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Open AccessArticle

Multiscale Modeling Applied to the Hydrodynamic Lubrication of Rough Surfaces for Computation Time Reduction

by Noël Brunetière 1,*,† and Arthur Francisco 2,†
1
Institut Pprime, CNRS, Université de Poitiers, ISAE-ENSMA, 86962 Futuroscope Chasseneuil, France
2
Institut Pprime, CNRS, Université de Poitiers, ISAE-ENSMA, 16021 Angoulême, France
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Lubricants 2018, 6(3), 83; https://doi.org/10.3390/lubricants6030083
Received: 26 July 2018 / Revised: 30 August 2018 / Accepted: 10 September 2018 / Published: 15 September 2018
(This article belongs to the Special Issue Multiphysics and Multiscale Models of Tribology)
This paper presents a multiscale finite element method applied to the simulation of a lubricating film flowing between rough surfaces. The objective of this approach is to study flows between large rough surfaces needing very fine meshes while maintaining a reasonable computation time. For this purpose, the domain is split into a number of subdomains (bottom-scale meshes) connected by a coarse mesh (top-scale). The pressure distribution at the top-scale is used as boundary conditions for the bottom-scale problems. This pressure is adjusted to ensure global mass flow balance between the contiguous subdomains. This multiscale method allows for a significant reduction of the number of operations as well as a satisfactory accuracy of the results if the top-scale mesh is properly fitted to the roughness lateral scale. Furthermore the present method is well-suited to parallel computation, leading to much more significant computation time reduction. View Full-Text
Keywords: rough surfaces; hydrodynamic lubrication; multiscale method; finite element rough surfaces; hydrodynamic lubrication; multiscale method; finite element
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MDPI and ACS Style

Brunetière, N.; Francisco, A. Multiscale Modeling Applied to the Hydrodynamic Lubrication of Rough Surfaces for Computation Time Reduction. Lubricants 2018, 6, 83.

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