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Neural network based generation of 1-dimensional stochastic fields with turbulent velocity statistics

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Abstract

We define and study a fully-convolutional neural network stochastic model, NN-Turb, which generates 1-dimensional fields with turbulent velocity statistics. Thus, the generated process satisfies the Kolmogorov 2/3 law for second order structure function. It also presents negative skewness across scales (i.e. Kolmogorov 4/5 law) and exhibits intermittency. Furthermore, our model is never in contact with turbulent data and only needs the desired statistical behavior of the structure functions across scales for training.
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Dates and versions

hal-03861273 , version 1 (19-11-2022)

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Carlos Granero-Belinchon. Neural network based generation of 1-dimensional stochastic fields with turbulent velocity statistics. 2022. ⟨hal-03861273⟩
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