• 설비공학논문집
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• 제16권6호
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• pp.522-529
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• 2004

In this study, external condensation heat transfer coefficients (HTCs) of flammable refrigerants of propylene, propane, isobutane, butane, DME, and HFC32 were measured on a horizontal plain tube, 26 fpi low fin tube, and Turbo-C tube. All data were taken at the temperature of 39$^{\circ}C$ with a wall subcooling of 3∼8$^{\circ}C$. Test results showed a typical trend that condensation HTCs of flammable refrigerants decrease with increasing wall subcooling. HFC32 had the highest HTCs among the tested refrigerants showing 44% higher HTCs than those of HCFC22 while DME showed 28% higher HTCs than those of HCFC22. HTCs of propylene and butane were similar to those of HCFC22 while those of propane and isobutane were similar to those of HFC134a. Based upon the tested data, Nusselt's equation is modified to predict the plain tube data within a deviation of 3%. For 26 fpi low fin tube, Beatty and Katz equation predicted the data within a deviation of 7.3% for all flammable refrigerants tested. The heat transfer enhancement factors for the 26 fpi low fin and Turbo-C tubes were 4.6∼5.7 and 4.7∼6.9 respectively for the refrigerants tested indicating that the performance of Turbo-C tube is the best among the tubes tested.

• 한국전자파학회지:전자파기술
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• 제4권2호
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• pp.4-10
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• 1993

이동통신에서, 전파경로는 이동국의 위치변동때문에 시간 및 공간에 따라 변한다. 전파경로 손실은 주 파수와 거리뿐만 아니라 안테나 높이, 지형구조와 인위적 환경에 따라 탄라지브로 이동 전파신호의 전파 경로손실을 예측하기는 매우 어렵다. 본 고에서는 대전 및 서울 지역에서 전계강도를 측정하여 단구간 중앙치,500m 거리별 평균치 및 표준 편차를 산출하여 분석하였다. 분석 결과, 경로손실 특성이 예측모텔과 유사하였으며, 특히 단구간 중앙치 는 기지국 안테나 높이, 지형구조와 인위적 환경에 의존하며, 표준편차는 2-1OdBuV사이에 있음을 알 수 있다.

• 한국해양공학회지
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• 제34권3호
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• pp.167-179
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• 2020

Recently, the increasing importance of artificial intelligence (AI) technology has led to its increased use in various fields in the shipbuilding and marine industries. For example, typical scenarios for AI include production management, analyses of ships on a voyage, and motion prediction. Therefore, this study was conducted to predict a response amplitude operator (RAO) through AI technology. It used a neural network based on one of the types of AI methods. The data used in the neural network consisted of the properties of the vessel and RAO values, based on simulating the in-house code. The learning model consisted of an input layer, hidden layer, and output layer. The input layer comprised eight neurons, the hidden layer comprised the variables, and the output layer comprised 20 neurons. The RAO predicted with the neural network and an RAO created with the in-house code were compared. The accuracy was assessed and reviewed based on the root mean square error (RMSE), standard deviation (SD), random number change, correlation coefficient, and scatter plot. Finally, the optimal model was selected, and the conclusion was drawn. The ultimate goals of this study were to reduce the difficulty in the modeling work required to obtain the RAO, to reduce the difficulty in using commercial tools, and to enable an assessment of the stability of medium/small vessels in waves.

• 한국안전학회지
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• 제22권5호
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• pp.84-89
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• 2007

폭발하한계는 가연성물질의 화재 및 폭발 위험성을 결정하는데 사용되는 중요한 연소특성치의 하나이다. 본 연구에서 에스테르 화합물에 대한 폭발하한계는 액체 열역학이론을 근거로 표준끓는점과 인화점을 이용하여 예측하였다. 그 결과, 문헌값과 예측값의 A.A.P.E.(average absolute percent error)는 8.80vo1%이고, A.A.D.(average absolute deviation)는 0.18vo1% 그리고 상관계수는 0.965로써 문헌값과 예측값은 일치하였다. 제시된 방법론 사용에 의해 다른 가연성물질의 폭발하한계 예측이 가능하다.

• Journal of Mechanical Science and Technology
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• 제20권7호
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• pp.1077-1088
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• 2006

This paper describes a numerical investigation on the performance deteriorations of a low speed, single-stage axial turbine due to use of rough blades. Numerical calculations have been carried out with a commercial CFD code, CFX-Tascflow, by using a modified wall function to implement rough surfaces on the stator vane and rotor blade. To assess the stage performance variations corresponding to 5 equivalent sand-grain roughness heights from a transition ally rough regime to a fully rough regime, stage work coefficient and total to static efficiency were chosen. Numerical results showed that both work coefficient and stage efficiency reduced as roughness height increased. Higher surface roughness induced higher blade loading both on the stator and rotor which in turn resulted in higher deviation angles and corresponding work coefficient reductions. Although, deviation angle changes were small, a simple sensitivity analysis suggested that their contributions on work coefficient reductions were substantial. Higher profile loss coefficients were predicted by higher roughness heights, especially on the suction surface of the stator and rotor. Furthermore sensitivity analysis similar to the above, suggested that additional profile loss generations due to roughness were accountable for efficiency reductions.

