|About this Abstract
||2018 TMS Annual Meeting & Exhibition
||Advanced High-strength Steels
||A Computational Approach to Designing Martensitic Microstructures in Carbon Steels
||Shengyen Li, Steven P Mates, Mark R Stoudt, Carelyn E Campbell
|On-Site Speaker (Planned)
High strength steels often employ martensitic transformations to enhance strength and toughness properties. A long time goal has been to tailor the composition and processing of a steel to control the volume fraction and morphology of the martensite formed for specific applications. A materials design infrastructure that integrates phase-based, mechanistic, and machine learning models with experimental data has been developed using python-based functions. This materials design toolkit (MDT) has been implemented to provide the insights into high speed machining applications where the workpiece experiences rapid heating and intense plastic deformation, which produces meta-stable microstructures and unique mechanical behavior. Specifically MDT framework is used to combine dilatometry, and high-strain rate Kolsky bar compression test data with existing models to predict the austenite stability, martensitic transformation and stress-strain curve. An example relating the predicted phase transformations and mechanical properties to experimental observations in rapidly heated, quenched and deformed 1045 steel is presented.
||Planned: Supplemental Proceedings volume