ON THE MOMENTS APPROXIMATION METHOD FOR CONSTRUCTING A LAGRANGIAN STOCHASTIC-MODEL

The exact Eulerian velocity probability density function (pdf) of a tu rbulent field is generally unknown, and one normally has available onl y partial information in the form of low order moments. We compare two alternative Lagrangian Stochastic (LS) approaches formed from this pa rtial information, (i) the ''moments approximation'' approach (Kaplan and Dinar, 1993); and (ii) the well-mixed model (Thomson, 1987) that c orresponds to the ''maximum missing information'' pdf formed from the available information. We show that the moments approximation model do es not in general satisfy the well-mixed constraint, and can give an i nferior prediction of dispersion.