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.
Micropitting and related surface fatigue mechanisms are influenced by the running-in behavior of contacting bodies subjected to rolling/sliding motion. The running-in of contacting surfaces results in significant change in many surface topography parameters, such as mean summit radius, the radius of individual summits, and standard deviation of summit height, which leads to contact pressure, real contact area, and plasticity index. In this work, running-in wear is simulated by developing a 3D numerical wear model. The simulation is performed on 3D rough surfaces having different skewness and kurtosis. It is shown that mean summit radius and radius of the individual summit are strongly influenced and significantly vary during wear process. It is found that a change in contact pressure and plasticity index can be related to a single topography parameter. The objective of this work is to show the topography parameters variation during running-in wear, which is hitherto not discussed elsewhere in detail. The variation with the number of cycles for roughness parameters determined from wear experiment and simulation are compared and a good match is found.
Surface topography parameters significantly control physical processes which have asperity‐to‐asperity contacts in tribological components undergoing friction and wear. In this study, the effect of correlation length, maximum contact load, and surface roughness on friction coefficient and load distribution is studied. The load‐sharing concept is employed to determine friction coefficient and load distribution in the mixed‐lubrication regime. Results clearly demonstrate the effect of correlation length on friction coefficient and load distribution. It is found that the lower value of the coefficient of friction may be achieved even at low velocity for the smooth surface as compared with rough surfaces having higher surface roughness. For a particular value of velocity, the coefficient of friction decreases with an increase in maximum contact load. This work will help in predicting the coefficient of friction in the mixed‐lubrication regime for the engineering surfaces produced by processes like grinding, which is the result of an abrasive action.
Rolling contact fatigue (RCF) is one of the major problems observed in gear mechanisms, which leads to high friction, ultimately resulting in high energy consumption. This paper demonstrates the evolution of surface topography during running-in and subsequent RCF tests under boundary or mixed-elastohydrodynamic lubrication regimes. The case-hardened disks of equal surface finish and hardness are used in the experiments, and the evolution of surface topography is investigated using a white light interferometer. Surface topography at different load stages is measured at three distinct points, on the disks and average roughness and topography parameters are reported. Semi-quantitative techniques are used to determine the asperity-level parameters at different load stages. From the running-in experiment, it is found that running-in is a fast process where substantial change in surface topography occurs due to plastic deformation of most prominent asperity. From the RCF test, it is concluded that within range of the fatigue cycles, the root-mean-square (RMS) roughness (Sq) is negatively correlated with the summit radius (R) and the autocorrelation length (Sal) and positively correlated with the summit density (Sds) and the RMS slope (Sdq). Scanning electron microscope (SEM) analysis reveals the disappearance of grinding ridges, the formation of micropits at a very small scale, and pit growth in the sliding direction.
Surfaces generated by various finishing techniques are inherently rough and manifest different characteristics at multiple scales. Due to the multiscale nature of rough surfaces, roughness parameters are different when calculated at different scales. In this work, self-affine surfaces are numerically generated and characterized using fractal, spectral, and statistical methodologies. Two new closed-form expressions are proposed to determine the mean summit radius and standard deviation of summit height. The atomic force microscope (AFM) is utilized to measure the polished surfaces. It is found that the fractal dimension of smooth surface is in the range of 2.15 ± 0.15. The effect of roll-off vector on roughness parameters is also discussed. Wear experiments are performed on pin-on-disc tribometer to see the evolution of fractal signature (H) with sliding time. It is shown numerically and verified experimentally that root mean square roughness decreases with increase in the fractal signature. This work is a part of understanding the fractal nature of surfaces, which can be further utilized to see the evolution of surface topography during the wear and rolling contact fatigue process. Furthermore, this work will be useful to analyze the surfaces produced by machining process like grinding, friction between the elastomer and self-affine fractal surfaces, in which wave vectors and topography parameters play significant role in controlling of friction.
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