Abstract
The approximate deconvolution model (ADM) is applied to LES of incompressible channel flow. With this approach an approximation to the unfiltered data is achieved by repeated filtering. This approximation can be used to compute the non-linear terms in the filtered NavierStokes equations directly without explicit subgrid scale terms. A priori tests show an excellent agreement with direct numerical simulation data. A posteriori tests are performed for incompressible channel flow at two different Reynolds numbers. Both simulations compare well with DNS data and show a significant improvement over classical subgrid scale models such as the standard or the dynamic Smagorinsky model. The computational overhead of the ADM is similar to that of the scale-similarity model and is considerably less than that of dynamic models or the velocity estimation model.
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