Influence of oxygen content on melt pool dynamics in metal additive manufacturing: High-fidelity modeling with experimental validation
Published in Acta Materialia, 2023
Abstract: In the metal additive manufacturing process, the exposure to oxygen and its incorporation into the melt pool are usually deemed unfavorable, but cannot be completely eliminated. Yet, the understanding of this inevitable process remains limited. This work aims to shed light on the effect of oxygen content on melt pool dynamics through multiphysics thermal-fluid flow simulations of the laser powder bed fusion process. Our simulations reveal that oxygen sources from the powder, base plate and oxygen absorption from the atmosphere influences the melt pool dynamics. Although changes in oxygen content barely affect melt pool dimensions, they induce huge differences in the melt pool dynamics and the corresponding material composition distribution within the melt pool. Moreover, our model further clarifies and explains observed experimental phenomena. We demonstrate that the melt pool flow characteristics are responsible for the formation of oxygen-rich streaks observed in experiments regardless of inward or outward Marangoni circulation, while previous experimental studies attributed that to the outward circulation. Additionally, we show that sulfur content minimizes the effect of oxygen on Marangoni flow in iron alloys, and thus leads to the apparent consistency of surface roughness for additively manufactured iron alloys. This work is a fundamental development towards modeling for additive manufacturing under reactive atmospheres and provides unprecedented details on the effects of oxygen on melt pool dynamics. Consequently, this work can further offer practical guidance on powder reuse and adjusting manufacturing parameters for reused powders, thereby improving the sustainability of additive manufacturing.
Recommended citation: Chia H Y, Wang L, Yan W. Influence of oxygen content on melt pool dynamics in metal additive manufacturing: High-fidelity modeling with experimental validation[J]. Acta Materialia, 2023, 249: 118824.