The hybridized Discontinuous Galerkin method for Implicit Large-Eddy Simulation of transitional turbulent flows
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JCP_Transition.pdf
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14.39 MB
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Author(s)
Fernandez del Campo, Pablo
Nguyen, Ngoc Cuong
Peraire, Jaime
Date Issued
February 2017
Journal
Journal of Computational Physics
Publisher
Elsevier BV
Citation
Fernandez, P., N.C. Nguyen, and J. Peraire. "The hybridized Discontinuous Galerkin method for Implicit Large-Eddy Simulation of transitional turbulent flows." Journal of Computational Physics, 336 (May 2017): 308-329.
Version
Original manuscript
Abstract
We present a high-order Implicit Large-Eddy Simulation (ILES) approach for transitional aerodynamic flows. The approach encompasses a hybridized Discontinuous Galerkin (DG) method for the discretization of the Navier–Stokes (NS) equations, and a parallel preconditioned Newton-GMRES solver for the resulting nonlinear system of equations. The combination of hybridized DG methods with an efficient solution procedure leads to a high-order accurate NS solver that is competitive to alternative approaches, such as finite volume and finite difference codes, in terms of computational cost. The proposed approach is applied to transitional flows over the NACA 65-(18)10 compressor cascade and the Eppler 387 wing at Reynolds numbers up to 460,000. Grid convergence studies are presented and the required resolution to capture transition at different Reynolds numbers is investigated. Numerical results show rapid convergence and excellent agreement with experimental data. In short, this work aims to demonstrate the potential of high-order ILES for simulating transitional aerodynamic flows. This is illustrated through numerical results and supported by theoretical considerations. Keyword: Discontinuous Galerkin methods; Implicit Large-Eddy Simulation; Navier–Stokes iterative solvers; High-order methods; Laminar separation bubble; Transition to turbulence
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Center for Computational Engineering
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Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1016/j.jcp.2017.02.015
