Wall Treatment for Turbulence

The use of turbulence models requires the imposition of boundary conditions at the walls and the imposition of specific turbulence values on the centroids of the near-wall cells.

For the turbulence models in Simcenter STAR-CCM+, the following approaches of accounting for turbulent wall boundary layers are available:

High- y +

The high- y + wall treatment is equivalent to the traditional wall-function approach. This approach uses algebraic relations based on the assumed distribution of velocity, temperature, and turbulence quantities across the boundary layer to provide boundary conditions when the centroid of a near-wall cell lies in the log layer of the boundary layer. The accuracy of the wall-function approach depends on the degree to which the assumptions and approximations embodied in the functions correspond with the reality of the application. Most standard wall functions apply only to equilibrium conditions. However, Simcenter STAR-CCM+ extends the wall functions to include non-equilibrium effects.

Low- y +

In general, the low- y + wall treatment is equivalent to the traditional low Reynolds number approach, where the boundary layer is resolved with a fine layered mesh and no modeling beyond the assumption of laminar flow is necessary in the near-wall cells.

However, for robustness reasons, Simcenter STAR-CCM+ does not apply this approach but uses standard wall functions for the low- y + wall treatment instead.

All- y +

The all- y + wall treatment uses blended wall functions and provides valid boundary conditions for flow, energy, and turbulence quantities for a wide range of near-wall mesh densities.

Two-layer all- y +

The two-layer all- y + wall treatment, which is available for the two-layer turbulence models, uses an approach that is identical to the all- y + wall treatment. However, specific values of turbulence dissipation rate are imposed at the centroids of the near-wall cells to make it consistent with the two-layer formulation of the underlying turbulence model.