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08/31/2023
Inverse designing surface curvatures by deep learning
Smooth and curved microstructural topologies found in nature - from soap...
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06/26/2023
Unifying the design space of truss metamaterials by generative modeling
The rise of machine learning has fueled the discovery of new materials a...
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06/12/2023
Enhanced Floating Isogeometric Analysis
The numerical simulation of additive manufacturing techniques promises t...
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05/25/2023
Automated discovery of interpretable hyperelastic material models for human brain tissue with EUCLID
We propose an automated computational algorithm for simultaneous model s...
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10/26/2022
Automated discovery of generalized standard material models with EUCLID
We extend the scope of our approach for unsupervised automated discovery...
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05/04/2022
NN-EUCLID: deep-learning hyperelasticity without stress data
We propose a new approach for unsupervised learning of hyperelastic cons...
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03/14/2022
Bayesian-EUCLID: discovering hyperelastic material laws with uncertainties
Within the scope of our recent approach for Efficient Unsupervised Const...
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02/10/2022
Discovering plasticity models without stress data
We propose a new approach for data-driven automated discovery of materia...
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01/17/2022
Numerical approaches for investigating quasiconvexity in the context of Morrey's conjecture
Deciding whether a given function is quasiconvex is generally a difficul...
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10/14/2021
Floating Isogeometric Analysis
We propose Floating Isogeometric Analysis (FLIGA), which extends the con...
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09/17/2021
What machine learning can do for computational solid mechanics
Machine learning has found its way into almost every area of science and...
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12/31/2020
Data-driven topology optimization of spinodoid metamaterials with seamlessly tunable anisotropy
We present a two-scale topology optimization framework for the design of...
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10/26/2020
