Macro-mesoscale microstructural evolution modeling under hot forging of a Ti-17 alloy with a lamellar (α+β) starting microstructure

• Published in: MATEC web of conferences 2020, Vol.321, p.13005
• Main Authors: Matsumoto, Hiroaki, Yamanaka, Kenta, Chiba, Akihiko, Yamabe-Mitarai, Yoko, Itsumi, Yoshio
• Format: Article
• Language: English
• Subjects: Artificial neural networks; Beta phase; Computer simulation; Constitutive equations; Constitutive models; Constitutive relationships; Dynamic recrystallization; Evolution; Finite element method; Heat treating; Hot forging; Kinking; Mathematical models; Microstructure; Modelling; Strain rate; Titanium base alloys; Transition temperature
• ISSN: 2261-236X; 2274-7214; 2261-236X
• DOI: 10.1051/matecconf/202032113005

Microstructural conversion mechanisms under hot forging process (at temperatures ranging from 750 °C to 1050 °C and strain rates ranging from 10 –3 s –1 to 1 s –1 ) of a Ti-5Al-2Sn-2Zr-4Mo-4Cr (Ti-17) alloy with a lamellar starting microstructure were experimentally identified in this work. After that, constitutive formulae for predicting the microstructural evolution were established followed by calculation using finite-element (FEM) analysis. In the α phase, a lamellae kinking is the dominant mode in the higher strain rate region and dynamic globularization frequently occurs at higher temperatures. On the other hand, continuous dynamic recrystallization is the dominant mode below the transition temperature, Tβ (880~890 °C) in the β phase. And, at conditions of lower strain rates and higher temperatures, dynamic recovery tends to be more active. For microstructural prediction, a set of constitutive equations modeling the microstructural evolution and forging properties are established by optimizing the experimental data followed by implementation in the DEFORM-3D software package. Herein, microstructural evolution on dynamic globularization process, dynamic recrystallization behavior are predicted according to both approaches of physical model and artificial neural network model followed by FEM simulation. In these calculated results, there is a satisfactory agreement between the experimental and simulated results, indicating that the established series of constitutive models can be used to reliably predict the properties of a Ti-17 alloy after forging.