Intra-grain orientation distributions in hot-deformed aluminium: Orientation dependence and relation to deformation mechanisms

Abstract

International audienceThe development of intra-grain orientation distributions is analysed for 92 individual grains of an aluminium polycrystal deformed in plane strain compression at 400 degrees C to an effective strain of epsilon = 1.2. Orientations of the crystallographic lattice were measured by using a microtexture tracking technique that combines deforming a split sample with collecting electron backscattering diffraction (EBSD) data on the internal surface at successively greater strains. In these experiments, more than 1000 orientations were taken within each of the grains at strains 0.19, 0.42, 0.77 and 1.2, as well as in the initial, undeformed state. A high-resolution finite element simulation (1000 elements/grain on average) was conducted on a polycrystal whose grains were assigned the experimental orientations. Attributes of the orientation distributions were extracted from both the experimental and simulation data, including the average disorientation angles and the preferential disorientation axes. For both experiment and simulation, the average disorientation angles were found to increase up to epsilon = 0.5 and then to saturate to values of 7-8 degrees. It is shown that the preferential disorientation axes are distributed about the transverse direction (TD) up to epsilon = 0.5 and then migrate at large strains to directions between the rolling (extension) direction (RD) and the normal (compression) direction (ND). Detailed crystal plasticity analyses show that the distribution of preferential disorientation axes is related to two mechanisms: (i) the development of anisotropy in the orientation distributions due to the accentuated activity of particular slip systems from stress heterogeneities and (ii) the peak-shifting transformation of the distribution arising from gradients of the reorientation velocity field imposed by the deformation. (C) 2015 Elsevier Ltd. All rights reserved

Optimal polyhedral description of 3D polycrystals: Method and application to statistical and synchrotron X-ray diffraction data

“…These methods provide both the grain structure of polycrystalline materials [8,9] and the local stresses and lattice rotations [10][11][12][13] that develop as they are deformed. Numerical methods are available to simulate these phenomena [14][15][16][17][18][19][20][21][22], e.g. the widely-used finite element method [14][15][16][17][18][19][20].…”

“…Numerical methods are available to simulate these phenomena [14][15][16][17][18][19][20][21][22], e.g. the widely-used finite element method [14][15][16][17][18][19][20]. Simulations can then be compared to experiments [19,20] or used alone to analyse systematically the influence of microstructural attributes, on condition that appropriate polycrystal models are available.…”

“…A major advantage is that they can be meshed with relatively standard approaches [26], while their cells being necessarily convex is often a minor limitation for representing polycrystals [29]. Voronoi tessellations, in particular, have been widely used in numerical simulations in the past few years [7,19,20,[30][31][32][33][34][35] but only partially reproduce elementary polycrystal properties such as their grain size distribution [26].…”

Grain interaction mechanisms leading to intragranular orientation spread in tensile deformed bulk grains of interstitial-free steel

“…Three dimensional data may be obtained by serial sectioning (Afrin et al, 2013;Lin et al, 2010), which is, however, destructive, implying that the dynamics of the grains cannot be monitored. By pressing two metal surfaces closely together during deformation, a three-dimensional environment of neighbouring grains has been mimicked while still enabling dynamic studies by intermittent separation and EBSD investigation of the surfaces (Bhattachayya et al, 2001;Quey et al, 2015Quey et al, , 2010.…”

“…More recently, advanced finite element (Roters et al, 2010;Zhang et al, 2016) or Fourier transformation (Eisenlohr et al, 2013;Lebensohn et al, 2012) based polycrystal plasticity models, which consider more detailed interactions, have been employed to simulate intragranular orientation spreads Quey et al, 2015). The grain structures used as input to these models differ in geometrical complexity, and assignment of neighbouring grains may be based on statistics or experimentally determined grain structures, either in 2D by EBSD or in 3D by synchrotron methods.…”