3 papers
physics.flu-dyn2021
Multiphase turbulence modeling using sparse regression and gene expression programming
S. Beetham, J. Capecelatro
In recent years, there has been an explosion of machine learning techniques for turbulence closure modeling, though many rely on augmenting existing models. While this has proven s…
physics.flu-dyn2021
On the thermal entrance length of moderately dense gas-particle flows
S. Beetham, A. Lattanzi, J. Capecelatro
The dissipative nature of heat transfer relaxes thermal flows to an equilibrium state that is devoid of temperature gradients. The distance to reach an equilibrium temperature -- t…
physics.flu-dyn2020
Formulating turbulence closures using sparse regression with embedded form invariance
S. Beetham, J. Capecelatro
A data-driven framework for formulation of closures of the Reynolds-Average Navier--Stokes (RANS) equations is presented. In recent years, the scientific community has turned to ma…