As design cycles tighten and engineered systems become more complex, companies are challenged to get the most out of their simulation and testing capabilities. There are a number of challenges faced when trying to fully leverage CAE models for which statistical methods can provide a powerful and viable solution.
This webinar will focus on strategies for handling three classes of CAE modeling challenges:
Some of the more powerful tools discussed in this webinar include Design of Experiments (DOEs), surrogate modeling, and statistical simulation calibration. Intelligent DOEs address the issue of inadequate and inefficient design space sampling. Surrogate models can augment computationally expensive simulations for design exploration and analysis. Statistical Calibration can be used to bridge the gap between simulations and physical testing, increasing the accuracy of simulation models while minimizing the number of physical tests required.
Webinar attendees will gain an understanding of how statistical methods can help increase early design phase efficiency, decrease the number of costly physical tests required to validate or calibrate CAE models, and reduce risks while increasing confidence in simulation models.