In this contribution we explore some numerical alternatives to derive efficient and robust low-order models of the Navier–Stokes equations. The first considered approach is based on an hybrid CFD-ROM approach in which the ROM is used to define the boundary conditions of a CFD simulation. This makes possible to reduce significantly the size of the domain studied by the CFD solver. An alternative approach, based on residual minimization, is presented in the following. We start from the fact that classical Galerkin or Petrov-Galerkin approaches for ROM can be derived in the context of a residual minimization method similar to variational multi scale modelling , VMS [1]. Based on this, we introduce a residual minimization scheme that directly i...
International audienceThis study focuses on stabilizing Reduced Order Model based on Proper Orthogon...
International audienceAbstract We propose the use of reduced order modeling (ROM) to reduce the comp...
Research into constructing reduced-order models (ROM) to reduce computational cost or to interpret c...
International audienceIn this contribution we explore some numerical alternatives to derive efficien...
The purpose of this work is to present different reduced order model strategies starting from full o...
This thesis presents the a stabilized projection-based Reduced Order Model (ROM) formulation in low ...
A new method is presented to generate reduced order models (ROMs) in Fluid Dynamics problems. The me...
This report explores some numerical alternatives that can be exploited to derive efficient low-order...
This article presents two new non-intrusive reduced order models based upon proper orthogonal decomp...
In this paper we present a collection of techniques used to formulate a projection-based reduced ord...
In this work, a domain decomposition strategy for non-linear hyper-reduced-order models is presented...
Galerkin projection of the Navier–Stokes equations on Proper Orthogonal Decomposition (POD) basis is...
In this paper we present a new domain decomposition non-intrusive reduced order model (DDNIROM) for ...
This article presents two new non-intrusive reduced order models based upon proper orthogonal decomp...
A novel reduced order model (ROM) for incompressible flows is developed by performing a Galerkin pro...
International audienceThis study focuses on stabilizing Reduced Order Model based on Proper Orthogon...
International audienceAbstract We propose the use of reduced order modeling (ROM) to reduce the comp...
Research into constructing reduced-order models (ROM) to reduce computational cost or to interpret c...
International audienceIn this contribution we explore some numerical alternatives to derive efficien...
The purpose of this work is to present different reduced order model strategies starting from full o...
This thesis presents the a stabilized projection-based Reduced Order Model (ROM) formulation in low ...
A new method is presented to generate reduced order models (ROMs) in Fluid Dynamics problems. The me...
This report explores some numerical alternatives that can be exploited to derive efficient low-order...
This article presents two new non-intrusive reduced order models based upon proper orthogonal decomp...
In this paper we present a collection of techniques used to formulate a projection-based reduced ord...
In this work, a domain decomposition strategy for non-linear hyper-reduced-order models is presented...
Galerkin projection of the Navier–Stokes equations on Proper Orthogonal Decomposition (POD) basis is...
In this paper we present a new domain decomposition non-intrusive reduced order model (DDNIROM) for ...
This article presents two new non-intrusive reduced order models based upon proper orthogonal decomp...
A novel reduced order model (ROM) for incompressible flows is developed by performing a Galerkin pro...
International audienceThis study focuses on stabilizing Reduced Order Model based on Proper Orthogon...
International audienceAbstract We propose the use of reduced order modeling (ROM) to reduce the comp...
Research into constructing reduced-order models (ROM) to reduce computational cost or to interpret c...