A physics-based deep learning framework for super-resolution in fluid dynamics based on higher-order singular value decomposition
In this work, a novel methodology combining higher-order singular value decomposition (HOSVD) with deep learning is presented for the super-resolution (SR) of computational fluid dynamics and sparse experimental datasets. This approach, referred to as HOSVD-SR (The software is available at https://modelflows.github.io/...