Deep Learning for Stress Field Prediction Using Convolutional Neural Networks

@article{Nie2018DeepLF,
  title={Deep Learning for Stress Field Prediction Using Convolutional Neural Networks},
  author={Zhenguo Nie and Haoliang Jiang and Levent Burak Kara},
  journal={ArXiv},
  year={2018},
  volume={abs/1808.08914}
}
This research presents a deep learning based approach to predict stress fields in the solid material elastic deformation using convolutional neural networks (CNN). Two different architectures are proposed to solve the problem. One is Feature Representation embedded Convolutional Neural Network (FR-CNN) with a single input channel, and the other is Squeeze-and-Excitation Residual network modules embedded Fully Convolutional Neural network (SE-Res-FCN) with multiple input channels. Both the tow… 
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