Average-based mesh adaptation for hybrid RANS/LES simulation of complex flows

Sajad Mozaffari , Emmanuel Guilmineau , Michel Visonneau , Jeroen Wackers (1)

1 LHEEA - Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique

Generating meshes with the right resolution is crucial for hybrid RANS/LES simulations of high Reynolds number flow with complex physical phenomena and geometries. This makes automatic mesh generation through adaptive refinement an interesting option. However, since the behavior of these turbulence models depends on the local grid size, mesh changes in time as a result of adaptive refinement may affect the production and destruction of turbulence. Therefore, grid adaptation with refinement criteria based on time-averaged quantities is proposed here to produce meshes that do not evolve rapidly in time and that are suitable for capturing the unsteady flow at each instant. Two averaging approaches, averaging over the instantaneous flow field, and averaging over the refinement criterion, are tested to simulate a turbulent flow behind a backward-facing step with a Detached Eddy Simulation type turbulence model. Compared to grid adaption based on instantaneous solutions, the computational cost is reduced, the accuracy of the solutions improves and an adapted mesh which has a generally static topology based on the main flow features is obtained. The investigation of this refinement process for two realistic test cases, a ship and a hybrid delta wing, confirms the reliability of the average-based adaptation and shows that automatic meshing for hybrid RANS/LES simulations of complex flows is possible.

Domaines: Sciences de l'ingénieur [physics]

Sajad Mozaffari, Emmanuel Guilmineau, Michel Visonneau, Jeroen Wackers. Average-based mesh adaptation for hybrid RANS/LES simulation of complex flows. Computers and Fluids, 2022, 232, pp.105202. ⟨10.1016/j.compfluid.2021.105202⟩. ⟨hal-03388256⟩