Multiscale simulation of powder-bed fusion processing of metallic alloys

TL;DR

This paper introduces a multiscale computational framework combining thermodynamic, macroscale thermal, and microscopic solidification simulations to better understand and predict the microstructure evolution during metallic alloy powder-bed fusion processes.

Contribution

It develops an integrated multiscale simulation approach for powder-bed fusion, incorporating realistic material properties and large-scale phase-field modeling on GPUs.

Findings

Insights into grain texture selection during solidification.

Demonstration of large-scale phase-field simulation on GPUs.

Highlighting the importance of temperature-dependent properties.

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.