2 citations · 2 across the 3 of their papers we have counts for
6 papers
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…
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…
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…