4 citations · 6 across the 7 of their papers we have counts for
7 papers
LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite
Artur P. Toshev, Gianluca Galletti, Fabian Fritz +2
Machine learning has been successfully applied to grid-based PDE modeling in various scientific applications. However, learned PDE solvers based on Lagrangian particle discretizati…
A variable speed of sound formulation for weakly compressible smoothed particle hydrodynamics
Fabian Thiery, Nikolaus A. Adams, Stefan Adami
We present a Weakly Compressible SPH (WCSPH) formulation with a temporally variable speed of sound. The benefits of a time-varying sound speed formulation and the weaknesses of a c…
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…
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…
Inferring incompressible two-phase flow fields from the interface motion using physics-informed neural networks
Aaron B. Buhendwa, Stefan Adami, Nikolaus A. Adams
In this work, physics-informed neural networks are applied to incompressible two-phase flow problems. We investigate the forward problem, where the governing equations are solved f…
A modular massively parallel computing environment for three-dimensional multiresolution simulations of compressible flows
Nils Hoppe, Stefan Adami, Nikolaus A. Adams
Numerical investigation of compressible flows faces two main challenges. In order to accurately describe the flow characteristics, high-resolution nonlinear numerical schemes are n…
Tipstreaming of a drop in simple shear flow in the presence of surfactant
S. Adami, X. Y. Hu, N. A. Adams
We have developed a multi-phase SPH method to simulate arbitrary interfaces containing surface active agents (surfactants) that locally change the properties of the interface, such…