A thermo-viscoelastic model for particle-reinforced composite...

科技工作者之家 2021-07-03

Cite this article: 

Chen, Y., Shi, X., Zhao, Z. et al. A thermo-viscoelastic model for particle-reinforced composites based on micromechanical modeling. Acta Mech. Sin. 37, 402–413 (2021). https://doi.org/10.1007/s10409-020-01035-1


A thermo-viscoelastic model for particle-reinforced composites based on micromechanical modeling

Yang Chen, Xiaohao Shi, Zhenqiang Zhao, Zaoyang GuoYulong Li


Micromechanics-based constitutive models offer superior ability to estimate the effective mechanical properties for the composites, which greatly promote the computational efficiency in the multiscale analysis for composite structures. In this work, a thermo-viscoelastic model for particle-reinforced composites is proposed to estimate their thermal–mechanical coupling behaviors in terms of a micromechanics-based homogenization method in the time domain. The matrix and particles of the composites are modeled as “thermo-rheologically complex” viscoelastic materials. The temperature-dependent effective elastic strain energy ratios of particle to composite are proposed to evaluate the contributions of the matrix and particles. The thermo-viscoelastic model for the composites is then formulated by superposing the matrix and particle’s contributions. Finite element simulations based on the representative volume element models are employed to validate the constitutive model under various thermal–mechanical coupling loads. The effects of the loading rate, viscous parameter and particle content on the effective thermal–mechanical responses of the composites are also comprehensively discussed. The experimental data from literature are also employed to verify the constitutive model. The findings show that the proposed thermo-viscoelastic model can accurately predict the thermal–mechanical coupling behaviors for the particle-reinforced composites.

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来源:ams_cstam AMS力学学报英文版

原文链接:http://mp.weixin.qq.com/s?__biz=MjM5MjA5MTA3Ng==&mid=2651349634&idx=5&sn=a70117c3c364eb4d7dee4c833a520746

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