Radha Krishnan on AI-Powered Simulation & Engineering Workflows
IT Voice- How is the convergence of AI and physics-based simulation changing the traditional approach to engineering and product development? What does this mean for the future of engineering teams?
Radha Krishnan-Traditional engineering has always moved in slow, sequential loops. You build a CAD model, mesh it, run an FEA or CFD solver overnight, and then realize you need to tweak the geometry all over again. Combining machine learning with first-principles physics completely breaks that cycle. By training reduced-order models directly on validated simulation data, we get near-instant feedback on design variations. Rather than waiting hours for an Ansys or Nastran run to finish, an engineer can explore performance curves in milliseconds. Teams change as a result. Engineers won’t spend half their weeks setting up boundary conditions or troubleshooting meshes. Instead, they operate more like system architects, evaluating trade-offs across crash, NVH, and thermal targets at the same time....
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