Reduced order models (ROMs) have become prevalent in many fields of physics as they offer the potential to simulate dynamical systems with substantially increased computation efficiency in comparison to standard techniques. Among the model reduction techniques, the proper orthogonal decomposition (POD) method has proven to be an efficient means of deriving a reduced basis for high-dimensional flow systems. The intrusive ROM (IROM) is normally derived by the POD and Galerkin projection methods. The IROM is appealing for non-linear and linear model reductions and has been successfully applied to numerous research fields. However, IROMs suffer from instability and non-linearity efficiency issues. In addition, they can be complex to code beca...
In this article, we describe a novel non-intrusive reduction model for three-dimensional (3D) free s...
International audienceThis paper focuses on improving the stability as well as the approximation pro...
This thesis presents advances in reduced-order modeling based on proper orthogonal decomposition (PO...
A novel non-intrusive reduced order model (NIROM) for fluid–structure interaction (FSI) has been dev...
A greedy nonintrusive reduced order method (ROM) is proposed for parameterized time-dependent proble...
A novel parameterized non-intrusive reduced order model (P-NIROM) based on proper orthogonal decompo...
This article presents two new non-intrusive reduced order models based upon proper orthogonal decomp...
A new method is presented to generate reduced order models (ROMs) in Fluid Dynamics problems. The me...
In this paper we present a new domain decomposition non-intrusive reduced order model (DDNIROM) for ...
International audienceThis study focuses on stabilizing Reduced Order Model based on Proper Orthogon...
This article presents two new non-intrusive reduced order models based upon proper orthogonal decomp...
This paper presents a non‐intrusive reduced order model for general, dynamic partial differential eq...
A novel reduced order model (ROM) for incompressible flows is developed by performing a Galerkin pro...
This work presents the first application of a non-intrusive reduced order method to model solid inte...
This paper deals with the construction of reduced order models (ROMs) for the simulation of the inte...
In this article, we describe a novel non-intrusive reduction model for three-dimensional (3D) free s...
International audienceThis paper focuses on improving the stability as well as the approximation pro...
This thesis presents advances in reduced-order modeling based on proper orthogonal decomposition (PO...
A novel non-intrusive reduced order model (NIROM) for fluid–structure interaction (FSI) has been dev...
A greedy nonintrusive reduced order method (ROM) is proposed for parameterized time-dependent proble...
A novel parameterized non-intrusive reduced order model (P-NIROM) based on proper orthogonal decompo...
This article presents two new non-intrusive reduced order models based upon proper orthogonal decomp...
A new method is presented to generate reduced order models (ROMs) in Fluid Dynamics problems. The me...
In this paper we present a new domain decomposition non-intrusive reduced order model (DDNIROM) for ...
International audienceThis study focuses on stabilizing Reduced Order Model based on Proper Orthogon...
This article presents two new non-intrusive reduced order models based upon proper orthogonal decomp...
This paper presents a non‐intrusive reduced order model for general, dynamic partial differential eq...
A novel reduced order model (ROM) for incompressible flows is developed by performing a Galerkin pro...
This work presents the first application of a non-intrusive reduced order method to model solid inte...
This paper deals with the construction of reduced order models (ROMs) for the simulation of the inte...
In this article, we describe a novel non-intrusive reduction model for three-dimensional (3D) free s...
International audienceThis paper focuses on improving the stability as well as the approximation pro...
This thesis presents advances in reduced-order modeling based on proper orthogonal decomposition (PO...