83 citations · 261 across the 22 of their papers we have counts for
7 papers · 1 filter
Automated Model Discovery for Tensional Homeostasis: Constitutive Machine Learning in Growth and Remodeling
Hagen Holthusen, Tim Brepols, Kevin Linka +1
Soft biological tissues exhibit a tendency to maintain a preferred state of tensile stress, known as tensional homeostasis, which is restored even after external mechanical stimuli…
A two-scale computational homogenization approach for elastoplastic truss-based lattice structures
Hooman Danesh, Lisamarie Heußen, Francisco J. Montáns +2
The revolutionary advancements in metal additive manufacturing have enabled the production of alloy-based lattice structures with complex geometrical features and high resolutions.…
FFT-based surrogate modeling of auxetic metamaterials with real-time prediction of effective elastic properties and swift inverse design
Hooman Danesh, Daniele Di Lorenzo, Francisco Chinesta +2
Auxetic structures, known for their negative Poisson's ratio, exhibit effective elastic properties heavily influenced by their underlying structural geometry and base material prop…
An anisotropic, brittle damage model for finite strains with a generic damage tensor regularization
Tim van der Velden, Stefanie Reese, Hagen Holthusen +1
This paper establishes a universal framework for the nonlocal modeling of anisotropic damage at finite strains. By the combination of two recent works, the new framework allows for…
A multi-field decomposed model order reduction approach for thermo-mechanically coupled gradient-extended damage simulations
Qinghua Zhang, Stephan Ritzert, Jian Zhang +3
Numerical simulations are crucial for comprehending how engineering structures behave under extreme conditions, particularly when dealing with thermo-mechanically coupled issues co…
Component based model order reduction with mortar tied contact for nonlinear quasi-static mechanical problems
Stephan Ritzert, Jannick Kehls, Stefanie Reese +1
In this work, we present a model order reduction technique for nonlinear structures assembled from components.The reduced order model is constructed by reducing the substructures w…
A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains
Yusuke Yamazaki, Ali Harandi, Mayu Muramatsu +5
We propose a novel finite element-based physics-informed operator learning framework that allows for predicting spatiotemporal dynamics governed by partial differential equations (…