Tag: neural operator

CFD

Proposes periodic Fourier Neural Mapping (p-FNM), a neural-operator framework for rapid prediction of unsteady pressure distributions on turbine rotor blades, targeting aeroelastic analysis in turbomachinery.

CFD

Proposes a geometry-aware anisotropic boundary correction method using neural operators as an efficient alternative to traditional CFD solvers for aerodynamic simulation, improving physical modeling near solid boundaries.

ScientificML

GENERIC-FNO embeds the metriplectic degeneracy structure of nonequilibrium thermodynamics into Fourier neural operators, coupling reversible energy-conserving and irreversible entropy-producing dynamics via degeneracy conditions, extending structure-preserving neural operators beyond single conservation laws.

CFD

Proposes WaveOp-LiteFM, a lightweight neural-operator flow matching approach that addresses the trade-off between computational cost and accuracy in satellite-to-radar precipitation retrieval for atmospheric remote sensing applications.