Large-scale graph-machine-learning surrogate models for 3D-flowfield prediction in external aerodynamics

Large-scale graph-machine-learning surrogate models for 3D-flowfield prediction in external aerodynamics

Abstract The article presents the application of inductive graph machine learning surrogate models for accurate and efficient prediction of 3D flow for industrial geometries, explicitly focusing here on external aerodynamics for a motorsport case. The final aim is to build a surrogate model that can...

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Bibliographic Details
Main Authors: Davide Roznowicz, Giovanni Stabile, Nicola Demo, Davide Fransos, Gianluigi Rozza
Format: Article
Language:English
Published: SpringerOpen 2024-03-01
Series:Advanced Modeling and Simulation in Engineering Sciences
Subjects:
Computational fluid dynamics
Graph machine learning
External aerodynamics
Large scale model
3D surrogate model
Online Access:https://doi.org/10.1186/s40323-024-00259-1

Internet

https://doi.org/10.1186/s40323-024-00259-1

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