Output-based space-time mesh adaptation for the compressible Navier-Stokes equations

  • Fidkowski K
  • Luo Y
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Abstract

This paper presents an output-based adaptive algorithm for unsteady simulations of convection-dominated flows. A space-time discontinuous Galerkin discretization is used in which the spatial meshes remain static in both position and resolution, and in which all elements advance by the same time step. Error estimates are computed using an adjoint-weighted residual, where the discrete adjoint is computed on a finer space obtained by order enrichment of the primal space. An iterative method based on an approximate factorization is used to solve both the forward and adjoint problems. The output error estimate drives a fixed-growth adaptive strategy that employs hanging-node refinement in the spatial domain and slab bisection in the temporal domain. Detection of space-time anisotropy in the localization of the output error is found to be important for efficiency of the adaptive algorithm, and two anisotropy measures are presented: one based on inter-element solution jumps, and one based on projection of the adjoint. Adaptive results are shown for several two-dimensional convection-dominated flows, including the compressible Navier-Stokes equations. For sufficiently-low accuracy levels, output-based adaptation is shown to be advantageous in terms of degrees of freedom when compared to uniform refinement and to adaptive indicators based on approximation error and the unweighted residual. Time integral quantities are used for the outputs of interest, but entire time histories of the integrands are also compared and found to converge rapidly under the proposed scheme. In addition, the final output-adapted space-time meshes are shown to be relatively insensitive to the starting mesh. © 2011 Elsevier Inc.

Author-supplied keywords

  • Compressible Navier-Stokes
  • Discontinuous Galerkin
  • Output error estimation
  • Space-time mesh adaptation
  • Unsteady adjoint

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Authors

  • Krzysztof J. Fidkowski

  • Yuxing Luo

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