| Download | - View accepted manuscript: Choosing an optimal austenitization submodel using Bayesian model selection (PDF, 759 KiB)
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| DOI | Resolve DOI: https://doi.org/10.1007/s11661-022-06722-1 |
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| Author | Search for: Zhao, Boxuan; Search for: Sipkens, Timothy A.1; Search for: Daun, Kyle J. |
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| Affiliation | - National Research Council of Canada. Metrology Research Centre
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| Format | Text, Article |
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| Abstract | 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. |
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| Publication date | 2022-05-26 |
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| Publisher | Springer Nature
The Minerals, Metals & Materials Society
ASM International 2022 |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | d484f5da-f2c7-4711-a405-0e711c883a4b |
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| Record created | 2023-06-28 |
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| Record modified | 2023-06-30 |
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