• Corpus ID: 232046152

Machine Learning-Based Optimal Mesh Generation in Computational Fluid Dynamics

@article{Huang2021MachineLO,
  title={Machine Learning-Based Optimal Mesh Generation in Computational Fluid Dynamics},
  author={Keefe Huang and Moritz Kr{\"u}gener and Alistair Brown and Friedrich Menhorn and Hans-Joachim Bungartz and Dirk Hartmann},
  journal={ArXiv},
  year={2021},
  volume={abs/2102.12923}
}
Computational Fluid Dynamics (CFD) is a major sub-field of engineering. Corresponding flow simulations are typically characterized by heavy computational resource requirements. Often, very fine and complex meshes are required to resolve physical effects in an appropriate manner. Since all CFD algorithms scale at least linearly with the size of the underlying mesh discretization, finding an optimal mesh is key for computational efficiency. One methodology used to find optimal meshes is goal… 
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