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Computational methods in stochastic micromechanics of heterogeneous solids.

机译:非均质固体随机微力学的计算方法。

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Due to the spatial variability in heterogenous (random) materials at microscopic level, its effective properties at various length scales have to be determined in a stochastic (probabilistic) fashion. In this dissertation, such a determination is based on a discrete random modeling of microstructure. Three problems of stochastic nature, are presented and methodologies of treatment are proposed. Solutions are performed via computer simulations. In the first problem, the effective elastic moduli of Delaunay networks, modeling two-phase granular media are calculated. Combined with a Delaunay network, two spring models are used to represent interactions between particles. In the first model, central interaction is taken into account, while in the second one both central and angular interactions are considered. Results of numerical simulations are used to identify that self-consistent model which most closely approximates effective elastic properties of two-phase Delaunay networks.; In the second problem, a micromechanics-based stochastic finite element method is developed to account for the variability in material properties at micro level. The method is illustrated through an out-of-plane elasticity problem of a membrane with a microstructure of a spatially random inclusion-matrix under a deterministic load. The key concept introduced here is a random meso scale continuum model. It is found that two bounds on the material properties and in turn on the global response have to be considered in the analysis.; In the last problem, the effective thermal conductivity of functionally graded heterogeneous interphases between fiber and matrix in such composites is determined. The topology of microstructure is taken as a mosaic or a random chessboard where both phases have locally isotropic properties. The resulting meso-continuum model of the interphase is used to calculate the effective macroscopic properties (transverse conductivity or, equivalently, axial shear modulus) of such composite materials. This problem requires the treatment of several length scales; the fine interphase microstructure, its meso-continuum representation, the fiber size and the macroscale level at which the effective properties are defined.
机译:由于异质(随机)材料在微观水平上的空间变异性,因此必须以随机(概率)方式确定其在各种长度范围内的有效特性。在本文中,这种确定是基于微结构的离散随机建模。提出了三个随机性问题,并提出了治疗方法。解决方案是通过计算机模拟执行的。在第一个问题中,计算了Delaunay网络的有效弹性模量,对两相颗粒介质进行了建模。结合Delaunay网络,使用两个弹簧模型来表示粒子之间的相互作用。在第一个模型中,考虑了中心相互作用,而在第二个模型中,考虑了中心和角度相互作用。数值模拟的结果被用来识别最接近两相Delaunay网络有效弹性特性的自洽模型。在第二个问题中,开发了一种基于微力学的随机有限元方法来解决材料性能在微观水平上的变化。通过在确定性载荷下具有空间随机包含矩阵微观结构的膜的平面外弹性问题来说明该方法。这里介绍的关键概念是随机的中观尺度连续模型。发现在分析中必须考虑材料特性的两个界限,进而要考虑整体响应。在最后一个问题中,确定了此类复合材料中纤维和基质之间功能梯度非均相的有效导热系数。微观结构的拓扑结构被视为镶嵌或随机棋盘,其中两相均具有局部各向同性的特性。所得的中间相的中连续谱模型用于计算此类复合材料的有效宏观性能(横向电导率或等效地,轴向剪切模量)。这个问题需要处理几个长度刻度。精细的相间微观结构,中观连续谱表示,纤维尺寸和定义有效性能的宏观水平。

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