• Nuclear Engineering and Technology
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• 제52권12호
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• pp.2709-2716
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• 2020

Compositions of large nuclear cores (e.g. boiling water reactors) are highly heterogeneous in terms of fuel composition, control rod insertions and flow regimes. For this reason, they usually lack high order of symmetry (e.g. 1/4, 1/8) making it difficult to estimate their neutronic parameters for large spaces of possible loading patterns. A detailed hyperparameter optimization technique (a combination of manual and Gaussian process search) is used to train and optimize deep neural networks for the prediction of three neutronic parameters for the Ringhals-1 BWR unit: power peaking factors (PPF), control rod bank level, and cycle length. Simulation data is generated based on half-symmetry using PARCS core simulator by shuffling a total of 196 assemblies. The results demonstrate a promising performance by the deep networks as acceptable mean absolute error values are found for the global maximum PPF (~0.2) and for the radially and axially averaged PPF (~0.05). The mean difference between targets and predictions for the control rod level is about 5% insertion depth. Lastly, cycle length labels are predicted with 82% accuracy. The results also demonstrate that 10,000 samples are adequate to capture about 80% of the high-dimensional space, with minor improvements found for larger number of samples. The promising findings of this work prove the ability of deep neural networks to resolve high dimensionality issues of large cores in the nuclear area.

• Environmental Engineering Research
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• 제13권1호
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• pp.1-7
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• 2008

Recently a new technology called the flexible-fiber deep-bed filter (FDF) claimed to replace the conventional sand filter including coagulation and sedimentation filter (CSF) processes in the water treatment plant. Therefore the life cycle assessment (LCA) approach was applied for evaluating the life cycle impacts of FDF compared with those of CSF. The used LCA softwares were the Simapro 6 and PASS and their life cycle impact assessment (LCIA) methodologies were the Eco-indicator 99 and the Korean Eco-indicator, respectively. The goal of this LCA was to identify environmental loads of CSF and FDF from raw material to disposal stages. The scopes of the systems have been determined based on the experiences of existing CSF and FDF. The function was to remove suspended solids by filtration and the functional unit was $1\;m^3$/day. Both systems showed that most environmental impacts were occurred during the operation stage. To reduce the environmental impacts the coagulants and electricity consumptions need to be cut down. If the CSF was replaced with the FDF, the environmental impacts would be reduced in most of the impact categories. The LCA results of Korean Eco-indicator and Eco- indicator99 were quite different from each other due to the indwelling differences such as category indicators, impact categories, characterization factors, normalization values and weighting factors. This study showed that the life cycle assessment could be a valuable tool for evaluating the environmental impact of the new technology which was introduced in water treatment process.

• 대한원격탐사학회지
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• 제34권6_3호
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• pp.1415-1425
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• 2018

다목적실용위성 5호는 국내 최초로 영상레이더(SAR)가 탑재된 지구관측위성이다. SAR 영상은 위성에 부착된 안테나로부터 방사된 마이크로파가 물체로부터 반사된 신호를 수신하여 생성된다. SAR는 대기 중의 입자의 크기에 비해 파장이 긴 마이크로파를 사용하기 때문에 구름이나 안개 등을 투과할 수 있으며, 주야간 구분 없이 고해상도의 영상을 얻을 수 있다. 하지만, SAR 영상에는 색상 정보가 부재하는 제한점이 존재한다. 이러한 SAR 영상의 제한점을 극복하기 위해, 도메인 변환을 위해 개발된 딥러닝 모델인 Cycle GAN을 활용하여 SAR 영상에 색상을 대입하는 연구를 수행하였다. Cycle GAN은 unpaired 데이터셋 기반의 무감독 학습으로 인해 학습이 불안정하다. 따라서 Cycle GAN의 학습 불안정성을 해소하고, 색상 구현의 성능을 향상하기 위해 다중 크기 식별자를 적용한 MS Cycle GAN을 제안하였다. MS Cycle GAN과 Cycle GAN의 색상 구현 성능을 비교하기 위하여 두 모델이 Florida 데이터셋을 학습하여 생성한 영상을 정성적 및 정량적으로 비교하였다. 다양한 크기의 식별자가 도입된 MS Cycle GAN은 기존의 Cycle GAN과 비교하여 학습 결과에서 생성자 및 식별자 손실이 대폭 감소되었고, 나뭇잎, 강, 토지 등의 영역 특성에 부합하는 색상이 구현되는 것을 확인하였다.

