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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Vydáno v:	Journal of computational and applied mathematics Ročník 469; s. 116663
Hlavní autoři:	Griese, Franziska, Hoppe, Fabian, Rüttgers, Alexander, Knechtges, Philipp
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.12.2025
Témata:	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
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