Fractal simulation of surface topography and prediction of its lubrication characteristics

A machined surface has observable fractal characteristics, with infinite local and overall self-similar consistency. Therefore, the fractal theory is considered to provide a better description of the morphological characteristics of rough surfaces, which accurately reflects the randomness and multi-scale characteristics of rough surfaces and it is not comparable with the surface characteristics obtained based on statistical parameters limited by sampling length and device resolution. In this study, the Weierstrass-Mandelbrot (W-M) function was applied to construct a fractal reconstruction surface, and the mixed elastohydrodynamic lubrication model was used to investigate the lubrication characteristics of real and reconstructed surfaces under the same fractal parameters. The effects of the fractal parameters on the fractal surface lubrication characteristics were further analyzed. The results demonstrate that the lateral roughness fractal surface provides greater resistance to the entrained flow of lubricant, which leads to a larger average film thickness, than the longitudinal roughness and isotropic fractal surface. With the increase in fractal dimension, the surface roughness peak density increases, which reduces the surface film thickness by 47%, and the friction coefficient increases by 46%. The lubrication parameter fluctuates slightly with the change in the number of overlapping ridges M of the fractal surface. Generally, M has little effect on the surface lubrication characteristics.

Automated summary

This study investigates the lubrication characteristics of fractal surfaces, finding that lateral roughness fractal surfaces offer greater resistance to lubricant flow and that as fractal dimension increases, surface film thickness decreases while friction coefficient increases.