LTS: A Lightweight Persistent-Latent Reformulation of Transolver for Transient Impact Simulation
Chia F Liao ⋅ Lin Chou ⋅ Shih-Chi Wang
Abstract
Physics surrogates accelerate engineering analysis, but Transolver-based models repeatedly route between full-resolution meshes and latent tokens in every Physics-Attention block, incurring substantial cost. We adopt single-pass latent projection within the Transolver backbone and obtain LTS, a Lightweight Transolver Surrogate that constructs physics-aware latent tokens once, processes them persistently through all intermediate blocks, reconstructs node features only at the output, and applies lightweight component and global adaptation after decoding. On DropTest, a fixed-topology industrial phone-drop benchmark, LTS reduces train-step latency by 84.6%, peak allocated training memory by 82.5%, and inference latency across all 99 independently queried target states by 86.9% relative to a depth-matched Transolver. It also lowers stress relative $\mathrm{L}_2$ error from 3.54% to 2.85%, while displacement relative $\mathrm{L}_2$ error increases from 0.47% to 0.64%. Routing-frequency experiments show that accuracy gains from re-routing are non-monotonic, whereas computational cost increases substantially. These results characterize the accuracy--efficiency trade-off of persistent latent processing in transient impact simulation.
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