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Autores principales: Rodriguez, N., Gontard, L., Ma, C., Xu, R., Persson, B. N. J.
Formato: Preprint
Publicado: 2024
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Acceso en línea:https://arxiv.org/abs/2408.05447
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author Rodriguez, N.
Gontard, L.
Ma, C.
Xu, R.
Persson, B. N. J.
author_facet Rodriguez, N.
Gontard, L.
Ma, C.
Xu, R.
Persson, B. N. J.
contents Analytical contact mechanics theories depend on surface roughness through the surface roughness power spectrum. In the present study, we evaluated the usability of various experimental methods for studying surface roughness. Our findings indicated that height data obtained from optical methods often lack accuracy and should not be utilized for calculating surface roughness power spectra. Conversely, engineering stylus instruments and atomic force microscopy (AFM) typically yield reliable results that are consistent across the overlapping roughness length scale region. For surfaces with isotropic roughness, the two-dimensional (2D) power spectrum can be derived from the one-dimensional (1D) power spectrum using several approaches, which we explored in this paper.
format Preprint
id arxiv_https___arxiv_org_abs_2408_05447
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle On how to determine surface roughness power spectra
Rodriguez, N.
Gontard, L.
Ma, C.
Xu, R.
Persson, B. N. J.
Materials Science
Soft Condensed Matter
Data Analysis, Statistics and Probability
Optics
Analytical contact mechanics theories depend on surface roughness through the surface roughness power spectrum. In the present study, we evaluated the usability of various experimental methods for studying surface roughness. Our findings indicated that height data obtained from optical methods often lack accuracy and should not be utilized for calculating surface roughness power spectra. Conversely, engineering stylus instruments and atomic force microscopy (AFM) typically yield reliable results that are consistent across the overlapping roughness length scale region. For surfaces with isotropic roughness, the two-dimensional (2D) power spectrum can be derived from the one-dimensional (1D) power spectrum using several approaches, which we explored in this paper.
title On how to determine surface roughness power spectra
topic Materials Science
Soft Condensed Matter
Data Analysis, Statistics and Probability
Optics
url https://arxiv.org/abs/2408.05447