Experimental and computational studies of ultrasound wave propagation in hexagonal close-packed polycrystals for texture detection
Source abstract
Abstract
Abstract Texture in hexagonal close-packed (hcp) polycrystalline metals, often developed during thermomechanical processing, affects ultrasonic wave velocity. In this study, the relationship between bulk texture and ultrasonic wave velocity in aggregates of (predominantly) hcp grains is investigated using theoretical, numerical and experimental methods. A representative volume element methodology is presented, enabling the effects of texture on ultrasonic wave speed to be investigated in two-phase polycrystals, and is employed to examine the ultrasonic response of random polycrystals, textured polycrystals and macro-zones often observed in titanium alloys. Numerical results show that ultrasonic wave speed varies progressively with changing texture, over a range of ∼200 m s −1 , within bounds set by the two extreme single-crystal orientations. Experimental ultrasound studies and full electron backscatter diffraction (EBSD) characterization are conducted on unidirectionally rolled and cross-rolled Ti–6Al–4V samples in three orthogonal directions. In addition, the EBSD-determined textures are incorporated within the polycrystal model and predicted ultrasonic velocities compared directly with ultrasonic experiments. Good quantitative agreement is obtained and both the experimental and computed results demonstrate that ultrasonic velocity profiles exist for random, unidirectionally rolled and cross-rolled textures. The combined results indicate the possibility of the development of a methodology for bulk texture determination within Ti polycrystal components using ultrasound.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Titanium Alloys Microstructure and Properties · Advanced Welding Techniques Analysis · Hydrogen embrittlement and corrosion behaviors in metals
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (40)
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