Learning solution of nonlinear constitutive material models using
physics-informed neural networks: COMM-PINN

v1v2 (latest)

Learning solution of nonlinear constitutive material models using physics-informed neural networks: COMM-PINN

10 April 2023

Ahmad Moeineddin

ArXiv (abs)PDF HTML

Papers citing "Learning solution of nonlinear constitutive material models using physics-informed neural networks: COMM-PINN"

13 / 13 papers shown

Title
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing Salah A. Faroughi N. Pawar C. Fernandes Maziar Raissi Subasish Das N. Kalantari S. K. Mahjour PINN AI4CE 71 52 0 14 Nov 2022
Spiking neural networks for nonlinear regression Alexander Henkes Jason K. Eshraghian Henning Wessels 84 29 0 06 Oct 2022
A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: comparison with finite element method Shahed Rezaei Ali Harandi Ahmad Moeineddin Bai-Xiang Xu Stefanie Reese 70 118 0 27 Jun 2022
Thermodynamically Consistent Machine-Learned Internal State Variable Approach for Data-Driven Modeling of Path-Dependent Materials Xiaolong He Jiun-Shyan Chen AI4CE 110 51 0 01 May 2022
Constitutive model characterization and discovery using physics-informed deep learning E. Haghighat S. Abouali R. Vaziri PINN AI4CE 90 51 0 18 Mar 2022
Physics-informed neural network simulation of multiphase poroelasticity using stress-split sequential training E. Haghighat Daniel Amini R. Juanes PINN AI4CE 107 100 0 06 Oct 2021
Lossless Multi-Scale Constitutive Elastic Relations with Artificial Intelligence J. Mianroodi Shahed Rezaei N. Siboni Bai-Xiang Xu Dierk Raabe AI4CE 51 32 0 05 Aug 2021
Polyconvex anisotropic hyperelasticity with neural networks Dominik K. Klein Mauricio Fernández Robert J. Martin P. Neff Oliver Weeger 79 155 0 20 Jun 2021
The mixed deep energy method for resolving concentration features in finite strain hyperelasticity J. Fuhg N. Bouklas PINN AI4CE 75 94 0 15 Apr 2021
Thermodynamic Consistent Neural Networks for Learning Material Interfacial Mechanics Jiaxin Zhang Congjie Wei Chenglin Wu AI4CE PINN 24 7 0 28 Nov 2020
When and why PINNs fail to train: A neural tangent kernel perspective Sizhuang He Xinling Yu P. Perdikaris 141 923 0 28 Jul 2020
An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications E. Samaniego C. Anitescu S. Goswami Vien Minh Nguyen-Thanh Hongwei Guo Khader M. Hamdia Timon Rabczuk X. Zhuang PINN AI4CE 229 1,389 0 27 Aug 2019
Deep Learning in Neural Networks: An Overview Jürgen Schmidhuber HAI 250 16,405 0 30 Apr 2014

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.