• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.179-183
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• 2009

본 연구에서는 GCM 기후변화 전망 시나리오를 이용하여 유역단위의 기후변화를 추정하였다. 원시 GCM 시나리오를 지역화 시키기 위해서 인공신경망 모형을 사용하였다. GCM에서 모의되는 강수플럭스, 해면기압, 지표면 근처에서의 일 평균온도, 지표면으로부터 발생하는 잠열플럭스 등과 같은 22개의 변수는 인공신경망의 잠재적 예측인자로 사용되었으며, AWS에서 관측된 강수량과 온도는 예측변수로 사용되었다. 원시 GCM 데이터는 CCCma(Canadian Centre for Climate Modeling and Analysis)에서 제공되는 CGCM3.1/T63 20C3M 시나리오를 사용하였으며, 인공신경망 학습과정에서 사용된 기준시나리오(reference scenario)자료의 기간은 1997년부터 2000년까지의 데이터를 사용하였다. 인공신경망을 학습을 통하여 결정된 각 층사이의 가중치를 이용하여 이산화탄소 배출농도를 가정하여 생성된 CGCM3.1/T63 SRES B1 기후변화시나리오(project scenario)를 인공신경망의 입력값으로 하여 미래의 기온과 강수변화를 전망하였다. 신경망의 학습효과를 높이기 위하여 기온과 강수에 대한 평균 및 누적기간을 각각 일단위와 월단위로 설정하였다. 본 연구에서 사용된 인공신경망은 3층 퍼셉트론(다층 퍼셉트론)을 사용하였으며, 학습방법으로는 역전파알고리즘(back-propagation algorithm)을 이용하였다. 민감도분석을 통하여 선택된 예측인자는 소양강댐유역(1011, 1012소유역)에서의 인공신경망 예측인자로 활용되었으며, 2001년부터 2100년까지의 일 평균온도와 일 강수량의 변화경향을 추정하였다. 1011유역, 1012유역에서는 여름철의 온도변화경향이 겨울철에 비하여 높게 나타났다. 일 평균온도의 통계분석 결과 평균예측오차가 가장 적게 나타나는 지역은 1001유역으로 -0.08로 평균예측오차가 가장 적게 나타났으며, 인공신경망기법을 이용하여 스케일 상세화된 일 평균온도와 관측된 일 평균온도가 얼마나 잘 일치하는지를 확인할 수 있는 1012유역에서 CORR이 0.74로 가장 높게 나타났다.

• Polymer(Korea)
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• v.25 no.2
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• pp.279-292
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• 2001

Two kinds of (hydroxypropyl)cellulose(HPCs) with different molar substitution (MS) and three types of derivatives based on the HPCs: (acetoxypropyl)celluloses, (ethoxypropyl)celluloses, and (cyanoethoxyprofyl)celluloses were synthesized, and their thermal and mesomorphic properties were investigated. All samples, which exhibit cholesteric reflection colours at room temperature, formed right-handed helicoidal structures whose optical pitches (λ$_{ms}$ ) increase with temperature. However, the isotropization ($T_{i}$) and glass temperatures, the magnitude of λ$_{m}$ of the mesophase at the same temperature, and the temperature dependence of λ$_{m}$ of the investigated derivatives highly depended on MS and the length and structure of the side chain introduced in HPC. The results were discussed in terms of the difference in the polarity and flexibility of the substituents and the distance between the main chains. For all derivatives, Am values approached infinity at temperatures above the $T_{i}$, of the mesophase, and no reversal in the sense of the pitch with temperature was detected.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.4
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• pp.414-422
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• 2002

In this paper, we propose a new method of adaptive neuro-fuzzy control using CFCM(Conditional Fuzzy c-means) clustering and fuzzy equalization method to deal with adaptive control problem. First, in the off-line design, CFCM clustering performs structure identification of adaptive neuro-fuzzy control with the homogeneous properties of the given input and output data. The parameter identification are established by hybrid learning using back-propagation algorithm and RLSE(Recursive Least Square Estimate). In the on-line design, the premise and consequent parameters are tuned to RLSE with forgetting factor due to a characteristic of time variant. Finally, we applied the proposed method to the water temperature control system and obtained better results than previous works such as fuzzy control.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.9
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• pp.361-366
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• 2016

As an alternative of well-mixed storage tank with lower coil only, we have proposed a tank with lower and upper coils and verified a superior thermal stratification in a tank, which results in increased collector efficiency and solar fraction. But the phenomenon of temperature reversal was often experimentally observed in the tank, so a revised control was successfully applied which is to heat only lower coil using three way valve if temperature reversal occurs and to operate the collector with low flow rate when the condition of solar radiation is not good. In the present study, using TRNSYS we compared the existing lower heating and the proposed lower and upper heating with a control preventing temperature reversal. The results showed that the proposed method has an increase of collector efficiency by 5.1% and solar fraction by 3.2%.

