FEA-Net: A Physics-guided Data-driven Model for Efficient Mechanical Response Prediction

31 January 2020

Papers citing "FEA-Net: A Physics-guided Data-driven Model for Efficient Mechanical Response Prediction"

6 / 6 papers shown

Title
EquiNO: A Physics-Informed Neural Operator for Multiscale Simulations Hamidreza Eivazi Jendrik-Alexander Tröger Stefan H. A. Wittek Stefan Hartmann Andreas Rausch AI4CE 43 0 0 27 Mar 2025
ParticleWNN: a Novel Neural Networks Framework for Solving Partial Differential Equations Yaohua Zang Gang Bao 24 4 0 21 May 2023
A Comprehensive Review of Digital Twin -- Part 1: Modeling and Twinning Enabling Technologies Adam Thelen Xiaoge Zhang Olga Fink Yan Lu Sayan Ghosh B. Youn Michael D. Todd S. Mahadevan Chao Hu Zhen Hu SyDa AI4CE 24 187 0 26 Aug 2022
Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics Xin-Yang Liu Min Zhu Lu Lu Hao Sun Jian-Xun Wang PINN AI4CE 28 45 0 09 May 2022
A physics and data co-driven surrogate modeling approach for temperature field prediction on irregular geometric domain K. Bao Wenjuan Yao Xiaoya Zhang Wei Peng Yu Li AI4CE 26 10 0 15 Mar 2022
NeuFENet: Neural Finite Element Solutions with Theoretical Bounds for Parametric PDEs Biswajit Khara Aditya Balu Ameya Joshi S. Sarkar C. Hegde A. Krishnamurthy Baskar Ganapathysubramanian 22 19 0 04 Oct 2021