Calibrated reduced-order POD-Galerkin system for fluid flow modelling

Authors:
M. Couplet;C. Basdevant;P. Sagaut
Affiliations:
ONERA, Computational Fluid Dynamics and Aeroacoustics Department, 29 av. de la Division Leclerc, BP 72, 92322 Chatillon, France;LMD, ícole Normale Supérieure, 24 rue Lhomond, 75231 Paris Cedex 5, France;LMM, Université Pierre et Marie Curie, Boıte 162, 4 place Jussieu, 75252 Paris Cedex 5, France
Venue:
Journal of Computational Physics
Year:
2005

Citing 1
Cited 11

Reduced-Order Adaptive Controllers for Fluid Flows Using POD

Journal of Scientific Computing

Model reduction for real-time fluids

ACM SIGGRAPH 2006 Papers
Optimal control of the cylinder wake in the laminar regime by trust-region methods and POD reduced-order models

Journal of Computational Physics
Enablers for robust POD models

Journal of Computational Physics
Modular bases for fluid dynamics

ACM SIGGRAPH 2009 papers
Reduced-order models for parameter dependent geometries based on shape sensitivity analysis

Journal of Computational Physics
Reduced order models based on local POD plus Galerkin projection

Journal of Computational Physics
Two-level discretizations of nonlinear closure models for proper orthogonal decomposition

Journal of Computational Physics
Reduced-order modeling of transonic flows around an airfoil submitted to small deformations

Journal of Computational Physics
Strong and weak constraint variational assimilations for reduced order fluid flow modeling

Journal of Computational Physics
Local POD Plus Galerkin Projection in the Unsteady Lid-Driven Cavity Problem

SIAM Journal on Scientific Computing
Towards a space reduction approach for efficient structural shape optimization

Structural and Multidisciplinary Optimization

Quantified Score

Hi-index	31.48

Visualization

Abstract

To improve the behaviour of reduced-order proper orthogonal decomposition (POD)-Galerkin systems, two numerical methods are proposed. These methods determine free parameters in the POD-Galerkin system from flow simulations via a minimization problem. They give rise to linear systems and their computational costs are reasonable. Both methods are assessed for two flow configurations: a two-dimensional flow around a square-cylinder for a Reynolds number of 100 and a three-dimensional flow past a backward-facing step for a Reynolds number of 7432 based on the step height and the streamwise velocity at the middle of the inlet. For both configurations, the methods are effective since accurate calibrated reduced-order POD-Galerkin systems are obtained.