Signal-Aware Conditional Diffusion Surrogates for Transonic Wing Pressure Prediction
Accurate and efficient surrogate models for aerodynamic surface pressure fields are essential for accelerating aircraft design and analysis, yet deterministic regressors trained with pointwise losses often smooth sharp nonlinear features. This work presents a conditional denoising diffusion probabilistic model for predicting surface pressure distributions on the NASA Common Research Model wing under varying conditions of Mach number, angle of attack, and four control surface deflections. The framework operates on unstructured surface data through a principal component representation used as a non-truncated, reversible linear reparameterization of the pressure field, enabling a fully conne...
| Authors | Víctor Francés-Belda, Carlos Sanmiguel Vila, Rodrigo Castellanos |
|---|---|
| Primary category | physics.flu-dyn |
| Published | 13 April 2026 |
| Last updated at source | 13 April 2026 |
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