Turbulence model performance for ventilation components pressure losses

dc.contributor.authorTawackolian, Karsten
dc.contributor.authorKriegel, Martin
dc.date.accessioned2021-12-06T07:34:27Z
dc.date.available2021-12-06T07:34:27Z
dc.date.issued2021-06-25
dc.description.abstractThis study looks to find a suitable turbulence model for calculating pressure losses of ventilation components. In building ventilation, the most relevant Reynolds number range is between 3×10 4 and 6×10 5 , depending on the duct dimensions and airflow rates. Pressure loss coefficients can increase considerably for some components at Reynolds numbers below 2×10 5 . An initial survey of popular turbulence models was conducted for a selected test case of a bend with such a strong Reynolds number dependence. Most of the turbulence models failed in reproducing this dependence and predicted curve progressions that were too flat and only applicable for higher Reynolds numbers. Viscous effects near walls played an important role in the present simulations. In turbulence modelling, near-wall damping functions are used to account for this influence. A model that implements near-wall modelling is the lag elliptic blending k-ε model. This model gave reasonable predictions for pressure loss coefficients at lower Reynolds numbers. Another example is the low Reynolds number k-ε turbulence model of Wilcox (LRN). The modification uses damping functions and was initially developed for simulating profiles such as aircraft wings. It has not been widely used for internal flows such as air duct flows. Based on selected reference cases, the three closure coefficients of the LRN model were adapted in this work to simulate ventilation components. Improved predictions were obtained with new coefficients (LRNM model). This underlined that low Reynolds number effects are relevant in ventilation ductworks and give first insights for suitable turbulence models for this application. Both the lag elliptic blending model and the modified LRNM model predicted the pressure losses relatively well for the test case where the other tested models failed.en
dc.description.sponsorshipBMWi, 03ET1606A, EnOB: LuftKonVerTeR - Berechnungs- und Bewertungsgrundlagen für den dynamischen Betrieb von Lüftungssystemen, bestehend aus RLT-Anlage (Konditionierung) und Kanalnetz (Verteilung) zur Steigerung der Energieeffizienz im Teillastbetrieb. Teilvorhaben: Verteilungen
dc.description.sponsorshipTU Berlin, Open-Access-Mittel – 2021en
dc.identifier.eissn1996-8744
dc.identifier.issn1996-3599
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/13976
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-12749
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc620 Ingenieurwissenschaften und zugeordnete Tätigkeitende
dc.subject.otherCFDen
dc.subject.otherductworken
dc.subject.otherHVACen
dc.subject.othermodel calibrationen
dc.subject.othersimulationen
dc.subject.otherturbulence modelen
dc.titleTurbulence model performance for ventilation components pressure lossesen
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.doi10.1007/s12273-021-0803-xen
dcterms.bibliographicCitation.issue3en
dcterms.bibliographicCitation.journaltitleBuilding Simulationen
dcterms.bibliographicCitation.originalpublishernameSpringer Natureen
dcterms.bibliographicCitation.originalpublisherplaceBerlin ; Heidelbergen
dcterms.bibliographicCitation.pageend399en
dcterms.bibliographicCitation.pagestart389en
dcterms.bibliographicCitation.volume15en
tub.accessrights.dnbfreeen
tub.affiliationFak. 3 Prozesswissenschaften>Inst. Energietechnik>FG Gebäudeenergiesystemede
tub.affiliation.facultyFak. 3 Prozesswissenschaftende
tub.affiliation.groupFG Gebäudeenergiesystemede
tub.affiliation.instituteInst. Energietechnikde
tub.publisher.universityorinstitutionTechnische Universität Berlinen
Files
Original bundle
Now showing 1 - 1 of 1
Loading…
Thumbnail Image
Name:
tawackolian_kriegel_2021.pdf
Size:
1.23 MB
Format:
Adobe Portable Document Format
Description:
Collections