Abstract 

Optimum mechanical behavior is achieved by means of controlling microstructural anisotropy. The latter is directly related to the crystallographic texture and is considerably affected by thermal and mechanical processes. Therefore, understanding the underlying mechanisms relating to its evolution during thermomechanical processing is of major importance. Towards that direction, an attempt to identify possible correlations among significant microstructural parameters relating to texture response during deformation was made. For this purpose, a 3104 aluminum alloy sheet sample (0.5 mm) was examined in the following states: (a) cold rolled (with 90% reduction), (b) recovered and (c) fully recrystallized. Texture, anisotropy as well as the mechanical properties of the samples from each condition were examined. Afterwards, samples were subjected to uniaxial loading (tensile testing) while the most deformed yet representative areas near the fractured surfaces were selected for further texture analysis. Electron backscatter diffraction (EBSD) scans and respective measurements were conducted in all three tensile test directions (0°, 45° and 90° towards rolling direction (RD)) by means of which the evolution of the texture components, their correlation with the three selected directions as well as the resulting anisotropy were highlighted. In the case of the cold-rolled and the recovered sample, the total count of S2 and S3 components did not change prior to and after tensile testing at 0° towards RD; however, the S2 and S3 sum mostly consisted of S3 components after tensile testing whereas it mostly consisted of S2 components prior to tensile testing. In addition, the aforementioned state was accompanied by a strong brass component. The preservation of an increased amount of S components, and the presence of strain-free elongated grains along with the coexistence of a complex and resistant-to-crack-propagation substructure consisting of both high-angle grain boundaries (HAGBs) and subgrain boundaries (SGBs) led into an optimal combination of Δr and rm parameters.