The Effort of Increasing Reynolds Number in Projection-Based Reduced Order Methods: from Laminar to Turbulent Flows

Abstract

We present two different reduced order strategies for incompressible parameterized Navier-Stokes equations characterized by varying Reynolds numbers. The first strategy deals with low Reynolds number (laminar flow) and is based on a stabilized finite element method during the offline stage followed by a Galerkin projection on reduced basis spaces generated by a greedy algorithm. The second methodology is based on a full order finite volume discretization. The latter methodology will be used for flows with moderate to high Reynolds number characterized by turbulent patterns. For the treatment of the mentioned turbulent flows at the reduced order level, a new POD-Galerkin approach is proposed. The new approach takes into consideration the contribution of the eddy viscosity also during the online stage and is based on the use of interpolation. The two methodologies are tested on classic benchmark test cases.

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Cited by in corpus (5)

• Data-Driven POD-Galerkin Reduced Order Model for Turbulent Flows
• A reduced order variational multiscale approach for turbulent flows
• A monolithic and a partitioned Reduced Basis Method for Fluid-Structure Interaction problems
• Enhancing CFD predictions in shape design problems by model and parameter space reduction
• Projection-based reduced order models for a cut finite element method in parametrized domains