论文标题

细胞傅立叶分析,用于几何无序材料

Cellular Fourier analysis for geometrically disordered materials

论文作者

Fruleux, Antoine, Boudaoud, Arezki

论文摘要

许多培养基被分为具有不规则形状和大小的基本单元,如磁性材料中的结构域,泡沫中的气泡或生物组织中的细胞所示。这种培养基的特征在于其基本单位的几何障碍,我们称其为细胞。细胞设置一个参考量表,通常评估反映材料特性和状态的参数和字段。在这里,我们考虑了空间变化场的光谱分析。这种分析在几何无序的介质中很困难,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。确实,我们发现两种经典光谱方法,即快速傅立叶变换和图傅立叶变换,无法再现平面波和白噪声光谱的所有预期特性。因此,我们构建了一种称为细胞傅立叶变换(CFT)的方法,以分析细胞尺度场,该字段构成了仅在细胞级别定义的离散字段,并且从其子细胞变化中平滑的连续字段。我们的方法基于构建适合无序几何形状的离散操作员和其特征向量的计算,该几何量分别与Laplace Operator和euclidean坐标系统中的Laplace Operator和正弦波相同。我们表明,CFT具有正弦场和具有远距离相关性的随机场的预期行为。我们的光谱分析方法适用于任何几何无序材料,例如具有复杂几何形状的生物组织,为材料行为的系统多尺度分析打开了途径。

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 are often assessed parameters and fields reflecting material properties and state. Here, we consider the spectral analysis of spatially varying fields. Such analysis is difficult in geometrically disordered media, because space discretization based on standard coordinate systems is not commensurate with the natural discretization into geometrically disordered cells. Indeed, we found that two classical spectral methods, the Fast Fourier Transform and the Graph Fourier transform, fail to reproduce all expected properties of spectra of plane waves and of white noise. We therefore built a method, which we call Cellular Fourier Transform (CFT), to analyze cell-scale fields, which comprise 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 a biological tissue with complex geometry, opening the path to systematic multiscale analyses of material behavior.

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