We present a comparative computational study of two stabilized Reduced Order Models
(ROMs) for the simulation of convection-dominated incompressible flow (Reynolds number
of the order of a few thousands). Representative solutions in the parameter space, which
includes either time only or time and Reynolds number, are computed with a Finite Volume method and used to generate a reduced basis via Proper Orthogonal Decomposition
(POD). Galerkin projection of the Navier–Stokes equations onto the reduced space is used to
compute the ROM solution. To ensure computational efficiency, the number of POD modes
is truncated and ROM solution accuracy is recovered through two stabilization methods: (i)
adding a global constant artificial viscosity to the reduced dimensional model, and (ii) adding
a different value of artificial viscosity for the different POD modes. We test the stabilized
ROMs for fluid flow in an idealized medical device consisting of a conical convergent, a
narrow throat, and a sudden expansion. Both stabilization methods significantly improve the
ROM solution accuracy over a standard (non-stabilized) POD-Galerkin model.
