Effects of Nonlinear Drag and Negative Loop Correlations on Heavy Particle Motion in Isotropic Stationary Turbulence Using a New Lagrangian Stochastic Model

Abstract

A new model for the prediction of particle dispersion in homogeneous isotropic stationary turbulence, based on an autoregressive moving average (ARMA) process, is presented in order to predict the fluctuating component of the fluid velocity along a heavy particle path. This model accounts for the crossing trajectory effect in that the transverse fluid velocity correlation is perfectly consistent with the negative loop correlation derived by Wang and Stock (1993). The particle turbulent intensity is shown to be increased compared to predictions based on exponential correlations. Possible consequences of the finite particle Reynolds number are also investigated, showing that the anisotropy of the motion of heavy particles is increased by nonlinear drag effects. In case of zero mean drift velocity, significant effects of nonlinear drag may also appear.