Preconditioned FEM-based neural networks for solving incompressible fluid flows and related inverse problems

The numerical simulation and optimization of technical systems described by partial differential equations is expensive, especially in multi-query scenarios in which the underlying equations have to be solved for different parameters. A comparatively new approach in this context is to combine the go...

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Veröffentlicht in:	Journal of computational and applied mathematics Jg. 469; S. 116663
Hauptverfasser:	Griese, Franziska, Hoppe, Fabian, Rüttgers, Alexander, Knechtges, Philipp
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.12.2025
Schlagworte:	FEM-based neural network Finite elements Machine learning Navier–Stokes Parametric PDEs Preconditioning Stokes Finite elements Stokes FEM-based neural network Machine learning Parametric PDEs Navier–Stokes Preconditioning
ISSN:	0377-0427
Online-Zugang:	Volltext
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