| Description |
Elastic contact between two computer-generated isotropic rough surfaces is studied. First the surface topography parameters, including the asperity density, mean summit radius, and standard deviation of asperity heights of the equivalent rough surface, are determined using an 8-nearest neighbor summit identification scheme. Second, many cross-sections of the equivalent rough surface are traced and their individual topography parameters are determined from their corresponding spectral moments. The topography parameters are also obtained from the average spectral moments of all cross-sections. The asperity density is found to be the main difference between the summit identification scheme and the spectral moments method. The contact parameters, such as the number of contacting asperities, real area of contact, and contact load for any given separation between the equivalent rough surface and a rigid flat, are calculated by summing the contributions of all the contacting asperities using the summit identification model. These contact parameters are also obtained with the Greenwood-Williamson (GW) model using the topography parameters from each individual cross-section and from the average spectral moments of all cross-sections. Three different surfaces characterized by a different autocorrelation length, and three different sampling intervals were used to study how the method to determine topography parameters affects the resulting contact parameters. iv The contact parameters are found to vary significantly based on the method used to determine the topography parameters, and as a function of the autocorrelation length of the surface, as well as the sampling interval. The contact parameters evaluated with the summit identification model or the GW model based on topography parameters obtained from a summit identification scheme were most accurate as the actual three-dimensional (3D) rough surface is considered for the analysis instead of relying on limited data, e.g., a discrete number of cross-sections. Hence, using a summit identification model or the GW model based on topography parameters obtained from a summit identification scheme is perhaps the most reliable approach. |
