A graph learning framework turns heterogeneous 3D engineering data into physics-aware graphs processed by GNNs for CAE mode classification and CFD field prediction in automotive applications.
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Toward Generalizable Graph Learning for 3D Engineering AI: Explainable Workflows for CAE Mode Shape Classification and CFD Field Prediction
A graph learning framework turns heterogeneous 3D engineering data into physics-aware graphs processed by GNNs for CAE mode classification and CFD field prediction in automotive applications.