A survey on processing map for the hot deformation of Copper - Alumina nanocomposites using artificial neural network

Based on the mechanic of nanoparticles, the present research studies the deformation of cu-alumina nanocomposite experimentally and also by modeling. To optimize the deformation parameters and to control the microstructure in hot deformation process for copper-alumina nano-composites, cylindrical alumina nanoparticles samples in different percentages has been heat pressure tested. Distributions of alumina nanoparticles in copper, as well as the effects of nanoparticles on deformation have been investigated by transmission electron microscopy (TEM). To study the parameters affecting the deformation of material, the test temperatures of 350, 400, 450, 500° C and strain rates of 0.3, 0.03, 0.003 1/s have been selected. By the results of 48 experiments of stress-strain curves and to optimize the process parameters in the hot deformation, processing map is obtained for different strains. Also the hot deformation behaviors of nano-composites modeling of neural network with 4 input and one output parameters have been used. The modeling and experimental results are compared and the most optimal conditions for hot deformation of nanocomposite materials have been presented.