• 한국유체기계학회 논문집
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• 제20권2호
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• pp.32-40
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• 2017

In this study, an in-house program to analyze the performance degradation for gas turbines is developed using MATLAB and is validated using commercial software. This program consists of design and off-design calculations. The results of design calculation is used for reference values of off-design calculation. The off-design calculation is composed of measured and expected performance analyses, and turbine inlet temperature correction. In general, performance degradation is analyzed by comparing the results of measured and expected performance analysis. However, if gas turbine performance degrades, turbine inlet temperature might increase due to the general control logic to comply with the power demand. Therefore, it is required to consider the deviation of turbine inlet temperature from the normal value in the performance diagnosis to analyze the performance degradation exactly. In this study, a special effort is given to the correction of turbine inlet temperature. The accuracy of the developed program is confirmed by comparison with commercial software, and its capability of performance diagnosis using the turbine inlet temperature correction is demonstrated.

• 한국유체기계학회 논문집
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• 제20권2호
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• pp.47-52
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• 2017

In general industry, TFM(turbine flow meters) as measuring instruments having high reliability are widely used in the trade of petroleum and in the measurement of tap water and hot water. The TFM is performed calibration for using in the field and is mainly calibrated at room temperature. Since accuracy of TFM depends on Reynolds number of fluid, TFM is calibrated at same Reynolds number by changing flow rate. Furthermore, the TFM using a fluid of high temperature should have considered for other factors such as the thermal expansion of the parts and characteristics change is unknown changes in the turbine flow meter accordingly. In this paper, two turbine flowmeter are experimentally studied about characteristics change using the facilities which can change fluid temperature from 6 degree celsius to 90 degree celsius. As a result, the turbine flow meter can be calibrated to minimize the error characteristic at a similar temperature and the actual temperature.

• 한국수소및신에너지학회논문집
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• 제27권6호
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• pp.727-736
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• 2016

Numerical simulations of n-heptane spray characteristics in a constant volume combustion chamber under diesel engine like conditions with increasing ambient gas density ($14.8-142kg/m^3$) and ambient temperature (800-1000 K) respectively were performed to understand the non-vaporizing and vaporizing spray behavior. The effect of fuel temperature (ranging 273-313 K) on spray characteristics was also simulated. In this simulation, spray modeling was implemented into ANSYS FORTE where the initial spray conditions at the nozzle exit and droplet breakups were determined through nozzle flow model and Kelvin-Helmholtz/Rayleigh-Taylor (KH-RT) model. Simulation results were compared with experimentally obtained spray tip penetration result to examine the accuracy. In case of non-vaporizing condition, simulation results show that with an increment of the magnitude of ambient gas density and pressure, the vapor penetration length, liquid penetration length and droplet mass decreases. On the other hand vapor penetration, liquid penetration and droplet mass increases with the increase of ambient temperature at the vaporizing condition. In case of lower injection pressure, vapor tip penetration and droplet mass are increased with a reduction in fuel temperature under the low ambient temperature and pressure.

• 설비공학논문집
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• 제11권2호
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• pp.193-204
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• 1999

Performance of a variable-speed, roller-type vane compressor was evaluated at low evaporating temperature. First, an experimental investigation was conducted to examine the performance variation as functions of both outdoor temperature and rotating speed. For this purpose, a typical heat pump was implemented as a test apparatus to measure mass flow rate and power input. Secondly, computational investigations corresponding to the heat pump test conditions were performed to predict compressor performance using ORNL Map-Based compressor model. Results obtained from the heat-pump experiments showed that both mass flow rate and power consumption were sensitively dependent on both evaporating temperature and compressor speed as was predicted from the computational results. From the comparisons of both experimental and computational results, it was well recognized that the ORNL model was subjected to larger error in the accuracy of prediction as outdoor temperature decreased. When the outdoor temperature was above $-5^{\cire}C$, errors of predicted values corresponding to both mass flow rate and power consumption were estimated as $\pm$10% and $\pm$ 15%, respectively. Finally, it is suggested that the ORNL model needs to be re-evaluated if compressor map data tested below $-5^{\cire}C$(in evaporating temperature) are available.

• 한국자동차공학회논문집
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• 제7권7호
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• pp.42-53
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• 1999

Two dimensional flame temperature and KL value distribution from the luminous flame containing soot in a DI diesel engine were measured by the tow-color method using tow different wavelengths of the flame image. The combustion chamber of a DI diesel engine was visualized by elongating the piston and cylinder and the flame in the combustion chamber was photographed on a nega-color film using a high speed camera. In this study, color CCD camera was used to digitize the three color density of the film exposed to the flame and standard lamp . The accuracy of the measuring method depends on the calibration line of film made from a high temperature standard tungsten lamp. The formation and oxidization of soot in the diesel engine were studied by observing measured time history of KL factor and flame temperature . Also , effects of various shapes of combustion chamber and fuel injection on flame temperature. Also, effects of various shapes of combustion chamber and fuel injection on flame temperature and KL value distribution were examined.

