Interdependence of Amplitude Roughness Parameters on Rough Gaussian Surfaces

According to international standards, the topography and the quality of machined surfaces can be characterized simultaneously by more than 70 roughness parameters. Despite the increased accuracy of topography measurements by modern instruments, the gained information about the 3D surface is still no...

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Bibliographic Details
Published inTribology letters Vol. 68; no. 1
Main Authors Fecske, Szeréna-Krisztina, Gkagkas, Konstantinos, Gachot, Carsten, Vernes, András
Format Journal Article
LanguageEnglish
Published New York Springer US 01.03.2020
Springer Nature B.V
Subjects
Amplitudes
Chemistry and Materials Science
Correlation analysis
Corrosion and Coatings
Differential equations
Gaussian process
Materials Science
Nanotechnology
Normal distribution
Numerical analysis
Original Paper
Parameters
Physical Chemistry
Random processes
Roughness
Surfaces and Interfaces
Theoretical and Applied Mechanics
Thin Films
Topography
Tribology
Computer-generated surfaces
Gaussian height distribution
Surface roughness parameters
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Summary:According to international standards, the topography and the quality of machined surfaces can be characterized simultaneously by more than 70 roughness parameters. Despite the increased accuracy of topography measurements by modern instruments, the gained information about the 3D surface is still not well understood. The fact that machined surfaces are in general of Gaussian height distribution motivated the authors to study the interdependence of the standardized amplitude roughness parameters of computer-generated random rough (Gaussian) surfaces. In this contribution, these rough surfaces are created by solving numerically a Langevin-type stochastic differential equation for a defined random process, namely a Gaussian one. This numerical scheme provides rough surfaces of pre-defined statistical features, e.g., given standard deviation and correlation length. The numerical analysis of 17 standardized amplitude roughness parameters collected from 90000 computer-generated rough surfaces revealed so far undetected interdependencies among some of these parameters, namely the results show a strong linear relation between 12 amplitude roughness parameters. Graphical Abstract
ISSN:1023-8883
1573-2711
DOI:10.1007/s11249-020-1282-4