Multi-fidelity Generative Deep Learning Turbulent Flows [FoDS][ArXiv]
Nicholas Geneva, Nicholas Zabaras
A novel multi-fidelity deep generative model is introduced for the surrogate modeling of high-fidelity turbulent flow fields given the solution of a computationally inexpensive but inaccurate low-fidelity solver.
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- Data Repository
Cite us with:
@article{geneva2020multi,
title={Multi-fidelity Generative Deep Learning Turbulent Flows},
author={Geneva, Nicholas and Zabaras, Nicholas},
journal={arXiv preprint arXiv:2006.04731},
year={2020}
}