Webinars

This webinar will discuss the role design of experiments, predictive machine learning models (aka surrogate models), and machine learning tools such as statistical calibration can play in accelerating CFD and maximizing the knowledge gained from the use of CFD. An area of focus for this webinar will be SmartUQ’s fast and accurate surrogate modeling approaches. For example, SmartUQ has developed non-parametric and mesh independent methods for predicting continuous output fields. For CFD this can mean rapid prediction of temperature, pressure, and velocity fields corresponding to new designs or conditions. This allows engineers to rapidly optimize designs and explore unlimited geometry variations up front rather than late in the design cycle. Compared to other methods, SmartUQ’s approaches require less data collected from CFD and run quickly and locally on standard desktop computing hardware, no HPC or Cloud data transfer needed. Your data and results stay secure in your environment. Join us for this webinar in which SmartUQ principal application engineer, Gavin Jones, will introduce the use of SmartUQ for CFD applications. Customer use cases from industries including aerospace, automotive, and semiconductor will be used for illustration of the tools and techniques discussed. SmartUQ’s ability to integrate with CFD tools such as ANSYS Fluent, STAR-CCM+, CFD++, and OpenFOAM will also be discussed.