Investigation into occurring dynamic strain aging in hot rolling of AA5083 using finite elements and stream function method

Two-dimensional finite element analysis together with stream function and neural network models are employed to determine thermo-mechanical behavior during hot strip rolling of AA5083. An appropriate velocity field and stream function is first determined using the rule of volume constancy and upper bound theorem and then temperature field within the metal is predicted by means of a two-dimensional conduction–convection model. In order to consider the effect of flow stress and its dependence on temperature, strain and strain rate, a neural network model is also employed in the analysis. Based on the performed tensile tests, two different neural network models are constructed one for smooth yielding and the other one for the serrated flow. Then, the ANN models are coupled with the thermo-mechanical analysis. In the next step, by combination of the predicted temperature, strain and strain rates fields and the experimental data achieved from the tensile tests, the occurence of dynamic strain ageing during hot rolling is predicted. The model predictions are then compared with the experimental data and good agreement is observed between the two sets of results that shows the validity of the proposed model.