We propose a Proper Orthogonal Decomposition (POD)-Galerkin based Reduced
Order Model (ROM) for a Leray model. For the implementation of the model, we
combine a two-step algorithm called Evolve-Filter (EF) with a computationally
efficient finite volume method. The main novelty of the proposed approach
relies in applying spatial filtering both for the collection of the snapshots
and in the reduced order model, as well as in considering the pressure field at
reduced level. In both steps of the EF algorithm, velocity and pressure fields
are approximated by using different POD basis and coefficients. For the
reconstruction of the pressures fields, we use a pressure Poisson equation
approach. We test our ROM on two benchmark problems: 2D and 3D unsteady flow
past a cylinder at Reynolds number 0 <= Re <= 100. The accuracy of the reduced
order model is assessed against results obtained with the full order model. For
the 2D case, a parametric study with respect to the filtering radius is also
presented.Comment: 29 pages, 16 figures, 9 table