{"refrec":{"BRefID":354385,"RR":"<b>Rezaeiha, A.; Montazeri, H.; Blocken, B.</b> (2020). Scale-adaptive simulation (SAS) of dynamic stall on a wind turbine, <b><i>in</i></b>: Hoarau, Y. <i>et al.</i> <i>Progress in hybrid RANS-LES modelling.</i> pp. 323-333. <a href=\"https://dx.doi.org/10.1007/978-3-030-27607-2_26\" target=\"_blank\">https://dx.doi.org/10.1007/978-3-030-27607-2_26</a>","BEntID":352098,"PublicFlag":1,"CheckedFlag":1,"wosflag":0,"vabbflag":0,"RefStringPartII":", <b><i>in</i></b>: Hoarau, Y. <i>et al.</i> <i>Progress in hybrid RANS-LES modelling.</i> pp. 323-333. <a href=\"https://dx.doi.org/10.1007/978-3-030-27607-2_26\" target=\"_blank\">https://dx.doi.org/10.1007/978-3-030-27607-2_26</a>","DocTypID":17,"DocType":"Book chapters","MarineFlag":0,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Rezaeiha, A.; Montazeri, H.; Blocken, B.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Rezaeiha, A.; Montazeri, H.; Blocken, B.","Englishabstract":"Scale-adaptive simulation (SAS) approach is employed to investigate the complex dynamic stall phenomena occurring on a wind turbine blade. The results are compared with the more popular less computationally-expensive unsteady Reynolds-averaged Navier-Stokes (URANS) approach where the latter is validated using three sets of experimental data. The comparison reveals that the two approaches have similar predictions of the instant of the formation/bursting/shedding of the laminar separation bubble (LSB) and dynamic stall vortex (DSV), the size of the LSB and aerodynamic loads during the upstroke. This is while the two approaches exhibit dissimilar predictions of the trailing-edge vortex characteristics, its interaction with the DSV, number of secondary vortices and aerodynamic loads during the downstroke.","AbstractOtherLang":null,"BibLvlCode":"AM","StandardTitle":"Scale-adaptive simulation (SAS) of dynamic stall on a wind turbine","OrigTitleLangCode":"en","OrigTitleLangCodeExtended":"eng","OrigTitleLangID":15,"DateLastModified":{"date":"2024-12-10 01:33:17.368041","timezone_type":1,"timezone":"+01:00"},"UserAccessRight":null,"UserAccID":null,"AuthorKeywords":null,"OtherDescriptors":null,"Notes":null,"AnaPub":2020,"MonPub":null,"DateUpdate":"2022-08-01","DateCreate":"2022-08-01","SecASFANote":null,"ConfID":null,"PeerRev":0,"VlizCoreFlag":1,"WoScode":"WOS:000634530900026","VABBcode":null,"OpenAcc":0,"DOI":"10.1007/978-3-030-27607-2_26"},"refs":null,"anarec":{"AnaID":354385,"PubliDate":2020,"Pagination":"323-333","XtraPublOfAnaID":null,"ISBN":"978-3-030-27606-5","Volume":null,"Issue":null,"BRefMon":354402,"BRefMonRR":"<b>Hoarau, Y. <i>et al.</i></b> (2020). Progress in hybrid RANS-LES modelling. Springer: Cham. ISBN 978-3-030-27606-5; e-ISBN 978-3-030-27607-2. 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