YorkSpace has migrated to a new version of its software. Access our Help Resources to learn how to use the refreshed site. Contact diginit@yorku.ca if you have any questions about the migration.
 

The Evaluation Of Modelling Techniques For Lubricant Cavitaion In The Application Of Squeeze Film Dampers

dc.contributor.authorFan, Tieshu
dc.contributor.authorBehdinan, Kamran
dc.date.accessioned2018-11-09T15:25:03Z
dc.date.available2018-11-09T15:25:03Z
dc.date.issuedMay-18
dc.description.abstractSqueeze film damper (SFD) is widely adopted in turbo-engines to suppress the rotor vibration. However, the prediction of SFD performance is complicated due to the inevitable occurrence of lubricant cavitation. This paper shows the application of three different cavitation algorithms for SFD with sealed conditions. In particular, the linear complementarity problem (LCP) method, which is advanced from a previous research study, is applied to compare results from the well-known methods, i.e. the π-film model and the Elrod cavitation method, for SFD executing circular centered orbits with fully degassed lubricant in the absence of oil feeding. Moreover, numerical models are developed incorporating the mentioned algorithms to predict the hydrodynamic pressure distribution over the cavitated fluid film. Results show that the conventional π-film model over-estimates the cavitation region but under-estimates the reaction force.en_US
dc.identifierCSME033
dc.identifier.isbn978-1-77355-023-7
dc.identifier.urihttp://hdl.handle.net/10315/35384
dc.identifier.urihttp://dx.doi.org/10.25071/10315/35384
dc.language.isoenen_US
dc.publisherCSME-SCGMen_US
dc.rightsThe copyright for the paper content remains with the author.
dc.subjectEngineering Analysis & Designen_US
dc.subjectSFDen_US
dc.subjectCavitationen_US
dc.subjectLCPen_US
dc.subjectElrod Algorithmen_US
dc.subjectπ-film modelen_US
dc.titleThe Evaluation Of Modelling Techniques For Lubricant Cavitaion In The Application Of Squeeze Film Dampersen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
CSME2018_paper_33.pdf
Size:
191.72 KB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.83 KB
Format:
Item-specific license agreed upon to submission
Description: