An optimisation-based domain-decomposition reduced order model for the incompressible Navier-Stokes equations

11/26/2022
by   Ivan Prusak, et al.
0

The aim of this work is to present a model reduction technique in the framework of optimal control problems for partial differential equations. We combine two approaches used for reducing the computational cost of the mathematical numerical models: domain-decomposition (DD) methods and reduced-order modelling (ROM). In particular, we consider an optimisation-based domain-decomposition algorithm for the parameter-dependent stationary incompressible Navier-Stokes equations. Firstly, the problem is described on the subdomains coupled at the interface and solved through an optimal control problem, which leads to the complete separation of the subdomain problems in the DD method. On top of that, a reduced model for the obtained optimal-control problem is built; the procedure is based on the Proper Orthogonal Decomposition technique and a further Galerkin projection. The presented methodology is tested on two fluid dynamics benchmarks: the stationary backward-facing step and lid-driven cavity flow. The numerical tests show a significant reduction of the computational costs in terms of both the problem dimensions and the number of optimisation iterations in the domain-decomposition algorithm.

READ FULL TEXT

page 16

page 17

page 21

page 25

page 26

page 27

page 29

page 30

research
08/03/2023

An optimisation-based domain-decomposition reduced order model for parameter-dependent non-stationary fluid dynamics problems

In this work, we address parametric non-stationary fluid dynamics proble...
research
06/12/2019

Nonintrusive proper generalised decomposition for parametrised incompressible flow problems in OpenFOAM

The computational cost of parametric studies currently represents the ma...
research
02/18/2022

Data-Driven Enhanced Model Reduction for Bifurcating Models in Computational Fluid Dynamics

We investigate various data-driven methods to enhance projection-based m...
research
10/25/2019

Bayesian identification of a projection-based Reduced Order Model for Computational Fluid Dynamics

In this paper we propose a Bayesian method as a numerical way to correct...
research
10/25/2019

Bayesian identification of a projection-based Reduced Order Model for Computational Fluid Dynamics Computers and Fluids

In this paper we propose a Bayesian method as a numerical way to correct...
research
07/20/2021

Hybrid neural network reduced order modelling for turbulent flows with geometric parameters

Geometrically parametrized Partial Differential Equations are nowadays w...

Please sign up or login with your details

Forgot password? Click here to reset