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使用先进的分形方法表征砂粒的表面粗糙度。

Characterization of the surface roughness of sand particles using an advanced fractal approach.

作者信息

Yang Hongwei, Baudet Béatrice A, Yao Ting

机构信息

Department of Civil Engineering , The University of Hong Kong , Pokfulam Road , Hong Kong.

Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong; Department of Civil, Environmental and Geomatic Engineering, University College, London, Gower Street, London WC1E 6BT, UK.

出版信息

Proc Math Phys Eng Sci. 2016 Oct;472(2194):20160524. doi: 10.1098/rspa.2016.0524.

Abstract

The surface roughness of soil grains affects the mechanical behaviour of soils, but the characterization of real soil grain roughness is still limited in both quantity and quality. A new method is proposed, which applies the power spectral density (PSD), typically used in tribology, to optical interferometry measurements of soil grain surfaces. The method was adapted to characterize the roughness of soil grains separately from their shape, allowing the scale of the roughness to be determined in the form of a wavevector range. The surface roughness can be characterized by a roughness value and a fractal dimension, determined based on the stochastic formation process of the surface. When combined with other parameters, the fractal dimension provides additional information about the surface structure and roughness to the value of roughness alone. Three grain sizes of a quarzitic sand were tested. The parameters determined from the PSD analysis were input directly into a Weierstrass-Mandelbrot function to reconstruct successfully a fractal surface.

摘要

土颗粒的表面粗糙度会影响土的力学行为,但目前对实际土颗粒粗糙度的表征在数量和质量上仍很有限。本文提出了一种新方法,该方法将摩擦学中常用的功率谱密度(PSD)应用于土颗粒表面的光学干涉测量。该方法适用于从土颗粒形状中分离出粗糙度进行表征,从而能够以波矢范围的形式确定粗糙度的尺度。表面粗糙度可以通过粗糙度值和分形维数来表征,这两个参数是根据表面的随机形成过程确定的。当与其他参数结合时,分形维数能为仅粗糙度值提供有关表面结构和粗糙度的额外信息。对三种粒度的石英砂进行了测试。通过PSD分析确定的参数被直接输入到魏尔斯特拉斯 - 曼德勃罗函数中,成功重建了分形表面。

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