Multiphase flow applications of nonintrusive reduced-order models with Gaussian process emulation

@article{Botsas2022MultiphaseFA,
  title={Multiphase flow applications of nonintrusive reduced-order models with Gaussian process emulation},
  author={Themistoklis Botsas and Indranil Pan and Lachlan Robert Mason and Omar K. Matar},
  journal={Data-Centric Engineering},
  year={2022},
  volume={3}
}
Abstract Reduced-order models (ROMs) are computationally inexpensive simplifications of high-fidelity complex ones. Such models can be found in computational fluid dynamics where they can be used to predict the characteristics of multiphase flows. In previous work, we presented a ROM analysis framework that coupled compression techniques, such as autoencoders, with Gaussian process regression in the latent space. This pairing has significant advantages over the standard encoding–decoding… 
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