Transfer learning enhanced physics informed neural network for phase-field modeling of fracture-Reference-Cited by-同舟云学术

Transfer learning enhanced physics informed neural network for phase-field modeling of fracture

Published:2020-04 Issue: Volume:106 Page:102447
ISSN:0167-8442
Container-title:Theoretical and Applied Fracture Mechanics
language:en
Short-container-title:Theoretical and Applied Fracture Mechanics

Author:

Goswami Somdatta,Anitescu Cosmin,Chakraborty Souvik,Rabczuk Timon

Funder

German Academic Exchange Service

Center for Research Computing, University of Notre Dame

Publisher

Elsevier BV

Subject

Applied Mathematics,Mechanical Engineering,Condensed Matter Physics,General Materials Science

Reference37 articles.

1. The Phenomena of Rupture and Flow in Solids;Griffith;Philisoph. Trans. Roy. Soc. London,1921

2. M. Abadi, A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G.S. Corrado, A. Davis, J. Dean, M. Devin, et al., Tensorflow: Large-scale machine learning on heterogeneous systems, 2015. Software available from tensorflow.org, 2015.

3. Hybrid discrete element/finite element method for fracture analysis;Azevedo;Comput. Methods Appl. Mech. Eng.,2006

4. Quasi-automatic simulation of crack propagation for 2D LEFM problems;Bittencourt;Eng. Fract. Mech.,1996

5. A phase-field description of dynamic brittle fracture;Borden;Comput. Methods Appl. Mech. Eng.,2012

Cited by 403 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Review of progress in calculation and simulation of high-temperature oxidation;Progress in Materials Science;2025-01

2. On the Gauss–Legendre quadrature rule of deep energy method for one-dimensional problems in solid mechanics;Finite Elements in Analysis and Design;2024-12

3. PDE generalization of in-context operator networks: A study on 1D scalar nonlinear conservation laws;Journal of Computational Physics;2024-12

4. A transfer learning physics-informed deep learning framework for modeling multiple solute dynamics in unsaturated soils;Computer Methods in Applied Mechanics and Engineering;2024-11

5. Interpretable physics-encoded finite element network to handle concentration features and multi-material heterogeneity in hyperelasticity;Computer Methods in Applied Mechanics and Engineering;2024-11