Investigation of thermal behavior and fluid dynamics within molten pool during quasi-continuous-wave laser directed energy deposition

Abstract

The quasi-continuous-wave laser directed energy deposition (QCW-DED), a form of directed energy deposition (DED), has garnered growing interest in recent years due to its ability to reduce thermal deformation and improve the performance of manufactured components. However, the interaction between the quasi-continuous-wave (QCW) laser and the molten pool surface, and its subsequent effects on the dynamics and morphology of the molten pool, is still not clear. In this work, a coupled ray-tracing computational fluid dynamics (CFD) model, which integrates a laser-powder interaction model and material deposition model, is developed to study the multi-physics coupling characteristics in QCW-DED process. The incident angle between the laser rays and molten pool surface was quantified and the corresponding laser absorptivity was analyzed. After accounting for the influence of laser-surface interaction, the heat transfer and fluid dynamics within the molten pool were subsequently investigated. Several dimensionless numbers, including the Fourier number (Fo), Peclet number (Pe), Marangoni number (Ma), and Grashof number (Gr), were employed to elucidate the physical mechanisms underlying the evolution of the molten pool. The results show that the heat transfer within the molten pool is controlled alternately by thermal convection and thermal conduction during the QCW-DED process. Furthermore, the Marangoni effect and buoyancy effect are weaker in the QCW-DED process compared to the continuous-wave laser directed energy deposition (CW-DED) process. However, the molten pool has a stronger heat dissipation capability in the QCW-DED process. Finally, the calculated molten pool geometry shows good agreement with the experimental results with the relative error less than 14.5%. This work provides a deeper insight into laser-surface interaction and the dynamics behavior within the molten pool during the QCW-DED process. The developed model can also serve as a fundamental tool for understanding the forming mechanism, predicting the deposition quality and optimizing the process of QCW-DED.