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CFT구조용 초고강도 콘크리트의 현장 적용을 위한 실물대 실험
정근호(Jung. Keun-Ho),정상진(Jung. Sang-Jin),최문식(Choi. Mun-Sik) 대한건축학회 2004 大韓建築學會論文集 : 構造系 Vol.20 No.7
CFT(Concrete Filled steel Tube) combines the benefits of steel structure with that of concrete as a advantageous structure of<br/> being able to exhibit the maximum performance and excels in workability, economical efficiency, with being able possible to make<br/> high-rise building and long-span space and use widely in spite of small-section of column. However, it is difficult to inspect the<br/> filling performance of concrete due to the closed section like circular and square CFT columns. Specially, in case of joint with<br/> diaphragm, there is probability to occur a void in bottom of the diaphragm after placing concrete. Moreover, it is so hard to<br/> guarantee the quality of CFT and facilitate placing of concrete that the ways are needed to control the proper degree of strength<br/> suitable for filled-concrete in steel tubes. Due to this actual circumstances, the fact is that it is difficult for CFT to apply in the<br/> workplace because of lack of confidence in quality control of owner and engineer of high-strength and high flow concrete and lack<br/> of experience in a method placing in sites.<br/> In this study, the research is focused on finding the data on methods of strength concrete for CFT while examining compactability<br/> and workability of concrete by the mock-up test used over 800㎏f/㎠high strength concrete. Through such like this research, it is<br/> aimed at offering required data for field application of CFT in building industry nationwide.
Attention Model 을 이용한 단안 영상 기반 깊이 추정 네트워크
정근호(Geunho, Jung),윤상민(Sang Min, Yoon) 한국방송·미디어공학회 2020 한국방송공학회 학술발표대회 논문집 Vol.2020 No.7
단안 영상에서의 깊이 추정은 주어진 시점에서 촬영된 2차원 영상으로부터 객체까지의 3차원 거리 정보를 추정하는 것이다. 최근 딥러닝 기반으로 단안 RGB 영상에서 깊이 정보 추정에 유용한 특징 맵을 추출하고 이를 이용해서 깊이를 추정하는 모델들이 기존 방법들의 성능을 넘어서면서 관련된 연구가 활발히 진행되고 있다. 또한 Attention Model 과 같이 특정 특징 맵의 채널 혹은 공간을 강조하여 전체적인 네트워크의 성능을 개선하는 연구가 소개되었다. 본 논문에서는 깊이 정보 추정을 위해 사용되는 특징 맵을 강조하기 위해서 Attention Model 을 추가한 AutoEncoder 기반의 깊이 추정 네트워크를 제안하고 적용 부분에 따른 네트워크의 깊이 정보 추정 성능을 평가 및 분석한다.
재생골재 콘크리트의 현장적용을 위한 실험적 연구 - 전기충격식으로 수중파쇄된 재생골재를 중심으로 -
박희곤,정근호,임남기,이영도,정상진,정재영,Park, Hee-Gon,Jung, Keun-Ho,Lim, Nam-Ki,Lee, Young-Do,Jung, Sang-Jin,Jung, Jae-Young 한국건축시공학회 2003 한국건축시공학회지 Vol.3 No.1
The production accounts of domestic by-product is increased after 1990's. It is worried about the life reduction of dump land, as dump land's capacity have reached to limitation and the amount of construction industrial wastes is going higher. Recently, recycling aggregates could be gained from the reconstruction works using recycle process, and the study research of recycle concretes developed concrete application methods. It could put some outcome of studies to practical use for concrete products. The methods of crushing waste concrete are going diverse. In this study. the fundamental experiments and recycling application is investigated and analyzed with use of recycling aggregate which made of mechanical crush and underwater electrical impact crush, and the difference between underwater electrical impact crush, mechanical crush and natural aggregates is studied.