  In this work we present a Reduced Order Model which is specifically designed
to deal with turbulent flows in a finite volume setting. The method used to
build the reduced order model is based on the idea of merging/combining
projection-based techniques with data-driven reduction strategies. In
particular, the work presents a mixed strategy that exploits a data-driven
reduction method to approximate the eddy viscosity solution manifold and a
classical POD-Galerkin projection approach for the velocity and the pressure
fields, respectively. The newly proposed reduced order model has been validated
on benchmark test cases in both steady and unsteady settings with Reynolds up
to Re=O(10^5).
