Model Order Reduction (MOR) methods are applied in different areas of physics in order to reduce the computational time of large scale systems. It has been an active field of research for many years, in mechanics especially, but it is quite recent for magnetoquasistatic problems. Although the most famous method, the Proper Orthogonal Decomposition (POD) has been applied for modelling many electromagnetic devices, this method can lack accuracy for low order magnitude output quantities, like flux associated with a probe in regions where the field is low. However, the Balanced Proper Orthogonal Decomposition (BPOD) is a MOR method which takes into account these output quantities in its reduced model to render them accurately. Even if the BPOD ...
The Proper Orthogonal Decomposition (POD) combined with the (Discrete) Empirical Interpolation Metho...
Manufacturing new Magnetic Resonance Imaging (MRI) scanners represents a computational challenge to ...
The Proper Orthogonal Decomposition (POD) is an interesting approach to compress into a reduced basi...
International audienceModel Order Reduction (MOR) methods are applied in different areas of physics ...
The proper orthogonal decomposition method and Arnoldi-based Krylov projection method are investigat...
In order to reduce the computation time and the memory resources required to solve an electromagneti...
In the domain of numerical computation, Model Order Reduction approaches are more and more frequentl...
Among the model order reduction techniques, the Proper Orthogonal Decomposition (POD) has shown its ...
Proper Orthogonal Decomposition (POD) has been successfully used to reduce the size of linear Finite...
The design of a new magnetic resonance imaging (MRI) scanner requires multiple numerical simulations...
Model order reduction methods, like the proper orthogonal decomposition (POD), enable to reduce dram...
International audienceThe Proper Orthogonal Decomposition method and the Arnoldi-based Krylov projec...
In this paper, proper orthogonal decomposition method is employed to build a reduced-order model fro...
The Proper Orthogonal Decomposition (POD) combined with the (Discrete) Empirical Interpolation Metho...
Proper Orthogonal Decomposition (POD) is an efficient model order reduction technique for linear pro...
The Proper Orthogonal Decomposition (POD) combined with the (Discrete) Empirical Interpolation Metho...
Manufacturing new Magnetic Resonance Imaging (MRI) scanners represents a computational challenge to ...
The Proper Orthogonal Decomposition (POD) is an interesting approach to compress into a reduced basi...
International audienceModel Order Reduction (MOR) methods are applied in different areas of physics ...
The proper orthogonal decomposition method and Arnoldi-based Krylov projection method are investigat...
In order to reduce the computation time and the memory resources required to solve an electromagneti...
In the domain of numerical computation, Model Order Reduction approaches are more and more frequentl...
Among the model order reduction techniques, the Proper Orthogonal Decomposition (POD) has shown its ...
Proper Orthogonal Decomposition (POD) has been successfully used to reduce the size of linear Finite...
The design of a new magnetic resonance imaging (MRI) scanner requires multiple numerical simulations...
Model order reduction methods, like the proper orthogonal decomposition (POD), enable to reduce dram...
International audienceThe Proper Orthogonal Decomposition method and the Arnoldi-based Krylov projec...
In this paper, proper orthogonal decomposition method is employed to build a reduced-order model fro...
The Proper Orthogonal Decomposition (POD) combined with the (Discrete) Empirical Interpolation Metho...
Proper Orthogonal Decomposition (POD) is an efficient model order reduction technique for linear pro...
The Proper Orthogonal Decomposition (POD) combined with the (Discrete) Empirical Interpolation Metho...
Manufacturing new Magnetic Resonance Imaging (MRI) scanners represents a computational challenge to ...
The Proper Orthogonal Decomposition (POD) is an interesting approach to compress into a reduced basi...