Transport phenomena during direct metal deposition
By X. He, Jyoti Mazumder. 2007
176 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Computational Mechanics, Mechanical Engineering
View Paper: https://www.semanticscholar.org/paper/35e4323dc0e41e954cf2366c96c4024763405954
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Aref Yadollahi
- Zhengtao Gan
- Ehsan Toyserkani
- Mir Behrad Khamesee
- Yuze Huang
- A. Pinkerton
- Linkan Bian
- Xiuli He
In Computational Mechanics
- A. Pinkerton
- Ehsan Toyserkani
- Aref Yadollahi
- Hao Liu
- Zhengtao Gan
- Mir Behrad Khamesee
- Yuze Huang
- Linkan Bian
In Mechanical Engineering
- Nima Shamsaei
- Aref Yadollahi
- Scott M. Thompson
- Linkan Bian
- Ehsan Toyserkani
- A. Pinkerton
- Yuze Huang
- Mir Behrad Khamesee
Citations in the corpus
- An overview of Direct Laser Deposition for additive manufacturing; Part I: Transport phenomena, modeling and diagnostics (2015, methodology): “For a given laser power, metallic fluids with high surface tension sensitivity to temperature will tend to have higher peak velocities within its melt pool during DLD, with characteristic peak velocities on-theorder of 1 m/s [101,139,142].”
- Numerical simulation of thermal behavior and multicomponent mass transfer in direct laser deposition of Co-base alloy on steel (2017, methodology): “The direct metal deposition was studied by a 3D numerical model [12].”
- A comprehensive analytical model for laser powder-fed additive manufacturing (2016, methodology): “Numerical methods based on finite element methods have also proved popular and can accurately simulate the powder flux distribution [3], laser particle interaction process [4], melt pool formation [5], clad layer geometry [6,7], temperature, velocity and thermal stress fields distribution over the p”
- Modeling of thermal behavior and mass transport in multi-layer laser additive manufacturing of Ni-based alloy on cast iron (2017, methodology): “In order to describe the dynamic surface of molten pool, surface tracking [18] or surface capturing methods [3,9] are highly computationally intensive.”