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Effective Properties of Random Composites and Fiber Networks.

机译:随机复合材料和纤维网络的有效特性。

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Random fiber networks are assemblies of one-dimensional mechanical elements used to model the mechanics of various natural and man-made materials such as biopolymer gels and synthetic nonwovens. The small-strain mechanics of identical straight fibers has been subjected to detailed investigation, resulting in homogenization relations that express relations between network stiffness and microstructural properties. Chapters 2 and 3 of this dissertation extend such studies to account for situations where non-identical fibers or crimped fibers are present in the network. Such situations are ubiquitously observed in various systems, e.g. in collagenous soft tissue where fibers might be crimped and multiple types of fibers can be present.;Chapter 2 addresses the mechanics of networks with non-identical fibers where fiber properties are sampled from statistical distributions. Finite element simulations and theoretical arguments are used to show that irrespective of network geometry, increasing the variance of fiber properties decreases the small strain network stiffness on average and the amount of network softening is proportional to the variance of fiber properties. It is further shown that the variance of small strain network stiffness scales linearly with the variance of fiber properties and inversely with the number of fibers. This chapter reports simulation results using 2D Mikado and 3D Voronoi and Delaunay networks. The analytical arguments used to prove the scaling laws include deriving a relation between fiber stiffness and network stiffness and ensemble averaging of a series approximation. Chapter 2 concludes with an extension to finite deformation behavior of networks with non-identical fibers. Estimating the effective stiffness of networks is followed in chapter 3 where the effect of fiber crimp (tortuosity) on network properties is addressed. In addition to numerical results for 3D Voronoi networks, semi-analytical arguments are provided to derive lower bounds for softening due to fiber crimp and also a series estimation for effective modulus. Implicit finite element analysis are performed to study the finite strain network behavior in the presence of crimp and finally the effect of fiber crimp is studied in a coupled fiber-matrix model for soft tissue.;Chapter 4 introduces two models for simulating the mechanics of cross-linked networks of ribbon-like fibers: a coarse-grained bead-spring model and a finite element model. The coarse-grained model is used to prepare geometric models mimicking those observed in experiments using cellulose fibers and then the two models are used to test the small-strain mechanical behavior of the prepared network geometries. The models predict qualitatively similar mechanical behavior predicting linear dependence of network stiffness on the density of cross-links. Chapter 4 concludes with analyzing the computational parallel performance of the two models.;The 5th chapter is an extension of the micromechanical results pertaining to random fiber networks to random continuum composites. The effective elasticity and conductivity of composites with random microstructural properties are studied using finite element models. The composite systems consist of isotropic homogeneous subdomains having properties sampled from a statistical distribution. It is shown numerically and analytically that the effective Young's modulus and heat conduction of the random composites linearly decrease with increasing the variance of microstructural properties. Also the variances of these effective properties scale linearly with the variance of microstructural properties and inversely with the number of considered subdomains. The analytical arguments in this chapter are a generalization of the relations introduced for fiber networks in chapter 2, introducing relations between effective composite properties and the properties of an inhomogeneity.;The conclusions are outlined in chapter 6, along with an outline of the principal advances made in this work and a discussion of the suggested future directions of research immediately related to the contents of this thesis.
机译:随机纤维网络是一维机械元件的组合,用于模拟各种天然和人造材料的力学,例如生物聚合物凝胶和合成无纺布。对相同直纤维的小应变力学进行了详细研究,得出了表示网络刚度和微观结构特性之间关系的均质关系。本文的第2章和第3章将此类研究扩展到考虑网络中存在不相同的纤维或卷曲纤维的情况。在各种系统中普遍观察到这种情况,例如。在第2章介绍了具有不相同纤维的网络的力学,其中纤维特性是从统计分布中采样的;在胶原性软组织中,纤维可能会卷曲并且可能存在多种类型的纤维。有限元模拟和理论论证表明,不管网络几何形状如何,增加纤维性能的方差平均都会减小小应变网络的刚度,并且网络软化的量与纤维性能的方差成正比。进一步表明,小应变网络刚度的变化与纤维性质的变化成线性比例,与纤维数量成反比。本章报告使用2D Mikado和3D Voronoi和Delaunay网络的仿真结果。用于证明缩放定律的分析论据包括推导纤维刚度和网络刚度之间的关系以及级数近似的整体平均。第2章在结尾部分扩展了具有不同纤维的网络的有限变形行为。在第3章中介绍了估计网络的有效刚度,其中讨论了纤维卷曲(曲折度)对网络特性的影响。除了3D Voronoi网络的数值结果外,还提供了半分析论据,以得出由于纤维卷曲而导致的软化下限,以及有效模量的一系列估计。进行了隐式有限元分析,研究了存在压接时的有限应变网络行为,最后在软组织的纤维矩阵耦合模型中研究了纤维压接的影响。第四章介绍了两种模拟交叉力学的模型。状纤维的链状网络:粗粒珠弹簧模型和有限元模型。粗粒度模型用于准备模仿在使用纤维素纤维的实验中观察到的几何模型,然后将两个模型用于测试所准备网络几何形状的小应变力学行为。该模型预测定性相似的机械行为,预测网络刚度对交联密度的线性依赖性。第四章以分析两个模型的并行计算性能作为结尾。第五章是将与随机纤维网络有关的微观力学结果扩展到随机连续体复合材料。使用有限元模型研究了具有随机微结构特性的复合材料的有效弹性和导电性。复合系统由各向同性的均匀子域组成,这些子域具有从统计分布中采样的属性。数值和分析表明,无规复合材料的有效杨氏模量和热导率随着微观结构性能的变化而线性降低。这些有效特性的变化也与微结构特性的变化成线性比例,而与所考虑的子域的数量成反比。本章中的分析论点是对第2章中为光纤网络引入的关系的概括,介绍了有效复合特性与不均匀性之间的关系。第6章概述了结论,并概述了主要进展。在这项工作中进行的讨论,以及对与本文内容直接相关的未来研究方向的讨论。

著录项

  • 作者

    Ban, Ehsan.;

  • 作者单位

    Rensselaer Polytechnic Institute.;

  • 授予单位 Rensselaer Polytechnic Institute.;
  • 学科 Mechanical engineering.;Biomechanics.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 88 p.
  • 总页数 88
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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