Optimizing process parameters for hot forging of Ti-6242 alloy: A machine learning and FEM simulation approach

Optimizing process parameters for hot forging of Ti-6242 alloy: A machine learning and FEM simulation approach

In this study, we investigated the hot deformation behavior of Ti–6Al–2Sn–4Zr–2Mo (Ti-6242) alloy and propose a method to derive optimal hot process parameters for grain refinement and avoidance of flow instability. Microstructural Risk Index (MRI) was introduced as a microstructural evaluation inde...

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Bibliographic Details
Main Authors: Yosep Kim, Ho Young Jeong, Joonhee Park, Kyungmin Kim, Hyukjoon Kwon, Gyeongjun Ju, Naksoo Kim
Format: Article
Language:English
Published: Elsevier 2023-11-01
Series:Journal of Materials Research and Technology
Subjects:
As-forged Ti-6242 alloy
Hot deformation behavior
Dynamic recrystallization
Flow instability
FEM numerical simulation
Online Access:http://www.sciencedirect.com/science/article/pii/S2238785423029666

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http://www.sciencedirect.com/science/article/pii/S2238785423029666

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