Is the kinetic equation for turbulent gas-particle flows ill posed?

This paper is about the kinetic equation for gas-particle flows, in particular its well-posedness and realizability and its relationship to the generalized Langevin model (GLM) probability density function (PDF) equation. Previous analyses, e.g. [J.-P. Minier and C. Profeta, Phys. Rev. E 92, 053020 (2015)PLEEE81539-375510.1103/PhysRevE.92.053020], have concluded that this kinetic equation is ill posed, that in particular it has the properties of a backward heat equation, and as a consequence, its solution will in the course of time exhibit finite-time singularities. We show that this conclusion is fundamentally flawed because it ignores the coupling between the phase space variables in the kinetic equation and the time and particle inertia dependence of the phase space diffusion tensor. This contributes an extra positive diffusion that always outweighs the negative diffusion associated with the dispersion along one of the principal axes of the phase space diffusion tensor. This is confirmed by a numerical evaluation of analytic solutions of these positive and negative contributions to the particle diffusion coefficient along this principal axis. We also examine other erroneous claims and assumptions made in previous studies that demonstrate the apparent superiority of the GLM PDF approach over the kinetic approach. In so doing, we have drawn attention to the limitations of the GLM approach, which these studies have ignored or not properly considered, to give a more balanced appraisal of the benefits of both PDF approaches.

Measuring segregation of inertial particles in turbulence by a full Lagrangian approach.

Preferential concentration of inertial particles in turbulence is studied numerically by evaluating the Lagrangian compressibility of the particle velocity field using the "full Lagrangian method." This is compared with the "mesoscopic Eulerian particle velocity field" both in a direct numerical simulation of turbulence and in a synthetic flow field. We demonstrate that the Lagrangian method, in contrast to the Eulerian, accurately predicts the compressibility of the particle velocity field even when the latter is characterized by singularities. In particular we use the method to evaluate the growth rates of spatial moments of the particle number density which reflect the fractal structure of segregation and the occurrence of singularities.

Stochastic transport of particles in straining flows.

Important features associated with the segregration of particles in turbulent flow are investigated by considering the statistical distribution (phase-space number density) of particles subject to the combined effects of straining flow and stochastic forcing. A Fokker-Planck model is used to obtain results for the phase-space distributions of particles that are entrained into straining flow fields. The analysis shows that, in marked contrast to the zero strain case, nonsingular steady-state distributions are generated, and also confirms that the diffusional effect resulting from stochastic forcing is sufficient to offset the otherwise singular distributions that would result from the indefinite accumulation of particles along stagnation lines. The influence of particle inertia (Stokes number) on the form of the resulting distributions is considered and several significant results are observed. The influence of strain rate on the attenuation of particle kinetic stresses is quantified and explained. The development of large third-order velocity moments is observed for Stokes numbers above a critical value. The mechanism underlying this phenomenon is seen to be a generic feature of particle transport in flows where vortex structures induce local counterflows of particles. The system therefore provides an ideal test for closure models for third-order moments of particle velocities, and here the standard Chapman-Enskog approximation is assessed.