ABSTRACT
The application of hyperbolic sine equation and Artificial Neural Network(ANN) model to predict high temperature flow behaviour of Ti-6Al-4V preform is assessed for development of a constitutive equation to model ring rolling process. Uniaxial compression specimens were obtained from a specific location and direction, where the radial deformation is the major deformation location, to study the ring rolling process. The adiabatic temperature corrected data was used to find constants for hyperbolic sine equation and train the ANN model. The ANN model used normalised strain, strain rate and temperature as input variables and the output parameter was the flow stress. Comparison of the predicting capability of both models showed that the predictions of ANN were better. The hyperbolic sine equation was integrated in a user subroutine and finite element-based simulations of isothermal uniaxial compression were carried out for validation.
Acknowledgments
The authors would like to acknowledge ARDB for funding under GTMAP program and MIDHANI for providing the Ti-64 preform ring. The authors are thankful to Aditya Sarkar, Manil Raj and Abhishek Kumar for their valuable inputs.
Disclosure statement
No potential conflict of interest was reported by the authors.