Description
ML/AI for Fluid Dynamics is a focused training program on machine learning and artificial intelligence for fluid mechanics.
It is designed for engineers, researchers, and students working with CFD and flow analysis.
The course is delivered in collaboration with the University of Michigan.
First, you will learn the basic ideas of machine learning.
Then, you will see how these methods apply to fluid dynamics problems.
As a result, you will understand how AI supports and improves traditional CFD.
What You Will Learn
- Basic machine learning concepts for fluid dynamics
- Data handling and feature extraction for flow problems
- Neural networks for flow prediction and analysis
- Reduced-order models for complex fluid systems
- AI-based methods for turbulence and flow control
- Limits and best practices of ML in CFD
Moreover, each topic includes clear explanations and practical examples.
Therefore, you will learn how to apply these methods correctly.
At the same time, you will understand their limits.
Instructor
The course is taught by Prof. Ricardo Vinuesa.
He is a faculty member at the University of Michigan.
His research focuses on fluid dynamics, AI, and data-driven modeling. This course is based on direct collaboration with Flowthermolab and the University of Michigan.
Finally, this course is suitable for academic research and industrial learning.
It helps you decide when AI methods add value to CFD problems.
