Axel Schwöppe

The DLR Flow Solver TAU - Status and Recent Algorithmic Developments

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.

Grid Convergence for Turbulent Flows(Invited)

A detailed grid convergence study has been conducted to establish accurate reference solutions corresponding to the one-equation linear eddy-viscosity Spalart-Allmaras turbulence model for two dimensional turbulent flows around the NACA 0012 airfoil and a flat plate. The study involved three widely used codes, CFL3D (NASA), FUN3D (NASA), and TAU (DLR), and families of uniformly refined structured grids that differ in the grid density patterns. Solutions computed by different codes on different grid families appear to converge to the same continuous limit, but exhibit different convergence characteristics. The grid resolution in the vicinity of geometric singularities, such as a sharp trailing edge, is found to be the major factor affecting accuracy and convergence of discrete solutions; the effects of this local grid resolution are more prominent than differences in discretization schemes and/or grid elements. The results reported for these relatively simple turbulent flows demonstrate that CFL3D, FUN3D, and TAU solutions are very accurate on the finest grids used in the study, but even those grids are not sufficient to conclusively establish an asymptotic convergence order.

Grid-Convergence of Reynolds-Averaged Navier–Stokes Solutions for Benchmark Flows in Two Dimensions

A detailed grid-convergence study has been conducted to establish reference solutions corresponding to the one-equation linear eddy-viscosity Spalart–Allmaras turbulence model for two-dimensional turbulent flows around the NACA 0012 airfoil and a flat plate. The study involved the three widely used codes CFL3D (NASA), FUN3D (NASA), and TAU (DLR, The German Aerospace Center), as well as families of uniformly refined structured grids that differed in the grid density patterns. Solutions computed by different codes on different grid families appeared to converge to the same continuous limit but exhibited strikingly different convergence characteristics. The grid resolution in the vicinity of geometric singularities, such as a sharp trailing edge, was found to be the major factor affecting accuracy and convergence of discrete solutions; the effects of this local grid resolution were more prominent than differences in discretization schemes and/or grid elements. The results reported for these relatively simple...

Investigation and Comparison of Implicit Smoothers Applied in Agglomeration Multigrid

A straightforward implicit smoothing method implemented in several codes solving the Reynolds-averaged Navier–Stokes equations is the lower–upper symmetric Gauss–Seidel method. It was proposed several years ago and is attractive to implement because of its low memory requirements and low operation count. Since, for many examples, often a severe restriction of the Courant–Friedrichs–Lewy number and loss of robustness are observed, it is the goal of this paper to revisit the lower–upper symmetric Gauss–Seidel implementation and to discuss several alternative implicit smoothing strategies used within an agglomeration multigrid for unstructured meshes. The starting point is a full implicit multistage Runge–Kutta method. Based on this method, several additional features and simplifications are developed and suggested, such that the implicit method is applicable to high-Reynolds-number viscous flows; that is, the required matrices fit into the fast memory of the cluster hardware and the arising linear systems c...

Accuracy of the Cell-Centered Grid Metric in the DLR TAU-Code

The drag prediction accuracy of the current version of the cell-centered grid metric discretization in the edge-based flow solver TAU lags behind the accuracy of the cell-vertex grid metric on highly-skewed unstructured meshes. Inaccurate convective fluxes and gradients contributing to the turbulence sources are identified as the reasons for this accuracy degradation. Alternative approaches for cell-centered discretizations are presented and shown to lead to significant accuracy and robustness improvements. Recommendations are given to improve spatial discretization schemes for the cell-centered grid metric in an edge-based finite volume code.