Texture Clustering and Long-Range Disorientation Representation Methods: Application to 6022 Aluminum Sheet

Two new graphical methods are presented for microstructural analysis of crystalline material. These analyses are intended to aid an understanding of deformation behavior at scales larger than the grain size. The correlation of orientation over large distances has rarely been investigated since long-range correlation has been assumed to be negligible, if present at all. The first method reveals orientation clustering by calculating the variance of the orientation distribution function. The second addresses orientation ordering or orientation autocorrelation and is named the Disorientation Correlation Function (DCF). We show that both analyses can be derived from the two-point auto-correlation functions of the orientation field.