微结构梁系统与两相非局部梁的关系

IF 2.5 3区 工程技术 Q2 MECHANICS
Xiao-Jian Xu, Min-Jie Bu, Chao-Hui Wang
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引用次数: 0

摘要

非局部弹性框架下的薄梁研究的最新进展表明,微结构梁系统与Eringen微分型非局部梁之间存在着密切的关系。本文在两种典型边界条件:无箝位和双箝位下,通过固有频率的等价,建立了微结构梁系统与两相非局部梁之间的关系。推导了两相非局部梁的解析特性方程,并与近似解析方程进行了比较,以防止在材料体积分数小和非局部参数情况下的数值溢出。这项工作提出了校准程序,可以促进工程应用中常用的材料力学的等效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Relationships of a micro-structured beam system and a two-phase nonlocal beam

Relationships of a micro-structured beam system and a two-phase nonlocal beam

Relationships of a micro-structured beam system and a two-phase nonlocal beam

Recent advances in the study of thin beams within the framework of nonlocal elasticity demonstrate a close relationship between micro-structured beam systems and Eringen’s differential-type nonlocal beams. In this paper, we establish relationships between a micro-structured beam system and a two-phase nonlocal beam through the equivalence of natural frequencies under two typical boundary conditions: clamped-free and doubly clamped. The analytical characteristic equations of two-phase nonlocal beams are derived and compared to approximately analytical equations to prevent numerical overflow in cases with small volume fractions of material and nonlocal parameters. This work proposes calibrated procedures that may facilitate the equivalence of material mechanics commonly used in engineering applications.

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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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