AirfoilGen generates valid airfoils with explicit control over aerodynamic performance using a novel circle-sweeping representation and a transformer-encoded conditional latent diffusion model.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
FluidFlow uses conditional flow-matching with U-Net and DiT architectures to predict pressure and friction coefficients on airfoils and 3D aircraft meshes, outperforming MLP baselines with better generalization.
citing papers explorer
-
AirfoilGen: A valid-by-construction and performance-aware latent diffusion model for airfoil generation
AirfoilGen generates valid airfoils with explicit control over aerodynamic performance using a novel circle-sweeping representation and a transformer-encoded conditional latent diffusion model.
-
FluidFlow: a flow-matching generative model for fluid dynamics surrogates on unstructured meshes
FluidFlow uses conditional flow-matching with U-Net and DiT architectures to predict pressure and friction coefficients on airfoils and 3D aircraft meshes, outperforming MLP baselines with better generalization.