Building AI Surrogate Models for Structural and Automotive Crash Analysis with NVIDIA PhysicsNeMo
Simulating automotive crash is one of the most complex computational workloads in computer-aided engineering (CAE). Crash simulation is a highly non-linear, dynamic event that happens in milliseconds. Therefore automotive crash simulations face significant bottlenecks in both human-driven workflows and raw computational demands. These challenges stem from the need to model highly non-linear, split-second events with extreme accuracy to meet strict regulatory standards (like NHTSA or Euro NCAP).
This post explains how to build an AI surrogate model for structural and automotive crash analysis with NVIDIA PhysicsNeMo, from finite element data curation and architecture selection through temporal training and validation.