16 citations · 18 across the 3 of their papers we have counts for
4 papers
Hyperreduction accelerates finite element model updating for the discovery of neural materials
Hagen Holthusen, Matthias Knipper, Kevin Linka
Finite element model updating is among the most general approaches to discover constitutive models from structural experiments: since the displacement field is computed rather than…
Automatic-Differentiation-Enabled Finite Element Model Updating: Learning Constitutive Neural Networks from Structural Deformation Data
Matthias Knipper, Chenyi Ji, Malte Brand +1
The identification of constitutive neural network models from heterogeneous full-field deformation data provides a robust alternative to traditional calibration methods based on ho…
A Comprehensive Framework for Predictive Computational Modeling of Growth and Remodeling in Tissue-Engineered Cardiovascular Implants
Mahmoud Sesa, Hagen Holthusen, Christian Böhm +3
Developing clinically viable tissue-engineered cardiovascular implants remains a formidable challenge. Achieving reliable and durable outcomes requires a deeper understanding of th…
A Spectral-based Physics-informed Finite Operator Learning for Prediction of Mechanical Behavior of Microstructures
Ali Harandi, Hooman Danesh, Kevin Linka +2
A novel physics-informed operator learning technique based on spectral methods is introduced to model the complex behavior of heterogeneous materials. The Lippmann-Schwinger operat…