Turbulent disperse two-phase flow: simulations and data-driven modeling
Lecture with Prof. Jesse Capecelatro, The University of Michigan
Turbulent disperse two-phase flows (liquid droplets or solid particles suspended in a carrier fluid) are encountered in numerous engineering and environmental applications, yet modeling such flows remains exceedingly challenging.
The first part of this talk will focus on the flow physics taking place at the microscale (scale of individual particles) and a new stochastic framework will be presented that captures the detailed hydrodynamics.
Then the focus will shift to modeling the macroscale. A new data-driven framework based on sparse regression will be presented for model closure of the multiphase Reynolds Average Navier—Stokes (RANS) equations. It will be shown that sparse regression can identify compact, algebraic models that respect frame invariance from high-resolution simulation data.
If interested in participating, please write to Prof. Daniele Marchisio: email@example.com