• Journal of the Korean Society of Propulsion Engineers
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• v.21 no.1
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• pp.72-83
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• 2017

A thermo-fluid dynamic analysis was performed through the numerical simulation of a missile canister. Calculation was made in a fixed analytical volume and fully evaporated water was used as a coolant. To analyze the interaction among the hot gas, coolant, and mixture flow, Realizable $k-{\varepsilon}$ turbulence and VOF(Volume Of Fluid) model were chosen and parametric study was performed with the change of coolant flow rate. It could be found that the pressure on the canister top nonlinearly increased with the increase of coolant flow rate. Temperature and coolant distribution were closely related to the flow behavior in canister. Temperature on the canister bottom indicated a decrease being proportional to coolant flow rate in early times but after a specific time, the temperature increased with the tendency being reversed. In addition, the early part of temperature showed a fluctuating phenomenon because of the overall circulatory flow of mixture gas.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.1
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• pp.9-15
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• 2011

Communication environments in the context of underwater channel are characterized to be bad by the characteristics of multipath. Multipaths are affected by various factors e.g. the temperature and the salinity of the ocean. In this paper, the representative sound speed profiles were calculated in the southern part of Baengnyeoung island so that the eigen-ray paths with the channel impulse responses were determined using the average sound speed profile of last decade. The performance of underwater communication was analyzed using the BPSK modulation and time reversal method. The significant differences of results were shown according to the change of season and carrier frequency by using computer simulation. In addition, improved performance is obtained using preprocess channel impulse response for the better comparison of two cases of summer and autumn.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.7
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• pp.51-60
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• 2002

The Monte-Carlo simulation of statistical analysis is used to investigate the final conditions of states as well as the footprint boundaries resulting from the atmospheric re-entry dispersions. The re-entry dispersions in this paper are specified by a $7\times7$ covariance matrix of latitude, longitude, altitude, bank angle, flight path angle, heading error, and range at entry velocity. The error sources that affect these at re-entry for a deboost are the uncertainties associated with atmospheric density and temperature, initial errors, wind, and estimation error of aerodynamic coefficients. Using $3{\sigma}_n$ deviations of these errors and a nominal flight trajectory, the covariance matrix of state variables can be determined by performing a trajectory error analysis. Major considerations in the application of the Monte-Carlo method are the simulation of perturbed trajectories, bank reversal, and determination of the impact points for each of these trajectories. This paper analyzes the results of uncertainties from the viewpoint of aero-coefficients and bank reversal.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4A
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• pp.639-645
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• 2006

FRP (Fiber Reinforced Polymer) is an excellent new constructional material in resistibility to corrosion, high intensity, resistibility to fatigue, and plasticity. FBG (Fiber Bragg Grating) sensor is widely used at present as a smart sensor due to lots of advantages such as electric resistance, small-sized material, and high durability. However, with insufficiency of measuring displacement, FBG sensor is used only as a sensor measuring physical properties like strain or temperature. In this study, FRP and FBG sensors are to be hybridized, which could lead to the development of a smart FRP rod. Moreover, developing the estimated model for deflection with neural network method, with the data measured through FBG sensor, could make conquest of a disadvantage of FBG sensor - uniquely used for sensing strain. Artificial neural network is MLP (Multi-layer perceptron), trained within error rate of 0.001. Nonlinear object function and back-propagation algorithm is applied to training and this model is verified with the measured axial displacement through UTM and the estimated numerical values.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1261-1267
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• 2000

외부에서 자극이 가해질 때 상전이(phase transformations)하는 방식으로 대응하는 재료들이 최근 다양하게 연구되고 있다. 예를 들어 형상기억합금은 주변 온도의 변화에 대응하여 그 형상을 변화시키는데 이 과정은 미시적으로는 격자의 형태가 - 예를 들면 정방형 격자에서 입방형격자로 혹은 그 반대로 - 변화하는 과정이다. 강유전체 역시 외부에서 인가되는 전계의 변화에 대응하여 그 격자구조가 변하는데 그와 함께 기계적 변형이 동반하게 된다. 본 논문에서는 상전이를 하는 재료에 적용될 수 있는 1차원 구성방정식을 강유전체의 예를 들어 제시하고 간단한 계산결과를 보이기로 한다. 본 모델을 확장하여 강유전체에서의 분극역전(polarization reversals)에 대한 3차원 유한요소 모델을 개발하고 응용하려는 시도가 이루어지고 있다.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.14 no.4
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• pp.94-100
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• 2006

The purpose of this case study is to determine the possibility of Numerical Forecasting of sea fog at West Sea in spring time. For practical method of analyzing the data collected from 24th to 26th March 2003, Numerical Weather Prediction model MM5(Mesoscale Model Version 5) and synoptic field study using synoptic chart, upper level chart, and sea surface temperature were employed. The results of synoptic field analysis summarized that sea fog at West sea in spring is intensified by the inflow of the warm flow from west or southwest, low sea surface temperature to increase the temperature difference between air and sea surface, and inversion layer to disturb the disperse. It appears that the possibility of sea fog forecasting by MM5, in view of the result that the MM5 output is similar to the synoptic fields analysis.