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.
ONERA’s CRM WBPN database for machine learning activities, related regression challenge and first results.Computers & Fluids, 302:106838, November 2025
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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.