Wetting of real engineering surfaces occurs in many industrial applications (liquid coating, lubrication, printing, painting…). Forced and natural wetting can be beneficial in many cases, providing lubrication and therefore reducing friction and wear. However the wettability of surfaces can be strongly affected by surface roughness. This influence can be very significant for static and dynamic wetting [1]. In this paper authors experimentally investigate the roughness influence on contact angle measurements and propose a simple model combining Wenzel and Cassie-Baxter theories with simple 2D roughness profile analysis. The modelling approach is applied to real homogeneous anisotropic surfaces, manufactured on a wide range of engineering materials including aluminium alloy, iron alloy, copper, ceramic, plastic (poly-methylmethacrylate: PMMA) and titanium alloy.
Influence of initial surface roughness on friction and wear processes under fretting conditions was investigated experimentally. Rough surfaces (Ra=0.15-2.52 µm) were prepared on two materials: carbon alloy (AISI 1034) and titanium alloy (Ti-6Al-4V). Strong influence of initial surface roughness on friction and wear processes is reported for both tested materials. Lower coefficient of friction and increase in wear rate was observed for rough surfaces. Wear activation energy is increasing for smoother surfaces. Lower initial roughness of surface subjected to gross slip fretting can delay activation of wear process and reduce wear rate, however it can slightly increase the coefficient of friction. Graphical Abstract
This is the pre-peer reviewed version of the following article: Deltombe R., Kubiak K.J., Bigerelle M, How to select the most relevant 3D roughness parameters of a surface (2011) Summary:In order to conduct a comprehensive roughness analysis, around sixty 3D roughness parameters are created to describe most of the surface morphology with regard to specific functions, properties or applications. In this paper, a multiscale surface topography decomposition method is proposed with application to stainless steel (AISI 304), which is processed by rolling at different fabrication stages and by electrical discharge tool machining. Fifty-six 3Droughness parameters defined in ISO, EUR, and ASME standards are calculated for the measured surfaces. Then, expert software "MesRug" is employed to perform statistical analysis on acquired data in order to find the most relevant parameters characterizing the effect of both processes (rolling and machining), and to determine the most appropriate scale of analysis. For the rolling process: The parameter Vmc (the Core Material Volume-defined as volume of material comprising the texture between heights corresponding to the material ratio values of p = 10% and q = 80%) computed at the scale of 3 mm is the most relevant parameter to characterize the cold rolling process. For the EDM Process, the best roughness parameter is SPD that represents the number of peaks per unit area after segmentation of a surface into motifs computed at the scale of 8 µm.
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