Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Seifallah Fetni"'
Autor:
Seifallah Fetni, Tommaso Maurizi Enrici, Tobia Niccolini, Hoang Son Tran, Olivier Dedry, Laurent Duchêne, Anne Mertens, Anne Marie Habraken
Publikováno v:
Materials & Design, Vol 204, Iss , Pp 109661- (2021)
This work focuses on the thermal modeling of the Directed Energy Deposition of a composite coating (316L stainless steel reinforced by Tungsten carbides) on a 316L substrate. The developed finite element model predicts the thermal history and the mel
Externí odkaz:
https://doaj.org/article/8de56f18fb7d456eb30917a50c91f7e6
Autor:
Thinh Quy Duc Pham, Truong Vinh Hoang, Xuan Van Tran, Seifallah Fetni, Laurent Duchêne, Hoang Son Tran, Anne M. Habraken
Publikováno v:
Key Engineering Materials. 926:323-330
This study quantifies the effects of uncertainty raised from process parameters, material properties, and boundary conditions in the directed energy deposition (DED) process of M4 High-Speed Steel using deep learning (DL)-based probabilistic approach
Autor:
Thinh Quy Duc Pham, Truong Vinh Hoang, Xuan Van Tran, Quoc Tuan Pham, Seifallah Fetni, Laurent Duchêne, Hoang Son Tran, Anne-Marie Habraken
Publikováno v:
Journal of Intelligent Manufacturing. 34:1701-1719
Autor:
Tobia Niccolini, Tommaso Maurizi Enrici, Ruben Antonio Tomé Jardin, Anne Habraken, Olivier Dedry, Laurent Duchene, Anne Mertens, Seifallah Fetni, Son Hoang Tran
Publikováno v:
Procedia Manufacturing. 50:86-92
In this work, a 2D-thermal model of laser cladding (also called Directed Energy Deposition) of composite coating (316L stainless steel reinforced by hard WC carbide particles) was developed. The temperature field and its time evolution were computed
Autor:
Seifallah Fetni, Thinh Quy Duc Pham, Truong Vinh Hoang, Hoang Son Tran, Laurent Duchêne, Xuan-Van Tran, Anne Marie Habraken
Publikováno v:
Computational Materials Science. 216:111820
Publikováno v:
Engineering Failure Analysis. 97:43-52
Microstructural changes in the T91 steel (also known as the modified 9Cr 1Mo steel), largely used in thermal and nuclear power plants as well as petrochemical factories, have been studied, after isothermal ageing (at 550 °C) in laboratory, for diffe
Publikováno v:
Probabilistic Engineering Mechanics. 69:103297
Autor:
Laurent Duchene, Van Xuan Tran, Seifallah Fetni, Quy Duc Thinh Pham, Anne Habraken, Hoang Son Tran
Publikováno v:
ESAFORM 2021.
In the last decade, machine learning is increasingly attracting researchers in several scientific areas and, in particular, in the additive manufacturing field. Meanwhile, this technique remains as a black box technique for many researchers. Indeed,
Autor:
Than Phuc Huynh, Anne Habraken, Truong-Vinh Hoang, Hoang Son Tran, Laurent Duchene, Van Xuan Tran, Quy Duc Thinh Pham, Quoc Tuan Pham, Seifallah Fetni
Publikováno v:
ESAFORM 2021.
In this study, a data-driven deep learning model for fast and accurate prediction of temperature evolution and melting pool size of metallic additive manufacturing processes are developed. The study focuses on bulk experiments of the M4 high-speed st
Publikováno v:
International Journal of Engineering Research and.