• 한국환경과학회지
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• 제16권3호
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• pp.347-355
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• 2007

In this paper, estimation of the compressive strength of the concrete incorporating blast furnace slag subjected to high temperature was discussed. Ordinary Portland cement and blast furnace slag cement (BSC;30% of blast furnace slag) were used, respectively. Water to binder ratio ranging from 30% to 60% and curing temperature ranging from $20^{\circ}C{\sim}65^{\circ}C$ were also chosen for the experimental parameters, respectively. At the high temperature, BSC had higher strength development at early age than OPC concrete and it kept its high strength development at later age due to accelerated latent hydration reaction subjected to high temperature. For the strength estimation, the Logistic model based on maturity equation and the Carino model based on equivalent age were applied to verify the availability of estimation model. It was found that fair agreements between calculated values and measured values were obtained evaluating compressive strength with logistic curve. The application of logistic model at high temperature had remarkable deviations in the same maturity. Whereas, the application of Carino model showed good agreements between calculated values and measured ones regardless of type of cement and W/B. However, some correction factors should be considered to enhance the accuracy of strength estimation of concrete.

• Journal of Electrical Engineering and Technology
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• 제9권3호
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• pp.970-977
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• 2014

In this paper, the artificial neural network is used to predict the junction temperature of the IGBT power module, by measuring the temperature sensitive electrical parameters (TSEP) of the module. An experiment circuit is built to measure saturation voltage drop and collector current under different temperature. In order to solve the nonlinear problem of TSEP approach as a junction temperature evaluation method, a Back Propagation (BP) neural network prediction model is established by using the Matlab. With the advantages of non-contact, high sensitivity, and without package open, the proposed method is also potentially promising for on-line junction temperature measurement. The Matlab simulation results show that BP neural network gives a more accuracy results, compared with the method of polynomial fitting.

• Nuclear Engineering and Technology
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• 제51권7호
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• pp.1853-1859
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• 2019

The two-thermocouple method was investigated experimentally to evaluate its accuracy for the measurement of local wall temperature and heat flux on a heat transfer tube with an electric heater rod installed in an annulus channel. This work revealed that a thermocouple flush-mounted in a surface groove serves as a good reference method for the accurate measurement of the wall temperature, whereas two thermocouples installed at different depths in the tube wall yield large bias errors in the calculation of local heat flux and wall temperature. These errors result from conductive and convective changes due to the fin effect of the thermocouple sheath. To eliminate the bias errors, we proposed a calibration method based on both the local heat flux and Reynolds number of the cooling water. The calibration method was validated with the measurement of local heat flux and wall temperature against experimental data obtained for single-phase convection and two-phase condensation flows inside the tube. In the manuscript, Section 1 introduces the importance of local heat flux and wall temperature measurement, Section 2 explains the experimental setup, and Section 3 provides the measured data, causes of measurement errors, and the developed calibration method.

• 한국가시화정보학회지
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• 제21권1호
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• pp.103-109
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• 2023

This research developed a measurement technique that can measure the oxygen temperature inside a high temperature furnace. Instead of measuring only changes in frequency components within a small range used in the existing variable laser absorption spectroscopy, laser spectroscopy technology was used to spread out wavelength of the light source passing through the gas Based on a total of 20,000 image data, research was conducted to predict the temperature of a high-temperature furnace using CNN with black and white images in the form of spectral bands by temperature of 25 to 800 degrees. The optimal model was found through Hyper parameter optimization, R2 score is 0.89, and the accuracy of the test data is 88.73%. Based on this research, it is expected that concentration measurement and air-fuel ratio control technology can be applied.

• 한국지구과학회지
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• 제40권6호
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• pp.606-612
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• 2019

채소작물과 과수작물의 생육에 악영향을 미치는 서리발생을 미리 예측하기 위해 모형을 구축하고 채소 주산지에 적용해 보았다. 서리 발생 전날에 관측되는 다양한 기상인자들(최저기온, 18시 기온, 21시 기온, 24시 기온, 평균풍속, 18시 풍속, 21시 풍속, 구름량, 5일간 강수량, 3일간 강수량, 상대습도, 이슬점온도, 초상최저기온, 지면온도)을 수집하고, 그 중에서 서리발생에 유의한 영향이 있다고 판단되는 변수들을 통계적 방법(T-test, Random Forest, Multicollinearity test, Akaike Informaiton Criteria, 그리고 Wilk's lambda values)을 통해 선택하였다. 여러 통계적 방법을 통해 선택된 유의한 기상 인자는 24시 기온, 구름량, 이슬점온도, 21시 풍속 이였으며, 이 기상인자를 기계학습법의 한 종류인 랜덤 포레스트에 적용하여 서리 발생 예측 모형을 구축하였다. 이렇게 구축 된 서리 발생예측 모형의 정확도는 70.6%로 나타났으며, 이 모형을 가을배추와 가을무의 주산지인 홍성과 서산에 적용하였을 때 65.2%와 78.6%로 나타났다.