On the possibility of doing reduced order, thermo-fluid modelling of laser powder bed fusion (L-PBF) – Assessment of the importance of recoil pressure and surface tension

Meso-scale, multi-physics simulations of metal additive manufacturing (MAM) processes have so far proven their capability as a reliable tool for predicting potential defect formations. Nevertheless, there is a large number of uncertainty contributions involved with the input process parameters as well as the implemented material properties in these models. As expected, both the process-related and material-related uncertainties affect the outcome of these multi-physics simulations to a large degree. The present work is therefore intended to quantify the impacts of some of the important material/process-related uncertainties involved with meso-scale multi-physics models, on the heat transfer conditions within melt pool. In this respect, a meso-scale multi-physics model of the laser powder bed fusion process of stainless steel 316-L is developed in the commercial Finite Volume Method (FVM) based software Flow-3D and then validated against in-house experiments prior to the main investigation. In the first part of the study, the impact of recoil pressure at different laser linear energy densities (LED) and different laser beam sizes on the melt pool morphology are investigated. It is found that there is a specific threshold of LED below which the melt pool shape is not affected by the recoil pressure and the melt pool fluid dynamics is mostly governed by the Marangoni effect. This threshold increases from 80 J/mm to 280 J/mm when the beam size is increased from 20 μm to 120 μm. Moreover, a parametric study using dimensionless numbers is carried out to understand the impact of different capillary forces on the melt pool shape and size. It is observed that for inverse Bond numbers below 4.105, the depth-to-width ratio of the melt pool is above 1 where the recoil pressure dominates the melt pool dynamics and a keyhole forms. In summary, this study specifies in essence the process window over which specific physics are unimportant so that a lower-fidelity meso-scale model could replace the higher-fidelity multi-physics models.