Getting the most out of Hexagon Adams simulations requires efficient use of the available simulation budget as well as validating that the simulation produces results that agree with reality. This webinar will discuss the role design of experiments, predictive machine learning models, and machine learning tools such as statistical calibration can play in calibrating Adams simulations to physical data, validating their accuracy, and maximizing the knowledge gained from their use.
Join us for this webinar in which SmartUQ principal application engineer, Gavin Jones, will introduce the use of SmartUQ for Adams simulation applications. SmartUQ’s ability to integrate with Adams will also be demonstrated and discussed.
