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

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, Karnakov, Petr, Koumoutsakos, Petros, Sapsis, Themistoklis Panagiotis
Other Authors: Massachusetts Institute of Technology. Department of Mechanical Engineering
Format: Article
Language:English
Published: Elsevier BV 2020
Online Access:https://hdl.handle.net/1721.1/126877

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https://hdl.handle.net/1721.1/126877

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