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Numerical validation of analytical homogenization models for the case of randomly distributed and oriented ellipsoidal fibers reinforced composites.

机译:随机分布和定向的椭圆形纤维增强复合材料情况下分析均质模型的数值验证。

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摘要

The development of new composite materials can be a long and expensive process. It would therefore be relevant to have predictive tools that can predict the mechanical behavior of composites before their fabrication. Using these tools could lead to shorter certification time and cost reductions. Several analytical approaches exist for predicting the mechanical properties of composites. The best known are the Rule of Mixtures and the Classical Lamination Theory. In most cases, both approaches lead to inaccurate predictions since they do not take into account all the available information about the microstructure.;Analytical homogenization models rely on microstructural information (e.g., constituents properties, volume fraction, shape, orientation, etc.) to predict the effective mechanical properties of heterogeneous materials. However, no systematic and thorough study evaluates the accuracy of these models for a wide range of constituents mechanical and geometrical properties. In order to validate the performance of analytical models, their predictions should be compared to those obtained by numerical methods. The different numerical methods that have been used in the literature had a high computational cost, which has limited the investigated range of composites. Furthermore, most numerical studies were performed without conducting a rigorous Representative Volume Element (RVE) determination process.;The main purpose of this thesis was to validate the performance of analytical homogenization models at predicting the effective mechanical properties and local field statistics of randomly distributed and oriented ellipsoidal fibers reinforced composites. Since a large validation campaign was planned, a fully automated numerical tool was developed. The latter dealt with two independent steps: i) random generation of the representative microstructures and ii) accurate computation of the effective properties.;The representative microstructures were generated using a molecular dynamics approach. A new computationally-efficient algorithm was developed for generating packings of randomly distributed and oriented ellipsoids. The proposed algorithm was able to generate all types of ellipsoids with high volume fractions and/or aspect ratios. The effective properties and local field statistics were accurately computed using a Fast Fourier Transforms (FFT) based technique.;The predictions of the numerical tool were compared to those of the best known analytical homogenization models for a broad range of phases mechanical properties, fibers volume fractions and aspect ratios. The validation campaign involved a thorough and rigorous RVE determination process and approximately, 1800 different ellipsoidal fibers reinforced composites were studied.;A validity domain was attributed to each analytical model. It was found that no analytical homogenization model stands out of the others as being more accurate over the studied range of phases mechanical and geometrical properties. However, if a single model was to be chosen to predict the effective properties and local field statistics of ellipsoidal fibers reinforced composites, this thesis recommend the Lielens' model. Indeed, it was shown that this model was suitable in most of the studied cases.;Besides the thorough and comprehensive validation of analytical homogenization models, the main contribution of this thesis is the development of two interpolation models. These models predict respectively the effective properties and the local field statistics of randomly distributed and oriented ellipsoidal fibers reinforced composites. It was shown that these models could be an alternative to analytical homogenization models since their accuracy is the highest published so far.
机译:新复合材料的开发可能是一个漫长而昂贵的过程。因此,具有可以在复合材料制造之前预测复合材料的机械性能的预测工具将很重要。使用这些工具可以缩短认证时间并降低成本。存在几种用于预测复合材料机械性能的分析方法。最著名的是混合法则和经典层压理论。在大多数情况下,这两种方法均会导致不准确的预测,因为它们没有考虑到有关微结构的所有可用信息。分析同质化模型依赖于微结构信息(例如,成分属性,体积分数,形状,方向等)来进行预测。预测异质材料的有效机械性能。但是,没有系统,透彻的研究评估这些模型在各种机械和几何特性方面的准确性。为了验证分析模型的性能,应将其预测与通过数值方法获得的预测进行比较。文献中使用的不同数值方法具有很高的计算成本,这限制了复合材料的研究范围。此外,大多数数值研究都是在没有进行严格的代表体积元素(RVE)确定过程的情况下进行的。本论文的主要目的是验证均匀化分析模型在预测随机分布的有效力学性能和局部场统计数据方面的性能。取向的椭圆形纤维增强复合材料。由于计划进行大规模的验证活动,因此开发了一种全自动的数值工具。后者涉及两个独立的步骤:i)随机生成代表性的微结构和ii)准确计算有效性能。;代表性的微结构是使用分子动力学方法生成的。开发了一种新的计算有效算法,用于生成随机分布和定向的椭球的堆积。所提出的算法能够生成具有高体积分数和/或纵横比的所有类型的椭球。使用基于快速傅立叶变换(FFT)的技术准确计算有效特性和局部场统计数据;将数值工具的预测结果与最广为人知的分析均质模型的预测结果进行比较,以了解广泛的相机械性能,纤维体积分数和长宽比。验证活动涉及一个彻底而严格的RVE确定过程,并研究了大约1800种不同的椭圆形纤维增强复合材料。结果发现,在研究的相力学和几何特性范围内,没有任何一种分析均质模型能比其他模型更准确。但是,如果要选择一个模型来预测椭圆形纤维增强复合材料的有效性能和局部场统计,则本文建议采用Lielens模型。的确,这表明该模型适用于大多数研究案例。除了对分析同质化模型进行全面而全面的验证之外,本论文的主要贡献是开发了两个插值模型。这些模型分别预测了随机分布和定向的椭圆形纤维增强复合材料的有效性能和局部场统计。结果表明,这些模型可以替代分析均质模型,因为它们的准确性是迄今为止发布的最高水平。

著录项

  • 作者

    Ghossein, Elias.;

  • 作者单位

    Ecole Polytechnique, Montreal (Canada).;

  • 授予单位 Ecole Polytechnique, Montreal (Canada).;
  • 学科 Mechanical engineering.;Mechanics.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 208 p.
  • 总页数 208
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:53:31

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