Classified substrate roughness parameters of blast-cleaned steel substrates and their effects on fractal dimensions

Abstract

Morphology and texture of substrate surfaces are crucial parameters for the establishment of reliable protective layers as they determine the performance of interlocking polymer-metal interfaces. Numerous parameters are known to characterize the morphology of metal substrates. In this study, mild steel samples were prepared using dry blast-cleaning with abrasive materials (metallic, minerals) of different particle shapes and particle sizes to investigate the effects of surface profile parameters on the fractal dimension. For this purpose, 2D profiles were taken from a total of 12 surface configurations with a digital contact profilometer. Fractal dimensions were estimated based on these recorded profiles using the box-counting method. For comparison, a total of 37 conventional roughness parameters were determined from the same set of measurements. Design of Experiment (DoE) was applied to evaluate significant interactions between roughness parameters and the corresponding fractal dimension. A new classification scheme for profile parameters, considering six profile sections, is suggested. A linear correlation model was utilized to rank the importance of roughness parameters, and of the surface profile sections, on the resulting fractal dimensions. Evidence is provided on which roughness parameter can be used to best explain fractal dimensions.