Mechanical failure frequently initiates at the grain level, at which intra-granular stresses are of paramount importance. Under cyclic loading conditions regions within grains that experience high values of tensile residual stress are more prone to damage processes that lead to the formation of slip bands, defects, micro-voids and fissures that induce crack nucleation and propagation. For these reasons, the knowledge and understanding of residual stress across the scales (Types I, II and III) is crucial for improving the accuracy of mechanical failure prediction. The present study was carried out with the purpose of revealing the presence and nature of inter- and intra-granular residual stresses (known as Type II and III) that were present in an Aluminium alloy sample as consequence of plastic deformation. To this end, a well-defined macroscopic residual stress field was introduced in a miniature four-point bent beam. Following sample microstructure mapping by EBSD, the evaluation of Type II & III residual stress at the grain level was conducted using FIB-DIC micro-ring-core method. The combination of two calibrated models at different length scales enabled the simulation of stress across the scales, from the continuum large scale down to the crystal level (CP-FEM). As the outcome of this multi-scale modelling, the RS simulation predictions at all scales (Type I, II & III) were obtained and compared with the experimental results using a statistical approach. A key significance of the finding was that the Standard Deviation of the local residual stress values (95% confidence interval half width) amounted to as much as 2/3 of the macroscopic Type I value. This highlights the importance of including the information about Type II+III stresses in predictive design for structural integrity and the avoidance of failure. Error propagation due to measurement uncertainty was accounted in the analysis. By considering Schmid factor at locations of residual stress measurement, a modest correlation was found with Type II & III residual stresses.
- Residual stress
- Statistical distribution