Mesh adaptation using adjoint methods and reduced-order models for large eddy simulation

Adaptive mesh refinement (AMR) is potentially an effective way to automatically generate computational meshes for high-fidelity simulations such as Large Eddy Simulation (LES). Adjoint methods, which are able to localize error contributions, can be used to optimize the mesh for computing a physical quantity of interest (e.g. lift, drag)...

Towards efficient adjoint-based mesh optimization for predictive Large Eddy Simulation

This thesis contributes to the effective and efficient application of unsteady adjoint methods to Adaptive Mesh Refinement (AMR) for Large Eddy Simulation (LES). Three aspects, i.e., subgrid-scale model error, storage cost of high-dimensional data, and stability of the adjoint problem for turbulent flows, were studied to make adjoint-based mesh...