| About this Abstract |
| Meeting |
MS&T21: Materials Science & Technology
|
| Symposium
|
Advances in Ferrous Metallurgy
|
| Presentation Title |
Evaluation of Different Austenitization Sub-Models for 22MnB5 Steel Using Bayesian Model Selection Technique |
| Author(s) |
Boxuan Zhao, Constantin Chiriac, Kyle Daun |
| On-Site Speaker (Planned) |
Boxuan Zhao |
| Abstract Scope |
Ultra-high strength steel (UHSS) alloys such as aluminized 22MnB5 are used to produce automotive parts through hot stamping. A thermal-metallurgical model that predicts the blank heating profile and the austenitization progress inside a roller hearth furnace is needed to improve process efficiency and ensure complete austenitization before forming. This paper evaluates two competing austenitization kinetics models: the Johnson-Mehl-Avrami-Kohnogorov (JMAK) model, and internal state variable (ISV) model as candidate metallurgical sub-models, using dilatometry data and temperature profiles from roller hearth furnace trials. Experimental data is used to calibrate the models. Models are assessed using Bayesian model selection technique, which quantify the trade-off between accuracy and complexity. |