A conditional denoising diffusion model with PCA reparameterization and a signal-aware training objective predicts transonic wing pressure fields more accurately than deterministic baselines, particularly at suction peaks, shocks, and control surface features.
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Signal-Aware Conditional Diffusion Surrogates for Transonic Wing Pressure Prediction
A conditional denoising diffusion model with PCA reparameterization and a signal-aware training objective predicts transonic wing pressure fields more accurately than deterministic baselines, particularly at suction peaks, shocks, and control surface features.