Pressure stabilization strategies for a LES filtering Reduced Order Model

TL;DR

This paper introduces a stabilized POD-Galerkin reduced order model for Leray models, combining an Evolve-Filter algorithm with pressure stabilization strategies, tested on 2D flow past a cylinder, showing comparable accuracy and efficiency.

Contribution

It develops a pressure stabilization approach for a POD-Galerkin ROM using Evolve-Filter and compares two strategies, enhancing stability and efficiency in flow simulations.

Findings

Both stabilization strategies yield similar errors in lift and drag coefficients.

The pressure Poisson equation method is more computationally efficient.

Supremizer enrichment is necessary for stable and accurate pressure approximation.

Abstract

We present a stabilized POD-Galerkin reduced order method (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. In both steps of the EF algorithm, velocity and pressure fields are approximated using different POD basis and coefficients. To achieve pressure stabilization, we consider and compare two strategies: the pressure Poisson equation and the supremizer enrichment of the velocity space. We show that the evolve and filtered velocity spaces have to be enriched with the supremizer solutions related to both evolve and filter pressure fields in order to obtain stable and accurate solutions with the supremizer enrichment method. We test our ROM approach on 2D unsteady flow past a cylinder at Reynolds number 0 <= Re <= 100. We find that both stabilization strategies produce comparable errors in the reconstruction of the lift and drag coefficients, with the pressure Poisson equation method being more computationally efficient.