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Identifying Constitutive Parameters for Complex Hyperelastic Materials
  using Physics-Informed Neural Networks
v1v2v3v4 (latest)

Identifying Constitutive Parameters for Complex Hyperelastic Materials using Physics-Informed Neural Networks

29 August 2023
Siyuan Song
Hanxun Jin
    AI4CEPINN
ArXiv (abs)PDFHTML

Papers citing "Identifying Constitutive Parameters for Complex Hyperelastic Materials using Physics-Informed Neural Networks"

10 / 10 papers shown
Title
Mechanical Characterization and Inverse Design of Stochastic Architected
  Metamaterials Using Neural Operators
Mechanical Characterization and Inverse Design of Stochastic Architected Metamaterials Using Neural Operators
Hanxun Jin
Enrui Zhang
Boyu Zhang
Sridhar Krishnaswamy
George Karniadakis
Horacio D. Espinosa
AI4CE
73
4
0
23 Nov 2023
Physics-Informed Neural Networks for Shell Structures
Physics-Informed Neural Networks for Shell Structures
Jan-Hendrik Bastek
D. Kochmann
AI4CE
50
55
0
26 Jul 2022
Calibrating constitutive models with full-field data via physics
  informed neural networks
Calibrating constitutive models with full-field data via physics informed neural networks
Craig M. Hamel
K. Long
S. Kramer
AI4CE
76
31
0
30 Mar 2022
Dynamic fracture of a bicontinuously nanostructured copolymer: A
  deep-learning analysis of big-data-generating experiment
Dynamic fracture of a bicontinuously nanostructured copolymer: A deep-learning analysis of big-data-generating experiment
Hanxun Jin
Tong Jiao
R. Clifton
Kyung-Suk Kim
AI4CE
51
24
0
03 Dec 2021
Physics informed neural networks for continuum micromechanics
Physics informed neural networks for continuum micromechanics
Alexander Henkes
Henning Wessels
R. Mahnken
PINNAI4CE
62
145
0
14 Oct 2021
Physics-informed neural networks (PINNs) for fluid mechanics: A review
Physics-informed neural networks (PINNs) for fluid mechanics: A review
Shengze Cai
Zhiping Mao
Zhicheng Wang
Minglang Yin
George Karniadakis
PINNAI4CE
88
1,209
0
20 May 2021
Physics-Informed Neural Networks for Nonhomogeneous Material
  Identification in Elasticity Imaging
Physics-Informed Neural Networks for Nonhomogeneous Material Identification in Elasticity Imaging
Enrui Zhang
Minglang Yin
George Karniadakis
73
66
0
02 Sep 2020
DeepONet: Learning nonlinear operators for identifying differential
  equations based on the universal approximation theorem of operators
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators
Lu Lu
Pengzhan Jin
George Karniadakis
248
2,158
0
08 Oct 2019
DeepXDE: A deep learning library for solving differential equations
DeepXDE: A deep learning library for solving differential equations
Lu Lu
Xuhui Meng
Zhiping Mao
George Karniadakis
PINNAI4CE
99
1,549
0
10 Jul 2019
Automatic differentiation in machine learning: a survey
Automatic differentiation in machine learning: a survey
A. G. Baydin
Barak A. Pearlmutter
Alexey Radul
J. Siskind
PINNAI4CEODL
174
2,820
0
20 Feb 2015
1