加压厚壁FGM球的解析解和数值解

IF 2.2 3区 工程技术 Q2 MECHANICS
P. Das, M. A. Islam, S. Somadder, M. A. Hasib
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引用次数: 1

摘要

功能梯度材料厚壁球的弹性分析被认为是许多工程设计中最重要的领域之一。本文研究了恒定内外压作用下FGM厚壁球的应力场和位移场。采用解析法和数值法进行了研究。建立了加压球形容器的精确有限元模型,假设并实现了杨氏模量沿径向连续变化。根据非线性广义公式,认为fgm的弹性模量随厚度变化。对于加压FGM球体,建立了径向位移和应力分布的解析解,并进行了验证。最后,将分析结果与有限元分析结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Analytical and numerical solutions of pressurized thick-walled FGM spheres

Analytical and numerical solutions of pressurized thick-walled FGM spheres

The elastic analysis of thick-walled spheres made of functionally graded materials (FGMs) is considered to be one of the most important areas in many engineering designs. This paper presents the stresses and displacement fields in an FGM thick-walled sphere under constant interior and exterior pressure. The investigation was carried out using analytical and numerical methods. Exact and finite element (FE) models of the pressurized spherical vessel were created, assuming and implementing continuous changing of Young modulus along the radial direction. It is considered that the elastic modulus of the FGMs varies with thickness according to the nonlinear generalized formula. For a pressurized FGM sphere, the analytical solutions for displacement and stress distribution were developed and demonstrated in the radial direction. Finally, the analytical results are compared to the results from the FE analysis.

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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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