Bubbles in turbulent flows: Data-driven, kinematic models with history terms

We present data driven kinematic models for the motion of bubbles in high-Re turbulent fluid flows based on recurrent neural networks with long-short term memory enhancements. The models extend empirical relations, such as Maxey-Riley (MR) and its variants, whose applicability is limited when either...

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Bibliographic Details
Main Authors: Wan, Zhong Yi (Author), Karnakov, Petr (Author), Koumoutsakos, Petros (Author), Sapsis, Themistoklis Panagiotis (Author)
Other Authors: Massachusetts Institute of Technology. Department of Mechanical Engineering (Contributor)
Format: Article
Language:English
Published: Elsevier BV, 2020-09-01T17:28:45Z.
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