Conservative neural networks for Darcy flow
Deep learning based reduced order modeling of Darcy flow systems with local mass conservation
Recent Posts
Multipoint MFEM for Biot poroelasticity
Mixed and multipoint finite element methods for rotation-based poroelasticity
Presentation at ICIAM
Together with Martin Hornkjøl, Miroslav Kuchta, and Ricardo Ruiz-Baier, we organized the minisymposium Robust formulations for coupled multiphysics problems ...
Elasticity with point sources
Analysis of Linearized Elasticity Models with Point Sources in Weighted Sobolev Spaces: Applications in Tissue Contraction
SIAM GS 23
Excited to be part of the Scientific Organizing Committee of the SIAM Conference on Mathematical & Computational Issues in the Geosciences.
PyGeoN v0.3
We released a new version of our open-source software PyGeoN: A Python package for Geo-Numerics. This release features several new discretization schemes, in...
Presentation at University of Oslo
The department of Mathematics of the University of Oslo invited me to give a talk in their mechanics seminar series. See the website of UiO for more informat...
Multipoint MFEM for Stokes flow
A multipoint vorticity mixed finite element method for incompressible Stokes flow
Flux-mortars with MPFA
Flux-mortar mixed finite element methods with multipoint flux approximation
Reduced Basis Methods with local mass conservation
A Reduced Basis Method for Darcy flow systems that ensures local mass conservation by using exact discrete complexes
Mixed-dimensional poromechanics
Mixed-dimensional poromechanical models of fractured porous media
PyGeoN v0.2
Happy to announce the next release of our open-source software PyGeoN: A Python package for Geo-Numerics.