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Mesoscale modelling of selective laser melting: Thermal fluid dynamics and microstructural evolution

Abstract:
In this paper, an integrated computational materials science approach for selective laser melting (SLM) at the mesoscale is presented. A particle dropping model was developed to simulate the representative powder-bed particle distribution of a measured titanium alloy powder. Thermal fluid flow and resulting microstructural evolution of a set of laser scanned single tracks with different powder layer thicknesses and scanning speeds during SLM were also studied using both computational and experimental approaches. The simulated powder particle distribution was found to be consistent with experimental measurement. The thermal fluid flow model predicts that single laser scanned tracks become increasingly irregular-shaped with increased powder layer thickness and increased laser scanning speed. These findings were reinforced by scanning electron microscopy analysis. The more dispersed dissipation of the localised heat for thicker powder layers is understood to cause increased melting and evaporation. This can lead to increased Marangoni force and recoil pressure which in turn destabilises the melt flow. The use of an argon atmosphere speeds up the solidification process when compared with air but does not affect the morphology of single tracks significantly. The predicted microstructure was consistent with the electron backscattered diffraction data. The microstructure-based modelling methodology considering the representative powder size distribution provides a good predictive capability for the laser-powder interaction behaviour, surface structure and porosity development.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.commatsci.2016.10.011

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Materials
Department:
Unknown
Role:
Author
ORCID:
0000-0003-2141-5865


Publisher:
Elsevier
Journal:
Computational Materials Science More from this journal
Volume:
126
Pages:
479-490
Publication date:
2016-10-27
Acceptance date:
2016-10-13
DOI:
EISSN:
1879-0801
ISSN:
0927-0256


Keywords:
Pubs id:
pubs:863795
UUID:
uuid:9edbe7ab-a235-4a9d-a1cd-73f02439577d
Local pid:
pubs:863795
Source identifiers:
863795
Deposit date:
2018-11-18

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