  We investigate the possibility of reducing the computational burden of LES
models by employing locally and dynamically adaptive polynomial degrees in the
framework of a high order DG method. A degree adaptation technique especially
featured to be effective for LES applications, that was previously developed by
the authors and tested in the statically adaptive case, is applied here in a
dynamically adaptive fashion. Two significant benchmarks are considered,
comparing the results of adaptive and non adaptive simulations. The proposed
dynamically adaptive approach allows for a significant reduction of the
computational cost of representative LES computation, while allowing to
maintain the level of accuracy guaranteed by LES carried out with constant,
maximum polynomial degree values.
