Machine Learning Tools for accelerating CAE and unleashing Design Exploration

As presented by Dimitris Drougkas from BETA CAE Systems at the 9th BEFORE REALITY Conference.
Machine learning tools have become increasingly prevalent in various software applications, offering numerous advantages and transforming the way we interact with technology. The challenge in the CAE-domain is to adapt and learn from the huge amount of Simulation data plus demanding load cases and complex physics. The ML-workflow which involves data collection and preparation, ML-model training and evaluation, and finally Prediction, is integrated into the BETA Products since v21.0.0.
The Prediction of scalar, 2d and 3d Simulation results give us the opportunity to use Machine learning for variety of applications.
The ML-based isolation of complex design components such as fasteners and clips can significantly reduce the modelling time.
Predictors as the ML-object in BETA Products enable CAE engineers to rapidly explore various design configurations without relying on time-consuming simulations. Engineers can now optimize their processes, streamline workflows and expedite the realization of innovative designs. In this presentation we will present the latest features along with some of the
most important applications.
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