Wenzheng Xu

Replacing costly aggregate-resolved impact simulations with graph neural operators yields a 4,000x acceleration in predicting dynamic 6-component stress tensors, sidestepping the severe erosion artifacts that compromise standard scalar penetration metrics.

Autoregressive predictions in transient dynamics can be stabilized with a physics-informed approach that constrains spectral properties, outperforming traditional neural operators.