Toward Generalizable Graph Learning for 3D Engineering AI: Explainable Workflows for CAE Mode Shape Classification and CFD Field Prediction

Toward Generalizable Graph Learning for 3D Engineering AI: Explainable Workflows for CAE Mode Shape Classification and CFD Field Prediction explores A graph learning framework for 3D engineering AI that converts heterogeneous data into physics-aware graph representations for explainable CAE and CFD decision support.. Commercial viability score: 7/10 in Graph Neural Networks.