23 citations · 26 across the 17 of their papers we have counts for
17 papers
A cut finite element method for the Biot system of poroelasticity
Nanna Berre, Kent-Andre Mardal, André Massing +1
We propose a novel cut finite element method for the numerical solution of the Biot system of poroelasticity. The Biot system couples elastic deformation of a porous solid with vis…
On a robust inf-sup condition for the Stokes problem in slender domains -- with application to preconditioning
Espen Sande, Timo Koch, Miroslav Kuchta +1
We identify a norm on the pressure variable in the Stokes equation that allows us to prove a continuous inf-sup condition with a constant independent of the domain's aspect ratio.…
Fully mixed virtual element schemes for a new model of steady-state poroelastic stress-assisted diffusion in the brain
Isaac Bermudez, Bryan Gomez-Vargas, Kent-Andre Mardal +2
We propose a fully mixed virtual element method for the numerical approximation of the coupling between linear poroelasticity equations with strong symmetry of total poroelastic st…
Geometry Reduced Order Modeling (GROM) with application to modeling of glymphatic function
Andreas Solheim, Geir Ringstand, Per Kristian Eide +1
Computational modeling of the brain has become a key part of understanding how the brain clears metabolic waste, but patient-specific modeling on a significant scale is still out o…
Parameter-robust preconditioner for Stokes-Darcy coupled problem with Lagrange multiplier
Xiaozhe Hu, Miroslav Kuchta, Kent-Andre Mardal +1
In this paper, we propose a parameter-robust preconditioner for the coupled Stokes-Darcy problem equipped with various boundary conditions, enforcing the mass conservation at the i…
Parameter-Robust Preconditioners for A Four-Field Thermo-Poroelasticity Model
Mingchao Cai, Miroslav Kuchta, Jingzhi Li +2
We study a thermo-poroelasticity model which describes the interaction between the deformation of an elastic porous material and fluid flow under non-isothermal conditions. The mod…
U-net based prediction of cerebrospinal fluid distribution and ventricular reflux grading
Melanie Rieff, Fabian Holzberger, Oksana Lapina +6
Previous work indicates evidence that cerebrospinal fluid (CSF) plays a crucial role in brain waste clearance processes, and that altered flow patterns are associated with various…
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…
Efficient and reliable divergence-conforming methods for an elasticity-poroelasticity interface problem
S. Badia, M. Hornkjøl, A. Khan +3
We present a finite element discretisation to model the interaction between a poroelastic structure and an elastic medium. The consolidation problem considers fully coupled deforma…
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…
HAZniCS -- Software Components for Multiphysics Problems
Ana Budisa, Xiaozhe Hu, Miroslav Kuchta +2
We introduce the software toolbox HAZniCS for solving interface-coupled multiphysics problems. HAZniCS is a suite of modules that combines the well-known FEniCS framework for finit…
Model order reduction of solidification problems
Florian Arbes, Øyvind Jensen, Kent-Andre Mardal +1
Advection driven problems are known to be difficult to model with a reduced basis because of a slow decay of the Kolmogorov -width. This paper investigates how this challenge tr…
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…
Robust approximation of generalized Biot-Brinkman problems
Q. Hong, J. Kraus, M. Kuchta +3
The generalized Biot-Brinkman equations describe the displacement, pressures and fluxes in an elastic medium permeated by multiple viscous fluid networks and can be used to study c…
Parameter-robust methods for the Biot-Stokes interfacial coupling without Lagrange multipliers
Wietse M. Boon, Martin Hornkjøl, Miroslav Kuchta +2
In this paper we advance the analysis of discretizations for a fluid-structure interaction model of the monolithic coupling between the free flow of a viscous Newtonian fluid and a…
Robust monolithic solvers for the Stokes-Darcy problem with the Darcy equation in primal form
Wietse M. Boon, Timo Koch, Miroslav Kuchta +1
We construct mesh-independent and parameter-robust monolithic solvers for the coupled primal Stokes-Darcy problem. Three different formulations and their discretizations in terms o…