Identifying constitutive parameters for complex hyperelastic materials using physics-informed neural networks-Reference-Cited by-同舟云学术

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Identifying constitutive parameters for complex hyperelastic materials using physics-informed neural networks

Published:2024 Issue:30 Volume:20 Page:5915-5926
ISSN:1744-683X
Container-title:Soft Matter
language:en
Short-container-title:Soft Matter

Author:

Song Siyuan¹^ORCID,Jin Hanxun¹^ORCID

Affiliation:

1. School of Engineering, Brown University, Providence, RI 02912, USA

Abstract

A robust PINN-based framework was developed to identify material parameters for hyperelastic soft materials, specifically those exhibiting complex constitutive behaviors, under large deformation in plane stress conditions.

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/SM/D4SM00001C

Reference59 articles.

1. J. R.Davis , Tensile testing , ASM International , 2004

2. Ruga mechanics of soft-orifice closure under external pressure

3. Stresses and Birefringence in Rubber subjected to General Homogeneous Strain

4. The electronic structure and magnetism of the Al/Fe interfaces

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1. Multi-Step Physics-Informed Deep Operator Neural Network for Directly Solving Partial Differential Equations;Applied Sciences;2024-06-25

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