Determining elastic anisotropy of textured polycrystals using resonant ultrasound spectroscopy

Abstract

Polycrystalline materials can have complex anisotropic properties depending on their crystallographic texture and crystal structure. In this study, we use resonant ultrasound spectroscopy (RUS) to nondestructively quantify the elastic anisotropy in extruded aluminum alloy 1100-O, an inherently low-anisotropy material. Further, we show that RUS can be used to indirectly provide a description of the material’s texture, which in the present case is found to be transversely isotropic. By determining the entire elastic tensor, we can identify the level and orientation of the anisotropy originated during extrusion. The relative anisotropy of the compressive (c11/c33) and shear (c44/c66) elastic constants is 1.5% ± 0.5% and 5.7% ± 0.5%, respectively, where the elastic constants (five independent elastic constants for transversely isotropic) are those associated with the extrusion axis that defines the symmetry of the texture. These results indicate that the texture is expected to have transversely isotropic symmetry. This finding is confirmed by two additional approaches. First, we confirm elastic constants and the degree of elastic anisotropy by direct sound velocity measurements using ultrasonic pulse echo. Second, neutron diffraction (ND) data confirm the symmetry of the bulk texture consistent with extrusion-induced anisotropy, and polycrystal elasticity simulations using the elastic self-consistent model with input from ND textures and aluminum single-crystal elastic constants render similar levels of polycrystal elastic anisotropy to those measured by RUS. We demonstrate the ability of RUS to detect texture-induced anisotropy in inherently low-anisotropy materials. Therefore, as many other common materials have intrinsically higher elastic anisotropy, this technique should be applicable for similar levels of texture, providing an efficient general diagnostic and characterization tool.

Non-destructive texture characterization by a robot-arm-driven X-ray diffractometer

“…Since the scattering-induced ultrasonic attenuation strongly depends on the length scale of the microstructure regions, it is reasonable to assume that the presence of macrotexture can be identified using this technique (Bhattacharjee et al, 2011;Davis et al, 2008). The results correlated well with electron diffraction results (Pilchak et al, 2014), and a number of more recent papers show good progress in utilizing ultrasound to quantify the texture in bulk material, but this has not been widely used (Rossin et al, 2021;Evans et al, 2021).…”

Effect of ECAP process on deformability, microstructure and conductivity of AA5083 under thermal effect

“…To findings firmly corroborate the assertion that UFG AA5083 is thermally stable up to 520 0 C, taking into account the gradually increase in the average particle size. The available of texture poles that are angled away from the sample's major axes shows the same mechanical anisotropy [23]. The texture unifies and the degree of the texturing poles intensity increases when the annealing temperature is raised further, reaching 610 0 C. This is brought on by the expansion of recrystallized grains, Large grains compared to indent sizes and a higher overall hardness value suggest that a tiny amount of phase was formed and stabilized during diffusion.…”

Through-Thickness Microstructure Characterization in a Centrifugally Cast Austenitic Stainless Steel Nuclear Reactor Primary Loop Pipe Using Time-of-Flight Neutron Diffraction

“…Results of this study, showing highly oriented textures throughout the samples in CASS will help further the development of non-destructive ultrasonic techniques for these materials. While a detailed discussion of our results in the context of quality control methods, such as acoustic methods, is beyond the scope of this paper, our dataset can be used to model, e.g., the acoustic response of the material (see, e.g., Evans et al and Wenk et al for detailed descriptions of bulk neutron texture results to predict and interpret material response in acoustic measurements) [37,38].…”