1 citations · 2 across the 3 of their papers we have counts for
3 papers
math.NA2022★ 1 cited
Discretisations and Preconditioners for Magnetohydrodynamics Models
Fabian Laakmann
The magnetohydrodynamics (MHD) equations are generally known to be difficult to solve numerically, due to their highly nonlinear structure and the strong coupling between the elect…
math.NA2022
Structure-preserving and helicity-conserving finite element approximations and preconditioning for the Hall MHD equations
Fabian Laakmann, Patrick E. Farrell, Kaibo Hu
We develop structure-preserving finite element methods for the incompressible, resistive Hall magnetohydrodynamics (MHD) equations. These equations incorporate the Hall current ter…
math.NA2020★ 1 cited
Efficient Approximation of Solutions of Parametric Linear Transport Equations by ReLU DNNs
Fabian Laakmann, Philipp Petersen
We demonstrate that deep neural networks with the ReLU activation function can efficiently approximate the solutions of various types of parametric linear transport equations. For…