Computational Fluid Mechanics Model for Numerical Investigation of Frictional Tribo-pair during Mixed LubricationShow others and affiliations
2022 (English)In: Proceedings of 2022 19th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2022, Institute of Electrical and Electronics Engineers Inc. , 2022, p. 815-820Conference paper, Published paper (Refereed)
Abstract [en]
All the machines are constructed through mechanical links and pairs. One of the crucial pairs is the sliding pair; due to their nature and general use, they are often subjected to a higher degree of dynamics and external forces leading to high frictional force. To reduce wear from friction formerly thick film of commercial oil is used. However, viscosity-based higher thickness yields higher energy losses, and nano-lubricants are popular in reducing friction while keeping film thickness and improving wear resistance. This paper develops a numerical model for sliding pairs that predicts the load carried by components under different lubrication regimes. The aim is to simulate hydrodynamic and mixed lubrication regimes for different loading conditions. A detailed multiphysics model of tribo-pair was modeled, including lubricant rheology, surface topology, oil film squeeze, and film temperature through the moving mesh. The fluid domain has been meshed with Arbitrary Lagrangian and Eulerian techniques. Energy loss due to viscous friction and boundary friction were determined by solving Naiver- Stokes equations in the moving mesh deformable geometry domain. The numerical model was compared with the available literature, and the results are presented. This numerical simulation remained valid and provides the fundamental understanding of oil film thickness and load-carrying capacity of sliding tribo-pair in the presence of nano-lubricants. The developed model is a useful methodology for studying lubricant oil enriched with nanoparticles.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2022. p. 815-820
Series
International Bhurban Conference on Applied Sciences and Technology, ISSN 2151-1403, E-ISSN 2151-1411
Keywords [en]
friction, mixed elastohydrodynamic lubrication, multiphysics, nanofluids, tribology
National Category
Other Mechanical Engineering
Research subject
Machine Learning; Machine Elements
Identifiers
URN: urn:nbn:se:ltu:diva-95536DOI: 10.1109/IBCAST54850.2022.9990409Scopus ID: 2-s2.0-85146490455ISBN: 978-1-6654-6051-4 (electronic)OAI: oai:DiVA.org:ltu-95536DiVA, id: diva2:1734972
Conference
19th International Bhurban Conference on Applied Sciences and Technology (IBCAST 2022), August 16-20, 2022, Islamabad, Pakistan
Funder
The Kempe FoundationsSwedish Research Council, 2019-042932023-02-072023-02-072025-02-14Bibliographically approved