Computational Materials Science2022,Vol.20913.DOI:10.1016/j.commatsci.2022.111383

Multiscale simulation of powder-bed fusion processing of metallic alloys

Elahi, S. M. Tavakoli, R. Boukellal, A. K. Isensee, T. Romero, I Tourret, D.
Computational Materials Science2022,Vol.20913.DOI:10.1016/j.commatsci.2022.111383

Multiscale simulation of powder-bed fusion processing of metallic alloys

Elahi, S. M. 1Tavakoli, R. 1Boukellal, A. K. 1Isensee, T. 1Romero, I 1Tourret, D.1
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作者信息

  • 1. IMDEA Mat
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Abstract

We present a computational framework for the simulations of powder-bed fusion of metallic alloys, which combines: (1) CalPhaD calculations of temperature-dependent alloy properties and phase diagrams, (2) macroscale finite element (FE) thermal simulations of the material addition and fusion, and (3) microscopic phase-field (PF) simulations of solidification in the melt pool. The methodology is applied to simulate the selective laser melting (SLM) of an Inconel 718 alloy using realistic processing parameters. We discuss the effect of temperature-dependent properties and the importance of accounting for different properties between the powder bed and the dense material in the macroscale thermal simulations. Using a two-dimensional longitudinal slice of the thermal field calculated via FE simulations, we perform an appropriately-converged PF solidification simulation at the scale of the entire melt pool, resulting in a calculation with over one billion grid points, yet performed on a single cluster node with eight graphics processing units (GPUs). These microscale simulations provide new insight into the grain texture selection via polycrystalline growth competition under realistic SLM conditions, with a level of detail down to individual dendrites.

Key words

Computational modeling/Powder-bed fusion/Finite elements/Phase-field/CalPhaD/PHASE-FIELD MODEL/SAMPLE DIRECTIONAL SOLIDIFICATION/COMPUTATIONAL MATERIALS DESIGN/COLUMNAR DENDRITIC GRAINS/CELLULAR-AUTOMATON MODEL/FINITE-ELEMENT/GROWTH COMPETITION/MICROSTRUCTURE EVOLUTION/THERMAL-CONDUCTIVITY/RAPID SOLIDIFICATION

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出版年

2022
Computational Materials Science

Computational Materials Science

EISCI
ISSN:0927-0256
被引量14
参考文献量95
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