Lagrangian Stochastic‐Deterministic (LSD) Predictions of Particle Dispersion in Turbulence

Abstract

AbstractA Lagrangian model of particle motion in turbulence has been developed. The model is stochastic in the sense that the "instantaneous" fluid velocity field is generated from known turbulence energy and time scales of large eddies by using a random sampling. The particle motion during the interaction with the eddies is deterministic as being predicted from solutions of Lagrangian momentum equations. On the basis of a large number of calculated trajectories, the distributions of local particle mean and fluctuation velocity components and of the mean square particle displacement are evaluated in a flow domain. The results of the predictions for the case of particle dispersion in nearly homogeneous and isotropic turbulence behind a grid are compared with existing experimental data and satisfactory agreement is achieved. The model is also applied to the case of the particle dispersion from a point source in a nonhomogeneous turbulence of fully developed pipe flow. The agreement with experiments is satisfactory for both heavy and tracer particles. An explanation is given for the experimentally observed phenomenon that in some cases heavy particles disperse faster than fluid points.