|About this Abstract
||2022 TMS Annual Meeting & Exhibition
||2022 Technical Division Student Poster Contest
||SPU-11: Model Based Control of Microstructure for Additive Manufacturing 316L Stainless Steel
||Matthew Michalek, Daniel Moser, Theron Rodgers
|On-Site Speaker (Planned)
Laser powder bed fusion (LPBF) process parameters directly affect microstructural properties such as grain size and eccentricity which play a significant role in local and global stress/strain behavior. A preliminary process parameter to microstructure optimization algorithm was developed based on SPPARKS kinetic Monte-Carlo (kMC) simulations to begin controlling microstructural properties of additively manufactured 316L micro-scale geometries. Sensitivity analyses performed on laser power, laser speed, laser radius, and time between hatches, show influences on microstructure consistent with experimental data. Dividing Rectangles (DiRECT) method optimization show laser power and speed alone contribute to a 25% decrease in grain size. Wait time and laser radius show contributions of a 0.1% added decrease. In the future, the process and algorithm can be used to: (i) quantify mechanical performance uncertainty due to microstructure, and (ii) design microstructures for generalized additively manufactured part geometries against a mechanical environmental response based on crystal plasticity simulations.
||Additive Manufacturing, Computational Materials Science & Engineering, Modeling and Simulation