Cellular Fourier analysis for geometrically disordered materials

A. Fruleux, A. Boudaoud
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引用次数: 3

Abstract

Many media are divided into elementary units with irregular shape and size, as exemplified by domains in magnetic materials, bubbles in foams, or cells in biological tissues. Such media are essentially characterized by geometrical disorder of their elementary units, which we term cells. Cells set a reference scale at which parameters and fields reflecting material properties and state are often assessed. In these media, it is difficult to quantify spatial variations of cell-scale fields, because space discretization based on standard coordinate systems is not commensurate with the natural discretization into geometrically disordered cells. Here we consider the spectral analysis of spatially varying fields. We built a method, which we call Cellular Fourier Transform (CFT), to analyze cell-scale fields, which includes both discrete fields defined only at cell level and continuous fields smoothed out from their sub-cell variations. Our approach is based on the construction of a discrete operator suited to the disordered geometry and on the computation of its eigenvectors, which respectively play the same role as the Laplace operator and sine waves in Euclidean coordinate systems. We show that CFT has the expected behavior for sinusoidal fields and for random fields with long-range correlations. Our approach for spectral analysis is suited to any geometrically disordered material, such as biological tissue with complex geometry, opening the way to systematic multiscale analyses of material behavior.
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几何无序材料的细胞傅里叶分析
许多介质被分成形状和大小不规则的基本单位,例如磁性材料中的畴、泡沫中的气泡或生物组织中的细胞。这种介质的本质特征是其基本单位(我们称之为细胞)的几何无序。单元设置了一个参考尺度,在这个尺度上经常评估反映材料属性和状态的参数和场。在这些介质中,很难量化细胞尺度场的空间变化,因为基于标准坐标系的空间离散化与几何无序细胞的自然离散化不相称。这里我们考虑空间变化场的光谱分析。我们建立了一种方法,我们称之为细胞傅里叶变换(CFT),来分析细胞尺度的场,其中既包括仅在细胞水平上定义的离散场,也包括从它们的亚细胞变化中平滑出来的连续场。我们的方法是基于一个适合于无序几何的离散算子的构造和它的特征向量的计算,它们分别在欧几里德坐标系中扮演着与拉普拉斯算子和正弦波相同的角色。我们证明了CFT对于正弦波场和随机场具有预期的行为。我们的光谱分析方法适用于任何几何无序的材料,例如具有复杂几何结构的生物组织,为材料行为的系统多尺度分析开辟了道路。
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