4 papers
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,…
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…
Surrogate-assisted multi-objective design of complex multibody systems
Augustina C. Amakor, Manuel B. Berkemeier, Meike Wohlleben +2
The optimization of large-scale multibody systems is a numerically challenging task, in particular when considering multiple conflicting criteria at the same time. In this situatio…
The impact of AI on engineering design procedures for dynamical systems
Kristin M. de Payrebrune, Kathrin FlaÃkamp, Tom Ströhla +19
Artificial intelligence (AI) is driving transformative changes across numerous fields, revolutionizing conventional processes and creating new opportunities for innovation. The dev…