activity
20082023
most citedPositivity-preserving flux limiters for high-order conservative schemes

258 citations · 1.3k across the 49 of their papers we have counts for

collaborators

49 papers

physics.flu-dyn2023★ 2 cited

Extended Eulerian SPH and its realization of FVM

Zhentong Wang, Chi Zhang, Oskar J. Haidn +2

Eulerian smoothed particle hydrodynamics (Eulerian SPH) is considered as a potential meshless alternative to a traditional Eulerian mesh-based method, i.e. finite volume method (FV…

cs.LG2023★ 1 cited

Learning Lagrangian Fluid Mechanics with E()-Equivariant Graph Neural Networks

Artur P. Toshev, Gianluca Galletti, Johannes Brandstetter +2

We contribute to the vastly growing field of machine learning for engineering systems by demonstrating that equivariant graph neural networks have the potential to learn more accur…

physics.comp-ph2023

A 2D hybrid method for interfacial transport of passive scalars

Yu Fan, Yujie Zhu, Xiaoliang Li +2

A hybrid Eulerian-Lagrangian method is proposed to simulate passive scalar transport on arbitrary shape interface. In this method, interface deformation is tracked by an Eulerian m…

cs.LG2023★ 1 cited

E() Equivariant Graph Neural Networks for Particle-Based Fluid Mechanics

Artur P. Toshev, Gianluca Galletti, Johannes Brandstetter +2

We contribute to the vastly growing field of machine learning for engineering systems by demonstrating that equivariant graph neural networks have the potential to learn more accur…

cs.LG2023★ 2 cited

On the Relationships between Graph Neural Networks for the Simulation of Physical Systems and Classical Numerical Methods

Artur P. Toshev, Ludger Paehler, Andrea Panizza +1

Recent developments in Machine Learning approaches for modelling physical systems have begun to mirror the past development of numerical methods in the computational sciences. In t…

physics.flu-dyn2023

An efficient and robust all-Mach consistent numerical scheme for simulation of compressible multi-component fluids including surface tension, cavitation, turbulence modeling and interface sharpening on compact stencils

Yu Jiao, Steffen J. Schmidt, Nikolaus A. Adams

We present an efficient, fully conservative numerical scheme valid in the entire range of highly to weakly compressible flows using a single-fluid four equation approach together w…