A new probability density function closure model for Lagrangian stochastic dispersion simulation

When modelling dispersion through a Lagrangian stochastic process based on the Thomson's (J. Fluid il,Mech, 180, 529-556) well mixed condition criterion, the Eulerian probability density function (pdf) for flow velocity: must be supplied in analytical form. This is done building a. pdf using the available information on its first few measured moments. Here a new model for representing: the Eulerian pdf using: a general solution for the bi-Gaussian scheme valid in the entire skewness-kurtosis plane. This was clone through a. free parameter eta that accounts for the closure of the system of equations generated by equating. bi-Gaussian moments with those measured. Constraints on eta arising from requirements of continuity and existence of the solution are shown and discussed together with a criterion derived from the maximum missing information theory for the choice of eta in a more theoretically based ground. It is proven that the mmi closure automatically satisfies the above requirements. An application to highly inhomogeneous, non-Gaussian turbulence with fourth moments given. shows that it also reduces the problem induced by the possible bi-modality of the bi-Gaussian representation even though in some cases it cannot remove it. Further investigation is needed in order to test. the model against some suitable. complete dataset.