FREE WEBINAR APRIL 28: Using Machine Learning to Improve Certainty in Engineering Simulation

In this webinar, you will learn how to use a predictive model trained using machine learning to simplify and speed up the process of sensitivity analysis for your simulation models.

In this webinar, you will learn how to use a predictive model trained using machine learning to simplify and speed up the process of sensitivity analysis for your simulation models.

DATE: April 28, 2022
TIME: 02:00 PM EDT/ 11:00 AM PDT

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:

  • Use machine learning to develop a predictive model for both global and local sensitivity analysis;
  • Identify insignificant parameters to reduce complexity in simulation;
  • Apply the trained machine learning model to represent real-world scenarios.

Register here.

Speakers:

Gavin Jones
Principal Application Engineer
SmartUQ

Moderator: Kenneth Wong
Senior Editor
Digital Engineering

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