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Fractal analysis of the three-dimensional fracture surfaces in materials by the box-counting method

机译:分箱计算法分析材料三维断裂面的分形

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摘要

Fractal geometry created by Mandelbrot [1] enabled the quantitative description of microstructures and fracture surfaces in materials by the fractal dimension. Almqvist [2] proposed the variance method for the estimation of the fractal dimension, D_v (2 ≦ D_v ≦ 3), of the three dimensional surface on the images (larger than about 300 * 300 in pixel) obtained by scanning probe microscopes (SPM). He estimated the fractal dimension (D_v) from a relationship between the average variance, {σ(B)}~2, and the size of the measurement boxes, B, in a given image ({σ(B)}~2 ∝ B~(2(3-D_(v)))). However, the fractal dimension of the three-dimensional surface may depend not only on the image size but also on the algorithms for the fractal analysis [1,3], and may be correlated with surface microstructures and properties of materials [4-6]. Further, the SPM are not suitable for the characterization of very rugged surfaces with many bumps or ridges.
机译:由Mandelbrot [1]建立的分形几何学使得能够通过分形维数来定量描述材料中的微结构和断裂表面。 Almqvist [2]提出了一种方差方法,用于估计通过扫描探针显微镜(SPM)获得的图像(像素上大于300 * 300左右)的三维表面的分形维数D_v(2≤D_v≤3)。 )。他根据给定图像({σ(B)}〜2 ∝ B中的平均方差{σ(B)}〜2与测量框B的大小之间的关系来估算分形维数(D_v)。 〜(2(3-D_(v))))。但是,三维表面的分形维数不仅取决于图像尺寸,还取决于分形分析的算法[1,3],并且可能与表面的微观结构和材料的特性相关[4-6]。 。此外,SPM不适合表征具有许多隆起或隆起的非常粗糙的表面。

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