Dispersion analysis of composite acousto-elastic waveguides
Dispersion analysis of composite acousto-elastic waveguides
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DOI：
10.1016/j.compositesb.2017.07.040
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发表时间：
2017-12-01
影响因子：
13.1
通讯作者：
Guddati, Murthy N.
中科院分区：
文献类型：
--
作者：
Astaneh, Ali Vaziri;Guddati, Murthy N.
导波的传播特性被广泛用于层合复合材料的无损表征。这些传播特性通过色散和衰减曲线来量化，并且需要在很宽的频率范围内对大量估计的结构和材料特性组合进行计算。为了解决这一核心问题，提出了一种有效的方法来分析三种类型的浸入波导：层合板；层压棒和管；具有通用截面的复合波导。该方法以半解析有限元（SAFE）方法为基础，在固体域的复长度有限元法（CFEM）和周围流体的完全匹配离散层法（PMDL）两种新的离散化方法的基础上进行了改进。由此产生的方法在计算上比现有方法更有效，因为它使潜在的特征值问题保持线性并且实质上更小。本文介绍了所提出的方法的基本思想，确定离散化参数的具体算法，以及由此产生的波导模型的开源实现。算例说明了该方法的有效性。最后，用几个结构构件的实验观测验证了该方法的理论预测。(C) 2017 Elsevier Ltd.版权所有。
Propagation characteristics of guided waves are widely utilized for nondestructive characterization of laminated composites which are often immersed in fluid. These propagation characteristics are quantified through dispersion and attenuation curves, and need to be computed for a large number of estimated structure and material property combinations, over a wide range of frequencies. To solve this central problem, an efficient approach is proposed for dispersion analysis of three types of immersed waveguides: laminated plates; laminated rods and pipes; composite waveguides with generic cross-section. The approach is based on Semi-Analytical Finite Element (SAFE) method enhanced with two novel discretization methods: Complex-length Finite Element Method (CFEM) for the solid domain and Perfectly Matched Discrete Layers (PMDL) for the surrounding fluid. The resulting approach is computationally more efficient than the existing methods in that it keeps the underlying eigenvalue problem linear and substantially smaller. The paper presents the basic ideas of the proposed approach, specific algorithms for determining the discretization parameters, and open-source implementation of the resulting waveguide models. Several numerical examples are presented to illustrate the method's efficiency. Finally, the theoretical predictions from the method are validated using experimental observations for several structural members. (C) 2017 Elsevier Ltd. All rights reserved.