activity
20242026
collaborators

10 papers

math.NA2026

Numerical analysis of the Biot equations coupled to frictional contact mechanics

Marius Nevland, Kundan Kumar, Inga Berre +2

We consider a mathematical model of a poro-visco-elastic medium subject to frictional contact with a rigid obstacle, and study its numerical approximation. This model couples the B…

math.NA2026

Splitting-strategies for arbitrary-order fully mixed finite element discretizations of the Biot equations

Fleurianne Bertrand, Jakub Wiktor Both, Tugay Dağlı +1

We study the fully-mixed formulation of the Biot equations which is characterized by a symmetric coupling between flow and deformation while each subphysics has internally a saddle…

math.NA2026

Efficient design of continuation methods for hyperbolic transport problems in porous media

Peter von Schultzendorff, Jakub Wiktor Both, Jan Martin Nordbotten +1

Full-physics modeling of multiphase flow in porous media, e.g., for carbon storage and groundwater management, requires the nonlinear coupling of various physical processes. Indust…

cs.LG2026

Partial Differential Equations in the Age of Machine Learning: A Critical Synthesis of Classical, Machine Learning, and Hybrid Methods

Mohammad Nooraiepour, Jakub Wiktor Both, Teeratorn Kadeethum +1

Partial differential equations (PDEs) govern physical phenomena across the full range of scientific scales, yet their computational solution remains one of the defining challenges…

physics.geo-ph2026

Consistent initialization of mixed-dimensional multiphysics models for fractured reservoirs under geomechanical constraints and field measurements

Jakub Wiktor Both, Inga Berre

Modeling coupled processes in fractured porous media -- flow, deformation, fracture mechanics, and thermal/chemical effects -- often relies on mixed dimensional multiphysics formul…

math.NA2026

A Machine-Learned Near-Well Model in OPM Flow

Peter von Schultzendorff, Tor Harald Sandve, Birane Kane +3

Recent advances in reservoir simulation increasingly utilize hybrid approaches that couple physics-based simulators with machine-learning (ML) components. ML components offer high…