Machine learning-augmented turbulence models for the simulation of two-phase shear flows

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Machine learning-augmented turbulence models for the simulation of two-phase shear flows

This dissertation focuses on the investigation of co-current two-phase stratified gas-liquid shearing flows with a sharp interface for industrial applications and more specifically for the study of flows present in aero-engine bearing chambers. Predicting the behaviour of shear flows in the differen...

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Bibliographic Details
Main Author:	Bertolotti, Luc
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2022
Subjects:	Aero-engine Bearing chamber Two-phase flow Computational Fluid Dynamics Quasi-Direct Numerical Simulation Interfacial Turbulence Neureal Network Machine Learning
Online Access:	https://eprints.nottingham.ac.uk/71515/

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