3 papers
physics.flu-dyn2025
An octree-based sampling algorithm for analyzing big simulation data
Janis Geise, Sebastian Spinner, Richard Semaan +1
As computational resources continue to increase, the storage and analysis of vast amounts of data will inevitably become a bottleneck in computational fluid dynamics (CFD) and rela…
physics.flu-dyn2024
Dynamic mode decomposition of noisy flow data
Andre Weiner, Janis Geise
Dynamic mode decomposition (DMD) is a popular approach to analyzing and modeling fluid flows. In practice, datasets are almost always corrupted to some degree by noise. The vanilla…
physics.flu-dyn2024
Model-based deep reinforcement learning for accelerated learning from flow simulations
Andre Weiner, Janis Geise
In recent years, deep reinforcement learning has emerged as a technique to solve closed-loop flow control problems. Employing simulation-based environments in reinforcement learnin…