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  • Feature-based and goal-orie...
    Alauzet, F.; Frazza, L.

    Journal of computational physics, 08/2021, Letnik: 439
    Journal Article

    •Anisotropic mesh adaptation is applied successfully to turbulent flows on complex geometries, it becomes a reality.•High-fidelity turbulent flow predictions can be obtained with unstructured meshes composed only of tetrahedra.•Mesh-converged solutions are achieved in 3D guaranteeing that the computed numerical solution is independent of the mesh.•The mesh adaptation process can correct itself to converge toward the correct solution. The scope of this paper is to demonstrate the viability of unstructured anisotropic mesh adaptation for commercial aircraft drag and high-lift prediction studies. The main achievement of this work is to demonstrate that mesh-independent certified numerical solutions can be achievable thanks to anisotropic mesh adaptation and that it is possible to run high-fidelity CFD on unstructured adapted meshes composed only of tetrahedra which is fundamental to design robust meshing process for complex geometries. It also points out the early capturing property of the solution-adaptive process in the sense that accurate output functional values are obtained on relatively coarse adapted meshes. On a more practical point of view, this paper demonstrates how mesh adaptation, thanks to its automation, is able to generate meshes that are extremely difficult to envision and almost impossible to generate manually, leading to highly accurate numerical solutions. Moreover, as the process can start from any coarse initial mesh, it greatly simplifies the overall meshing process. This study also analyze the influence of different strategies in the mesh adaptation algorithm and in the error analysis which are key components of the process. Several error estimates are considered: feature-based ones which are based on the standard multiscale Lp interpolation error estimate and goal-oriented ones to control the error on output functionals which rely on an accurate computation of the adjoint state. The adjoint problem proves to be a stiff problem for RANS equations, failing to converge the adjoint state to machine zero may impact negatively the adaptive process. The maturity of the solution-adaptive process is demonstrated on numerous drag and high-lift prediction cases. It has also excelled in sonic boom and turbomachine applications.