CAE Computational Scaling Challenges Solved by Data and AI-based Physics

Simulation-driven design has replaced most physical prototyping as it enables early and frequent assessments of a product’s design space. As products become more complex, however, simulations have become a new bottleneck for product design cycles. The computational power needed to produce these complex simulations with reasonable speed, accuracy, and cost is becoming a challenge for large organizations — let alone small-to-medium businesses.

This white paper explores how simulation-heavy, design processes that produce a lot of data can be used as a catalyst to nullify the bottleneck challenges of complex simulations. It discusses how the data can train AI models that return results orders-of-magnitude faster with all the accuracy of full simulations. It also explains how these AI models can be trained quickly mitigating the major bottleneck associated with AI tools.