Elastic waves which are propagating in polycrystals are permanently scattered at the boundaries between adjacent grains, due to an abrupt change of acoustic material properties caused by changing crystallite orientation. This leads to a macroscopic, measurable spatial attenuation in propagation direction, which is related to details of the microstructure (e.g. the average grain size) and thus might be used for its characterization. On the other hand, wave scattering leads to amplitude fluctuations (grain-noise) of ultrasonic signals, and thus hinders flaw detection. A deep physical understanding is thus vital for the development and improvement of non-destructive evaluation (NDE) techniques. Here, we present a numerical method to investigate the grain boundary scattering induced effective attenuation of Rayleigh-type surface acoustic waves (SAWs) in a virtual digital twin of a real metal sample.Although the idea of using ultrasonic attenuation measurements for microstructure characterization exists for more than half a century, even today no direct extraction of the statistical moments of the microstructure by inversion of acoustic attenuation measurements has been achieved. One reason for this is that a reliable and reproducible measurement of the effective acoustic attenuation, in accordance with analytical mean-field attenuation theories, is difficult. In most experimental studies, longitudinal bulk waves are used. In a recent study, we presented a non-contact method for the determination of Rayleigh-type surface acoustic wave attenuation in polycrystalline metals. It is based on a frequency domain Laser-Ultrasound (LUS) system. The obtained frequency dependent SAW attenuation showed good quantitative agreement to analytical models, but a slightly different frequency power-law in the stochastic scattering regime.Here, we present a novel approach to study the effective SAW attenuation with finite element method (FEM) model based on a realistic material model. It depends on statistically matching a virtual polycrystal based on a Laguerre-tessellation with a previously experimentally studied aluminum sample. Therefore, the spatial autocorrelation functions of the real and virtual microstructures are matched. Signal-processing methods are presented to extract the effective SAW attenuation from the FEM-data. Finally, comparisons to the previous experimental results are made and conclusions are drawn.

Finite Element Modelling of Effective Surface Acoustic Wave Propagation in a Digital Twin of a Polycrystalline Aluminum Sample

Paper Proceedings: https://asmedigitalcollection.asme.org/qnde/QNDE2021/volume/85529

ASME 2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation (QNDE2021)

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