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Naji, M. |
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Motta, Antonella |
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Mohamed, Tarek |
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Petrov, R. H. | Madrid |
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Ali, M. A. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Mikhaylovskaya, Anastasia
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article
Modelling of the superplastic deformation of the near-a titanium alloy (Ti-2.5AL-1.8MN) using arrhenius-type constitutive model and artificial neural network
Abstract
<p>The paper focuses on developing constitutive models for superplastic deformation behaviour of near-α titanium alloy (Ti-2.5Al-1.8Mn) at elevated temperatures in a range from 840 to 890 °C and in a strain rate range from 2 × 10<sup>−4</sup> to 8 × 10<sup>−4</sup> s<sup>−1</sup>. 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-αTitanium 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.</p>