spread of plastic zones.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.11
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• pp.369-382
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(quality of service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to activate only the minimum number of servers needed to handle current user requests. Previous studies on energy aware server cluster put efforts to reduce power consumption or heat dissipation, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management method to improve not only performance per watt but also QoS of the existing server power mode control method based on autonomous learning. Our proposed method is to adjust server power mode based on a hybrid approach of autonomous learning method with multi level thresholds and power consumption prediction method. Autonomous learning method with multi level thresholds is applied under normal load situation whereas power consumption prediction method is applied under abnormal load situation. The decision on whether current load is normal or abnormal depends on the ratio of the number of current user requests over the average number of user requests during recent past few minutes. Also, a dynamic shutdown method is additionally applied to shorten the time delay to make servers off. We performed experiments with a cluster of 16 servers using three different kinds of load patterns. The multi-threshold based learning method with prediction and dynamic shutdown shows the best result in terms of normalized QoS and performance per watt (valid responses). For banking load pattern, real load pattern, and virtual load pattern, the numbers of good response per watt in the proposed method increase by 1.66%, 2.9% and 3.84%, respectively, whereas QoS in the proposed method increase by 0.45%, 1.33% and 8.82%, respectively, compared to those in the existing autonomous learning method with single level threshold.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.1
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• pp.53-59
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• 2004

In case of load forcasting the most important problem is to deal with the load of special days. According this paper presents forecasting method for speaial days peak load by neural networks model. by means of neural networks mothod using the historical past special- days load data, special-days load was directly forecasted, and forecasting % error showed good result as 1∼2% except vacation season in summer Consequently, it is capable of directly special days load, With the models, precision of forecasting was brought satisfactory result. When neural networks was compared with the orthogonal polynomials models at a view of the results of special-days load forecasting, neural networks model which used pattern conversion ratio was more effective on forecasting for special-days load. On the other hand, in case of short special-days load forecasting, both were valid.

• Journal of Electrical Engineering and Technology
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• v.5 no.2
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• pp.307-318
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• 2010

In this work, an accurate analysis of low frequency current ripple in residential fuel cell power generation systems is performed based on the proposed residential load model and its unique operation algorithm. Rather than using a constant dc voltage source, a proton exchange membrane fuel cell (PEMFC) model is implemented in this research so that a system-level analysis considering the fuel cell stack, power conditioning system (PCS), and the actual load is possible. Using the attained results, a comparative study regarding the discrepancies of low frequency current ripple between a simple resistor load and a realistic residential load is performed. The data indicate that the low frequency current ripple of the proposed residential load model is increased by more than a factor of two when compared to the low frequency current ripple of a simple resistor load under identical conditions. Theoretical analysis, simulation data, and experimental results are provided, along with a model of the load usage pattern of low frequency current ripples.

• Journal of Environmental Impact Assessment
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• v.14 no.5
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• pp.255-262
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• 2005

In summer and early autumn, eutrophication occurs occasionally in many reservoirs. Lakeside macrophyte which is one of internal pollutants effects on water quality when it is submerged during water surface is rising after rainy season. This study include examination of pollutant load, species of plant, community structure and productivity of macrophyte in unit area at lakeside. The result of this research will be used as a guideline of water quality management on reservoir through assessing water quality effect of submerged plant. The areal distribution, composition of species and submerged area of macrophyte changes according to rainfall pattern every year, so it is difficult to calculate nutrient load annually from submerged macrophyte. In this study, the nutrient load from submerged macrophyte assess from Daecheong and Juam reservoir in 2001. TN and TP load of submerged macrophyte shows 0.043% and 0.069%, respectively, of annual discharge load on Daecheong watershed. At lake Juam, TN and TP shows 0.64% and 1.28% load, respectively. The reason that nutrient load of lake Juam is greater than that of lake Daecheong is that macrophyte distribution area of lake Juam is 5 times greater than that of lake Daecheong. Total nutrient load of lake Daecheong is 3 times greater than that of lake Juam.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.1
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• pp.47-53
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• 2005

Most of the loads in industrial power distribution systems are balanced and connected to three power systems. However, in the user power distribution systems, most of the loads are single & three phase and unbalanced, generating voltage unbalance. Voltage unbalance factor is mainly affected by load system rather than stable power system. Unbalanced voltage will draw a highly unbalanced current. As a result, the three-phase currents may differ considerably, thus resulting in an increased temperature rise in the machine. This paper presents a scheme on the characteristics of voltage and current unbalance factor under the load variation at the three phase 4-wire system. Load unbalance factor is measured by the power quality measurement apparatus and compared by the current unbalance factor. Two methods are indicated similar results. The voltage unbalance factor of the three-phase 4-wire system is approved by the field measurement. Each phase has an impedance each other by the unbalanced operation pattern and give rise to voltage unbalance.