An efficient local moving thermal-fluid framework for accelerating heat and mass transfer simulation during welding and additive manufacturing processes

Abstract

Numerical prediction of melt pool morphology and temperature distribution of thermomechanical processes (welding, additive manufacturing) plays an important role in understanding the relationships between process parameters and the quality of manufactured parts. The heat conduction models are limited in their predictability because the transport phenomena relevant to the melt pool dynamic are ignored. In contrast, the multiphysics model allows consideration of the heat transfer, free surface evolution, and transport phenomena in the melt pool, leading to more accurate predictions. However, the computational cost of multiphysics models makes them impractical for part-scale simulations. In this paper, a local moving thermal-fluid framework based on the finite element method is presented, which allows solving the thermal-fluid problem only in the small moving zone containing the melt pool and the heat transfer problem in the rest part. Therefore, this new proposed moving thermal-fluid (MTF) framework is predictive as well as the full thermal-fluid model, while it is much more efficient than a full thermal-fluid model since there are much fewer degrees of freedom (DOF) to solve. Finally, numerical validation tests in welding and additive manufacturing simulations highlight its computational efficiency and high-fidelity, and a relative error of less than 2.6% was observed in predicting melting pool dimensions compared to full thermal-fluid model. In the part-scale simulation of laser welding benchmark, the MTF model takes only 62 h in place of about three weeks required by a full thermal-fluid model.