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Published May 5, 2021 | Submitted
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A nonlinear subgrid-scale model for large-eddy simulations of rotating turbulent flows


Rotating turbulent flows form a challenging test case for large-eddy simulation (LES). We, therefore, propose and validate a new subgrid-scale (SGS) model for such flows. The proposed SGS model consists of a dissipative eddy viscosity term as well as a nondissipative term that is nonlinear in the rate-of-strain and rate-of-rotation tensors. The two corresponding model coefficients are a function of the vortex stretching magnitude. Therefore, the model is consistent with many physical and mathematical properties of the Navier-Stokes equations and turbulent stresses, and is easy to implement. We determine the two model constants using a nondynamic procedure that takes into account the interaction between the model terms. Using detailed direct numerical simulations (DNSs) and LESs of rotating decaying turbulence and spanwise-rotating plane-channel flow, we reveal that the two model terms respectively account for dissipation and backscatter of energy, and that the nonlinear term improves predictions of the Reynolds stress anisotropy near solid walls. We also show that the new SGS model provides good predictions of rotating decaying turbulence and leads to outstanding predictions of spanwise-rotating plane-channel flow over a large range of rotation rates for both fine and coarse grid resolutions. Moreover, the new nonlinear model performs as well as the dynamic Smagorinsky and scaled anisotropic minimum-dissipation models in LESs of rotating decaying turbulence and outperforms these models in LESs of spanwise-rotating plane-channel flow, without requiring (dynamic) adaptation or near-wall damping of the model constants.

Additional Information

The authors gratefully acknowledge Geert Brethouwer for his support in identifying turbulent bursts in spanwise-rotating plane-channel flow. M.H.S. is supported by the research programme Free Competition in the Physical Sciences (Project No. 613.001.212), which is financed by the Netherlands Organization for Scientific Research (NWO). F.X.T. is supported by a Ramón y Cajal postdoctoral contract (No. RYC-2012-11996) financed by the Ministerio de Economía y Competitividad, Spain. Part of this research was conducted during the Center for Turbulence Research (CTR) Summer Program 2016 at Stanford University. M.H.S., F.X.T. and R.V. thank the CTR for its hospitality and financial support. We would like to thank the Center for Information Technology of the University of Groningen for their support and for providing access to the Peregrine high-performance computing cluster. The authors also acknowledge use of computational resources from the Certainty cluster awarded by the National Science Foundation to CTR and from the MareNostrum supercomputer at the Barcelona Supercomputing Center.

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