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Surface roughness genomics in contact mechanics : a new method enabling roughness design towards surface prototyping

Cinat, Paolo (2018) Surface roughness genomics in contact mechanics : a new method enabling roughness design towards surface prototyping. Advisor: Paggi, Prof. Marco. pp. 172. [IMT PhD Thesis]

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In actual age of Industry 4.0, the miniaturization of mechanical components is becoming extremely sophisticated, thanks to enhancing techniques such as additive manufacturing technologies. This requires an efficient description of multi-scale roughness to properly characterize the interface contact problem. In this dissertation, a new approach called surface roughness genomics is proposed to uniquely characterize surfaces at different length scales, from the topological point of view. Similar to biological systems, where the biological information is encoded in DNA base pairs, surface roughness is decomposed in elementary waves, whose unique ensemble is the surface genome. The identification process of the real surfaces genome, the sequencing procedure, is based on the solution of a constrained convex optimization problem. A rough profile (chromosome), collecting the features of roughness at a fixed length-scale is isolated from the surface genome So, a rough profile is reconstructed by summing up subsequent chromosomes. The top-down and bottom-up approaches are pursued to reconstruct a rough profile, to quantify the role of specific multi-scale features in the frictional normal contact problem. New algorithms are then proposed to generate roughness morphology achieving a target mechanical response, enabling surface prototyping towards morphology real time control.Beside the mechanical contact problem, the fluid sealing between contacting bodiesis herein investigated by proposing a simple algorithm and applying it to a set of fractal rough surfaces. This algorithm evaluates the free networks involved in leakage process, considering different normal contact indentations at various surface resolutions.

Item Type: IMT PhD Thesis
Subjects: T Technology > TJ Mechanical engineering and machinery
PhD Course: Computational mechanics
Identification Number: 10.6092/imtlucca/e-theses/252
NBN Number: urn:nbn:it:imtlucca-27278
Date Deposited: 11 Sep 2018 14:11
URI: http://e-theses.imtlucca.it/id/eprint/252

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