• 한국해양공학회지
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• 제36권1호
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• pp.32-40
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• 2022

Underwater optical images face various limitations that degrade the image quality compared with optical images taken in our atmosphere. Attenuation according to the wavelength of light and reflection by very small floating objects cause low contrast, blurry clarity, and color degradation in underwater images. We constructed an image data of the Korean sea and enhanced it by learning the characteristics of underwater images using the deep learning techniques of CycleGAN (cycle-consistent adversarial network), UGAN (underwater GAN), FUnIE-GAN (fast underwater image enhancement GAN). In addition, the underwater optical image was enhanced using the image processing technique of Image Fusion. For a quantitative performance comparison, UIQM (underwater image quality measure), which evaluates the performance of the enhancement in terms of colorfulness, sharpness, and contrast, and UCIQE (underwater color image quality evaluation), which evaluates the performance in terms of chroma, luminance, and saturation were calculated. For 100 underwater images taken in Korean seas, the average UIQMs of CycleGAN, UGAN, and FUnIE-GAN were 3.91, 3.42, and 2.66, respectively, and the average UCIQEs were measured to be 29.9, 26.77, and 22.88, respectively. The average UIQM and UCIQE of Image Fusion were 3.63 and 23.59, respectively. CycleGAN and UGAN qualitatively and quantitatively improved the image quality in various underwater environments, and FUnIE-GAN had performance differences depending on the underwater environment. Image Fusion showed good performance in terms of color correction and sharpness enhancement. It is expected that this method can be used for monitoring underwater works and the autonomous operation of unmanned vehicles by improving the visibility of underwater situations more accurately.

• 한국태양에너지학회 논문집
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• 제27권3호
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• pp.37-44
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• 2007

For the past few years, the concern for clean energy has been greatly increased. Ocean Thermal Energy Conversion(OTEC) power plants are studied as a viable option for the supply of clean energy. In this paper, the thermodynamic performance of OTEC cycle was examined. Computer simulation programs were developed under the same condition and various working fluids for closed Rankine cycle, regeneration cycle, Kalina cycle, open cycle and hybrid cycle. The results show that the regeneration cycle using R125 showed a 0.17 to 1.56% increase in energy efficiency, and simple Rankine cycle can generate electricity when the difference in warm and cold sea water inlet temperatures are greater than $15^{\circ}C$. Also, the cycle efficiency of OTEC power plant using the condenser effluent from nuclear power plant instead of the surface water increased about 2%.

• 동력기계공학회지
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• 제20권1호
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• pp.11-17
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• 2016

In this study, the simulation for performance comparison between basic single stage organic rankine cycle, multi stage reheater cycle and multi stage reheater & recuperator cycle was carried out. The multi stage reheater cycle and multi stage reheater & recuperator cycle was designed to improve the efficiency for organic rankine cycle using heat source from industrial waste heat and heat sink from deep ocean water. R245fa was selected as a refrigerant for the cycle and system efficiencies were simulated by the variation of the heat sink temperature and the cycle classification. Performance characteristics were simulated by using the Aspen HYSYS. It was confirmed that the system efficiency was decreased by the increase of heat sink temperature. These results can be considered to be applied as geo-ocean thermal energy conversion in where plenty of geothermal or ocean thermal resource exist.

