13 citations · 13 across the 2 of their papers we have counts for
3 papers · 1 filter
Quantifying data needs in surrogate modeling for flow fields in two-dimensional stirred tanks with physics-informed neural networks
Veronika Trávníková, Eric von Lieres, Marek Behr
Stirred tanks are vital in chemical and biotechnological processes, particularly as bioreactors. Although computational fluid dynamics (CFD) is widely used to model the flow in sti…
An Ising Machine Formulation for Design Updates in Topology Optimization of Flow Channels
Yudai Suzuki, Shiori Aoki, Fabian Key +5
Topology optimization is an essential tool in computational engineering, for example, to improve the design and efficiency of flow channels. At the same time, Ising machines, inclu…
A Model Hierarchy for Predicting the Flow in Stirred Tanks with Physics-Informed Neural Networks
Veronika Trávníková, Daniel Wolff, Nico Dirkes +3
This paper explores the potential of Physics-Informed Neural Networks (PINNs) to serve as Reduced Order Models (ROMs) for simulating the flow field within stirred tank reactors (ST…