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An Enhanced Stochastic Two-Scale Model for Metal-to-Metal Seals
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0002-3556-328x
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Machine Elements.ORCID iD: 0000-0001-7029-1112
2018 (English)In: Lubricants, ISSN 2075-4442, Vol. 6, no 4, article id 87Article in journal (Refereed) Published
Abstract [en]

Leakage in static metal-to-metal seals is predominantly determined by the topography of the contacting surfaces. The topography consists of features that span the entire range from its carefully engineered geometry down to micro-sized surface asperities. The mesh density necessary to fully resolve all the features, in this large span of length scales, generates too many degrees of freedom for a direct numerical approach to be applicable. Some kind of sophistication, either incorporated in the mathematical model or in the numerical solution procedure or even a combination of both is therefore required. For instance, in a two-scale model, the geometrical features can be addressed in the global-scale model, while the features belonging to length scales smaller than a given cut-off value are addressed in the local-scale model. However, the classical two-scale approaches do not explicitly address the stochastic nature of the surfaces, and this has turned out to be a requirement in order to obtain quantitative predictions of leakage in metal-to-metal seals. In this work, we present a continued development of an already existing two-scale model, which incorporates a stochastic element. The novelty lies in the way we characterise the permeability at the local scale and how this is used to build a more efficient and useful approach

Place, publisher, year, edition, pages
MDPI, 2018. Vol. 6, no 4, article id 87
Keywords [en]
leakage, contact mechanics, reynolds equation, two-scale modelling, stochastic, metal-to-metal seal
National Category
Tribology (Interacting Surfaces including Friction, Lubrication and Wear)
Research subject
Machine Elements
Identifiers
URN: urn:nbn:se:ltu:diva-71294DOI: 10.3390/lubricants6040087ISI: 000455618500003Scopus ID: 2-s2.0-85056378906OAI: oai:DiVA.org:ltu-71294DiVA, id: diva2:1257743
Note

Validerad;2018;Nivå 2;2018-10-22 (svasva)

Available from: 2018-10-22 Created: 2018-10-22 Last updated: 2019-02-01Bibliographically approved

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Ràfols, Francesc PérezAlmqvist, Andreas

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