Abstract: 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.
About the Speaker: Spencer Bryngelson joined Georgia Tech in 2021 as a tenure-track assistant professor in the College of Computing. Previously, he was a senior postdoctoral researcher at Caltech (with Tim Colonius). He has been a visiting researcher at MIT (with Themis Sapsis) and a postdoctoral researcher at the Center for Exascale Simulation of Plasma-Coupled Combustion (with Dan Bodony, Jon Freund, and Carlos Pantano). He received his Ph.D. and M.S. in Theoretical and Applied Mechanics from the University of Illinois at Urbana-Champaign in 2017 and 2015, working with Jonathan Freund. In 2013, he received B.S. degrees in both Mechanical Engineering and Mathematics from the University of Michigan-Dearborn.
Host: Professor Jon Freund
