A Lagrangian probability-density-function model for collisional turbulent fluid-particle flows. I. Model derivation
Alessio Innocenti, Rodney O Fox, Sergio Chibbaro

TL;DR
This paper develops a Lagrangian stochastic model for dense turbulent particle flows, capturing particle clustering, segregation, and turbulence generation due to particle-fluid interactions, advancing the understanding of complex multiphase flows.
Contribution
It introduces a rigorous Lagrangian formalism that includes two-way coupling and particle velocity decomposition, providing a novel framework for dense particle-laden flow modeling.
Findings
Framework captures particle clustering and segregation.
Model distinguishes correlated and uncorrelated particle velocities.
Provides a basis for future applications to dense flows.
Abstract
Inertial particles in turbulent flows are characterised by preferential concentration and segregation and, at sufficient mass loading, dense particle clusters may spontaneously arise due to momentum coupling between the phases. These clusters, in turn, can generate and sustain turbulence in the fluid phase, which we refer to as cluster-induced turbulence. In the present theoretical work, we tackle the problem of developing a framework for the stochastic modelling of moderately dense particle-laden flows, based on a Lagrangian formalism, which naturally includes the Eulerian one. A rigorous formalism and a general model have been put forward focusing, in particular, on the two ingredients that are key in moderately dense flows, namely, two-way coupling in the carrier phase, and the decomposition of the particle-phase velocity into its spatially correlated and uncorrelated components.…
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