Modeling of solidification microstructure evolution in laser powder bed fusion fabricated 316L stainless steel using combined computational fluid dynamics and cellular automata

Abstract This work presents a novel modeling framework combining computational fluid dynamics (CFD) and cellular automata (CA), to predict the solidification microstructure evolution of laser powder bed fusion (PBF) fabricated 316 L stainless steel. A CA model is developed which is based on the modified decentered square method to improve computational efficiency. Using this framework, the fluid dynamics of the melt pool flow in the laser melting process is found to be mainly driven by the competing Marangoni force and the recoil pressure on the liquid metal surface. Evaporation occurs at the front end of the laser spot. The initial high temperature occurs in the center of the laser spot. However, due to Marangoni force, which drives high-temperature liquid flowing to low-temperature region, the highest temperature region shifts to the front side of the laser spot where evaporation occurs. Additionally, the recoil pressure pushes the liquid metal downward to form a depression zone. The simulated melt pool depths are compared well with the experimental data. Additionally, the simulated solidification microstructure using the CA model is in a good agreement with the experimental observation. The simulations show that higher scan speeds result in smaller melt pool depth, and lack-of-fusion pores can be formed. Higher laser scan speed also leads to finer grain size, larger laser-grain angle, and higher columnar grain contents, which are consistent with experimental observations. This model can be potentially used as a tool to optimize the metal powder bed fusion process, through generating desired microstructure and resultant material properties.