Computing Residual Diffusivity by Adaptive Basis Learning via Super-Resolution Deep Neural Networks

27 Sep 2019 Lyu Jiancheng Xin Jack Yu Yifeng

It is expensive to compute residual diffusivity in chaotic in-compressible flows by solving advection-diffusion equation due to the formation of sharp internal layers in the advection dominated regime. Proper orthogonal decomposition (POD) is a classical method to construct a small number of adaptive orthogonal basis vectors for low cost computation based on snapshots of fully resolved solutions at a particular molecular diffusivity $D_{0}^{*}$... (read more)

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  • COMPUTATIONAL PHYSICS
  • NUMERICAL ANALYSIS
  • NUMERICAL ANALYSIS