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Topological data analysis for friction modeling

Published: 13 September 2021

Abstract: Dry sliding friction is a complex but ubiquitous phenomenon. Experimental studies of friction produce large amounts of data, while most models are phenomenological rather than deduced from fundamental principles. Proper identification of relevant degrees of freedom is crucial for the development of adequate frictional models, such as the state-and-rate models. Topological data analysis is a mathematical method for the dimensionality reduction for datasets characterizing surface roughness, contact of rough surfaces and frictional sliding. We study tribological systems including the surface roughness and multiasperity contacts using 3×3, 4×4, and 5×5 pixel patches. Depending on whether the surface is isotropic or anisotropic with particular lay directions, the data tends to concentrate at certain "primary" and "secondary" circles yielding different values of the Betti numbers. Scale dependency of corresponding structures is analyzed with persistence diagrams. Moreover, statistics of stick-slip zones can provide insights on relevant internal degrees of friction.
Keywords: models / surface roughness / structures / Topological / frictional sliding / friction modeling / data analysis

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