Non-oscillatory forward-in-time method for incompressible flows
thesisposted on 01.06.2018, 11:13 by Zhixin Cao
This research extends the capabilities of Non-oscillatory Forward-in-Time (NFT) solvers operating on unstructured meshes to allow for accurate simulation of incompressible turbulent flows. This is achieved by the development of Large Eddy Simulation (LES) and Detached Eddy Simulation (DES) turbulent flow methodologies and the development of parallel option of the flow solver. The effective use of LES and DES requires a development of a subgrid-scale model. Several subgrid-scale models are implemented and studied, and their efficacy is assessed. The NFT solvers employed in this work are based on the Multidimensional Positive Definite Advection Transport Algorithm (MPDATA) that facilitates novel implicit Large Eddy Simulation (ILES) approach to treating turbulence. The flexibility and robustness of the new NFT MPDATA solver are studied and successfully validated using well established benchmarks and concentrate on a flow past a sphere. The flow statistics from the solutions are compared against the existing experimental and numerical data and fully confirm the validity of the approach. The parallel implementation of the flow solver is also documented and verified showing a substantial speedup of computations. The proposed method lays foundations for further studies and developments, especially for exploring the potential of MPDATA in the context of ILES and associated treatments of boundary conditions at solid boundaries.
- Mechanical, Electrical and Manufacturing Engineering