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마이크로핀 관의 기하학적 형상면화에 대한 열전달 특성(II) -증발 열전달-
곽경민,장재식,배철호,정모,Kwak, Kyung-Min,Jang, Jae-Sik,Bae, Chul-Ho,Jung, Mo 대한설비공학회 1999 설비공학 논문집 Vol.11 No.6
The evaporating heat transfer experiments with refrigerant HCFC 22 are performed for performance evaluation using 4 and 6 kinds of microfin tubes with outer diameter of 9.52mm and 7.0mm, respectively. Used microfin tubes have different shape and number of fins with each other, The experimental results are represented with effects of quality, mass flux and EPR. The evaporating heat transfer characteristics are represented by the existence of not only heat transfer area and turbulence promotion effect but also additional other enhancement mechanism, which are the overflow of the refrigerant over the microfin and microfin arrangement. Microfin tubes having a shape which can give much overflow over the microfin show large evaporating heat transfer coefficients. The effect of refrigerant overflow is much severe in evaporation than condensation. The effect of microfin arrangement is related to overflow effect of the refrigerant over the microfin.
곽경민,노영주,Gwak, Kyung-Min,Rho, Young J. 한국인터넷방송통신학회 2021 한국인터넷방송통신학회 논문지 Vol.21 No.4
4차 산업혁명 시대에 맞추어 인공지능 기술은 눈에 띄게 발전하고 있다. 그 중 CNN 등을 활용한 시각 데이터 기반의 인공지능이 활발히 연구 진행 중이다. 시각 기반 모델 중 하나인 U-net은 Semantic Segmentation에 강한 정확도를 보이고 있다. 기존의 U-net을 활용하여 여러 가지 연구들이 진행 되어왔지만 가스, 연기와 같이 외곽선이 뚜렷하지 않은 연구들은 아직 부족한 실정이다. 또한 이와 대조적으로 가스, 연기 탐지에 대해 많은 연구들이 진행이 되어왔지만 U-net 등을 활용하여 단순한 Detection이 아닌 Segmentation 연구는 부족하다. 이를 토대로 본 연구에서는 U-net을 활용하여 가스, 연기 등을 탐지하는 연구를 진행하였다. 본 논문에서는 설정한 실험환경에서 3D camera를 활용하여 데이터를 수집하고 학습 및 테스트 셋을 생성한 방법을 기술하고, U-net을 적용한 방법과 얻은 결과를 검증한 내용을 서술하고, 마지막으로 활용방안 등에 대하여 논하였다. Artificial intelligence technology is developing as it enters the fourth industrial revolution. Active researches are going on; visual-based models using CNNs. U-net is one of the visual-based models. It has shown strong performance for semantic segmentation. Although various U-net studies have been conducted, studies on tracking objects with unclear outlines such as gases and smokes are still insufficient. We conducted a U-net study to tackle this limitation. In this paper, we describe how 3D cameras are used to collect data. The data are organized into learning and test sets. This paper also describes how U-net is applied and how the results is validated.
레이놀즈 수가 낮은 영역에서 와류발생기를 적용한 핀-관 열교환기 성능평가
곽경민,송길달 대한설비공학회 2006 설비공학 논문집 Vol.18 No.2
The present paper reports the method for evaluation of heat-transfer performance of finned tube heat exchangers in a low Reynolds number regime(Re=160∼800) and also reports the data of heat transfer and pressure loss taken from a finned tube heat exchanger with/without vortex generators(VGs) installed as a heat-transfer enhancement device. The evaluation is based on the modified single blow method conducted in a specially designed low Reynolds number duct. Three different test core geometries, i.e., fin only, fin-tube without VGs and that with VGs, are studied here. The data of heat transfer and pressure loss taken from the fin only geometry agree well with the empirical correlations, thus validating the present method as used for low Reynolds number regime. The data taken from the finned tube geometries with and without VGs are presented and compared to examine the effect of VGs in the low Reynolds number regime.