Prof. Dr. Bernat Font, Data-Informed Computational Fluid Dynamics (DI-CFD) research group, TU Delft, The Netherlands

Title: Data-informed CFD: From RL for active flow control to optimal numerical methods using AD

Abstract:

The advancement of scientific machine learning (SciML) has reshaped how we control, model, and compute turbulent flows. Together with the widespread use of graphics processing units, we are now in a unique position to perform scale-resolving simulations combining data-driven techniques with classic methods, yielding the data-informed CFD paradigm. In this talk, we will review established numerical methods and physical models which can be enhanced through data, including linear solvers, turbulence models, and active flow control techniques. We will also discuss the solver-in-the-loop optimization approach using automatic differentiation, thus avoiding well-known a-priori/a-posteriori errors. Last, we will conclude with basic guidelines in the use of SciML for CFD.

How to join online

You can join online via Zoom, using the following link:
https://uni-kl-de.zoom-x.de/j/69269239534?pwd=Z9UOzMpkhMjrxVhll3d49sNHFe9Fd1.1