|About this Abstract
||7th World Congress on Integrated Computational Materials Engineering (ICME 2023)
||Prediction of prior austenite structure as a function of processing parameters in additively processed high-strength steel
||Stephen Cluff, Clara Mock, Brandon Mcwilliams
|On-Site Speaker (Planned)
The ability to control microstructure in high-strength steel via additive manufacturing (AM) is of interest for many structural applications, providing a means to homogenize mechanical properties across varied part geometries and implement designed heterogeneities. The localized application of heat during AM, coupled with predictive modeling, enables the optimization of microstructure for steels showing sensitivity to AM parameters. One such steel is known as AF9628. This steel’s final microstructure is mediated by the prior austenite microstructure. The current work presents a model that captures the evolution of the parent austenite grain structure in AF9628 during AM processing using a Potts/Monte Carlo method implemented in the SPPARKS software. This model is used to predict austenite grain size and morphology as a function of processing and can be used as a design tool for the control of austenitic and final microstructures.
||Planned: Other (describe below)