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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…
cs.LG2024★ 15 cited
Combining Machine Learning with Computational Fluid Dynamics using OpenFOAM and SmartSim
Tomislav Maric, Mohammed Elwardi Fadeli, Alessandro Rigazzi +2
Combining machine learning (ML) with computational fluid dynamics (CFD) opens many possibilities for improving simulations of technical and natural systems. However, CFD+ML algorit…