On the moments approximation method for constructing a Lagrangian Stochastic model |
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| Authors: | Shuming Du John D Wilson Eugene Yee |
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| Institution: | (1) Department of Geography, University of Alberta, T6G 2H4 Edmonton, Canada;(2) Defense Research Establishment Suffield, Medicine Hat, T1A 8K6, Canada |
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| Abstract: | The exact Eulerian velocity probability density function (pdf) of a turbulent field is generally unknown, and one normally has available only partial information in the form of low order moments. We compare two alternative Lagrangian Stochastic (LS) approaches formed from this partial information, (i) the  moments approximation approach (Kaplan and Dinar, 1993); and (ii) the well-mixed model (Thomson, 1987) that corresponds to the maximum missing information pdf formed from the available information. We show that the moments approximation model does not in general satisfy the well-mixed constraint, and can give an inferior prediction of dispersion. |
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