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Constitutive model characterization and discovery using physics-informed
  deep learning
v1v2 (latest)

Constitutive model characterization and discovery using physics-informed deep learning

18 March 2022
E. Haghighat
S. Abouali
R. Vaziri
    PINNAI4CE
ArXiv (abs)PDFHTML

Papers citing "Constitutive model characterization and discovery using physics-informed deep learning"

11 / 11 papers shown
Title
Learning Memory and Material Dependent Constitutive Laws
Learning Memory and Material Dependent Constitutive Laws
K. Bhattacharya
Lianghao Cao
George Stepaniants
Andrew M. Stuart
Margaret Trautner
131
1
0
08 Feb 2025
Physics-informed neural network simulation of multiphase poroelasticity
  using stress-split sequential training
Physics-informed neural network simulation of multiphase poroelasticity using stress-split sequential training
E. Haghighat
Daniel Amini
R. Juanes
PINNAI4CE
96
100
0
06 Oct 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
CMLAI4CE
100
26
0
20 May 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
85
1,201
0
20 May 2021
Physics-Informed Neural Network for Modelling the Thermochemical Curing
  Process of Composite-Tool Systems During Manufacture
Physics-Informed Neural Network for Modelling the Thermochemical Curing Process of Composite-Tool Systems During Manufacture
S. Niaki
E. Haghighat
Trevor Campbell
Xinglong Li
R. Vaziri
AI4CE
125
209
0
27 Nov 2020
Energy-based error bound of physics-informed neural network solutions in
  elasticity
Energy-based error bound of physics-informed neural network solutions in elasticity
Mengwu Guo
E. Haghighat
PINN
125
29
0
18 Oct 2020
Learning Unknown Physics of non-Newtonian Fluids
Learning Unknown Physics of non-Newtonian Fluids
B. Reyes
Amanda A. Howard
P. Perdikaris
A. Tartakovsky
PINN
52
48
0
26 Aug 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
PINNAI4CE
70
226
0
10 Jun 2020
A nonlocal physics-informed deep learning framework using the
  peridynamic differential operator
A nonlocal physics-informed deep learning framework using the peridynamic differential operator
E. Haghighat
A. Bekar
E. Madenci
R. Juanes
PINN
51
107
0
31 May 2020
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
172
2,820
0
20 Feb 2015
Speech Recognition with Deep Recurrent Neural Networks
Speech Recognition with Deep Recurrent Neural Networks
Alex Graves
Abdel-rahman Mohamed
Geoffrey E. Hinton
230
8,526
0
22 Mar 2013
1