Quantitative characterization of surface topography using spectral analysis
By T. Jacobs, Till Junge, Lars Pastewka. 2016
433 citations recorded by the source corpus.
Roughness determines many functional properties of surfaces, such as adhesion, friction, and (thermal and electrical) contact conductance. Recent analytical models and simulations enable quantitative prediction of these properties from knowledge of the power spectral density (PSD) of the surface topography. The utility of the PSD is that it contains statistical information that is unbiased by the particular scan size and pixel resolution chosen by the researcher. In this article, we first review the mathematical definition of the PSD, including the one- and two-dimensional cases, and common variations of each. We then discuss strategies for reconstructing an accurate PSD of a surface using topography measurements at different size scales. Finally, we discuss detecting and mitigating artifacts at the smallest scales, and computing upper/lower bounds on functional properties obtained from models. We accompany our discussion with virtual measurements on computer-generated surfaces. This discussion summarizes how to analyze topography measurements to reconstruct a reliable PSD. Analytical models demonstrate the potential for tuning functional properties by rationally tailoring surface topography—however, this potential can only be achieved through the accurate, quantitative reconstruction of the PSDs of real-world surfaces.
Subfields: Computational Mechanics, Mechanical Engineering, Mechanics of Materials
View Paper: https://www.semanticscholar.org/paper/307c40124e86e1c3cdd9ee9fcef068931ed70cae
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In Computational Mechanics
In Mechanical Engineering
In Mechanics of Materials
Citations in the corpus
- A Review of Elastic–Plastic Contact Mechanics (2017, background): “Notably, natural surfaces may be rough but still not adhere strictly to a fractal description [216–219] or may be difficult to effectively characterize experimentally due to instrument limitations [220].”