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08/21/2023
Stress representations for tensor basis neural networks: alternative formulations to Finger-Rivlin-Ericksen
Data-driven constitutive modeling frameworks based on neural networks an...
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04/27/2023
Physics-informed Data-driven Discovery of Constitutive Models with Application to Strain-Rate-sensitive Soft Materials
A novel data-driven constitutive modeling approach is proposed, which co...
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10/15/2022
Modular machine learning-based elastoplasticity: generalization in the context of limited data
The development of accurate constitutive models for materials that under...
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04/15/2021
The mixed deep energy method for resolving concentration features in finite strain hyperelasticity
The introduction of Physics-informed Neural Networks (PINNs) has led to ...
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07/02/2019
An innovative adaptive kriging approach for efficient binary classification of mechanical problems
Kriging is an efficient machine-learning tool, which allows to obtain an...
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05/12/2019
