• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2005년도 추계 학술대회논문집
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• pp.39-44
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• 2005

In HANARO, a multi-purpose research reactor of 30 MWth, the emergency water supply system consists essentially of an emergency water storage tank located in the level of about thirteen meter (13 m) above the reactor core, a three inch ('3\%') diameter water injection pipe line including injection valves from the tank to the reactor cooling inlet pipe and a test loop to do periodic system performance test. When the water level of the reactor pool comes down to the extremely low due to a loss of reactor pool water accident the emergency water stored in the tank should be fed to the core by the gravity force and at that time the design flow rate is eleven point four kilogram per second (11.4 kg/s). But it is impossible periodically to measure the injection flow rate under the emergency condition because the normal water level should be maintained during the reactor operation. This paper describes a flow network analysis to simulate the flow rate under the emergency condition. As results, it was confirmed through the analysis results that the calculated flow rate agrees with the design requirement under the emergency condition.

• 한국통신학회논문지
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• 제30권8A호
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• pp.688-696
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• 2005

본 논문에서는 위성을 이용한 디지털 위성방송 시스템에 적용하기 위한 고효율 평면안테나를 설계 및 제작하였다. 전통적인 접시형 안테나에 비하여 높은 개구효율, 용11한 설치 및 미려한 외관 등의 장점을 가지고 있는 평면 안테나를 설계하였다. 안테나 소자의 설계에는 마이크로스트립을 이용한 Annular Ring 공진기를 이용하였으며, 방사형 도파관을 이용한 급전구조를 채택하였다. 또한 수신신호를 중간주파 신호로 변환하기 위한 LNB를 안테나의 뒷면에 설치함으로써 전송손실의 최소화를 꾀하였다. 제작된 안테나는 직경 35cm, 이득은 31.8dBi 이며 개구효율은 약 $80\%$이다.

• The Journal of Advanced Prosthodontics
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• 제12권2호
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• pp.61-66
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• 2020

PURPOSE. The aim of the present study was to determine the degree of conversion of light- and dual-cured resin cements used in the cementation of all-ceramic restorations under different thicknesses of translucent (T) and high-translucent (HT) polymer-infiltrated ceramic-network (PICN) material. MATERIALS AND METHODS. T and HT PICN blocks were prepared at 0.5, 1.0, 1.5, and 2.0 mm thicknesses (n=80). Resin cement samples were prepared with a diameter of 6 mm and a thickness of 100 ㎛. Light-cured resin cement was polymerized for 30 seconds, and dual-cure resin cement was polymerized for 20 seconds (n=180). Fourier transform infrared spectroscopy (FTIR) was used for degree of conversion measurements. The obtained data were analyzed with ANOVA and Tukey HSD, and independent t-test. RESULTS. As a result of FTIR analysis, the degree of conversion of the light-cured resin cement prepared under 1.5- and 2.0-mm-thick T and HT ceramics was found to be lower than that of the control group. Regarding the degree of conversion of the dual-cured resin cement group, there was no significant difference from the control group. CONCLUSION. Within the limitation of present study, it can be concluded that using of dual cure resin cement can be suggested for cementation of PICN material, especially for thicknesses of 1.5 mm and above.

• 한국정보처리학회논문지
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• 제1권1호
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• pp.92-98
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• 1994

Hypercubes와 유사한 구조를 가진 X-hypercubes는 hypercubes와 같은수의 node와 edge를 갖고 있다.그러나 node들을 연결한는 방법을 약간 바꾸어 줌으로써 X-hypercubes내의 node들간의 통신시의 delay는 hypercubes 의 그것보다 훨씬 적어지는 것을 기대할 수 있다. 본 논문에서는 X-hypercubes를 새롭게 정의함으로써 두 node들 간의 연결에 관한 조건들을 명확히 해준다.이 정의에 대한 응용으로서,본 논문은 hypercubes 를 X-hypercubes로 그리고 X-hypercubes 를 hypercubes로 embedding시키는 algorthm을 보여준다.이는 이들 두 network에서 운용되는 program 들이 최소한 overhead만으로써 서로 호완될 수 있음을 말해준다.또한 본 논문은 hypercubes 에서의 bitionic merge sort를 simulate함으로써,X-hypercubes에서 운용될 수 있는 bitonic merge sort도 보여주고 있다.

• 한국통신학회논문지
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• 제36권10A호
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• pp.816-822
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• 2011

본 논문은 모바일 컨버전스를 위해서는 가장 필요하다고 보이는 대중적인 무선통신 방법인 IEEE802.11 무선랜의 성능이 이동성을 가지는 환경에서 어떠한지를 실제로 측정하고 성능을 분석해본다. 성능 분석을 위해서는 기존의 IEEE802.11b/g와 차량간 통신(V2V) 환경에 적합하게 설계된 IEE802.11p에 대해서 성능을 측정하여 분석하였다. 본 논문에서는 기존의 IEEE802.11b/g는 V2I, IEEE802.11p는 V2I와 V2V에서 실험을 진행하였다. 따라서 각각 자동차의 주행속도를 점차 증가시켜 실험을 진행하였으며, 그에 따른 통신반경, 링크접속시간, 데이터 전송속도, 지연시간을 측정하였다. 또한 무선 채널에 512, 1024, 1518 byte의 부하를 가지게 함으로써, 주위에 통신량이 많고 적은 상황에 따른 성능도 확인하였다. 결론을 통해서는 분석된 내용을 기반으로 향후 연구 내용을 논한다.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제2권11호
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• pp.471-474
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• 2013

