Effect of grain size distribution of polycrystalline microstructure on in-plane wave propagation

衰减 平面波 波传播 材料科学 相速度 表面波 平面(几何) 光学 计算物理学 物理 几何学 数学
作者
Manas Kumar Padhan,Mira Mitra
出处
期刊:Waves in Random and Complex Media [Taylor & Francis]
卷期号:: 1-17
标识
DOI:10.1080/17455030.2023.2226241
摘要

This paper presents a study on in-plane wave propagation in two-dimensional polycrystalline microstructure with different grain distributions. The numerical simulations are performed using commercial finite element (FE) package and the microstructure is generated using Voronoi tessellation. The different grain distributions are generated using a regularity parameter, α. In-plane wave results in simultaneous P and S waves unlike conventional bulk wave, where only P or S wave is observed. Such in-plane wave propagation resulting from localized excitation is more realistic and has important applications in microstructural flaw detection. Here, an analogy is drawn with seismic wave in heterogeneous geophysical media to understand the in-plane waves in the polycrystalline microstructure. First, the effect of grain distributions on the attenuation and phase velocity behavior of in-plane wave is studied in the low-frequency Rayleigh regime. The numerical simulations are performed for Inconel-600 for grain sizes of 100 and 250 μm. Then, the numerical model is validated with experimental results using piezoelectric transducers on an Inconel-600 plate. The physical microstructure of Inconel-600 material is observed using a scanning electron microscope. The frequency dependency of attenuation for in-plane waves is close to unity similar to that of seismic wave. The attenuation and phase velocity vary with the change in regularity parameter, α. Additionally, it is observed that the scattering of P wave is higher than that of S wave during in-plane wave propagation, resulting in higher attenuation of P wave. Finally, an exponential expression is established between regularity parameter and attenuation, which will help in characterizing and predicting the grain distribution inversely.
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