Choosing an optimal austenitization submodel using Bayesian model selection

Autor: Boxuan Zhao, Timothy A. Sipkens, Kyle J. Daun
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Popis: Ultra-high strength steel (UHSS) alloys such as aluminized 22MnB5 are used to produce automotive parts through hot stamping. A thermometallurgical model that predicts the blank-heating profile and austenitization inside a roller hearth furnace is needed to maximize process efficiency while ensuring that the blanks are completely austenitized. Three competing austenitization kinetics models: a Johnson–Mehl–Avrami–Kohnogorov (JMAK) type model, an internal state variable (ISV) model, and a phenomenological model, are evaluated as candidate metallurgical submodels, using dilatometry data and Bayesian model selection. This technique has the capability of quantitatively assessing the trade-off between accuracy and complexity. The ISV model is recommended by the Bayesian model selection technique.
Databáze: OpenAIRE