Get simulation results 10,000x faster, claims Xccelerate AI.
Late last week, Xccelerate AI announced its new AI-based framework for engineering simulations, Pearl CAE. The tool is the latest integration of AI and CAE technology that produces easy to compute surrogate models that can replace complex simulation models in certain situations. The aim is to reduce the computational time of simulations without limiting the quality of results. In theory, this could enable engineers to assess more product design options, explore the design space and better optimize final products.
“By leveraging advanced machine learning, we’ve turned what used to be weeks of computation into mere seconds, without sacrificing accuracy,” said Kaan Inal, the lead visionary behind Xccelerate, AI in a release. “This is more than just a step change; it’s a whole new paradigm that opens limitless possibilities for innovation across industries.”
Pearl CAE trains the surrogate models based on the existing simulation data many organizations will already have. The idea is that by using internal CAE data, the user gets a bespoke model that is optimized to their own use cases. Xccelerate AI notes that with the right data, training an algorithm can take a few days. However, if the data needs to be collected, the company also offers consulting services to produce the simulation models and data required to train the algorithms.
Though the tool was originally designed to serve engineers producing structural analyses for the automotive industry, Xccelerate AI has expanded Pearl CAE’s applicability to any engineer using digital simulation for product and manufacturing design.
For more on how AI will affect simulation in 2024, read: 10 AI Features for Simulation Engineers Coming in 2024.
