DREAM-GNN, a multiscale graph neural network with boundary-aware features, predicts turbulent flow-thermal fields around spline-parameterized pin-fins accurately and about 500x faster than RANS CFD.
Flow reconstruction in time - varying geometries using graph neural networks,
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Multiscale Graph Neural Network for Turbulent Flow-Thermal Prediction Around a Complex-Shaped Pin-Fin
DREAM-GNN, a multiscale graph neural network with boundary-aware features, predicts turbulent flow-thermal fields around spline-parameterized pin-fins accurately and about 500x faster than RANS CFD.