StampFormer: A Physics-Guided Material-Geometry-Coupled Multimodal Model for Rapid Prediction of Physical Fields in Sheet Metal Stamping

In three linesStampFormer is a multimodal deep learning model predicting physical fields in sheet metal stamping by fusing geometry and material properties. Tested on steel/aluminium panels, it achieves <8.5% relative error in <1 second, replacing costly FEA analyses.

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