Generation of Composite Surfaces With Bimodal Distribution and Contact Analysis for Optimum Tribological Performance

Abstract

Most contact analyses assume that the surface height distributions follow a single modal distribution. However, there are many surfaces with multi-modal roughness distributions, e.g., magnetic particulate tape, super alloys with precipitates, and hydrophobic leaves. In this study, an algorithm is developed to generate bimodal surfaces by superimposing particles with radii following a Gaussian distribution on a Gaussian rough surface. Two different cases are presented to produce composite surfaces with particles; the first case is particles sitting on a surface and the other case is particles sitting on the mean plane of a surface. Statistical analysis is carried out for the generated bimodal surfaces to study the effect of the bimodal roughness distributions on the surface’s probability density function shapes. Contact analysis is also conducted to identify optimum bimodal roughness distributions for low friction, stiction, and wear. It is assumed that particles and matrix have uniform elastic properties as it is a reasonable assumption in some applications such as magnetic tapes. Variation of fractional contact area, maximum contact pressure, and relative meniscus force as functions of relative mean radius and relative standard deviation of particles are studied for different values of particle densities. It is found that bimodal surfaces with lower particle density are beneficial to low friction and stiction, whereas those with higher particle density are beneficial to low wear. Relative mean radii of particles of 2–3 in bimodal surfaces with particles sitting on surface and 3–5 in bimodal surfaces with particles sitting on the mean plane of surface are desirable for low friction, stiction, and wear.