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arXiv2019

A Kinetic Equation for Particle Transport in Turbulent Flows

One key issue in the probability density function (PDF) approach for disperse two-phase turbulent flows is to close the diffusion term in the phase space. This study aimed to derive a kinetic equation for particle dispersion in turbulent flows by ensemble averaging over all possible realisations of state transition paths in the phase space. The probability density function is expanded as a series in terms of the cumulants of particle paths in the phase space, by introducing a local path density operator to identify the distribution of particle paths. The expansion enables us to directly obtain a kinetic equation with the diffusion term in closed form. The kinetic equation derived in this study has following features that: (1) it has its coefficients expressed as functions of the cumulants of particle paths in the phase space; (2) it applies to particle dispersion by non-Gaussian random forcing with long correlation time scales; (3) it presents new mechanisms responsible for particle diffusion. An application of the kinetic equation is also presented in this paper.

cond-mat.stat-mech↗

arXiv2019

Path-averaged Kinetic Equation for Stochastic Systems

For a stochastic system, its evolution from one state to another can have a large number of possible paths. Non-uniformity in the field of system variables leads the local dynamics in state transition varies considerably from path to path and thus the distribution of the paths affects statistical characteristics of the system. Such a characteristic can be referred to as path-dependence of a system, and long-time correlation is an intrinsic feature of path-dependence systems. We employed a local path density operator to describe the distribution of state transition paths, and based on which we derived a new kinetic equation for path-dependent systems. The kinetic equation is similar in form to the Kramers-Moyal expansion, but with its expansion coefficients determined by the cumulants with respect to state transition paths, instead of transition moments. This characteristic makes it capable of accounting for the non-local feature of systems, which is essential in studies of large scale systems where the path-dependence is prominent. Short-time correlation approximation is also discussed. It shows that the cumulants of state transition paths are equivalent to jump moments when correlation time scales are infinitesimal, as makes the kinetic equation derived in this paper has the same physical consideration of the Fokker-Planck equation for Markov processes.

cond-mat.stat-mech↗