Surrogated finite element models using machine learning
Author:
Affiliation:
1. San Jose State University
Publisher
American Institute of Aeronautics and Astronautics
Reference20 articles.
1. A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis
2. Bridging Finite Element and Machine Learning Modeling: Stress Prediction of Arterial Walls in Atherosclerosis
3. A finite element-based machine learning approach for modeling the mechanical behavior of the breast tissues under compression in real-time
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1. Tendon Stress Estimation from Strain Data of a Bridge Girder Using Machine Learning-Based Surrogate Model;Sensors;2023-05-24
2. A State-of-the-Art Review on Machine Learning-Based Multiscale Modeling, Simulation, Homogenization and Design of Materials;Archives of Computational Methods in Engineering;2022-08-05
3. Optimal sensor location along a beam using machine learning;AIAA SCITECH 2022 Forum;2022-01-03
4. A Machine Learning Approach as a Surrogate for a Finite Element Analysis: Status of Research and Application to One Dimensional Systems;Sensors;2021-02-27
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