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<p>Laser heating during additive manufacturing (AM) induces extreme and transient thermal conditions which critically influence the microstructure evolution and part integrity. However, accurately resolving these conditions with sufficient spatiotemporal accuracy remains a central challenge. We demonstrate a unique approach that couples high-speed infrared imaging, during laser melting of MAR-M247, with a transient three-dimensional (3D) multiphysics simulation to reconstruct the dynamic sub-surface temperature distribution of the melt pool. This integrated framework enables the estimation of experimentally-validated, 3D solidification conditions—including solidification velocities and cooling rates—at the solid-liquid interface while also significantly lowering computational cost. By quantifying solidification conditions, we predict variations in microstructure size and orientation driven by laser processing parameters. We validate the predictions with ex situ scanning electron microscopy and electron backscatter diffraction maps. Our findings substantiate that an integrated experimental-computational approach is crucial to enable in situ prediction and optimization of microstructures in a commercial laser melting process.</p>

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Coupled infrared imaging and multiphysics modeling reconstruct three-dimensional solidification dynamics during metal laser melting

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月23日

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  • Vijay Kumar,
  • Kaitlyn M. Mullin,
  • Hyunggon Park,
  • Matthew Gerigk,
  • Andrew Bresk,
  • Tresa M. Pollock,
  • Yangying Zhu

摘要

Laser heating during additive manufacturing (AM) induces extreme and transient thermal conditions which critically influence the microstructure evolution and part integrity. However, accurately resolving these conditions with sufficient spatiotemporal accuracy remains a central challenge. We demonstrate a unique approach that couples high-speed infrared imaging, during laser melting of MAR-M247, with a transient three-dimensional (3D) multiphysics simulation to reconstruct the dynamic sub-surface temperature distribution of the melt pool. This integrated framework enables the estimation of experimentally-validated, 3D solidification conditions—including solidification velocities and cooling rates—at the solid-liquid interface while also significantly lowering computational cost. By quantifying solidification conditions, we predict variations in microstructure size and orientation driven by laser processing parameters. We validate the predictions with ex situ scanning electron microscopy and electron backscatter diffraction maps. Our findings substantiate that an integrated experimental-computational approach is crucial to enable in situ prediction and optimization of microstructures in a commercial laser melting process.