A New Probability Density Function Closure Model For Lagrangian Stochastic Dispersion Simulation
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When modelling dispersion through a Lagrangian stochastic process based on the Thomson's (J. Fluid Mtch, 180. 529-556) well mixed condition crite- rion, the Eulerian probability density function (pelf) for flow velocity must be supplied in analytical form. This is done building a pdf using the avail- able information on its first few measured moments. Here a new model for representing the Eulerian pdf using a general solu- tion for the bi- Gaussian scheme valid in the entire skewness-kurtosis plane. This was done through a free parameter // that accounts for the closure ot the system of equations generated by equating bi-Gaussian moments with those measured. Constraints on 77 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 ?