Warm and hot deformation behaviors and hot workability of an aluminum-magnesium alloy using artificial neural network

In this work, flow stress behavior, softening mechanisms and processing maps during deformation of aluminum-magnesium alloy i.e. AA5052, were investigated. Firstly, tensile tests were carried out in the range of room temperature up to 450 degrees C under different strain rates between 0.001 s-1 to 0.05 s-1. Then, neural network al-gorithms together with dynamic materials modeling were employed for determination of stain rate sensitivity parameter and processing maps under different working conditions. Moreover, the governing constitutive equations as well as the activation energies of dynamic strain aging and hot deformation were defined. Accordingly, the processing maps were developed for different strains of 0.15, 0.2 and 0.3. The alloy showed a higher resistance to flow instability at high temperatures i.e. temperature above 350 degrees C. Besides, the activation energy for dynamic strain aging was computed as 46.2 kJ/mole while the apparent activation energy for hot deformation was calculated about 192.1 kJ/mole. It has been inferred that the governing softening mechanism in temperatures ranging 250-400 degrees C could be dynamic recovery, however, by increasing deformation temperature and/or under low strain rates, dynamic recrystallization would be operative leading to higher resistance to flow localization.