aerodynamic data generation 1bézier surface manifolds 1computational fluid dynamics 1generative adversarial networks 1intrinsic geometry 1radial basis function discriminator 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.LG2026
IG-GAN: A Generative Adversarial Network for Aerodynamic Data Generation Based on Intrinsic Geometry
Ying Yan, Liwei Hu, Xiaoming Zhang
The paper introduces IG‑GAN, a generative adversarial network that creates aerodynamic data by modeling it as a piecewise smooth manifold of Bézier surfaces and using a radial‑basi…
cs.LG2026
Geodesic Gradient Descent: A Generic and Learning-rate-free Optimizer on Objective Function-induced Manifolds
Liwei Hu, Guangyao Li, Wenyong Wang +2
Euclidean gradient descent algorithms barely capture the geometry of objective function-induced hypersurfaces and risk driving update trajectories off the hypersurfaces. Riemannian…
cs.LG2024
Learning with Geometry: Including Riemannian Geometric Features in Coefficient of Pressure Prediction on Aircraft Wings
Liwei Hu, Wenyong Wang, Yu Xiang +1
We propose to incorporate Riemannian geometric features from the geometry of aircraft wing surfaces in the prediction of coefficient of pressure (CP) on the aircraft wing. Contrary…