| publication name | Modelling of the Superplastic Deformation of the Near-α Titanium Alloy (Ti-2.5 Al-1.8 Mn) Using Arrhenius-Type Constitutive Model and Artificial Neural Network |
|---|---|
| Authors | Ahmed Mosleh, Anastasia Mikhaylovskaya, Anton Kotov, Theo Pourcelot, Sergey Aksenov, James Kwame, Vladimir Portnoy |
| year | 2017 |
| keywords | superplasticity; titanium alloys; constitutive modelling; arrhenius-type constitutive equation; artificial neural network; activation energy |
| journal | Metals |
| volume | 7 |
| issue | 12 |
| pages | 568 |
| publisher | Multidisciplinary Digital Publishing Institute |
| Local/International | International |
| Paper Link | http://www.mdpi.com/2075-4701/7/12/568 |
| Full paper | download |
| Supplementary materials | Not Available |
Abstract
The paper focuses on developing constitutive models for superplastic deformation behaviour of near-α titanium alloy (Ti-2.5 Al-1.8 Mn) at elevated temperatures in a range from 840 to 890 C and in a strain rate range from 2× 10− 4 to 8× 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-α Titanium alloy (Ti-2.5 Al-1.8 Mn) at superplastic forming than the Arrhenius-type constitutive model. However, the tested