4 papers
Deep reinforcement learning for separation control in turbulent wind-tunnel flow
Sofia Avdiiv, Andre Weiner, Ben Steinfurth
This work investigates Deep Reinforcement Learning (DRL) as a tool for model-free closed-loop active separation control in a fully turbulent wind tunnel flow over a one-sided diffu…
Standing-Wave Dynamics in Low-Frequency Breathing of a Turbulent Separation Bubble
Lukas M. Fuchs, Ben Steinfurth, Jakob G. R. von Saldern +2
This study investigates the low-frequency dynamics of a turbulent separation bubble (TSB) over a backward-facing ramp, with a focus on large-scale coherent structures associated wi…
Optimizing pulsed blowing parameters for active separation control in a one-sided diffuser using reinforcement learning
Alexandra Müller, Tobias Schesny, Ben Steinfurth +1
Reinforcement learning is employed to optimize the periodic forcing signal of a pulsed blowing system that controls flow separation in a fully-turbulent diffuser flow…
Automatic extraction of wall streamlines from oil-flow visualizations using a convolutional neural network
Jonas Schulte-Sasse, Ben Steinfurth, Julien Weiss
Oil-flow visualizations represent a simple means to reveal time-averaged wall streamline patterns. Yet, the evaluation of such images can be a time-consuming process and is subject…