Topography Analysis of Random Anisotropic Gaussian Rough Surfaces

Abstract

Engineered surfaces (ground and similarly structured rough surfaces) show anisotropic characteristics and their topography parameters are direction dependent. Statistical characterization of these surfaces is still complex because of directional nature of surfaces. In this technical brief, an attempt is made to simulate anisotropic surfaces through use of topography parameters (three-dimensional (3D) surface parameters). First, 3D anisotropic random Gaussian rough surface is generated numerically with fast Fourier transform (FFT). Numerically generated anisotropic random Gaussian rough surface shows statistical properties (texture direction, texture ratio) similar to ground and similarly directional anisotropic rough surfaces. For numerically generated anisotropic Gaussian rough surface, important 3D roughness parameters are determined. Sayles and Thomas' (1976, “Thermal Conductance of Rough Elastic Contact,” Appl. Energy, 2(4), pp. 249–267.) theoretical model for directional anisotropic rough surface is adopted here for calculating the summit parameters, i.e., equivalent bandwidth parameter, mean summit curvature, skewness of summit height, standard deviation of summit height, and equivalent spectral moments. This work demonstrates the variation of spectral moments in both across and parallel to the lay directions with pattern ratio (γ=βx/βy). Correlation length (βx) is fixed 10μm and correlation length (βy) is varied from 100 to 10 μm. Variation of summit parameters with pattern ratio is also discussed in detail. Results shows that mean summit curvature and skewness of summit heights increase with increase in pattern ratio, whereas standard deviation of summit heights and equivalent bandwidth parameter (αe) decreases with pattern ratio. A significant difference is found in “Abbott-Firestone” parameters when calculated in both perpendicular and parallel to lay directions. Effect of these parameters on wear process is discussed in brief.

The correlation between friction coefficient and areal topography parameters for AISI 304 steel sliding against AISI 52100 steel

“…3.2 that S al is used to get the spatial information of the rough surface. Any change in S al value leads to a change in topography parameters [34]. It has been shown in Ref.…”

Wear Behavior of CuSn Coated Piston Ring Sliding against Nodular Cast Iron Cylinder Liner under Heavy-Duty Conditions

“…On the other hand, the mean summit curvature of worn cylinder liner matched with Cr coated ring (0.88 µm) was greater than that of the cylinder liner matched with CuSn-Cr coated ring (0.71 µm). This indicates that the surface micro-asperities of the cylinder liner matched with CuSn-Cr coated ring were flatter than that of the cylinder liner matched with Cr coated ring [43,44]. A larger contact area on the CuSn-Cr coated ring appeared on the PRCL interface under the same load condition.…”

Influence of the 6061 Aluminium Alloy Thermo-Viscoplastic Behaviour on the Load-Area Relation of a Contact

“…Certain manufacturing processes, such as laser texturing, may result in a more deterministic pattern, whereas others, such as electrical discharge texturing, result in a random topography [36][37][38]. In this work, an artificially created random isotropic surface, which can be generated following, e.g., [39,40], was used as the reference topography to represent a rigid rough tool. While it is true that surfaces are rough at different scales, the study presented here dealt with roughness in the micrometer range and, thus, in the "microtribology regime" as per [41].…”