Geodesic
Development of semi-parametric models of Raleigh–Taylor instability by means of neuronet processing of the results of numerical experiment
Matematičeskoe modelirovanie, Tome 16 (2004) no. 7, pp. 21-30 
A. S. Nuzhny; V. B. Rozanov; R. V. Stepanov; S. A. Shumsky. Development of semi-parametric models of Raleigh–Taylor instability by means of neuronet processing of the results of numerical experiment. Matematičeskoe modelirovanie, Tome 16 (2004) no. 7, pp. 21-30. http://geodesic.mathdoc.fr/item/MM_2004_16_7_a3/
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     author = {A. S. Nuzhny and V. B. Rozanov and R. V. Stepanov and S. A. Shumsky},
     title = {Development of semi-parametric models of {Raleigh{\textendash}Taylor} instability by means of neuronet processing of the results of numerical experiment},
     journal = {Matemati\v{c}eskoe modelirovanie},
     pages = {21--30},
     year = {2004},
     volume = {16},
     number = {7},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/MM_2004_16_7_a3/}
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Voir la notice de l'article provenant de la source Math-Net.Ru

Investigation of turbulent flows, and, in particular, the flows arising due to Raleigh–Taylor instability, is a fundamental hydrodynamic problem. Due to complexity of direct numerical calculation and scantiness of a parametric approach one has to look for new methods for the description of turbulent flows. A principally new approach to studying of the problem is proposed in this work, i.e. the development of a semi-parametric model by means of a neuronet analysis of the experimental (calculation) data. Below we describe a technique for coding the initial physical fields aimed at the creation of neuronet input vectors, present a stable description of Raleigh–Taylor mixing processes, show a possibility in principle to predict the development of turbulent flows.

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