Pre-training AeroTransformer on nearly 30,000 diverse wing geometries and fine-tuning with 450 specific samples achieves 0.36% error on surface-flow prediction for transonic wings, an 84.2% reduction versus training from scratch.
Numerical investigation of min- imum drag profiles in laminar flow using deep learning surrogates.Journal of Fluid Mechanics, 919, 2021
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Towards a Foundation-Model Paradigm for Aerodynamic Prediction in Three-dimensional Design
Pre-training AeroTransformer on nearly 30,000 diverse wing geometries and fine-tuning with 450 specific samples achieves 0.36% error on surface-flow prediction for transonic wings, an 84.2% reduction versus training from scratch.