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PyTorch implementations of Learning Mesh-based Simulation With Graph Networks

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Learning Mesh-Based Simulation with Graph Networks

This repository contains PyTorch implementations of meshgraphnets for flow around circular cylinder problem on the basic of PyG (pytorch geometric).

The original paper can be found as following:

Pfaff T, Fortunato M, Sanchez-Gonzalez A, et al. Learning mesh-based simulation with graph networks[J]. International Conference on Learning Representations (ICLR), 2021.

Some code of this repository refer to Differentiable Physics-informed Graph Networks.

Authors


  • Jiang
  • Zhang
  • Chu
  • Qian
  • Li
  • Wang

Requirements


  • h5py==3.6.0
  • matplotlib==3.4.3
  • numpy==1.21.1
  • opencv_python==4.5.4.58
  • Pillow==9.1.0
  • torch==1.9.0+cu111
  • torch_geometric==2.0.4
  • torch_scatter==2.0.8
  • tqdm==4.62.3
pip install -r requirements.txt

Sample usage


Demos


  • Here are some examples, trained on cylinder_flow dataset.

  • In addition, we use simulation software to generate new training data. The test results on our data are as following:

Contact me

📧 jianglx@whu.edu.cn

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