Refining the mesh involves increasing the number of cells in areas with high gradients or complex geometries. You can use adaptive mesh refinement techniques, where the mesh is automatically refined based on error estimates or solution gradients. Ensure that the mesh is sufficiently fine near boundaries and interfaces to capture important flow features accurately.
The choice of turbulence model depends on the specific flow characteristics and the level of accuracy required. Common models include the k-ε, k-ω, and Reynolds Stress Models (RSM). For high-Reynolds-number flows, the k-ε model is often used, while the k-ω model can be more accurate for flows with adverse pressure gradients and separation. For highly complex flows, RSM or Large Eddy Simulation (LES) might be necessary.
Correctly defining boundary conditions is crucial for obtaining accurate CFD results. Ensure that inlet and outlet boundary conditions match the physical situation, and use appropriate wall functions or no-slip conditions for solid boundaries. For transient simulations, initial conditions should be as accurate as possible to reduce convergence time and improve results.
Post-processing techniques such as contour plots, vector plots, and streamline visualizations can help identify areas where the solution may need further refinement. Additionally, performing a sensitivity analysis by varying key parameters can provide insights into the robustness of your results. Quantitative validation against experimental or benchmark data is also essential.
To reduce numerical errors, use higher-order discretization schemes and ensure that the mesh quality is high, with minimal skewness and aspect ratio issues. Monitor residuals and key flow variables to assess convergence. If the solution is not converging, consider reducing the time step size for transient simulations or using under-relaxation factors for steady-state simulations.