Volume 11, Issue 3
Large Eddy Simulation of Spanwise Rotating Turbulent Channel Flow with Subgrid-Scale Eddy Viscosity Model Based on Helicity

Adv. Appl. Math. Mech., 11 (2019), pp. 711-722.

Published online: 2019-01

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• Abstract

Fully developed rotating turbulent channel flow (RTCF) has been numerically investigated using large-eddy simulation (LES). The subgrid-scale (SGS) eddy viscosity model is based on the SGS helicity dissipation balance and the spectral relative helicity. Posterior test has been implemented to RTCF with rotation in spanwise direction. The friction Reynolds number $Re_\tau=u_\tau\delta/\nu$ based on wall shear velocity $u_\tau$, half width of the channel $\delta$ and the kinematic viscosity $\nu$ is 180. Two rotation numbers $Ro_\tau=2\Omega\delta/u_\tau$ equal to 22 and 80 have been computed with respective grid resolution. The results from dynamic Smagorinsky model (DSM) and direct numerical simulation (DNS) are used as references. The results demonstrate that the eddy viscosity model can predict both the precise velocity profile and the turbulent intensity.

• Keywords

Large eddy simulation, rotating turbulent channel flow, turbulence.

65M10, 78A48

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@Article{AAMM-11-711, author = {Jiang , Zhou and Yu , Changping}, title = {Large Eddy Simulation of Spanwise Rotating Turbulent Channel Flow with Subgrid-Scale Eddy Viscosity Model Based on Helicity}, journal = {Advances in Applied Mathematics and Mechanics}, year = {2019}, volume = {11}, number = {3}, pages = {711--722}, abstract = {

Fully developed rotating turbulent channel flow (RTCF) has been numerically investigated using large-eddy simulation (LES). The subgrid-scale (SGS) eddy viscosity model is based on the SGS helicity dissipation balance and the spectral relative helicity. Posterior test has been implemented to RTCF with rotation in spanwise direction. The friction Reynolds number $Re_\tau=u_\tau\delta/\nu$ based on wall shear velocity $u_\tau$, half width of the channel $\delta$ and the kinematic viscosity $\nu$ is 180. Two rotation numbers $Ro_\tau=2\Omega\delta/u_\tau$ equal to 22 and 80 have been computed with respective grid resolution. The results from dynamic Smagorinsky model (DSM) and direct numerical simulation (DNS) are used as references. The results demonstrate that the eddy viscosity model can predict both the precise velocity profile and the turbulent intensity.

}, issn = {2075-1354}, doi = {https://doi.org/10.4208/aamm.2018.s14}, url = {http://global-sci.org/intro/article_detail/aamm/12993.html} }
TY - JOUR T1 - Large Eddy Simulation of Spanwise Rotating Turbulent Channel Flow with Subgrid-Scale Eddy Viscosity Model Based on Helicity AU - Jiang , Zhou AU - Yu , Changping JO - Advances in Applied Mathematics and Mechanics VL - 3 SP - 711 EP - 722 PY - 2019 DA - 2019/01 SN - 11 DO - http://doi.org/10.4208/aamm.2018.s14 UR - https://global-sci.org/intro/article_detail/aamm/12993.html KW - Large eddy simulation, rotating turbulent channel flow, turbulence. AB -

Fully developed rotating turbulent channel flow (RTCF) has been numerically investigated using large-eddy simulation (LES). The subgrid-scale (SGS) eddy viscosity model is based on the SGS helicity dissipation balance and the spectral relative helicity. Posterior test has been implemented to RTCF with rotation in spanwise direction. The friction Reynolds number $Re_\tau=u_\tau\delta/\nu$ based on wall shear velocity $u_\tau$, half width of the channel $\delta$ and the kinematic viscosity $\nu$ is 180. Two rotation numbers $Ro_\tau=2\Omega\delta/u_\tau$ equal to 22 and 80 have been computed with respective grid resolution. The results from dynamic Smagorinsky model (DSM) and direct numerical simulation (DNS) are used as references. The results demonstrate that the eddy viscosity model can predict both the precise velocity profile and the turbulent intensity.

Zhou Jiang & Changping Yu. (2020). Large Eddy Simulation of Spanwise Rotating Turbulent Channel Flow with Subgrid-Scale Eddy Viscosity Model Based on Helicity. Advances in Applied Mathematics and Mechanics. 11 (3). 711-722. doi:10.4208/aamm.2018.s14
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