On the Effectiveness of Optimisation Algorithms for Hydrodynamic Lubrication Problems

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dc.contributor.authorKocman, Františekcs
dc.contributor.authorNovotný, Pavelcs
dc.coverage.issue5cs
dc.coverage.volume13cs
dc.date.accessioned2025-06-02T11:55:58Z
dc.date.available2025-06-02T11:55:58Z
dc.date.issued2025-05-08cs
dc.description.abstractIn many applications, it is necessary to optimise the performance of hydrodynamic (HD) bearings. Many studies have proposed different strategies, but there remains a lack of conclusive research on the suitability of various optimisation methods. This study evaluates the most commonly used algorithms, including the genetic (GA), particle swarm (PSWM), pattern search (PSCH) and surrogate (SURG) algorithms. The effectiveness of each algorithm in finding the global minimum is analysed, with attention to the parameter settings of each algorithm. The algorithms are assessed on HD journal and thrust bearings, using analytical and numerical solutions for friction moment, bearing load-carrying capacity and outlet lubricant flow rate under multiple operating conditions. The results indicate that the PSCH algorithm was the most efficient in all cases, excelling in both finding the global minimum and speed. While the PSWM algorithm also reliably found the global minimum, it exhibited lower speed in the defined problems. In contrast, genetic algorithms and the surrogate algorithm demonstrated significantly lower efficiency in the tested problems. Although the PSCH algorithm proved to be the most efficient, the PSWM algorithm is recommended as the best default choice due to its ease of use and minimal sensitivity to parameter settings.en
dc.formattextcs
dc.format.extent1-32cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationLubricants. 2025, vol. 13, issue 5, p. 1-32.en
dc.identifier.doi10.3390/lubricants13050207cs
dc.identifier.issn2075-4442cs
dc.identifier.orcid0009-0005-4091-8259cs
dc.identifier.orcid0000-0002-7513-2345cs
dc.identifier.other198031cs
dc.identifier.researcheridP-8188-2015cs
dc.identifier.scopus57032004000cs
dc.identifier.urihttps://hdl.handle.net/11012/251225
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofLubricantscs
dc.relation.urihttps://www.mdpi.com/2075-4442/13/5/207cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/2075-4442/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectjournal bearingen
dc.subjectthrust bearingen
dc.subjecthydrodynamic lubricationen
dc.subjectparticle swarm algorithmen
dc.subjectpattern searchen
dc.subjectsurrogate algorithmen
dc.subjectgenetic algorithmen
dc.titleOn the Effectiveness of Optimisation Algorithms for Hydrodynamic Lubrication Problemsen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.grantNumberinfo:eu-repo/grantAgreement/MSM/EH/EH23_020/0008528cs
sync.item.dbidVAV-198031en
sync.item.dbtypeVAVen
sync.item.insts2025.06.02 13:55:58en
sync.item.modts2025.06.02 13:32:51en
thesis.grantorVysoké učení technické v Brně. Fakulta strojního inženýrství. Ústav automobilního a dopravního inženýrstvícs
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