Automating Error Quantification and Reduction for Computational Fluid Dynamics (CFD)

Solution errors are inherent in any Computational Fluid Dynamics (CFD) simulation. Sources of error include spatial and temporal discretization, inadequacy or incapacity of physical models to capture complex fluid flow phenomena, and human errors in the setup and use of the CFD code. Systematic identification, reduction, and control of these various error sources is crucial if the results of CFD simulations are to be trusted for design and performance assessment of air vehicles. While grid refinement studies may verify the spatial accuracy of a solution, these studies are generally very laborious and time intensive. Solution verification using Richardson extrapolation techniques has largely been limited to structured grid applications. To automate grid refinement studies and solution verification for unstructured meshes, and render such studies more practical, the proposed research program exploits an existing mesh adaptation package and recent advances in generalized Richardson extrapolation. The CRISP CFD® mesh adaptation code, used with several unstructured Navier-Stokes solvers including the Air Vehicles Unstructured Solver (AVUS), provides a viable path for automated mesh refinement and solution verification. In addition to solution verification studies, the proposed research will explore issues in mesh suitability and ways of addressing errors due to near wall resolution and human factors.