1 citations · 1 across the 5 of their papers we have counts for
6 papers
Directional flow in perivascular networks: Mixed finite elements for reduced-dimensional models on graphs
Ingeborg G. Gjerde, Miroslav Kuchta, Marie E. Rognes +1
The flow of cerebrospinal fluid through the perivascular spaces of the brain is believed to play a crucial role in eliminating toxic waste proteins. While the driving forces of thi…
Robust Preconditioning of mixed-dimensional PDEs on 3d-1d domains coupled with Lagrange multipliers
Nunzio Dimola, Miroslav Kuchta, Kent-Andre Mardal +1
In the context of micro-circulation, the coexistence of two distinct length scales - the vascular radius and the tissue/organ scale - with a substantial difference in magnitude, po…
Algebraic multigrid methods for metric-perturbed coupled problems
Ana Budisa, Xiaozhe Hu, Miroslav Kuchta +2
We develop multilevel methods for interface-driven multiphysics problems that can be coupled across dimensions and where complexity and strength of the interface coupling deteriora…
The modelling error in multi-dimensional time-dependent solute transport models
Rami Masri, Marius Zeinhofer, Miroslav Kuchta +1
Starting from full-dimensional models of solute transport, we derive and analyze multi-dimensional models of time-dependent convection, diffusion, and exchange in and around pulsat…
Rational approximation preconditioners for multiphysics problems
Ana Budisa, Xiaozhe Hu, Miroslav Kuchta +2
We consider a class of mathematical models describing multiphysics phenomena interacting through interfaces. On such interfaces, the traces of the fields lie (approximately) in the…
Investigating molecular transport in the human brain from MRI with physics-informed neural networks
Bastian Zapf, Johannes Haubner, Miroslav Kuchta +3
In recent years, a plethora of methods combining deep neural networks and partial differential equations have been developed. A widely known and popular example are physics-informe…