A 3D simulation of grain structure evolution during powder bed fusion additive manufacturing and subsequent laser rescanning process

Laser rescanning is often used as a post-process treatment during Laser Powder Bed Fusion (LPBF) processes to improve product quality. Taking AlSi10Mg material as a case, this study presents a 3D mesoscopic Cellular Automaton (CA) model coupled with Finite Element Analysis (FEA) to simulate grain structure evolution during the Laser Powder Bed Fusion process and its subsequent laser rescanning treatments incorporating non-equilibrium effects under rapid solidification conditions. A key focus of our investigation centers on exploring the potential origins of grain refinement during the laser rescanning process, and the subsequent impact on the resultant grain structure. Our model introduces two key innovations: (i) a diffusion-based grain growth function that tracks composition redistribution during solidification, enhancing the accuracy of grain structure prediction, and (ii) a novel fusion boundary nucleation model that accounts for local composition variations, providing deeper insights into grain refinement mechanisms. By incorporating epitaxial growth, bulk nucleation and fusion boundary nucleation models, we have observed a mixed grain structure in the melt pool, mirroring experimental findings in other studies, delineated into three zones: fine grains at the melt pool boundary (Zone I), long columnar grains (Zone II), and fine equiaxed grains (Zone III). Two factors contributing to grain refinement in our model are presented: (i) Columnar to equiaxed transition (CET) and elevated cooling rate within the rescan melt pool; (ii) Extending volume of fine grains near the rescan melt pool boundary due to fusion boundary nucleation. As a result, laser rescanning treatments, notably, yielded a refined grain structure with approximately 20% reduction in grain dimensions and a pronounced texture under current process parameters. The implications of these findings hold potential for optimized Laser Powder Bed Fusion processes and grain refinement control in future applications. • Development of a 3D CA model with FEA integration for LPBF simulation and rescanning. • Simulation of microstructure evolution and composition redistribution. • Incorporation of bulk, fusion boundary nucleation, and epitaxial growth for accuracy. • Investigation of laser rescanning effects on LPBF grain structure and refinement. • Quantitative grain refinement analysis using Principal Component Analysis.

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Publication Details

Journal
Journal of Materials Processing Technology
Published
2024-09-20
DOI
https://doi.org/10.1016/j.jmatprotec.2024.118603
Citations
9
Primary Topic
Additive Manufacturing Materials and Processes
Type
article
Field-Weighted Citation Impact
1.91

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article

A 3D simulation of grain structure evolution during powder bed fusion additive manufacturing and subsequent laser rescanning process

Kai Kang, Andre Bernard Phillion, Lang Yuan
9 citations
Journal of Materials Processing Technology
Additive Manufacturing Materials and Processes
1.91
article

A 3D simulation of grain structure evolution during powder bed fusion additive manufacturing and subsequent laser rescanning process

Kai Kang, Andre Bernard Phillion, Lang Yuan
article en
9 citations

Abstract

Laser rescanning is often used as a post-process treatment during Laser Powder Bed Fusion (LPBF) processes to improve product quality. Taking AlSi10Mg material as a case, this study presents a 3D mesoscopic Cellular Automaton (CA) model coupled with Finite Element Analysis (FEA) to simulate grain structure evolution during the Laser Powder Bed Fusion process and its subsequent laser rescanning treatments incorporating non-equilibrium effects under rapid solidification conditions. A key focus of our investigation centers on exploring the potential origins of grain refinement during the laser rescanning process, and the subsequent impact on the resultant grain structure. Our model introduces two key innovations: (i) a diffusion-based grain growth function that tracks composition redistribution during solidification, enhancing the accuracy of grain structure prediction, and (ii) a novel fusion boundary nucleation model that accounts for local composition variations, providing deeper insights into grain refinement mechanisms. By incorporating epitaxial growth, bulk nucleation and fusion boundary nucleation models, we have observed a mixed grain structure in the melt pool, mirroring experimental findings in other studies, delineated into three zones: fine grains at the melt pool boundary (Zone I), long columnar grains (Zone II), and fine equiaxed grains (Zone III). Two factors contributing to grain refinement in our model are presented: (i) Columnar to equiaxed transition (CET) and elevated cooling rate within the rescan melt pool; (ii) Extending volume of fine grains near the rescan melt pool boundary due to fusion boundary nucleation. As a result, laser rescanning treatments, notably, yielded a refined grain structure with approximately 20% reduction in grain dimensions and a pronounced texture under current process parameters. The implications of these findings hold potential for optimized Laser Powder Bed Fusion processes and grain refinement control in future applications. • Development of a 3D CA model with FEA integration for LPBF simulation and rescanning. • Simulation of microstructure evolution and composition redistribution. • Incorporation of bulk, fusion boundary nucleation, and epitaxial growth for accuracy. • Investigation of laser rescanning effects on LPBF grain structure and refinement. • Quantitative grain refinement analysis using Principal Component Analysis.

Journal of Materials Processing TechnologyVol. 333
University of South Carolina (US), McMaster University (CA)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 15%
Additive Manufacturing Materials and Processes
1.91
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