4.7 Article

Reflection and transmission of elastic waves in the multilayered orthotropic couple-stressed plates sandwiched between two elastic half-spaces

期刊

APPLIED MATHEMATICAL MODELLING
卷 75, 期 -, 页码 52-72

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.apm.2019.05.023

关键词

Legendre polynomial method; Anisotropic couple-stress theory; Multilayered structures; Orthotropic interlayers; Reflection and transmission

资金

  1. National Natural Science Foundation of China [U1804134, U1504106]
  2. Program for Innovative Research Team of Henan Polytechnic University [T2017:3]
  3. Fundamental Research Funds for the Universities of Henan Province [NSFRF140301]

向作者/读者索取更多资源

In this paper, a high efficient computational approach, the extended Legendre orthogonal polynomial method (LOPM) is provided to investigate the reflection and transmission of elastic waves in orthotropic couple-stress layered plates sandwiched between two elastic half-spaces. In this approach, the anisotropic couple-stress theory is introduced into the LOPM to calculate the reflection and transmission coefficients of the orthotropic interlayers. The stress components, couple-stress components, rotation vectors and governing equations are derived in terms of the Legendre orthogonal polynomial. The present method does not require calculations of the displacement solutions of each partial wave in anisotropic multilayered microstructures, but expands the displacement vector of each layer into a Legendre orthogonal polynomial series with the expansion coefficients to be calculated. The incident P wave and SH wave are calculated, respectively. The effects of length scale parameters in three different directions are studied. It is found that the reflection and transmission coefficients of the incident P wave are only related to the length scale parameter in the z direction. For incident SH wave, the influence of the length scale parameter along the thickness direction is much more significant than that of the length scale parameter in the y direction. (C) 2019 Elsevier Inc. All rights reserved.

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