Christopher Wingel, Nicolas Binder, Yannick Bousquet, J. Boussuge, N. Buffaz, Sébastien Le Guyader
{"title":"Analysis and Modelling of Turbulence Anisotropy of a Swirled Hot Streak Flow","authors":"Christopher Wingel, Nicolas Binder, Yannick Bousquet, J. Boussuge, N. Buffaz, Sébastien Le Guyader","doi":"10.1115/1.4064609","DOIUrl":null,"url":null,"abstract":"\n This study is carried out in the context of hot streak flows in high-pressure turbines, for which a correct prediction of the temperature evolution is required. The present work particularly focuses on the turbulence anisotropy analysis of a swirled hot streak flow in a bent channel representative of a NGV passage of a high-pressure turbine. LES are conducted with the in-house solver IC3 in order to measure and characterise the anisotropy of turbulence. Moreover, to evaluate turbulence modelling, steady simulations of the bent channel are performed with the ELSA software, which solves the RANS equations. LES is firstly used to complete a TKE budget that enables to understand the energetic transfers associated with turbulence. This budget reveals two distinct zones where turbulence activity is impacted when the curvature is reached. The analysis of the anisotropy of turbulence based on two metrics highlights a misalignment of the Reynolds stress tensor and the mean strain-rate tensor (Schmitt's criterion), and a strong anisotropy developing inside the bent duct (Lumley's analysis) that may cause the failure of the classical RANS turbulence models based on Boussinesq's hypothesis. To check this hypothesis, RANS is positioned against LES with different turbulence models that accounts or not for the anisotropy of turbulence. Both turbulence activity (TKE budgets, Lumley's analysis) and aerothermal fields (radial distributions) are compared. Results show that EARSM models enable to better account for the anisotropy of turbulence, which in turn promote a better prediction of temperature, both in terms of intensity and trajectory.","PeriodicalId":504378,"journal":{"name":"Journal of Fluids Engineering","volume":"63 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Fluids Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/1.4064609","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study is carried out in the context of hot streak flows in high-pressure turbines, for which a correct prediction of the temperature evolution is required. The present work particularly focuses on the turbulence anisotropy analysis of a swirled hot streak flow in a bent channel representative of a NGV passage of a high-pressure turbine. LES are conducted with the in-house solver IC3 in order to measure and characterise the anisotropy of turbulence. Moreover, to evaluate turbulence modelling, steady simulations of the bent channel are performed with the ELSA software, which solves the RANS equations. LES is firstly used to complete a TKE budget that enables to understand the energetic transfers associated with turbulence. This budget reveals two distinct zones where turbulence activity is impacted when the curvature is reached. The analysis of the anisotropy of turbulence based on two metrics highlights a misalignment of the Reynolds stress tensor and the mean strain-rate tensor (Schmitt's criterion), and a strong anisotropy developing inside the bent duct (Lumley's analysis) that may cause the failure of the classical RANS turbulence models based on Boussinesq's hypothesis. To check this hypothesis, RANS is positioned against LES with different turbulence models that accounts or not for the anisotropy of turbulence. Both turbulence activity (TKE budgets, Lumley's analysis) and aerothermal fields (radial distributions) are compared. Results show that EARSM models enable to better account for the anisotropy of turbulence, which in turn promote a better prediction of temperature, both in terms of intensity and trajectory.