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DOE OSTI · 1565344

Using statistical learning to close two-fluid multiphase flow equations for a simple bubbly system

Ma, Ming·Lu, Jiacai·Tryggvason, Gretar
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Abstract

Direct numerical simulations of bubbly multiphase flows are utilized to find closure terms for a simple model of the average flow, using Neural Networks (NNs). The flow considered consists of several nearly spherical bubbles rising in a periodic domain where the initial vertical velocity and the average bubble density are homogeneous in two directions but non-uniform in one of the horizontal directions. After an initial transient motion the average void fraction and vertical velocity become approximately uniform. The NN is trained on a dataset from one simulation and then used to simulate the evolution of other initial conditions. As a whole, the resulting model predicts the evolution of the various initial conditions reasonably well.

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71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS

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Ma, Ming, Lu, Jiacai, Tryggvason, Gretar. 2015-09-15. Using statistical learning to close two-fluid multiphase flow equations for a simple bubbly system. https://doi.org/10.1063/1.4930004

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