3 papers
cs.LG2025
Improving the Robustness of Control of Chaotic Convective Flows with Domain-Informed Reinforcement Learning
Michiel Straat, Thorben Markmann, Sebastian Peitz +1
Chaotic convective flows arise in many real-world systems, such as microfluidic devices and chemical reactors. Stabilizing these flows is highly desirable but remains challenging,…
physics.flu-dyn2025
Control of Rayleigh-Bénard Convection: Effectiveness of Reinforcement Learning in the Turbulent Regime
Thorben Markmann, Michiel Straat, Sebastian Peitz +1
Data-driven flow control has significant potential for industry, energy systems, and climate science. In this work, we study the effectiveness of Reinforcement Learning (RL) for re…
physics.flu-dyn2025
Solving Turbulent Rayleigh-Bénard Convection using Fourier Neural Operators
Michiel Straat, Thorben Markmann, Barbara Hammer
We train Fourier Neural Operator (FNO) surrogate models for Rayleigh-Bénard Convection (RBC), a model for convection processes that occur in nature and industrial settings. We com…