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A short review on model order reduction based on proper generalized decomposition
This paper revisits a new model reduction methodology based on the use of separated
representations, the so called Proper Generalized Decomposition—PGD. Space and time …
representations, the so called Proper Generalized Decomposition—PGD. Space and time …
Recent advances and new challenges in the use of the proper generalized decomposition for solving multidimensional models
This paper revisits a powerful discretization technique, the Proper Generalized
Decomposition—PGD, illustrating its ability for solving highly multidimensional models. This …
Decomposition—PGD, illustrating its ability for solving highly multidimensional models. This …
PGD-Based Computational Vademecum for Efficient Design, Optimization and Control
In this paper we are addressing a new paradigm in the field of simulation-based engineering
sciences (SBES) to face the challenges posed by current ICT technologies. Despite the …
sciences (SBES) to face the challenges posed by current ICT technologies. Despite the …
Data-driven non-linear elasticity: constitutive manifold construction and problem discretization
The use of constitutive equations calibrated from data has been implemented into standard
numerical solvers for successfully addressing a variety problems encountered in simulation …
numerical solvers for successfully addressing a variety problems encountered in simulation …
An overview of the proper generalized decomposition with applications in computational rheology
We review the foundations and applications of the proper generalized decomposition (PGD),
a powerful model reduction technique that computes a priori by means of successive …
a powerful model reduction technique that computes a priori by means of successive …
Advanced simulation of models defined in plate geometries: 3D solutions with 2D computational complexity
Many models in polymer processing and composites manufacturing are defined in
degenerated three-dimensional domains, involving plate or shell geometries. The reduction …
degenerated three-dimensional domains, involving plate or shell geometries. The reduction …
A multidimensional data‐driven sparse identification technique: the sparse proper generalized decomposition
Sparse model identification by means of data is especially cumbersome if the sought
dynamics live in a high dimensional space. This usually involves the need for large amount …
dynamics live in a high dimensional space. This usually involves the need for large amount …
Fast alternating LS algorithms for high order CANDECOMP/PARAFAC tensor factorizations
CANDECOMP/PARAFAC (CP) has found numerous applications in wide variety of areas
such as in chemometrics, telecommunication, data mining, neuroscience, separated …
such as in chemometrics, telecommunication, data mining, neuroscience, separated …
Proper generalized decompositions and separated representations for the numerical solution of high dimensional stochastic problems
Uncertainty quantification and propagation in physical systems appear as a critical path for
the improvement of the prediction of their response. Galerkin-type spectral stochastic …
the improvement of the prediction of their response. Galerkin-type spectral stochastic …
[PDF][PDF] Model order reduction
This chapter presents an overview of Model Order Reduction–a new paradigm in the field of
simulationbased engineering sciences, and one that can tackle the challenges and leverage …
simulationbased engineering sciences, and one that can tackle the challenges and leverage …