Surface topography is important as it influences contact load-carrying capacity and operational efficiency through generated friction, as well as wear. As a result, a plethora of machining processes and surface finishing techniques have been developed. These processes yield topographies, which are often non-Gaussian, with roughness parameters that alter hierarchically according to their interaction heights. They are also subject to change through processes of rapid initial running-in wear as well as any subsequent gradual wear and embedding. The stochastic nature of the topography makes for complexity of contact mechanics of rough surfaces, which was first addressed by the pioneering work of Greenwood and Williamson, which among other issues is commemorated by this contribution. It is shown that their seminal contribution, based on idealised Gaussian topography and mean representation of asperity geometry should be extended for practical applications where surfaces are often non-Gaussian, requiring the inclusion of surface-specific data which also evolve through process of wear. The paper highlights a process dealing with practical engineering surfaces from laboratory-based testing using a sliding tribometer to accelerated fired engine testing for high performance applications of cross-hatched honed cylinder liners. Such an approach has not hitherto been reported in literature.
Funding
The authors would like to thank the UK Engineering and
Physical Sciences Research Council (EPSRC) for the sponsorship
of this research under the Encyclopaedic Program
Grant (www.encyclopaedic.org).
History
School
Mechanical, Electrical and Manufacturing Engineering
Published in
Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology
Citation
LEIGHTON, M. ... et al., 2016. Boundary interactions of rough non-gaussian surfaces. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, 230 (11), pp. 1359-1370.
This work is made available according to the conditions of the Creative Commons Attribution 3.0 (CC BY 3.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by/3.0/
Acceptance date
2016-05-26
Publication date
2016
Notes
This is an Open Access article published by Sage and distributed under the terms of the Creative Commons Attribution 3.0 Licence (CC BY 3.0), https://creativecommons.org/licenses/by/3.0/