• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.4
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• pp.355-363
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• 2022

Development of supersonic flying vehicle is one of the most latest issue in modern military technology. Specifically, structural integrity of supersonic flying vehicle can be verified by high temperature structural test. High temperature structural test is required to consider thermal load caused by aerodynamic heating while applying structural load simultaneously. Tubular quartz lamps are generally used to generate thermal load by emitting infrared radiation. In this study, modified heat flux model of tubular quartz lamp is proposed based on existing model. Parameters of the proposed model are optimized upon measured heat flux in three dimensions. Finally, thermal load of plate specimen is designed by the heat flux model. In conclusion, it is possible to predict heat flux applied on plate specimen and desired thermal load of high temperature structural test can be obtained.

• Journal of Industrial Technology
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• v.13
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• pp.19-24
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• 1993

Compensation of temperature is very important to make high precision load cell. In this study, we developed a new type load cell. The structure of the load cell has four strain gauges on single side of the load cell beam. Also a new temperature compensation method was proposed and these characteristics were better than previous one. This study will offer application to other type of load cell and another sensors.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.6
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• pp.358-363
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• 2004

Due to the weather sensitivity of the power load, it is difficult to forecast accurately the peak power load of summer season. We improve the accuracy of the load forecasting considering weather condition. We introduced the sensitivity of temperature and proposed an improved forecasting algorithm. The proposed algorithm shows that the error of the load forecasting is 1.5%.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.5
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• pp.211-221
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• 1998

Thermal behavior on the cylinder block of a 4-cylinder, 4-stroke 2.0L SOHC gasoline engine was numerically and experimentally analyzed. The numerical calculation was performed using the finite element method. The cylinder block was modelled as a three dimensional finite element by considering its geometry. The physical domain was devided into hexahedron elements. 16 thermocouples were installed at points of 2mm inside from cylinder wall near top ring of piston in cylinder block, which points have suffered major thermal loads and suggested as proper measurement points for engine design by industrial engineers. Under full load and 9$0^{\circ}C$ coolant temperature condition, temperature behavior of cylinder block according to engine speed were analyzed. The results showed that temperature rose gradually to conform to a function of 2nd~4th order of engine speed at intake side, exhaust and siamese side, respectively. As engine load was changed from 100 to 50% by 25% step, temperature curve also conformed to 2nd~7th order function of engine speed. Temperature differences by load condition were similar among 100, 75% and 50%. Under full load and coolant temperature of 11$0^{\circ}C$, temperature behavior were also analyzed and the result also showed conformance to 2n d~7th order function of engine speed. Temperature curve was transferred in parallel upwards corresponding coolant temperature rise.

• Steel and Composite Structures
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• v.15 no.6
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• pp.705-724
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• 2013

The behaviour of steel column at elevated temperature is significantly different than that at ambient temperature due to its changes in the mechanical properties with temperature. Reported literature suggests that steel column may become vulnerable when exposed to fire condition, since its strength and capacity decrease rapidly with temperature. The present study aims at investigating the lateral load resistance of non-insulated steel columns under fire exposure through finite element analysis. The studied parameters include moment-rotation behaviour, lateral load-deflection behaviour, stiffness and ductility of columns at different axial load levels. It was observed that when the temperature of the column was increased, there was a significant reduction in the lateral load and moment capacity of the non-insulated steel columns. Moreover, it was noted that the stiffness and ductility of steel columns decreased sharply with the increase in temperature, especially for temperatures above $400^{\circ}C$. In addition, the lateral load capacity and the moment capacity of columns were plotted against fire exposure time, which revealed that in fire conditions, the non-insulated steel columns experience substantial reduction in lateral load resistance within 15 minutes of fire exposure.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.1964-1968
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• 2007

The river water heat source heat pump has the advantage in the performance compared to air source heat pump. Although its better performance, the large temperature difference between load and source makes system performance worse by nature. In this study, 2-stage compression is considered as the solution of this problem. Generally, heat pump is designed for maximum capacity rate, but it actually operates at part load condition in many cases. Therefore, an information on the part-load character is very important in view of the system overall performance. In this study, part-load performance tests of a R134a 2-stage compression heat pump were carried out over the river water and supply heating water temperature changes. The experimental results show that the system performance is influenced by the part load rates, river water temperature, load temperature, etc.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.6
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• pp.852-856
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• 2015

Demand side management (DSM) program has been frequently used for reducing the system peak load because it gives utilities and independent system operator (ISO) a convenient way to control and change amount of electric usage of end-use customer. Planning and operating methods are needed to efficiently manage a DSM program. This paper presents a planning method for DSM program. A planning method for DSM program should include an electric load forecasting, because this is the most important factor in determining how much to reduce electric load. In this paper, load forecasting with the temperature stochastic modeling and the sensitivity to temperature of the electric load is used for improving load forecasting accuracy. The proposed planning method can also estimate the required day, hour and total capacity of DSM program using Monte-Carlo simulation. The results of case studies are presented to show the effectiveness of the proposed planning method.

• International Journal of Air-Conditioning and Refrigeration
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• v.11 no.4
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• pp.170-177
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• 2003

The electric power load during the summer peak time is strongly affected by cooling load, which decreases the preparation ratio of electricity and brings about the failure in the supply of electricity in the electric power system. The ice storage system and heat pump system etc. are used to settle this problem. In this study, the method of estimating temperature and humidity to forecast the cooling load of ice storage system is suggested. The method of forecasting the cooling load using neural network is also suggested. The daily cooling load is mainly dependent on actual temperature and humidity of the day. The simulation is started with forecasting the temperature and humidity of the following day from the past data. The cooling load is then simulated by using the forecasted temperature and humidity data obtained from the simulation. It was observed that the forecasted data were closely approached to the actual data.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.10
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• pp.529-535
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• 2004

Load forecasting is essential in the electricity market for the participants to manage the market efficiently and stably. A wide variety of techniques/algorithms for load forecasting has been reported in many literatures. These techniques are as follows: multiple linear regression, stochastic time series, general exponential smoothing, state space and Kalman filter, knowledge-based expert system approach (fuzzy method and artificial neural network). These techniques have improved the accuracy of the load forecasting. In recent 10 years, many researchers have focused on artificial neural network and fuzzy method for the load forecasting. In this paper, we propose an algorithm of a hybrid load forecasting method using fuzzy linear regression and general exponential smoothing and considering the sensitivities of the temperature. In order to consider the lower load of weekends and Monday than weekdays, fuzzy linear regression method is proposed. The temperature sensitivity is used to improve the accuracy of the load forecasting through the relation of the daily load and temperature. And the normal load of weekdays is easily forecasted by general exponential smoothing method. Test results show that the proposed algorithm improves the accuracy of the load forecasting in 1996.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.6
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• pp.39-43
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• 2013

The current representative temperature selection method with five cities cannot reflect the sufficient regional climate characteristics. In this paper, the new representative temperature selection method is proposed with the consideration of eight representative cities. The proposed method considered the recent trend of power sales, the climate characteristics and population distribution to improve the accuracy of short-term load forecasting. Case study results for the accuracy of short-term load forecasting are compared for the traditional temperature weights of five cities and the proposed temperature weights of eight cities. The simulation results show that the proposed method provides more accurate results than the traditional method.