• 전자공학회논문지
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• 제51권7호
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• pp.103-110
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• 2014

최근 등장한 TSV(Through Silicon Via)기반의 3D 적층 기술은 보다 강력한 발열관리 기법을 필요로 하며 냉각 비용과 폼팩터(form factor)의 제한을 고려했을 때 소프트웨어적인 열관리 기법의 중요성이 더욱 강조되고 있다. 이러한 접근 방식의 유력한 후보 중 하나로 제시되었던 스로틀링을 통한 열관리 기법의 경우, 증가하는 버스 점유율로 인해 전체적인 성능저하를 야기하는 문제점이 있다. 본 논문에서는 향후 TSV 기반 3D SoC의 커뮤니케이션 병목 현상을 해결하기 위한 3D 네트워크-온-칩 (Network-on-Chip, NoC) 구조에서 어댑티브 스로틀링 기법을 제안하여, 열관리와 더불어 온-칩 네트워크상의 트래픽 감소를 통해 전체적인 성능향상을 목표로 한다. 본 논문에서는 실험을 통하여 기존의 방식에 비하여 스로틀링으로 인해 저하된 처리량이 최소경로 라우팅 시 최대 72% 향상됨을 알 수 있었다.

• Composites Research
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• 제37권3호
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• pp.197-203
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• 2024

고분자 복합재료의 기계적 특성 향상에 유리한 탄소섬유(Carbon fiber, CF)와 전도 특성 향상에 유리한 다중벽 탄소나노튜브(Multi-walled carbon nanotube, MWCNT)의 동시 혼입을 통해 기계적, 전기적 및 열적 특성을 동시에 향상시킬 수 있다. 본 연구에서는 우수한 양산 가공성과 준수한 기계적 특성을 나타내는 탄소장섬유 열가소성플라스틱(Carbon long fiber thermoplastic, CLFT)에 MWCNT를 혼입하여 전기적 및 열적 특성 제어하였다. 제조된 복합재료의 기계적 및 전기적 특성은 필러의 혼입 양에 가장 크게 영향을 받았다. 반면, 열적 특성은 MWCNT의 혼입으로 연결된 필러 네트워크가 형성됨으로써 더 우수한 결과를 나타내었다. MWCNT 혼입 CLFT의 필러 혼입량, 필러 조성 및 필러 네트워크 구조를 조절함으로써 목적에 적합한 기계적, 전기적 및 열적 특성 제어할 수 있었다.

• 대한기계학회논문집B
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• 제21권3호
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• pp.457-472
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• 1997

We studied the temperature distribution and heat transfer characteristics of TEFC induction motor with thermal network program for more efficient design and better cooling performance of it. We knew the characteristics and the windage loss of outer cooling fan from fan test experiments. Frame axial and peripheral heat transfer coefficients and endwinding heat transfer coefficient were measured by various model experiments and then, compared with other experimental results. Frame was the main heat transfer surface, load-side and fan-side surface were not thermally symmetric from the heat flux distribution analysis. Steady and unsteady temperature distributions were measured by real motor experiments. From the results, we knew that rotor surface temperature was higher than coil temperature and the hottest spot in the coil was loadside endwinding outside surface. We compared the simulation results with those of real motor test and the two results showed a good agreement.

• Advances in materials Research
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• 제1권4호
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• pp.245-268
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• 2012

Results of isothermal torsional oscillation tests are reported on melts of linear low density polyethylene and isotactic polypropylene. Prior to rheological tests, specimens were annealed at various temperatures ranging from $T_a$ = 180 to $310^{\circ}C$ for various amounts of time (from 30 to 120 min). Thermal treatment induced degradation of the melts and caused pronounced decreases in their molecular weights. With reference to the concept of transient networks, constitutive equations are developed for the viscoelastic response of polymer melts. A melt is treated as an equivalent network of strands bridged by junctions (entanglements and physical cross-links). The time-dependent response of the network is modelled as separation of active strands from and merging of dangling strands with temporary nodes. The stress-strain relations involve three adjustable parameters (the instantaneous shear modulus, the average activation energy for detachment of active strands, and the standard deviation of activation energies) that are determined by matching the dependencies of storage and loss moduli on frequency of oscillations. Good agreement is demonstrated between the experimental data and the results of numerical simulation. The study focuses on the effect of molecular weight of polymer melts on the material constants in the constitutive equations.

• 제어로봇시스템학회논문지
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• 제6권1호
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• pp.104-111
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• 2000

A fuzzy logic Run-by-Run(RbR) controller and an in -line wafer characteristics prediction scheme for the rapid thermal processing system have been developed for the study of process repeatability. The fuzzy logic RbR controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The fuzzy logic RbR controller combines the advantages of both fuzzy logic and feedback control. It has two components : fuzzy logic diagnostic system and model modification system. At first, a neural network model is constructed with the I/O data collected during the designed experiments. The wafer state after each run is assessed by the fuzzy logic diagnostic system with featuring step. The model modification system updates the existing neural network process model in case of process shift or drift, and then select a new recipe based on the updated model using genetic algorithm. After this procedure, wafer characteristics are predicted from the in-line wafer characteristics prediction model with principal component analysis. The fuzzy logic RbR controller has been applied to the control of Titanium SALICIDE process. After completing all of the above, it follows that: 1) the fuzzy logic RbR controller can compensate the process draft, and 2) the in-line wafer characteristics prediction scheme can reduce the measurement cost and time.