• 방사성폐기물학회지
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• 제11권4호
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• pp.303-309
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• 2013

사용후핵연료의 지층처분의 대안으로 심부시추공을 설치하여 지하 3-5 km 구간에 사용후핵연료를 처분하는 개념이 여러나라에서 제시된 바 있다. 특히 미국 샌디아국립연구소의 최근 연구 결과를 분석하고, 국내 적용을 위한 한국형 캐니스터 디자인과 심부시추공 디자인 개념을 처분 소요 면적과 함께 제시하였다.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 1996년도 춘계학술대회논문집
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• pp.110-120
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• 1996

A crank-slider mechanism is driven by the rotating disk with are crank-pin guide to be applied to the deep drawing and cold forging presses. Load characteristics for different presses are summarized to see the basics of deep drawing of sheet metal and forging in terms of load-stroke relationship. Several types of conventional deep drawing presses are also shown to be compared with the ratating disk-types press. Kinematic performances by thearc guide driving mechanism are anlayzed in terms of load capaicty, stroke, and slide velocity characteristics, and they are compared with those by conventional driving , e.g. Niagara-typepress and so on. Kinematically better performances is shown by arc guide drive than those by conventional ones. The new driving mechanism is also proven to be one of the best for mass production press in terms of short cycle time. Possible applications of the arc guide press to deep drawing and cold forging work are in terms of kinematics and load capacity.

• Journal of Advanced Marine Engineering and Technology
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• 제35권1호
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• pp.46-52
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• 2011

본 연구에서는 폐쇄형 해양온도차발전 효율 향상 방안으로 재열기, 재생기 및 다단 터빈을 적용하여 각 사이클 성능을 비교 분석하였다. 기화기 증발 열원으로 $26^{\circ}C$의 해양표층수를 이용하고 응축기 냉각 열원으로 $5^{\circ}C$의 해양심층수를 이용하는 것으로 가정하였고, 작동유체로는 암모니아를 적용하였다. 3가지 효율 향상 방안에 대한 사이클 효율, 응축기 및 증발기 용량 등 사이클 성능을 비교 분석하였다. 기본 폐쇄형 해양온도차발전 사이클에 재생기를 적용하기 위해서 사이클 시뮬레이션을 수행한 결과, 재생기 부착을 위한 열교환 라인은 터빈 출구 작동유체와 펌프 출구의 작동유체를 열교환하는 것이 사이클 효율 향상에 기여하는 것으로 나타났다. 또한, 기본 사이클에 유용도 0.9의 재열기를 적용한 결과, 터빈 2기를 적용시 사이클 효율이 3.14%로 증가하였고, 동일 총 출력에 대해서 응축기 및 증발기에 필요한 해양표층수 및 해양심층수량이 감소하였다. 사이클 성능 향상 방안으로 기본적인 폐쇄형 해양온도차발전 사이클에 재생기, 재열기 및 터빈 2기를 적용한 결과 기본 폐쇄형 해양온도차발전 사이클에 비해 효율은 약 6.5% 향상되었다.

• 한국산학기술학회논문지
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• 제5권2호
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• pp.128-131
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• 2004

본 연구에서는 STS-ICP ASEHR을 이용하여 Etch와 Deposition 공정을 반복하여 에칭을 하는 Bosch 식각에 관하여 연구하였다. 기본적인 Etch rate의 변화는 Etching하고자 하는 Wafer에 Deposition된 PR 또는 SiO₂의 두께와 Etching하고자 하는 Wafer의 Depth 및 Pattern size가 영향을 준다. 그러나 이러한 기본적인 변수 외에 STS-ICP ASEHR 장비의 Platen power, Coil power 및 Process pressure에 다양한 변화를 주어 각 변수에 따른 Etch rate을 관찰하였다. 각 공정별 변수를 준 결과 Platen power 12W, Coil power 500W, Etch/Passivation Cycle 6/7sec 일 경우 Etch rate은 1.2㎛/min 이었고, Sidewall prpfile은 90±0.2˚로 나타나 매우 우수한 결과를 보였다. 이는 ICP를 이용한 Bosch Process에 의한 결과임을 확인할 수 있었다.