• 한국도로학회논문집
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• 제6권3호
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• pp.55-64
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• 2004

최대건조단위중량은 노상토 재료 특성으로서 매우 중요한 인자이다. 최대건조단위중량을 예측하는 기존의 모델들은 많은 변수를 포함하고 있어 다소 복잡해 보인다 본 논문에서는 사질토의 최대건조단위중량을 예측할 수 있는 간편한 식을 제안하였다. 이를 위해 36개 시료를 체분석하여 입도분포를 구하고, 다짐시험 한 후 그 결과를 회귀 분석하였다. 제안식은 변수로 노상토의 기하평균과 기하표준편차 또는 입도분포계수를 포함한다. 제안식의 검증을 위해 전국16개 지역의 채취 시료에 대한 최대건조단위중량의 실측치와 예측치를 비교한 결과 잘 맞는 것으로 밝혀졌다.

• Journal of Mechanical Science and Technology
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• 제20권3호
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• pp.399-408
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• 2006

Nucleate pool boiling heat transfer coefficient (HTCs) were measured with one nonazeotropic mixture of propane/isobutane and two azeotropic mixtures of HFC134a/isobutane and propane/HFC 134a. All data were taken at the liquid pool temperature of $7^{\circ}C$ on a horizontal plain tube of 19.0mm outside diameter with heat fluxes of $10\;kW/m^2\;to\;80kW/m^2$ with an interval of $10\;kW/m^2$ in the decreasing order of heat flux. The measurements were made through electrical heating by a cartridge heater. The nonazeotropic mixture of propane/isobutane showed a reduction of HTCs as much as 41% from the ideal values. The azeotropic mixtures of HFC134a/isobutane and propane/HFC134a showed a reduction of HTCs as much as 44% from the ideal values at compositions other than azeotropic compositions. At azeotropic compositions, however, the HTCs were even higher than the ideal values due to the increase in the vapor pressure. For all mixtures, the reduction in heat transfer was greater with larger gliding temperature difference. Stephan and Korner's and lung et al's correlations predicted the HTCs of mixtures with a mean deviation of 11%. The largest mean deviation occurred at the azeotropic compositions of HFC134a/isobutane and propane/HFC134a.

• Nuclear Engineering and Technology
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• 제52권11호
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• pp.2565-2571
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• 2020

Background: Understanding the behaviour of nuclear fuel claddings by conducting burst test on single cladding tube under simulated loss-of-coolant accident conditions and developing theoretical cum empirical predictive computer codes have been the focus of several investigations. The developed burst criterion (a) assumes symmetrical deformation of cladding tube in contrast to experimental observation (b) interpolates the properties of Zircaloy-4 cladding in mixed α+β phase (c) does not account for azimuthal temperature variations. In order to overcome all these drawbacks of burst criterion, it is reasoned that artificial intelligence technique may be a better option to predict the burst parameters. Methods: Artificial neural network models based on feedforward backpropagation algorithm with logsig transfer function are developed. Results: Neural network architecture of 2-4-4-3, that is model with two hidden layers having four nodes in each layer is found to be the most suitable. The mean, maximum, and minimum prediction errors for this optimised model are 0.82%, 19.62%, and 0.004%, respectively. Conclusion: The burst stress, burst temperature, and burst strain obtained from burst criterion have average deviation of 19%, 12%, and 53% respectively whereas the developed neural network model predicted these parameters with average deviation of 6%, 2%, and 8%, respectively.

• Korean Chemical Engineering Research
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• 제56권5호
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• pp.663-678
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• 2018

Refractive index and speeds of sound for the binary mixture of isomer of butanol (1) + cyclohexane, benzene and toluene (2) were measured at 308.15 K. The measured data were used to calculate deviation in refractive index ${\Delta}n$, ultrasonic speed ${\Delta}u$, isentropic compressibility $K_s^E$, available volume $V_a$, excess intermolecular free length $L_f$ and molecular association $M_A$. All the derived properties were correlated with polynomial equation. Ultrasonic speed data were predicted using various empirical correlations like Nomoto, van Dael, impedance dependence and theoretically with Schaaff's collision factor theory (CFT). Jacobson free length theory (FLT) was used to calculate $L_f$. The measured refractive index was also correlated with various mixing rules. The deviation in refractive index Δn and ultrasonic speed ${\Delta}u$ was used to determine the intermolecular interactions.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2007년도 동계학술발표대회 논문집
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• pp.241-246
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• 2007

The present paper dealt with an experimental study of boiling heat transfer characteristics of $CO_2$. Heat transfer coefficients of the refrigerant flow inside horizontal smooth microchannel were obtained with inner tube diameter of 0.3mm and length of 300mm. The direct electric heating method was applied for supplying the heat uniformly to the refrigerant. The experiments were conducted with $CO_2$ purity of 99.99%, at saturation temperature of $10^{\circ}C$, mass flux ranges of $300{\sim}900\;kg/m^2s$, and heat flux ranges of $15{\sim}45\;kW/m^2$. While heat transfer coefficient increased with the increase of heat flux in the low quality region, the heat transfer coefficient decreased with the increase of quality in the high quality region. The heat transfer coefficients were compared with seven existing correlations with the Gungor-Winterton's(1986) correlation gave the best prediction. A new corelation to predict the two-phase flow heat transfer coefficient was developed based on the Chen(1966) correlation. The new correlation predicted the experimental data well with a mean deviation of 9.69% and average deviation of -3.03%.