Zobrazeno 1 - 10
of 309
pro vyhledávání: '"Hahn Choo"'
Autor:
Rongxuan Wang, David Garcia, Rakesh R. Kamath, Chaoran Dou, Xiaohan Ma, Bo Shen, Hahn Choo, Kamel Fezzaa, Hang Z. Yu, Zhenyu (James) Kong
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-17 (2022)
Abstract Laser powder bed fusion is a promising technology for local deposition and microstructure control, but it suffers from defects such as delamination and porosity due to the lack of understanding of melt pool dynamics. To study the fundamental
Externí odkaz:
https://doaj.org/article/d8c99b6be4d84748b99f9a3b5e969a02
Publikováno v:
Materials & Design, Vol 202, Iss , Pp 109562- (2021)
Effect of dynamic recrystallization (DRX) on the grain refinement and texture modification was studied by conducting a series of hot compression on AZ31B Mg alloy. Processing-grain size-texture maps were established as a function of temperature, stra
Externí odkaz:
https://doaj.org/article/eed808b2a9d441a48951f74bb321e6dc
Autor:
Hahn Choo, Kin-Ling Sham, John Bohling, Austin Ngo, Xianghui Xiao, Yang Ren, Philip J. Depond, Manyalibo J. Matthews, Elena Garlea
Publikováno v:
Materials & Design, Vol 164, Iss , Pp - (2019)
The effect of laser power on defect characteristics, microstructure development, constituent phases, and crystallographic texture was studied on a laser powder bed fusion (L-PBF) processed 316L stainless steel. A series of specimens was additively ma
Externí odkaz:
https://doaj.org/article/d3a75ea7e6df420bb8609a4606ff8ee5
Publikováno v:
Crystals, Vol 10, Iss 2, p 101 (2020)
In situ neutron diffraction was employed to examine the phase transformation behavior of high-Mn steels with different carbon contents (0.1, 0.3, and 0.5 wt.%C). With increasing carbon contents from 0.1 C to 0.5 C, the austenite phase fraction among
Externí odkaz:
https://doaj.org/article/4ad946bd8d334ea0939d86160f40c103
Publikováno v:
Technometrics. 64:2-17
Recent developments of advanced imaging systems spur their applications in many areas, ranging from satellite remote sensing for geographic information to thermal imaging analysis for manufacturing...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7379a74ebb5183146d7b69d345d3cda9
https://doi.org/10.1080/00401706.2021.1905074
https://doi.org/10.1080/00401706.2021.1905074
Autor:
Rongxuan Wang, David Garcia, Rakesh Kamath, Chaoran Dou, Xiaohan Ma, Bo Shen, Hahn Choo, Kamel Fezzaa, Zhenyu Kong, Hang Yu
Laser powder bed fusion still suffers from defects such as delamination and porosities due to the lack of understanding of melt pool dynamics. To study the fundamental of the melt pool behavior, both geometrical and thermal sensing with high spatial
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a867c802461fc79dcc947b00b6803c6b
https://doi.org/10.21203/rs.3.rs-1581310/v1
https://doi.org/10.21203/rs.3.rs-1581310/v1
Autor:
Robert Maaß, Gongyao Wang, Liang Jiang, Soo Yeol Lee, Yanfei Gao, E. Wen Huang, Michael C. Gao, Xie Xie, Yunfeng Shi, Hahn Choo
Publikováno v:
Metallurgical and Materials Transactions A. 52:3671-3673
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d41f788ba8f54ad4a4c42e9188897fb4
https://doi.org/10.1007/s11661-021-06369-4
https://doi.org/10.1007/s11661-021-06369-4
Publikováno v:
International Materials Reviews. 66:394-425
This review examines the development and current state of Cu-rich Cu–Cr–Nb alloys commonly referred to as GRCop or Glenn Research copper alloys with emphasis on Cu–8Cr–4Nb (at%), or GRCop-84, and C...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::25b5de6c3e5bc96c9d716e1467f41214
https://doi.org/10.1080/09506608.2020.1821485
https://doi.org/10.1080/09506608.2020.1821485
Background/foreground separation is one of the most fundamental tasks in computer vision, especially for video data. Robust PCA (RPCA) and its tensor extension, namely, Robust Tensor PCA (RTPCA), provide an effective framework for background/foregrou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d94ec2ce8cd502c03268260d6b759e1b
https://doi.org/10.36227/techrxiv.14561775.v2
https://doi.org/10.36227/techrxiv.14561775.v2
Background/foreground separation is one of the most fundamental tasks in computer vision, especially for video data. Robust PCA (RPCA) and its tensor extension, namely, Robust Tensor PCA (RTPCA), provide an effective framework for background/foregrou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::961ad716c5fbd90ce99148b1a39f97af
https://doi.org/10.36227/techrxiv.14561775.v1
https://doi.org/10.36227/techrxiv.14561775.v1