On analysis and stochastic modeling of the particle kinetic energy equation in particle-laden isotropic turbulent flows

We analyze three-dimensional particle-laden, isotropic turbulence to develop an understanding of inertial particle dynamics from a kinetic energy perspective. Data trends implying inhomogeneous sampling of the flow by particles are identified and used to support a proposed particle behavior: particles appear to accumulate in regions of low flow kinetic energy over time because they lose kinetic energy and slow down in such regions, ultimately causing them to spend more time there. To elucidate this behavior, we derive a particle kinetic energy equation from the particle momentum equation, which incorporates inertial effects through the Schiller-Naumann drag correlation. Upon extracting fundamental physics from this equation, hypotheses regarding the role of the Stokes number in the temporal change of particle kinetic energy and the previously proposed particle behavior are evaluated using simulation data considering three Stokes numbers. Finally, a Fokker-Planck equation is used to derive the steady-state probability density function of the particle kinetic energy. The model fits the simulation data well and provides a tool for further investigation into understanding preferential concentration, as well as a reduced order model for predicting particle kinetic energy in turbulent flows.

Automated summary

This study analyzes particle-laden, isotropic turbulence in three dimensions to understand the dynamics of inertial particles from a kinetic energy perspective. By identifying data trends, it is found that particles tend to accumulate in regions of low flow kinetic energy over time, as they lose kinetic energy and slow down in such regions. A particle kinetic energy equation is derived and hypotheses regarding the temporal change of particle kinetic energy and particle behavior are evaluated using simulation data. The steady-state probability density function of particle kinetic energy is derived using a Fokker-Planck equation. The model fits the simulation data well and provides a tool for investigating preferential concentration and predicting particle kinetic energy in turbulent flows.