Stress field prediction in fiber-reinforced composite materials using a
deep learning approach

Stress field prediction in fiber-reinforced composite materials using a deep learning approach

1 November 2021

Anindya Bhaduri

L. Graham‐Brady

Papers citing "Stress field prediction in fiber-reinforced composite materials using a deep learning approach"

14 / 14 papers shown

Title
Global Stress Generation and Spatiotemporal Super-Resolution Physics-Informed Operator under Dynamic Loading for Two-Phase Random Materials Tengfei Xing Xiaodan Ren Jie Li DiffM 34 0 0 26 Apr 2025
Predicting Stress in Two-phase Random Materials and Super-Resolution Method for Stress Images by Embedding Physical Information Tengfei Xing Xiaodan Ren Jie Li 38 1 0 26 Apr 2025
Micrometer: Micromechanics Transformer for Predicting Mechanical Responses of Heterogeneous Materials Sifan Wang Tong-Rui Liu Shyam Sankaran P. Perdikaris AI4CE 40 3 0 23 Sep 2024
$A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: efficient mapping of concrete microstructures to its fracture properties$ A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: efficient mapping of concrete microstructures to its fracture properties Rasoul Najafi Koopas Shahed Rezaei N. Rauter Richard Ostwald R. Lammering AI4CE 43 2 0 22 Jul 2024
Bayesian neural networks for predicting uncertainty in full-field material response G. Pasparakis Lori Graham-Brady Michael D. Shields AI4CE 34 4 0 21 Jun 2024
A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains Yusuke Yamazaki Ali Harandi Mayu Muramatsu A. Viardin Markus Apel T. Brepols Stefanie Reese Shahed Rezaei AI4CE 26 12 0 21 May 2024
Crack-Net: Prediction of Crack Propagation in Composites Hao Xu Wei Fan A. Taylor Dongxiao Zhang Lecheng Ruan Rundong Shi AI4CE 14 1 0 24 Sep 2023
Challenges and opportunities for machine learning in multiscale computational modeling Phong C. H. Nguyen Joseph B. Choi H. Udaykumar Stephen Seung-Yeob Baek AI4CE 22 8 0 22 Mar 2023
Application of probabilistic modeling and automated machine learning framework for high-dimensional stress field Lele Luan Nesar Ramachandra S. Ravi Anindya Bhaduri Piyush Pandita Prasanna Balaprakash M. Anitescu Changjie Sun Liping Wang AI4CE 21 0 0 15 Mar 2023
Image-based Artificial Intelligence empowered surrogate model and shape morpher for real-time blank shape optimisation in the hot stamping process Hao Zhou Nan Li AI4CE 29 1 0 01 Dec 2022
Linking Properties to Microstructure in Liquid Metal Embedded Elastomers via Machine Learning Abhijith Anantharanga Mohammad Saber Hashemi A. Sheidaei AI4CE 13 4 0 24 Jul 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 19 112 0 27 Jun 2022
Reinforcement Learning based Sequential Batch-sampling for Bayesian Optimal Experimental Design Yonatan Ashenafi Piyush Pandita Sayan Ghosh OffRL 28 6 0 21 Dec 2021
Predicting Mechanical Properties from Microstructure Images in Fiber-reinforced Polymers using Convolutional Neural Networks Yixuan Sun I. Hanhan M. Sangid Guang Lin AI4CE 21 14 0 07 Oct 2020