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Adrien Leygue
Researcher at École centrale de Nantes
Publications - 92
Citations - 2699
Adrien Leygue is an academic researcher from École centrale de Nantes. The author has contributed to research in topics: Parametric statistics & Constitutive equation. The author has an hindex of 24, co-authored 88 publications receiving 2343 citations. Previous affiliations of Adrien Leygue include École Centrale Paris & University of Nantes.
Papers
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Book
The Proper Generalized Decomposition for Advanced Numerical Simulations: A Primer
TL;DR: The present text is the first available book describing the Proper Generalized Decomposition (PGD), and provides a very readable and practical introduction that allows the reader to quickly grasp the main features of the method.
Journal ArticleDOI
PGD-Based Computational Vademecum for Efficient Design, Optimization and Control
Francisco Chinesta,Adrien Leygue,Felipe Bordeu,Jose Vicente Aguado,Elías Cueto,David González,Icíar Alfaro,Amine Ammar,Antonio Huerta +8 more
TL;DR: A new paradigm in the field of simulation-based engineering sciences (SBES) to face the challenges posed by current ICT technologies is addressed, by combining an off-line stage in which the general PGD solution, the vademecum, is computed, and an on-line phase in which real-time response is obtained as a result of the queries.
Journal ArticleDOI
An overview of the proper generalized decomposition with applications in computational rheology
TL;DR: The use of the PGD is illustrated in four problem categories related to computational rheology: the direct solution of the Fokker-Planck equation for complex fluids in configuration spaces of high dimension, the development of very efficient non-incremental algorithms for transient problems, and the solution of multidimensional parametric models obtained by introducing various sources of problem variability as additional coordinates.
BookDOI
The Proper Generalized Decomposition for Advanced Numerical Simulations
TL;DR: The Proper Generalized Decomposition (PGD) method as mentioned in this paper is a technique for solving high-dimensional problems in science and engineering that has proven to be a significant step forward.
Journal ArticleDOI
Advanced simulation of models defined in plate geometries: 3D solutions with 2D computational complexity
TL;DR: In-plane–out-of-plane separated representation of the involved fields within the context of the Proper Generalized Decomposition allows solving the fully 3D model by keeping a 2D characteristic computational complexity, without affecting the solvability of the resulting multidimensional model.