BIEM via graded piezoelectric half-plane Green’s function for wave scattering by curvilinear cracks

IF 2.2 3区 工程技术 Q2 MECHANICS
Tsviatko Rangelov, Petia Dineva
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引用次数: 0

Abstract

This work presents numerical solution for wave motion in a functionally graded piezoelectric half-plane that includes contributions of incident time-harmonic SH waves, waves reflected by the traction-free surface and scattered by multiple curvilinear cracks. A special type of material gradient is studied, where material properties vary exponentially with respect to the depth coordinate. A non-hypersingular traction Boundary Integral Equation Method based on analytically derived Green’s function of a graded half-plane is developed and verified. A series of numerical results show the influence of the material gradient characteristics, the properties of the applied dynamic load, the cracks geometry, the cracks interaction phenomenon and the coupled character of the electromechanical continuum on the wave motions and on the local mechanical and electrical stress concentration fields developing in the graded half-plane.

Abstract Image

基于梯度压电半平面格林函数的曲线裂纹波散射BIEM
本文提出了功能梯度压电半平面中波动的数值解,该半平面包括入射时谐SH波的贡献,无牵引力表面反射的波和多个曲线裂纹散射的波。研究了一种特殊类型的材料梯度,其中材料性质随深度坐标呈指数变化。提出并验证了一种基于梯度半平面解析导出格林函数的非超奇异牵引边界积分方程方法。一系列数值结果表明,材料梯度特性、外加动载荷特性、裂纹几何形状、裂纹相互作用现象和机电连续体耦合特性对梯度半平面上的波动和局部机电应力集中场的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.40
自引率
10.70%
发文量
234
审稿时长
4-8 weeks
期刊介绍: Archive of Applied Mechanics serves as a platform to communicate original research of scholarly value in all branches of theoretical and applied mechanics, i.e., in solid and fluid mechanics, dynamics and vibrations. It focuses on continuum mechanics in general, structural mechanics, biomechanics, micro- and nano-mechanics as well as hydrodynamics. In particular, the following topics are emphasised: thermodynamics of materials, material modeling, multi-physics, mechanical properties of materials, homogenisation, phase transitions, fracture and damage mechanics, vibration, wave propagation experimental mechanics as well as machine learning techniques in the context of applied mechanics.
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