This study presents a comprehensive evaluation of Equal Channel Angular Pressing (ECAP) processing on the structural evolution and mechanical properties of AA2xxx aluminum alloy. Finite element analysis (FE) was used to study the deformation behavior of the AA2xxx billets during processing in addition investigate the strain homogeneity in the longitudinal and transverse direction. Billets of AA2011 aluminum alloy were processed successfully through ECAP up to 4-passes with rotating the sample 90° along its longitudinal axis in the same direction after each pass (route Bc) at 150 °C. The microstructural evolution and crystallographic texture were analyzed using the electron back-scatter diffraction (EBSD) and optical microscopy (OM). An evaluation of the hardness and tensile properties was presented and correlated with the EBSD findings and FE simulations. The FE analysis results were in good agreement with the experimental finding and microstructural evolution. Processing through 4-passes produced an ultrafine-grained structure (UFG) and a recrystallized fine grain dominated the structure coupled with a geometric grain subdivision which indicated by grain refining and very high density of substructures. This reduction in grain size was coupled with an enhancement in the hardness, tensile strength by 66.6%, and 52%, respectively compared to the as-annealed counterpart. Processing through 1-pass and 2-passes resulted in a strong texture with significant rotation for the texture components whereas 4-passes processing led to losing the symmetry of the texture with significant reduction in the texture intensity.

The main aim of the current work is to investigate the effect of equal channel angular pressing (ECAP) processing parameters, namely, number of passes, ECAP die angle, route type, and processing temperature on the mechanical and electrical properties of pure copper (Cu). The finite element method was used to simulate the homogeneity of stress and plastic strain distribution during ECAP processing. The response surface methodology (RSM) was used to identify the optimum ECAP processing parameters by analyzing the impact of ECAP conditions on responses. A second-order regression model and analysis of variance were created to analyze the ECAP condition of optimum responses. A genetic algorithm (GA) was also applied to optimize the ECAP condition. Finally, a hybrid RSM–GA was created to improve the optimization of ECAP responses and corresponding conditions evaluated using GA. The developed models were validated and compared with the experimental findings to prove that they are reliable as predictive tools. The optimization findings revealed that route Bc was more effective in improving the hardness, yield stress, ductility, and impact energy whereas route A was more effective in improving the ultimate tensile strength and the electrical conductivity of the Cu billets. Furthermore, the optimum die angle, number of passes, and processing temperature for the mechanical and electrical properties were also identified individually.