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September 10, 2025Physics of Fluids

Fast prediction of three-dimensional wing inviscid flow fields from sparse data based on an autoencoder and a deep attention network

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Novel deep learning method predicts flow fields in wing designs under sparse data, highlighting speed and accuracy.

The RAMLP model predicts flow field variables efficiently under sparse data conditions, outperforming traditional models.
Results demonstrate that RAMLP processes predictions in under one second, maintaining high accuracy compared to MLP and MHP.
The model utilizes an autoencoder for geometric feature extraction, transforming complex wing data into a manageable representation.
Comparative analysis shows RAMLP's effectiveness against standard aerodynamic surrogate models in flow field prediction.

Li et al. (2025) studied this question.

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