Modern AI methods can dramatically speed up engineering innovation. By learning from past engineering data, future engineering workflow steps can be accelerated or even automated. SimScale is built from the ground up to leverage AI methods along the simulation workflow and enable engineering teams to deploy them safely without any IT overhead.
Natively integrated deep learning capabilities allow training, deploying, and version modeling for instant physics predictions. These AI models enable engineering teams to explore design spaces faster, deeper, and broader than possible with traditional PDE solver methods. The capabilities, powered by NAVASTO, include:
Not just the actual physics simulation itself can be accelerated with SimScale’s AI capabilities, but also the setup. SimScale uses a constantly learning AI model to select the best HPC compute infrastructure for each simulation automatically. More such co-pilot capabilities will be released in the future based on the same architecture (e.g., automatically cleaning geometries, selecting the initial simulation setup, pre-conditioning steady-state simulations with AI results, and more).
See how SimScale’s AI simulation features sit side by side with traditional physics solvers, all accessed in a web browser.
See the new AI-powered simulation features launching in SimScale soon.
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