|About this Abstract
||7th World Congress on Integrated Computational Materials Engineering (ICME 2023)
||Simulation of Dynamic Recrystallization in a 316L Stainless Steel Friction Stir Weld with Kinetic Monte Carlo Modeling
||William E. Frazier, Lei Li, Ayoub Soulami, Matthew Olszta, Donald Todd, Keerti S Kappagantula, Neil Henson, Erin Barker, Eric Smith
|On-Site Speaker (Planned)
||William E. Frazier
In order to improve upon existing predictive capabilities for the evolution of alloy microstructures subjected to friction stir processing (FSP), an approach was developed integrating a Kinetic Monte Carlo (KMC) Potts Model of recrystallization and grain growth with macroscale Smoothed Particle Hydrodynamics (SPH) simulations of a 316L stainless steel plate. To this end, the KMC Potts Model used the thermomechanical data provided by SPH calculations of the FSP process in order to predict the recrystallization behavior, final grain size, and grain size distribution within the processed region as a function of position. Potts Model simulations were thus able to predict microstructure as a function of 316L stainless steel thermomechanical history and FSP process parameters. Simulation results were validated through experimental comparison with scanning electron microscopy data obtained by 316L stainless steel samples subjected to corresponding process parameters. The fidelity of our results to these experiments are discussed.