The DLR Flow Solver TAU - Status and Recent Algorithmic Developments

Abstract

The only implicit smoothing method implemented in the DLR Flow Solver TAU is the LU-SGS method. It was chosen several years ago because of its low memory requirements and low operation counts. Since in the past for many examples a severe restriction of the CFL number and loss of robustness was observed, it is the goal of this paper to revisit the LU-SGS implementation and to discuss several alternative implicit smoothing strategies used within an agglomeration multigrid for unstructured meshes. Starting point is a full implicit multistage Runge-Kutta method. Based on this method we develop and suggest several additional features and simplifications such that the implicit method is applicable to high Reynolds number viscous flows, that is the required matrices fit into the fast memory of our cluster hardware and the arising linear systems can be approximately solved efficiently. To this end we focus on simplifications of the Jacobian as well as efficient iterative approximate solution methods. To significantly improve the approximate linear solution methods we take care of grid anisotropy for both approximately solving the linear systems and agglomeration strategy. The procedure creating coarse grid meshes is extended by strategies identifying structured parts of the mesh. This seems to improve the quality of coarse grid meshes in the way that an overall better reliability of multigrid can be observed. Furthermore we exploit grid information within the iterative solution methods for the linear systems. Numerical examples demonstrate the gain with respect to reliability and efficiency.