3 papers
physics.flu-dyn2026
Development and application of a multiphase Lagrangian structure function model in anisotropic turbulence
Andrew P. Grace, David Richter
The energetic response of inertial particles to turbulent flow motions is important for both a fundamental understanding of the multi-phase dynamics at play, and for applications s…
physics.flu-dyn2025
A Physics-Informed Spatiotemporal Deep Learning Framework for Turbulent Systems
Luca Menicali, Andrew Grace, David H. Richter +1
Fluid thermodynamics underpins atmospheric dynamics, climate science, industrial applications, and energy systems. However, direct numerical simulations (DNS) of such systems can b…
physics.flu-dyn2024
Multi-scale interactions in turbulent mixed convection drive efficient transport of Lagrangian particles
Andrew P. Grace, David H. Richter
When turbulent convection interacts with a turbulent shear flow, the cores of convective cells become aligned with the mean current, and these cells (which span the height of the d…