A comparative study of Deep Neural Network architectures for the high-accuracy prediction of pressure coefficients ($C_p$) in low Reynolds number airfoils, achieving a 97.58% correlation with XFoil CFD data.
python data-science machine-learning deep-learning mechanical-engineering neural-networks research-project cfd fluid-dynamics aerodynamics keras-tensorflow xfoil airfoil-analysis beng-dissertation
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Updated
Mar 9, 2026