A machine learning-driven approach to predicting thermo-elasto-hydrodynamic lubrication in journal bearings-Reference-Cited by-同舟云学术

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A machine learning-driven approach to predicting thermo-elasto-hydrodynamic lubrication in journal bearings

Published:2024-08 Issue: Volume:196 Page:109670
ISSN:0301-679X
Container-title:Tribology International
language:en
Short-container-title:Tribology International

Author:

Cartwright Samuel^ORCID,Rothwell Benjamin C.^ORCID,Figueredo Grazziela^ORCID,Medina Humberto^ORCID,Eastwick Carol^ORCID,Layton James,Ambrose Stephen^ORCID

Funder

Rolls-Royce

EPSRC

Publisher

Elsevier BV

Reference43 articles.

1. History of tribology;Dowson,1998

2. A new thermal elasto-hydrodynamic lubrication solver implementation in OpenFOAM;Layton;Lubricants,2023

3. A numerical solution to the elasto-hydrodynamic problem;Dowson;J Mech Eng Sci,1959

4. Contributions of molecular dynamics simulations to elastohydrodynamic lubrication;Ewen;Tribol Lett,2021

5. The Navier–Stokes approach for thermal EHL line contact solutions;Almqvist;Tribol Int,2002

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