most citedAero-Nef: Neural Fields for Rapid Aircraft Aerodynamics Simulations

36 citations · 36 across the 4 of their papers we have counts for

collaborators
Showing physics.flu-dynShow all

1 paper · 1 filter

physics.flu-dyn2025

Towards scalable surrogate models based on Neural Fields for large scale aerodynamic simulations

Giovanni Catalani, Jean Fesquet, Xavier Bertrand +3

This paper introduces a novel surrogate modeling framework for aerodynamic applications based on Neural Fields. The proposed approach, MARIO (Modulated Aerodynamic Resolution Invar…