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Geometric deep learning for computational mechanics Part I: Anisotropic
  Hyperelasticity

Geometric deep learning for computational mechanics Part I: Anisotropic Hyperelasticity

8 January 2020
Nikolaos N. Vlassis
R. Ma
WaiChing Sun
    AI4CE
ArXivPDFHTML

Papers citing "Geometric deep learning for computational mechanics Part I: Anisotropic Hyperelasticity"

20 / 20 papers shown
Title
Large Language Model Agent as a Mechanical Designer
Large Language Model Agent as a Mechanical Designer
Yayati Jadhav
A. Farimani
AI4CE
LLMAG
101
9
0
26 Apr 2024
Peridynamic Neural Operators: A Data-Driven Nonlocal Constitutive Model
  for Complex Material Responses
Peridynamic Neural Operators: A Data-Driven Nonlocal Constitutive Model for Complex Material Responses
S. Jafarzadeh
Stewart Silling
Ning Liu
Zhongqiang Zhang
Yue Yu
AI4CE
36
16
0
11 Jan 2024
Graph Neural Networks-based Hybrid Framework For Predicting Particle
  Crushing Strength
Graph Neural Networks-based Hybrid Framework For Predicting Particle Crushing Strength
Tongya Zheng
Tianli Zhang
Qingzheng Guan
Wenjie Huang
Zunlei Feng
Min-Gyoo Song
Chun-Yen Chen
AI4CE
33
1
0
26 Jul 2023
Investigating Deep Learning Model Calibration for Classification
  Problems in Mechanics
Investigating Deep Learning Model Calibration for Classification Problems in Mechanics
S. Mohammadzadeh
Peerasait Prachaseree
Emma Lejeune
AI4CE
36
2
0
01 Dec 2022
Cooperative data-driven modeling
Cooperative data-driven modeling
Aleksandr Dekhovich
O. T. Turan
Jiaxiang Yi
Miguel A. Bessa
CLL
KELM
AI4CE
21
5
0
23 Nov 2022
MAgNET: A Graph U-Net Architecture for Mesh-Based Simulations
MAgNET: A Graph U-Net Architecture for Mesh-Based Simulations
Saurabh Deshpande
Stéphane P. A. Bordas
J. Lengiewicz
AI4CE
GNN
89
28
0
01 Nov 2022
Geometric deep learning for computational mechanics Part II: Graph
  embedding for interpretable multiscale plasticity
Geometric deep learning for computational mechanics Part II: Graph embedding for interpretable multiscale plasticity
Nikolaos N. Vlassis
WaiChing Sun
AI4CE
37
32
0
30 Jul 2022
NN-EUCLID: deep-learning hyperelasticity without stress data
NN-EUCLID: deep-learning hyperelasticity without stress data
Prakash Thakolkaran
Akshay Joshi
Yiwen Zheng
Moritz Flaschel
L. Lorenzis
Siddhant Kumar
36
98
0
04 May 2022
Learning the nonlinear dynamics of soft mechanical metamaterials with
  graph networks
Learning the nonlinear dynamics of soft mechanical metamaterials with graph networks
Tianju Xue
S. Adriaenssens
S. Mao
AI4CE
17
26
0
24 Feb 2022
Learning Mechanically Driven Emergent Behavior with Message Passing
  Neural Networks
Learning Mechanically Driven Emergent Behavior with Message Passing Neural Networks
Peerasait Prachaseree
Emma Lejeune
PINN
AI4CE
33
11
0
03 Feb 2022
PH-Net: Parallelepiped Microstructure Homogenization via 3D
  Convolutional Neural Networks
PH-Net: Parallelepiped Microstructure Homogenization via 3D Convolutional Neural Networks
Hao Peng
An-Qing Liu
Jingcheng Huang
Lingxin Cao
Jikai Liu
Lin Lu
AI4CE
23
20
0
18 Jan 2022
Multi-Objective Loss Balancing for Physics-Informed Deep Learning
Multi-Objective Loss Balancing for Physics-Informed Deep Learning
Rafael Bischof
M. Kraus
PINN
AI4CE
35
93
0
19 Oct 2021
Data-driven Tissue Mechanics with Polyconvex Neural Ordinary
  Differential Equations
Data-driven Tissue Mechanics with Polyconvex Neural Ordinary Differential Equations
Vahidullah Tac
F. Sahli Costabal
A. B. Tepole
AI4CE
44
70
0
03 Oct 2021
Polyconvex anisotropic hyperelasticity with neural networks
Polyconvex anisotropic hyperelasticity with neural networks
Dominik K. Klein
Mauricio Fernández
Robert J. Martin
P. Neff
Oliver Weeger
41
151
0
20 Jun 2021
Data-driven discovery of interpretable causal relations for deep
  learning material laws with uncertainty propagation
Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty propagation
Xiao Sun
B. Bahmani
Nikolaos N. Vlassis
WaiChing Sun
Yanxun Xu
CML
AI4CE
70
26
0
20 May 2021
Local approximate Gaussian process regression for data-driven
  constitutive laws: Development and comparison with neural networks
Local approximate Gaussian process regression for data-driven constitutive laws: Development and comparison with neural networks
J. Fuhg
M. Marino
N. Bouklas
41
59
0
07 May 2021
A Data-Driven Approach to Full-Field Damage and Failure Pattern
  Prediction in Microstructure-Dependent Composites using Deep Learning
A Data-Driven Approach to Full-Field Damage and Failure Pattern Prediction in Microstructure-Dependent Composites using Deep Learning
R. Sepasdar
Anuj Karpatne
Maryam Shakiba
AI4CE
29
60
0
09 Apr 2021
Predicting the Mechanical Properties of Biopolymer Gels Using Neural
  Networks Trained on Discrete Fiber Network Data
Predicting the Mechanical Properties of Biopolymer Gels Using Neural Networks Trained on Discrete Fiber Network Data
Yue Leng
Vahidullah Tac
S. Calve
A. B. Tepole
28
32
0
23 Jan 2021
Sobolev training of thermodynamic-informed neural networks for smoothed
  elasto-plasticity models with level set hardening
Sobolev training of thermodynamic-informed neural networks for smoothed elasto-plasticity models with level set hardening
Nikolaos N. Vlassis
WaiChing Sun
AI4CE
19
2
0
15 Oct 2020
Physics informed deep learning for computational elastodynamics without
  labeled data
Physics informed deep learning for computational elastodynamics without labeled data
Chengping Rao
Hao Sun
Yang Liu
PINN
AI4CE
27
222
0
10 Jun 2020
1