Particle Shape Complexity Reduction for Estimation of Effective Elastic Properties of the Composite

Pascal Alexander Happ , Romana Piat
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引用次数: 0

Abstract

The material development is an expensive process, especially considering composite materials as their microstructure can be very complex. Particle reinforced composites in particular can consist of particles with complicated shapes. Traditionally ellipsoid approximations are used to reduce shape complexity, which comes at the drawback of neglecting the influence of the particles shape onto the composite mechanical properties. The computational method as proposed in this work employs particle swarm optimization in combination with the FE method to create spherical equivalents, which reduces the complexity but also stores the particle shape information. The proposed method can minimize the development cost of new particle reinforced composite materials, while increasing the spectrum of evaluated material features.

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降低颗粒形状复杂性以估算复合材料的有效弹性特性
材料开发是一个昂贵的过程,尤其是复合材料,因为其微观结构可能非常复杂。特别是颗粒增强复合材料可能由形状复杂的颗粒组成。传统上使用椭球近似来降低形状的复杂性,其缺点是忽略了颗粒形状对复合材料机械性能的影响。本研究提出的计算方法采用了粒子群优化与 FE 方法相结合的方法来创建等效球形,这不仅降低了复杂性,还存储了粒子形状信息。所提出的方法可以最大限度地降低新型颗粒增强复合材料的开发成本,同时增加评估材料特性的范围。
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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Editorial Editorial Preface Editorial Strain measurement consistency of distributed fiber optic sensors for monitoring composite structures under various loading
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