Efficient thermal finite element modeling of selective laser melting of Inconel 718

In the powder bed fusion process, an accurate prediction of the transient temperature field of a part is essential to calculate the subsequent thermal stress evolution and microstructure propagation in that part. The experimental method is time-consuming and expensive since the temperature field is controlled by many process parameters. Numerical heat transfer models can be used to estimate the temperature field at any time point. However, traditional numerical simulation schemes are not suitable for the layer-wised fabrication process due to the extremely high computational cost. The computational cost mainly relies on the element number and time step size. This research provides a new efficient and part-level simulation scheme based on an open-source finite element library, which is able to adaptively refine and coarsen the mesh and solve finite element equations with multiple processors in a parallel way. Here, a new mesh strategy that aims to reduce the element number while keeping the solution accuracy is developed. The simulation speed is 12x to 18x faster compared with the traditional simulation scheme depending on the scale of the simulated domain and number of processors. Simulation results have been compared with the experimental results of an Inconel 718 component. It is shown that the testing point in the simulation experiences the same thermal cycles of the same point in the experiment. This simulation scheme can also be used to optimize the process parameters such as scanning pattern, scan velocity, and layer thickness and can be easily extended to other additive manufacturing processes.