Numerical investigation on heat transfer of melt pool and clad generation in directed energy deposition of stainless steel

Due to its prevailing advantages such as rapid production of complex metallic parts, efficient cladding and repairing the sophisticated components, the directed energy deposition (DED) process has been widely adopted in the additive manufacturing industry recently. Numerous research efforts were placed in the studies of clad formation and the influences of process parameters during the DED process. As the flow dynamics of melt pool plays a significant role in the heat transfer characteristics as well as the mass transfer mechanism, further understanding of the metallic flow evolutions of melt pool becomes practically demanded for the DED process. Therefore, the abilities to model the complex process of heat transfer and accurately predict the mass addition during the DED process are highly desirable. A computational fluid dynamics model is proposed to simulate the melt pool generation and clad formation in this study. The volume of fluid (VOF) method is incorporated to distinguish the interface between the gaseous and metallic cells. Effect of surface active element-sulfur content on melt pool dynamics is evaluated. Investigations of thermal evolutions of melt pool and solidification of the clad are systematically performed. Moreover, accuracy and reliability of the proposed model are implemented through comparisons between simulation results and their corresponding experimental measurements.

Automated summary

The directed energy deposition (DED) process is widely used in the additive manufacturing industry due to its advantages in rapid production of complex metallic parts and efficient cladding. A computational fluid dynamics model is proposed in this study to simulate melt pool generation and clad formation, evaluating the effect of surface active element-sulfur content on melt pool dynamics. Investigations on thermal evolutions of melt pool and solidification of the clad are systematically conducted to ensure accuracy and reliability of the proposed model.