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Automating Simulation Workflows for Sensitivity Analysis, Machine Learning and Optimization

In this webinar, you will learn how to automate simulation processes using a parameterized simulation model designed using Ansys and utilize the generated data for sensitivity studies, machine learning and optimization.

Venue:
Virtual

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Overview

Workflow automation produces dramatic benefits, such as reducing time and costs for product development, design optimization and data for AI and machine learning. In this webinar, we will show you how to automate simulation processes using a parameterized simulation model designed using Ansys and utilize the data generated for sensitivity studies, machine learning and optimization.

 

What You Will Learn

  • Set up simulation workflows with Ansys tools, parameterize and automate them. 
  • Automatically run multiple (hundreds or even thousands) of different designs. 
  • Perform sensitivity analysis (using proprietary statistical algorithms) for better design understanding and generate machine learning models from the data.
  • Improve the design by using state-of-the-art optimization algorithms where optimization can be performed with a reduced number of parameters, achieving extremely fast optimization by simulating thousands of designs in a few minutes through machine learning capabilities.

 

Who should attend

  • Simulation Engineers - to learn how to automate simulation processes, utilize data for machine learning and optimization.
  • Product designers, R&D engineers and managers in industrial equipment manufacturing.

 

Speaker

  • Markus Goldgruber, Principal Application Engineer, Ansys part of Synopsys

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