Mesh deformation based on artificial neural networks

DOI10.1080/10618562.2011.619500zbMath1271.76286OpenAlexW1989998887MaRDI QIDQ2847522

Domen Stadler, Andrej Lipej, Franc Kosel, Damjan Čelič

Publication date: 10 September 2013

Published in: International Journal of Computational Fluid Dynamics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10618562.2011.619500

zbMATH Keywords

artificial neural networksback-propagation learning algorithmmesh deformationFrancis water turbinemesh quality criteria

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Mesh generation, refinement, and adaptive methods for boundary value problems involving PDEs (65N50) Mesh generation, refinement, and adaptive methods for the numerical solution of initial value and initial-boundary value problems involving PDEs (65M50) Basic methods in fluid mechanics (76M99)

Related Items (4)

A novel three-dimensional mesh deformation method based on sphere relaxation ⋮ A study on numerical methods for transient rotating flow induced by starting blades ⋮ Developing a new mesh deformation technique based on support vector machine ⋮ Delaunay Graph Based Inverse Distance Weighting for Fast Dynamic Meshing

Cites Work

• Transonic velocity fluctuations simulated using extremum diminishing uncertainty quantification based on inverse distance weighting
• Multilayer feedforward networks are universal approximators
• Multivariate interpolation for fluid-structure-interaction problems using radial basis functions
• Approximation by superpositions of a sigmoidal function

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