Numerical prediction of grain structure formation during laser powder bed fusion of 316 L stainless steel

Abstract

Additive Manufacturing (AM) processes enable the reduction of manufacturing time, material waste, and allows for the creation of complex structures. However, anisotropic mechanical behaviour is frequently observed in additively manufactured parts, and it is directly linked to the component's grain structure characteristics, which itself is dependent on the process parameters. The formation of grain structure in 316 L stainless steel fusion lines is investigated in this paper, combining experimental results and numerical simulations. Experimentally, fusion lines are built on a 316 L substrate, using an instrumented LPBF process. The high-speed camera recordings combined with the characterization of the samples enables capturing of melt-pool sizes and grain characteristics. The numerical modelling is based on a three-dimensional “CAFE” model, coupling Cellular Automata and Finite Element models to predict grain formation. The thermal model is defined and calibrated using the experiments. The experimental and numerical grain characteristics are compared. Numerical results are discussed with regards to the growth models and the process parameters. The growth model defined here is compared to existing models and is well fitted to capture grain formation in single-track configurations. Finally, the average grain size and aspect ratio of the grains increase with an increase of the process' linear energy.

Keywords

• Additive manufacturing
• Laser powder bed fusion (LPBF)
• CAFE model
• 316 L stainless steel
• Grain structure prediction