Complex Flow Systems (CFS) Laboratory

Complex flow — Beyond canonical flow configurations, we address real-world problems using simulations, experiments, high-performance computing, and data-driven methods.

Systems — We consider not only the flow itself, but also its integration into larger physical and computational systems, connecting complex flows with open-source software and optimization frameworks.

A collaborative research study lead by Christian Lagemann has been published in Nature. The study presents HydroGym, a computational platform that combines reinforcement learning (RL) and computational fluid dynamics (CFD) for the development of flow-control strategies. A particularly striking result of the study is that learned flow-control strategies can transfer to substantially different flow environments without retraining.

[PAPER]