Grid Independence Test (GIT) in CFD

The meshing process cannot be entirely calculated analytically, such as mesh size, y+ size, mesh type, and so on.

This occurs due to the nature of the geometry and physical phenomena itself, which are generally complex. For instance, it's impractical to compute each component for the 'perfect' mesh in simulating a race car with specific details. There's an element of 'art' and experience involved for the operator.

Nevertheless, one commonly used method to verify the suitability of the mesh is to ensure that when we slightly modify our mesh settings, it does not affect the simulation results. In other words, the simulation results become insensitive or independent of the mesh settings. This testing process is known as the “mesh sensitivity test” or “grid independence test (GIT)”.

There aren't specific rules discussing this method because each simulation has different objectives.

For example, when testing a heat exchanger with the same model, one researcher wants to analyze the pressure drop, while another wants to focus on temperature changes. Hence, their GIT parameters will differ.

For instance, the first researcher will create a test for pressure drop changes concerning grid settings, while the second will test temperature changes concerning grid settings.

The next point is defining what should be modified in the grid settings. Generally, the independent variable used is the number of elements or grids for simulations covering a large domain. For geometries with numerous walls and relatively low Reynolds numbers, variations in y+ are commonly used.

However, all choices, both for independent and dependent variables, heavily depend on the specific case at hand.

In the example below, GIT is conducted on a NACA 2412 airfoil CFD simulation using openFOAM software. In this scenario, the researcher aims to find the most suitable mesh refinement settings around the airfoil, where higher refinement leads to more cells.

Therefore, in this scenario, a graph of the lift generated by the airfoil against the number of cells was created. Here are the results:

From the above graph, it can be shown that with the number of cells exceeding 5,000, the lift force tends to remain constant with an increase in the number of cells.

 We can conclude that using a mesh with 5,500 cells will yield the same lift force as a mesh with 6,500 or more cells, requiring significantly more computational effort than the 5,500-cell mesh.

Based on these results, we can select the most optimal mesh to be used, which is the 5,500-cell mesh. However, this conclusion only applies to lift force calculations. For computations involving frictional forces, vortexes, and others, this may not be true and should be tested based on the specific case.

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