3 papers
physics.comp-ph2026
Finite Element-Based Material Learning via Automatic Differentiation: Learning constitutive neural network models from full-field 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…
cond-mat.mtrl-sci2025
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…
cs.CE2025
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…