Material modeling for parametric, anisotropic finite strain hyperelasticity based on machine learning with application in optimization of metamaterials

被引：0
|
作者：
Fernández, Mauricio [1 ,2 ]
Fritzen, Felix [3 ]
Weeger, Oliver [1 ]
机构：
[1] Cyber-Physical Simulation, Technical University of Darmstadt, Darmstadt, Germany
[2] Multiscale and Data-Driven Material Modeling, ACCESS e.V., Aachen, Germany
[3] Data Analytics in Engineering, University of Stuttgart, Stuttgart, Germany
来源：
International Journal for Numerical Methods in Engineering | 2022年 / 123卷 / 02期
关键词：
Compilation and indexing terms; Copyright 2024 Elsevier Inc;
D O I：
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中图分类号：
学科分类号：
摘要：
Machine learning - Topology - Aspect ratio - Deformation - Elasticity - Anisotropy - Cytology - Neural networks - Cells - Metamaterials
引用
收藏
页码：577 / 609
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