Quantitative evaluation of surface roughness for granular materials using Gaussian filter method

This contribution proposes a methodology to measure the surface roughness of granular materials using the Gaussian filter. Artificially generated rough surfaces with known root mean square roughness (S-q) combined with the spherical shape are analysed to determine the optimum cut-off wavelength (sigma*) adopted in the Gaussian filter. Considering a combined dependency of Sq and particle size (D) on sigma*, an empirical regression equation is derived to describe their relationship. The regression equation is further found to be applicable for granular materials including glass beads and natural sand grains with irregular base shapes. To implement the proposed Gaussian filter method into practical use, a detailed guideline is given to determine Sq including the selection of representative measurement area. Finally, quantitative comparisons of Sq are made to distinguish the difference between the proposed method and motif method. (C) 2021 Elsevier B.V. All rights reserved.