Luc Bertolotti
HIGH FIDELITY CFD-TRAINED MACHINE LEARNING TO INFORM RANS-MODELLED INTERFACIAL TURBULENCE
Bertolotti, Luc; Jefferson-Loveday, Richard; Ambrose, Stephen; Korsukova, Evgenia
Authors
RICHARD JEFFERSON-LOVEDAY Richard.Jefferson-Loveday@nottingham.ac.uk
Associate Professor
STEPHEN AMBROSE Stephen.Ambrose3@nottingham.ac.uk
Assistant Professor
EVGENIA KORSUKOVA EVGENIA.KORSUKOVA@NOTTINGHAM.AC.UK
Research Fellow Gas Turbines and Transmissions Research Centre
Abstract
In aero-engine bearing chambers, two-phase shearing flows are difficult to predict as Computational Fluid Dynamics (CFD) RANS models tend to overestimate interfacial turbulence levels, leading to inaccuracies in the modelling of the flow. Turbulence damping methods have been developed to address this problem, such as Egorov's correction, however, this method is mesh dependent and results differ considerably according to the choice of turbulence damping coefficient. In addition, this approach assumes a smooth interface between the air and oil phases when in reality they are wavy. In this paper, a Machine Learning method is used to inform an unsteady RANS turbulence modelling. It is trained using high fidelity quasi-DNS simulation data and used to provide an appropriate correction to the popular Wilcox's standard RANS í µí± − í µí¼ turbulence model. The correction consists of a machine learning-predicted source term which is used to adjust the energy budget in the RANS transport equations. Demonstration of the approach is presented for a range of interfacial flow regimes.
Citation
Bertolotti, L., Jefferson-Loveday, R., Ambrose, S., & Korsukova, E. (2022). HIGH FIDELITY CFD-TRAINED MACHINE LEARNING TO INFORM RANS-MODELLED INTERFACIAL TURBULENCE. In Proceedings of Global Power and Propulsion Society. https://doi.org/10.33737/gpps22-tc-30
Conference Name | GPPS Chania22 |
---|---|
Conference Location | Chania, Greece |
Start Date | Sep 12, 2022 |
End Date | Sep 14, 2022 |
Acceptance Date | Sep 1, 2022 |
Online Publication Date | Sep 28, 2022 |
Publication Date | Sep 14, 2022 |
Deposit Date | Nov 3, 2022 |
Publicly Available Date | Nov 3, 2022 |
Series ISSN | 2504-4400 |
Book Title | Proceedings of Global Power and Propulsion Society |
DOI | https://doi.org/10.33737/gpps22-tc-30 |
Public URL | https://nottingham-repository.worktribe.com/output/13177361 |
Publisher URL | https://gpps.global/wp-content/uploads/2022/09/GPPS-TC-2022_paper_30.pdf |
Additional Information | GPPS-TC-2022-0030 |
Files
GPPS-TC-2022 Paper 30
(660 Kb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by-nc-nd/4.0/
You might also like
Modelling Knudsen number effects in suspension high velocity oxy fuel thermal spray
(2020)
Journal Article
Enhanced Delayed Detached Eddy Simulation for Cavities and Labyrinth Seals
(2019)
Journal Article
Prediction of Film Thickness of an Aero-Engine Bearing Chamber using Coupled VOF and Thin Film Model
(2019)
Conference Proceeding
Assessment of an Enhanced Thin Film Model to Capture Wetting and Drying Behavior in an Aero-Engine Bearing Chamber
(2019)
Conference Proceeding