
handle: 11368/1698151
We consider Lagrangian stochastic modelling of the relative motion of two fluid particles in the inertial range of a turbulent flow. Eulerian analysis of such modelling corresponds to an equation for the Eulerian probability distribution of velocity-vector increments which introduces a hierarchy of constraints for making the model consistent with results from the theory of locally isotropic turbulence. A nonlinear Markov process is presented, which is able to satisfy exactly, in the statistical sense, incompressibility, the exact results on the third-order structure function, and the experimental second-order statistics. The corresponding equation for the Eulerian probability density of velocity-vector increments is solved numerically. Numerical results show non-Gaussian statistics of the one-dimensional Lagrangian probability distributions, and a complex shape of the three-dimensional Eulerian probability density function. The latter is then compared with existing experimental data.
Turbulence, two fluid particles, Eulerian probability distribution, Stochastic analysis applied to problems in fluid mechanics, incompressibility, non-Gaussian statistics, Other physical applications of random processes, nonlinear Markov process, Lagrangian stochastic modelling
Turbulence, two fluid particles, Eulerian probability distribution, Stochastic analysis applied to problems in fluid mechanics, incompressibility, non-Gaussian statistics, Other physical applications of random processes, nonlinear Markov process, Lagrangian stochastic modelling
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