期刊
METALS
卷 7, 期 12, 页码 -出版社
MDPI AG
DOI: 10.3390/met7120568
关键词
superplasticity; titanium alloys; constitutive modelling; arrhenius-type constitutive equation; artificial neural network; activation energy
资金
- universities Russian Federation [11.7172.2017/8.9]
- Basic Research Program at the National Research University Higher School of Economics (HSE)
- [MK-2301.2017.8]
The paper focuses on developing constitutive models for superplastic deformation behaviour of near-alpha titanium alloy (Ti-2.5Al-1.8Mn) at elevated temperatures in a range from 840 to 890 degrees C and in a strain rate range from 2 x 10(-4) to 8 x 10(-4) s(-1). Stress-strain experimental tensile tests data were used to develop the mathematical models. Both, hyperbolic sine Arrhenius-type constitutive model and artificial neural-network model were constructed. A comparative study on the competence of the developed models to predict the superplastic deformation behaviour of this alloy was made. The fitting results suggest that the artificial neural-network model has higher accuracy and is more efficient in fitting the superplastic deformation flow behaviour of near- Titanium alloy (Ti-2.5Al-1.8Mn) at superplastic forming than the Arrhenius-type constitutive model. However, the tested results revealed that the error for the artificial neural-network is higher than the case of Arrhenius-type constitutive model for predicting the unmodelled conditions.
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