Multi-scale modeling for complex flows at extreme computational scales

Applied and Computational Mathematics Seminar
Monday, October 10, 2022 - 2:00pm for
Skiles 005 and
Spencer Bryngelson – Georgia Tech CSE – shb@gatech.edu
Wenjing Liao and Molei Tao

Many fluid flows display at a wide range of space and time scales. Turbulent and multiphase flows can include small eddies or particles, but likewise large advected features. This challenge makes some degree of multi-scale modeling or homogenization necessary. Such models are restricted, though: they should be numerically accurate, physically consistent, computationally expedient, and more. I present two tools crafted for this purpose. First, the fast macroscopic forcing method (Fast MFM), which is based on an elliptic pruning procedure that localizes solution operators and sparse matrix-vector sampling. We recover eddy-diffusivity operators with a convergence that beats the best spectral approximation (from the SVD), attenuating the cost of, for example, targeted RANS closures. I also present a moment-based method for closing multiphase flow equations. Buttressed by a recurrent neural network, it is numerically stable and achieves state-of-the-art accuracy. I close with a discussion of conducting these simulations near exascale. Our simulations scale ideally on the entirety of ORNL Summit's GPUs, though the HPC landscape continues to shift.