Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/96029
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dc.contributorDepartment of Mechanical Engineeringen_US
dc.creatorXiao, Len_US
dc.creatorLiu, Yen_US
dc.creatorChen, Sen_US
dc.creatorFu, Ben_US
dc.date.accessioned2022-11-01T03:39:08Z-
dc.date.available2022-11-01T03:39:08Z-
dc.identifier.issn2046-0546en_US
dc.identifier.urihttp://hdl.handle.net/10397/96029-
dc.language.isoenen_US
dc.publisherW I T Pressen_US
dc.rights© 2018 WIT Pressen_US
dc.rightsThe following publication Xiao, L., Liu, Y., Chen, S., & Fu, B. (2017). Dissipative particle dynamics simulation of multiple deformable red blood cells in a vessel. International Journal of Computational Methods and Experimental Measurements, 6(2), 303-313 is available at https://doi.org/10.2495/CMEM-V6-N2-303-313en_US
dc.subjectBlood flowen_US
dc.subjectDissipative particle dynamicsen_US
dc.subjectRed blood cellen_US
dc.titleDissipative particle dynamics simulation of multiple deformable red blood cells in a vesselen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage303en_US
dc.identifier.epage313en_US
dc.identifier.volume6en_US
dc.identifier.issue2en_US
dc.identifier.doi10.2495/CMEM-V6-N2-303-313en_US
dcterms.abstractThe blood flow properties in microvessels were examined through simulating the dynamics of deformable red blood cells suspended in plasma using dissipative particle dynamics. The cell membrane was considered as a spring-based triangulated network and the intercellular interaction was modeled by a Morse potential function. The cell distribution in the cross section indicated that red blood cells migrate away from the wall to the tube center, resulting in a cell-free layer near the wall and blunt velocity profile. The findings also showed that the bluntness of velocity profile increases with increasing hematocrit. In addition, the Fahraeus and Fahraeus-Lindqvist effects were captured through investigating the effects of tube diameter and hematocrit on the discharge hematocrit and relative apparent viscosity. It appears that this flow model can capture the blood flow behaviors under physiological and pathological conditions.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationInternational journal of computational methods and experimental measurements, 1 Nov. 2017, v. 6, no. 2, p. 303-313en_US
dcterms.isPartOfInternational journal of computational methods and experimental measurementsen_US
dcterms.issued2017-11-01-
dc.identifier.scopus2-s2.0-85064192110-
dc.identifier.eissn2046-0554en_US
dc.description.validate202211 bckwen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberME-0738-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextPolyU; NSFC; NIHen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS43362651-
dc.description.oaCategoryVoR alloweden_US
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