303 citations · 630 across the 13 of their papers we have counts for
13 papers
Mechanical modeling of the maturation process for tissue-engineered implants: application to biohybrid heart valves
Mahmoud Sesa, Hagen Holthusen, Lukas Lamm +4
The development of tissue-engineered cardiovascular implants can improve the lives of large segments of our society who suffer from cardiovascular diseases. Regenerative tissues ar…
Mixed formulation of physics-informed neural networks for thermo-mechanically coupled systems and heterogeneous domains
Ali Harandi, Ahmad Moeineddin, Michael Kaliske +2
Physics-informed neural networks (PINNs) are a new tool for solving boundary value problems by defining loss functions of neural networks based on governing equations, boundary con…
A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: comparison with finite element method
Shahed Rezaei, Ali Harandi, Ahmad Moeineddin +2
Physics-informed neural networks (PINNs) are capable of finding the solution for a given boundary value problem. We employ several ideas from the finite element method (FEM) to enh…
A multiphysics modeling approach for in-stent restenosis: Theoretical aspects and finite element implementation
Kiran Manjunatha, Marek Behr, Felix Vogt +1
Development of in silico models are intrinsic in understanding disease progression in soft biological tissues. Within this work, we propose a fully-coupled Lagrangian finite elemen…
Modeling moving boundary value problems in electrochemical machining
Tim van der Velden, Stephan Ritzert, Stefanie Reese +1
This work presents a new approach to efficiently model the cathode in the moving boundary value problem of electrochemical machining. Until recently, the process simulation with fi…
An anisotropic cohesive fracture model: advantages and limitations of length-scale insensitive phase-field damage models
Shahed Rezaei, Ali Harandi, Tim Brepols +1
The goal of the current work is to explore direction-dependent damage initiation and propagation within an arbitrary anisotropic solid. In particular, we aim at developing anisotro…
A macroscopic approach for stress driven anisotropic growth in bioengineered soft tissues
L. Lamm, H. Holthusen, T. Brepols +2
The simulation of growth processes within soft biological tissues is of utmost importance for many applications in the medical sector. Within this contribution we propose a new mac…
A geometrically adapted reduced set of frequencies for a FFT-based microstructure simulation
Christian Gierden, Johanna Waimann, Bob Svendsen +1
We present a modified model order reduction (MOR) technique for the FFT-based simulation of composite microstructures. It utilizes the earlier introduced MOR technique (Kochmann et…
A novel approach for the efficient modeling of material dissolution in electrochemical machining
Tim van der Velden, Bob Rommes, Andreas Klink +2
This work presents a novel approach to efficiently model anodic dissolution in electrochemical machining. Earlier modeling approaches employ a strict space discretization of the an…
Finite element modelling of in-stent restenosis
Kiran Manjunatha, Marek Behr, Felix Vogt +1
From the perspective of coronary heart disease, the development of stents has come significantly far in reducing the associated mortality rate, drug-eluting stents being the epitom…
Model-free Data-Driven Computational Mechanics Enhanced by Tensor Voting
Robert Eggersmann, Laurent Stainier, Michael Ortiz +1
The data-driven computing paradigm initially introduced by Kirchdoerfer & Ortiz (2016) is extended by incorporating locally linear tangent spaces into the data set. These tangent s…
Proper orthogonal decomposition (POD) combined with hierarchical tensor approximation (HTA) in the context of uncertain parameters
Steffen Kastian, Dieter Moser, Stefanie Reese +1
The evaluation of robustness and reliability of realistic structures in the presence of uncertainty involves costly numerical simulations with a very high number of evaluations. Th…
Model-Free Data-Driven Inelasticity
Robert Eggersmann, Trenton Kirchdoerfer, Stefanie Reese +2
We extend the Data-Driven formulation of problems in elasticity of Kirchdoerfer and Ortiz (2016) to inelasticity. This extension differs fundamentally from Data-Driven problems in…