Characterization of Superplastic Deformation Behavior for a Novel Al-Mg-Fe-Ni-Zr-Sc Alloy: Arrhenius-Based Modeling and Artificial Neural Network Approach

The application of superplastic forming for complex components manufacturing is attractive automotive and aircraft industries has been great interest in recent years. current analytical modeling theories are far from perfect this area, the results deduced it characterize conditions insufficiently well; therefore, successful numerical essential. In study, behavior novel Al-Mg-Fe-Ni-Zr-Sc alloy with high-strain-rate superplasticity was modeled. An Arrhenius-type constitutive hyperbolic-sine equation model (ACE) an artificial neural network (ANN) were developed. A comparative study between constructed models performed based on statistical errors. cross validation approach utilized to evaluate predictability developed models. revealed that ACE ANN demonstrated strong workability predicting investigated alloy’s flow stress, whereas exhibited better than ANN.