Reducing the source of solution error (that is, the magnitude of terms excluded in the discrete approximations) is critical if accurate numerical solutions are desired. The two most effective strategies for accomplishing this are to increase the order-accuracy of discrete approximations (for example, using the high resolution rather than the upwind difference advection scheme) and/or to reduce the mesh spacing in regions of rapid solution variation. The former strategy is discussed above (see Advection Term), and implications of the latter are now considered.

Finely spaced isotropic mesh distributions are ideal, but they are often not tractable. A more useful strategy for reducing sources of solution error is to generate anisotropic meshes with fine spacing in directions of most rapid solution variation and relatively coarse spacing in other directions. This is exemplified by typical boundary layer meshes that are compressed in the direction of most rapid solution variation (that is, normal to the wall).

It is important to realize, however, that sources of solution error are also affected by poor geometrical mesh quality (see Measures of Mesh Quality in the CFX-Solver Modeling Guide). In particular, the error source contributions due to the discretization of transient/storage, diffusion, source and Rhie-Chow redistribution terms increase with mesh anisotropy. This is why, for example, high orthogonality and low expansion factors are recommended in boundary layer meshes where diffusive transport dominates.