Sponsored
Do you know which input parameters are contributing to uncertainty in your simulation model? How robust are your designs to uncertainty?
Following the guidance and best practices documented by professional organizations such as FAA, FDA, AIAA, and ASME, you can use direct sampling to answer such questions, in a process known as sensitivity analysis. However, even for simple simulations with a modest run time, the direct approach may be too computationally expensive, thus infeasible.
In this webinar, we’ll show you how to use a predictive model trained using machine learning to simplify and speed up the process.
This webinar will show how to:


Gavin Jones
Principal Application Engineer
SmartUQ

Moderator: Kenneth Wong
Senior Editor
Digital Engineering

Brian Albright is the editorial director of Digital Engineering.
Contact him at [email protected].

Join over 90,000 engineering professionals who get fresh engineering news as soon as it is published.