본 논문에서는 효율적인 peer-to-peer(P2P) 네트워크의 토폴로지 구축을 위해 참여 피어의 용양과 데이터 소스까지의 홉 수를 고려한 분산적 부모 피어 선택 기법을 제안한다. 이를 위해 우선 각 피어가 부모 피어로 선정될 확률을 결정하기 위해 피어의 용양과 거리를 결합하는 방안을 제시하고 각 피어가 분산적으로 관리하는 이웃피어의 상태 정보를 이용하여 확률적으로 부모 피어를 선택하는 방안을 제시한다. 모의실험을 통해 제안 기법은 용양이 큰 피어가 보다 많은 자식 피어들을 지원하게 함으로써 타 기법들에 비해 동일 환경에서 P2P 네트워크의 지름과 네트워크 구성의 효율성 측면에서 우수함을 정량적으로 검증하였다.

• Journal of the Korean Physical Society
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• 제73권12호
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• pp.1834-1839
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• 2018

A tabletop ultrafast soft x-ray has been generated from the laser-produce plasma with a femtosecond pulsed Ti:Sapphire laser. The estimated total flux of Al $K{\alpha}$ is of $2.2{\times}10^9photons/sec$ in $4{\pi}$ radian and the parameters related to the optical performance were obtained. The tungsten/silicon multilayer, flat quartz and bent thallium acid phthalate (TLAP) crystal were used for monochromatization of soft x-ray to refine the aluminum $K{\alpha}$ radiation and compared the respective value of $E/{\Delta}E$. To estimate the size of the x-ray source beam generated by a fs laser, the approximation using the FWHM obtained from the x-ray beam scan near the focal point was discussed, and the size of the diameter was about $9.76{\mu}m$.

• 소성∙가공
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• 제30권3호
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• pp.125-133
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• 2021

In this study, response surface method (RSM), back propagation neural network (BPNN), and genetic algorithm (GA) were used for modeling and multi-objective optimization of the parameters of AA5052-H32 in incremental sheet forming (ISF). The goal of optimization is to determine the maximum forming angle and minimum surface roughness, while varying the production process parameters, such as tool diameter, tool spindle speed, step depth, and tool feed rate. A Box-Behnken experimental design (BBD) was used to develop an RSM model and BPNN model to model the variations in the forming angle and surface roughness based on variations in process parameters. Subsequently, the RSM model was used as the fitness function for multi-objective optimization of the ISF process the GA. The results showed that RSM and BPNN can be effectively used to control the forming angle and surface roughness. The optimized Pareto front produced by the GA can be utilized as a rational design guide for practical applications of AA5052 in the ISF process

• Structural Engineering and Mechanics
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• 제84권1호
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• pp.101-111
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• 2022

It is widely known that axially loaded fiber-reinforced polymer (FRP) confined concrete presents significant and enhanced mechanical properties with reference to the unconfined concrete. Therefore, to predict the mechanical behavior of FRP-confined concrete two quantities-peak strength and ultimate strain are required. Despite the significant advances, the determination of the ultimate strain of FRP-confined concrete is one of the most challenging problems to be resolved. This is often attributed to our persistence in desiring the conventional methods as the sole technique to examine this phenomenon and the complex nature of the ultimate strain of FRP-confined concrete. To bridge the research gap, this study adopted two machine learning (ML) techniques-artificial neural network (ANN) and Gaussian process regression (GPR)-to analyze observations obtained from 627 datasets of FRP-confined concrete circular and non-circular sections under axial loading test. Besides, the techniques are also used to predict the ultimate strain of FRP-confined concrete. Seven parameters namely width/diameter of the specimens, corner radius ratio, the strength of concrete, FRP elastic modulus, FRP thickness, FRP tensile rupture strain, and the axial strain of unconfined concrete-are the input parameters used to predict the ultimate strain of FRP-confined concrete. The results of the current study highlight the merit of using AI techniques in structural engineering applications given their extraordinary ability to comprehend multidimensional phenomena of FRP-confined concrete structures with ease, low computational cost, and high performance over the existing empirical models.

• Smart Structures and Systems
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• 제29권2호
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• pp.337-350
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• 2022

This paper focuses on predicting the post-heating mechanical properties of cementitious composites reinforced with multi-scale additives using the Artificial Neural Network (ANN) approach. A total of four different feed-forward ANN models are developed using 261 data sets collected from 18 published sources. The models are optimized using 12 input parameters selected based on a comprehensive literature review to predict the residual compressive strength, the residual flexural strengths, elastic modulus, and fracture energy of heat-damaged cementitious specimens. Furthermore, the ANN is employed to predict the impact of several variables including; the content of polypropylene (PP) microfibers and carbon nanotubes (CNTs) used in the concrete, mortar, or paste mix design, length of PP fibers, the average diameter of CNTs, and the average length of CNTs. The influence of the studied parameters is investigated at different heating levels ranged from 25℃ to 800℃. The results demonstrate that the developed ANN models have a strong potential for predicting the mechanical properties of the heated cementitious composites based on the mixing ingredients in addition to the heating conditions.