Theses
CutFEM for Porous Media with CT-Based Geometries
Porous media derived from CT imaging often exhibit complex microstructures, thin features, and irregular interfaces, which make conforming mesh generation difficult for classical finite element methods. Cut Finite Element Methods (CutFEM) address this issue by embedding the physical domain into a fixed background mesh, significantly simplifying geometry handling while maintaining numerical accuracy. […]
Physics-informed neural networks for porous material
Coupled hydro-mechanical (HM) problems arise in a wide range of natural and engineered porous materials. Traditionally, these problems are solved using spatial discretization methods such as the finite element method (FEM) or the finite volume method (FVM). More recently, computational science has explored the application of physics-informed neural networks (PINNs), which provide a unified [...]
Digital Twin of Elastic Beam Deformation
Digital twins provide a virtual representation of engineering structures and allow the deformation state to be estimated from limited sensor data. In this thesis, a simulation-based digital twin of an elastic beam will be developed and evaluated. A high-fidelity Finite Element Method model will be used as the reference “real system” and provides the ground truth deformation of the beam. [...]