What is it about?

The effects of laser beam shaping on melt-pool behaviour, solidified bead profile and microstructural gain morphology were studied comprehensively through high-fidelity numerical experiments for conduction-mode laser melting of stainless steel AISI 316L. Three-dimensional unsteady numerical simulations were performed to examine the effects of laser beam intensity profile, shape and inclination angle on the melt-pool behaviour. Critical physical phenomena in laser melting such as temporal and spatial variations of absorptivity, heat and fluid flow dynamics, solidification and melting, and free-surface oscillations were accounted for in the present computational model. Moreover, experiments were performed using different laser beam shapes and the validity of the present numerical predictions was demonstrated.

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Why is it important?

Laser beam shaping offers remarkable possibilities to control and optimise process stability and tailor material properties and structure in laser-based welding and additive manufacturing. However, little is known about the influence of laser beam shaping on the complex melt-pool behaviour, solidified melt-track bead profile and microstructural grain morphology in laser material processing. A simulation-based approach is utilised in the present work to study the effects of laser beam intensity profile and angle of incidence on the melt-pool behaviour in conduction-mode laser melting of stainless steel 316L plates. The present high-fidelity physics-based computational model accounts for crucial physical phenomena in laser material processing such as complex laser–matter interaction, solidification and melting, heat and fluid flow dynamics, and free-surface oscillations. Experiments were carried out using different laser beam shapes and the validity of the numerical predictions is demonstrated.

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This page is a summary of: Revealing the effects of laser beam shaping on melt pool behaviour in conduction-mode laser melting, Journal of Materials Research and Technology, November 2023, Elsevier,
DOI: 10.1016/j.jmrt.2023.11.046.
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