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Lu, Y.,Kim, H.C.,Lee, Je Hyun,Oh, Myung Hoon,Wee, Dang Moon,Hirano, Toshiyuki Trans Tech Publications, Ltd. 2006 Materials science forum Vol.510 No.-
<P>Directional or single crystal technique was applied to enhance the ductility, and two phases of γ (Ni) phase or β (NiAl) phase in γ‘(Ni3Al) matrix were also considered to increase the strength and ductility. In this study, directionally solidified rods were prepared at the solidification rate of 50µm/s in 23-27 at.% Al-Ni alloys, and tensile strengths of these rods were analyzed at room temperature. Directionally solidified samples showed the γ dendrite fibers formed in the Ni3Al matrix in the hypo eutectic composition of 23 at.% Al, the γ‘ single phase in the eutectic composition of 24.5 at. % Al, and the β dendrite fibers in the γ‘ matrix in the hyper eutectic compositions of 25, 26, 27 at.% Al. The hypoeutectic alloy including γ dendrites with γ‘ matrix exhibited a large elongation of over 70% with ductile transgranular fracture at room temperature. With increasing Al contents, the γ dendritic microstructure changed to the β dendrite in the γ‘ matrix, which resulted in decreasing the elongation by increasing the volume fraction of the brittle β dendrites in the ductile γ’ matrix.</P>
Equilibrium and Metastable Eutectics Near the Ni<sub>3</sub>Al Composition
Lu, Y.,Lee, J.S.,Lee, Je Hyun,Wee, Dang Moon,Oh, Myung Hoon Trans Tech Publications, Ltd. 2005 Materials science forum Vol.486 No.-
<P>Ni3Al has been considerable research area due to its high temperature behavior increasing strength with increasing temperature. A series of directional solidification studies showed that the eutectic occurred between g’/b and the metastable eutectic of g/b forms under slightly different conditions, however, it is not well established whether the eutectic is composed of g/g‘, g’/b, or g/b . In order to understand solidification behavior of the eutectic structure, directional solidification experiments have been carried out with solidification rate near the Ni3Al composition in this study. The effects of the solidification rate and composition on formation of the equilibrium and metastable eutectics have been discussed. The (g’+g) coupled phase was also shown to form with the eutectic at the solid/liquid interface.</P>
In-Situ Synthesis of Co<sub>p</sub>/Cu Coating by Laser Cladding
Lu, Y.,Lee, J.H.,He, Y. Zh. Trans Tech Publications, Ltd. 2007 Materials science forum Vol.544 No.-
<P>Homogeneous Cop/Cu coating alloys were fabricated by laser cladding rapid solidification technique and their microstructures were investigated, with the emphasis on the influence of processing on microstructure. The experimental results showed that a Cop/Cu composite coating can be successfully in situ synthesized when the processing conditions were controlled. The as-solidified microstructures were characterized by a homogeneous distribution of small spherical Co-rich particles dispersed in the Cu-rich matrix. The Cop/Cu coating was consisted of γ-Co, Cu-rich solution and et al. With the increasing of line energy, the spherical particles diameter in coating was increasing. The structural evolution and refining mechanism of the Cop/Cu coating were also discussed.</P>
Application of Fractal Dimension for Rubbed Surface Morphology of Hydraulic Members
M. R. LUY,S. J. JUN,Y. S. CHO,H. S. PARK 한국트라이볼로지학회 2002 한국트라이볼로지학회 학술대회 Vol.2002 No.10
The surface morphology of oil-lubricated surface for hydraulic piston motor is believed to be extremely effective in contact mechanics, adhesion, friction and wear. In order to describe morphology of various rubbed surface on driving condition, the wear test was carried out under different experimental conditions in oil-lubricated system. And fractal descriptors was applied to rubbed surface of hydraulic members with image processing system. These descriptors to analyze surface structure are fractal dimension. Surface fractal dimension can be determined by sum of intensity difference of surface pixel. Morphology of rubbed surface can be effectively obtained by fractal dimension.
XSL-FO 문서에 대한 PostScript 변환기 설계
유동석,김차종 한밭대학교 정보통신전문대학원 2004 정보통신전문대학원 논문집 Vol.2 No.1
현재의 전자문서처리 환경은 WYSiWYG방식이다. 이를 위해 문서를 논리적인 구조와 물리적인 구조로 구조화하였고 이러한 구조를 마크업언어로 표현하고 있다. 특히 인터넷상의 전자문서 작성 및 교환을 위한 마크 업언어로 XML이 발표되어 전자문서의 표현과 같은 전통적인 사용에서부터 검색을 위한 데이터베이스화에 이르기까지 전자문서의 활용 영역이 다양해지고 있다. 그러나 출력 품질 면에서 워드프로세서나 전자출판에 의한 전 자문서와 XML. 문서의 출력 품질은 매우 큰 차이가 있다. 이는 비록 XML문서가 스타일 정보를 포함하고 있긴 하지만 화면 출력과 인쇄 매체로의 출력 모두 고품질의 출력을 위한 적용이 부족했기 때문이다. 이러한 문제 해결 을 위해 W3C에서는 고품질의 XML출력 문서를 얻을 수 있도록 XSL-FO(XSL-Formatting Object)를 개발 하였다. 한편 고품질의 전자출판물을 얻기 위해 페이지 기술 언어(PDL)가 필요하고, 이의 업계표준인 PostScript가 이미 널리 사용되고 있다. 따라서 본 논문에서는 XML-FO를 Postscript에 적용함으로써 고품질의 XML 출력문서를 얻기 위한 변환기를 설계하였다. At present, the electronic document is being processed in WYSWYG mode. For this, a document is structured by the logical structure and the physical structure, and is presented by the markup language. After XML is announced, and application scope of the electronic document is extended from interchanging to searching. However, in point of output quality, a XML document image on a browser has lower quality than a general document image on desktop publishing. The reason is which output function of a browser has not capability for high quality printing. The W3C developed XSL-FO(XSL-formatting Object) for stylesheet formatting and PDL(Page Sescription Language) as like PostScript is already developed and used widely. In this paper, we designed the PostScript-Converter to get a high quality document image by converting XSL-FO into PostScript format.
3D CAD Model Classification with Deep Neural Networks
Feiwei Qin,Luye Li,Shuming Gao,Xiaoling Yang,Xiang Chen (사)한국CDE학회 2013 한국CAD/CAM학회 국제학술발표 논문집 Vol.2010 No.8
Model classification is essential to the management and reuse of 3D CAD models. Manual model classification is laborious and error prone. At the same time, the automatic classification methods are scarce due to the intrinsic complexity of 3D CAD models. In this paper, we propose an automatic 3D CAD model classification approach based on deep neural networks. According to prior knowledge of CAD domain, features are selected and extracted from 3D CAD models first, then preprocessed as high dimensional input vectors for category recognition. Furthermore, by anal ogy with the thinking process of engineers, a deep network classifier for 3D CAD models is constructed with the aid of deep learning techniques. To get an optimal solution, multiple strategies are appropriately chosen and applied in the training phase, which makes our classifier achieve better performance. We demonstrate the efficiency and effectiveness of our approach through experiments on 3D CAD model datasets.