High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention

In three linesGeoTransolver, a geometry-aware operator learning framework, accurately predicts industrial-scale automotive crash dynamics. On bumper beam and full-vehicle crash datasets, it captures plastic deformations and acceleration profiles. A FLARE-based modification reduces memory overhead by 2x while improving accuracy for high-frequency transients.

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