Discovering plasticity models without stress data
We propose an approach for data-driven automated discovery of material laws, which we
call EUCLID (Efficient Unsupervised Constitutive Law Identification and Discovery), and we …
call EUCLID (Efficient Unsupervised Constitutive Law Identification and Discovery), and we …
A comparative investigation using machine learning methods for concrete compressive strength estimation
Concrete compressive strength plays an important role in determining the mechanical
properties of concrete. The determination of concrete compressive strength requires lengthy …
properties of concrete. The determination of concrete compressive strength requires lengthy …
[HTML][HTML] Void growth in ductile materials with realistic porous microstructures
In this paper, we have investigated void growth in von Mises materials which contain
realistic porous microstructures. For that purpose, we have performed finite element …
realistic porous microstructures. For that purpose, we have performed finite element …
Machine-learning convex and texture-dependent macroscopic yield from crystal plasticity simulations
The influence of the microstructure of a polycrystalline material on its macroscopic
deformation response is still one of the major problems in materials engineering. For …
deformation response is still one of the major problems in materials engineering. For …
Estimation of constituent properties of concrete materials with an artificial neural network based method
Multi-scale models are developed for heterogeneous concrete materials to estimate their
macroscopic mechanical properties in terms of micro-structural data. One crucial challenge …
macroscopic mechanical properties in terms of micro-structural data. One crucial challenge …
[HTML][HTML] Data-driven modelling of the multiaxial yield behaviour of nanoporous metals
L Dyckhoff, N Huber - International journal of mechanical sciences, 2023 - Elsevier
Nanoporous metals, built out of complex ligament networks, can be produced with an
additional level of hierarchy. The resulting complexity of the structure makes modelling of the …
additional level of hierarchy. The resulting complexity of the structure makes modelling of the …
[HTML][HTML] FE-LSTM: A hybrid approach to accelerate multiscale simulations of architectured materials using Recurrent Neural Networks and Finite Element Analysis
A Danoun, E Prulière, Y Chemisky - Computer Methods in Applied …, 2024 - Elsevier
In the present work, a novel modeling strategy to accelerate multi-scale simulations of
heterogeneous materials using deep neural networks is developed. This approach, called …
heterogeneous materials using deep neural networks is developed. This approach, called …
A data-driven yield criterion for porous ductile single crystals containing spherical voids via physics-informed neural networks
L Wu, J Fu, H Sui, X Wang, B Tao… - … of the Royal …, 2023 - royalsocietypublishing.org
Yield criteria for porous material have been widely used to model the decrease of yield
strength caused by porosity during ductile failure which deserves long-term efforts in …
strength caused by porosity during ductile failure which deserves long-term efforts in …
[HTML][HTML] A simple machine learning-based framework for faster multi-scale simulations of path-independent materials at large strains
AMC Carneiro, AFC Alves, RPC Coelho… - Finite Elements in …, 2023 - Elsevier
Coupled multi-scale finite element analyses have gained traction over the last years due to
the increasing available computational resources. Nevertheless, in the pursuit of accurate …
the increasing available computational resources. Nevertheless, in the pursuit of accurate …
Automated Discovery of Material Models in Continuum Solid Mechanics
M Flaschel - 2023 - research-collection.ethz.ch
The mathematical description of the mechanical behavior of solid materials at the continuum
scale is one of the oldest and most challenging tasks in solid mechanics and material …
scale is one of the oldest and most challenging tasks in solid mechanics and material …