A Simulation Method for Non-Gaussian Rough Surfaces Using Fast Fourier Transform and Translation Process Theory

Abstract

The simulated rough surface with desired parameters is widely used as an input for the numerical simulation of tribological behavior such as the asperity contact, lubrication, and wear. In this study, a simulation method for generating non-Gaussian rough surfaces with desired autocorrelation function (ACF) and spatial statistical parameters, including skewness (Ssk) and kurtosis (Sku), was developed by combining the fast Fourier transform (FFT), translation process theory, and Johnson translator system. The proposed method was verified by several numerical examples and proved to be faster and more accurate than the previous methods used for the simulation of non-Gaussian rough surfaces. It is convenient to simulate the non-Gaussian rough surfaces with various types of ACFs and large autocorrelation lengths. The significance of this study is to provide an efficient and accurate method of non-Gaussian rough surfaces generation to numerically simulate the tribological behavior with desired rough surface parameters.

Towards optimum additive performance: A numerical study to understand the influence of roughness parameters on the zinc dialkyldithiophosphates tribofilm growth

“…In the current work, the method previously proposed by the authors is used to generate rough surfaces. 52 The roughness parameters mentioned above only describe the overall features of rough surfaces which may not provide adequate information to comprehensively understand the influence of rough surfaces on the tribofilm growth. This is crucial as the chemical reaction is believed to be occurring at the asperity contact spots.…”

“…Several roughness parameters 51 are used to define this distribution of roughness, for example, the root‐mean‐square roughness ( S q ), skewness ( S sk ), kurtosis ( S ku ) and autocorrelation length ( S al ). In the current work, the method previously proposed by the authors is used to generate rough surfaces 52 …”

“…Therefore, the current study set out to highlight the key roughness parameters affecting the growth of ZDDP tribofilms. Rough surfaces with more comprehensive characteristic parameters were generated numerically 52 and then selected roughness parameters were calculated based on the ISO 25178‐2:2012 51 . These rough surfaces were given as input to the tribofilm growth modelling framework.…”

A Novel Simulation Method of Micro-Topography for Grinding Surface

“…Reizer simulated the surface topography by 3D Gaussian surface [ 9 ]. Wang combined Fourier transform with Johnson conversion system [ 10 ] to simulate non-Gaussian surfaces with specific roughness parameters [ 11 ]. The simulation surface obtained by NSM was based on the roughness parameters, which can meet the statistical characteristics [ 1 ].…”

A High Precision Modeling Technology of Material Surface Microtopography and Its Influence on Interface Mechanical Properties

“…The simulation process mainly uses a stochastic process theory and a time series theory. Wang et al [10] compared and analyzed the advantages and disadvantages of different rough surface simulation methods, and realized the effective simulation of three-dimensional rough surface by effective conversion between autocorrelation function and non-linear equation group. Some scholars have made contributions in topography data processing and surface quality evaluation.…”