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Material modeling for parametric, anisotropic finite strain hyperelasticity based on machine learning with application in optimization of metamaterials
Research article (International Journal for Numerical Methods in Engineering, 2021) · cited 55× · AI/ML
Material modeling for parametric, anisotropic finite strain hyperelasticity based on machine learning with application in optimization of metamaterials
Summary
Material modeling for parametric, anisotropic finite strain hyperelasticity based on machine learning with application in optimization of metamaterials is a scholarly article[1].
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Material modeling for parametric, anisotropic finite strain hyperelasticity based on machine learning with application in optimization of metamaterials's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Material modeling for parametric, anisotropic finite strain hyperelasticity based on machine learning with application in optimization of metamaterials. Retrieved May 24, 2026, from https://4ort.xyz/entity/material-modeling-for-parametric-anisotropic-finite-strain-hyperelasticity-based-on-machine-learning-with-application-in
MLA“Material modeling for parametric, anisotropic finite strain hyperelasticity based on machine learning with application in optimization of metamaterials.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/material-modeling-for-parametric-anisotropic-finite-strain-hyperelasticity-based-on-machine-learning-with-application-in.
BibTeX@misc{4ortxyz_material-modeling-for-parametric-anisotropic-finite-strain-hyperelasticity-based-on-machine-learning-with-application-in_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Material modeling for parametric, anisotropic finite strain hyperelasticity based on machine learning with application in optimization of metamaterials}}, year = {2026}, url = {https://4ort.xyz/entity/material-modeling-for-parametric-anisotropic-finite-strain-hyperelasticity-based-on-machine-learning-with-application-in}, note = {Accessed: 2026-05-24}}
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