• Journal of information and communication convergence engineering
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• 제20권4호
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• pp.303-308
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• 2022

Simulating the heat transfer in a composite material is an important topic in material science. Difficulties arise from the fact that adjacent materials cannot match perfectly, resulting in discontinuity in the temperature variables. Although there have been several numerical methods for solving the heat-transfer problem in imperfect contact conditions, the methods known so far are complicated to implement, and the computational times are non-negligible. In this study, we developed a ResNet-type deep neural network for simulating a heat transfer model in a composite material. To train the neural network, we generated datasets by numerically solving the heat-transfer equations with Kapitza thermal resistance conditions. Because datasets involve various configurations of composite materials, our neural networks are robust to the shapes of material-material interfaces. Our algorithm can predict the thermal behavior in real time once the networks are trained. The performance of the proposed neural networks is documented, where the root mean square error (RMSE) and mean absolute error (MAE) are below 2.47E-6, and 7.00E-4, respectively.

• 대한조선학회논문집
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• 제60권4호
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• pp.222-230
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• 2023

In the present work, the scale effect on the Boil-Off Rate (BOR) was investigated based on an analytical method to systematically evaluate the thermal performance of a Liquefied Natural Gas (LNG) Cargo Containment System (CCS). A two-dimensional thermal resistance network model was developed to accurately estimate the heat ingress into the CCS from the outside. The analysis was performed for the KC-1 LNG membrane tank under the IGC and USCG design conditions. The ballast compartment of both the LNG tank and cofferdam was divided into six sections and a thermal resistance network model was made for each section. To check the validity of the developed model, the analysis results were compared with those from existing literature. It was shown that the BOR values under the IGC and USCG design conditions were agreed well with previous numerical results with a maximum error of 1.03% and 0.60%, respectively. A SDR, the scale factor of the LNG CCS was introduced and the BOR, air temperature of the ballast compartment, and the surface temperature of the inner hull were obtained to examine the influence of the SDR on the thermal performance. Finally, a correlation for the BOR was proposed, which could be expressed as a simple formula inversely proportional to the SDR. The proposed correlation could be utilized for predicting the BOR of a full-scale LNG tank based on the BOR measurement data of lab-scale model tanks.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 B
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• pp.946-948
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• 2002

최근 컴퓨팅 기술의 발전으로 3차원 복합열전달(conjugate heat transfer) 문제를 계산하는 수 치해석 기술이 어느 정도 가능해 졌지만, 실제적인 전력기기 내부의 온도분포를 수치적으로 계산하는 것은 탑재된 구성요소의 다양한 크기와 형상으로 인한 매우 복잡한 경계조건을 수반하고 조밀한 격자를 요구하기 때문에 공학적이지 않다. 이를 위하여 해석적 모델을 수립하여 전력기기 열설계를 위한 수치적 해석에 적용하는 방법이 널리 사용되고 있다. 본 연구에서는 열회로망법(Thermal Network Analysis, TNA)을 이용하여 전력기기 내부의 온도분포를 예측할 수 있는 프로그램을 개발하였다. 전류가 흘러 열이 발생하고 소산되는 주회로 성분들을 각각의 노드로 분할하는 절차를 확립하였고 열접촉저항과 주울열을 적절히 선정함으로써 실제 전류가 흐르는 회로망 내 온도분포를 계산하였다.

• 대한안전경영과학회지
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• 제9권5호
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• pp.79-85
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• 2007

Intelligent machines respond to external environments on the basis of decisions that are made by sensing the changes in the environment and analyzing the obtained information. This study focuses on the construction of a knowledge base which enables decision making with that information. Approximately 70% of all errors that occur in machine tools are caused by thermal error. In order to proactive deal with these errors, a system which measures the temperature of each part and predicts and compensates the displacement of each axis has been developed. The system was built in an open type controller to enable machine tools to measure temperature changes and compensate the displacement. The construction of a machining knowledge base is important for the implementation of intelligent machine tools, and is expected to be applicable to the network based intelligent machine tools which look set to appear sooner or later.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1999년도 추계학술대회 논문집
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• pp.475-478
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• 1999

The thermal properties of epoxy resin/siloxane for the electrical insulation were investigated by using dynamic DSC run method. As the heating rate increased, the peak temperature on dynamic DSC curve increased. From the linear relation on the Kissinger plot the curing reaction activation energy and pre-exponential factor could be obtained. The curing activation energy from the straight line of the Kissinger plot was 46.72 kJ/mol.