A Comprehensive Numerical Study of the Effect of Hybrid Reinforcement of Fiber Sizing on the Transverse Elastic Modulus of Polymeric Nanocomposites

IF 1.8 4区 材料科学 Q2 MATERIALS SCIENCE, CHARACTERIZATION & TESTING Physical Mesomechanics Pub Date : 2023-04-19 DOI:10.1134/S1029959923020091
E. Hayati, M. Safarabadi, M. Moghimi Zand
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Abstract

One of the most critical degradation modes in polymeric composites is fiber–matrix debonding. Therefore, utilizing nanoparticles in the fiber sizing instead of dispersing nanoparticles in the matrix as a traditional method could postpone the separation of fibers from the matrix. Covering of fibers during the production process is called sizing. The present study simulates two three-dimensional representative volume elements (RVEs) to predict the transverse elastic modulus of the glass/epoxy composite. The sizing region in the RVEs, provided in Abaqus software, is simulated with both homogeneous and heterogeneous mechanical properties. Then the numerical models are validated using the available numerical and experimental data. Furthermore, the Mori–Tanaka, Halpin–Tsai, and random distribution methods are employed to calculate equivalent properties for the nanoparticle-reinforced sizing, which are used for the sizing region of the RVEs to predict the transverse elastic modulus of the four-phase glass/epoxy composite. Compared to the available experimental data, the random distribution method is a more accurate procedure to predict the transverse Young’s modulus. Finally, with the assistance of the random distribution method, nanoparticles with different dimensions or even types are dispersed in the sizing region. In fact, carbon nanofibers (CNFs) and silica (SiO2) nanoparticles are simultaneously distributed in the sizing with various dimensions to predict the overall transverse elastic modulus of the composite. Once again, these nanoparticles are modeled in the sizing region with specific measurements. Besides, the results for all of the states are compared.

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纤维浆料混杂增强对聚合物纳米复合材料横向弹性模量影响的综合数值研究
高分子复合材料中最关键的降解方式之一是纤维基体脱粘。因此,在纤维施胶中使用纳米颗粒代替传统的将纳米颗粒分散在基体中的方法可以延缓纤维与基体的分离。在生产过程中对纤维的覆盖称为上浆。本研究模拟了两个三维代表性体积元(RVEs)来预测玻璃/环氧复合材料的横向弹性模量。在Abaqus软件中,模拟了RVEs中具有均匀和非均匀力学性能的施胶区域。然后利用现有的数值和实验数据对数值模型进行了验证。此外,采用Mori-Tanaka、Halpin-Tsai和随机分布方法计算了纳米颗粒增强施胶的等效性能,并将其用于RVEs施胶区域,以预测四相玻璃/环氧复合材料的横向弹性模量。与已有的实验数据相比,随机分布法是预测横向杨氏模量更为准确的方法。最后,借助随机分布方法,将不同尺寸甚至不同类型的纳米颗粒分散在施胶区域。事实上,碳纳米纤维(CNFs)和二氧化硅(SiO2)纳米颗粒同时分布在不同尺寸的浆料中,以预测复合材料的整体横向弹性模量。再一次,这些纳米粒子在施胶区域用特定的测量进行建模。此外,还对所有州的结果进行了比较。
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来源期刊
Physical Mesomechanics
Physical Mesomechanics Materials Science-General Materials Science
CiteScore
3.50
自引率
18.80%
发文量
48
期刊介绍: The journal provides an international medium for the publication of theoretical and experimental studies and reviews related in the physical mesomechanics and also solid-state physics, mechanics, materials science, geodynamics, non-destructive testing and in a large number of other fields where the physical mesomechanics may be used extensively. Papers dealing with the processing, characterization, structure and physical properties and computational aspects of the mesomechanics of heterogeneous media, fracture mesomechanics, physical mesomechanics of materials, mesomechanics applications for geodynamics and tectonics, mesomechanics of smart materials and materials for electronics, non-destructive testing are viewed as suitable for publication.
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