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Title: Divergence free development of the synthetic eddy method in order to improve synthetic turbulence for embedded LES simulations
Author: Poletto, Ruggero
ISNI:       0000 0004 5366 8522
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2015
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In order to increase results accuracy and to provide some time-dependency to CFD results, embedded RANS/LES simulations are getting more and more interesting. In order to run these simulations accurate LES boundary conditions are required, not to affect the downstream results with a poor quality synthetic turbulence generation. Considering the currently developped methodologies, it is not possible to generate a divergence free turbulent flow which satisfy a non isotropic state of turbulence. The author started from the Synthetic Eddy Method (SEM) defined by Jarrin (2009), and defined a new shape function with the ability to satisfy continuity. The new methodology, named Divergence Free SEM (DFSEM), is able to reproduce almost any kind of turbulence anisotropy by using a special shape function and adapting the eddies intensities in order to match the Reynolds stress tensor rather than using the Lund coefficients, as most of the precursor methodologies did. Results comparisons against SEM and some other very popular synthetic turbulence models in some academic cases, proved that a reduce influence on the downstream flow was achieved. In most of the cases the friction coefficient Cf , used as a performance parameter, benefit by reducing the downstream developping zone by almost 50% in most cases, when compared against SEM. Another issue that has been tackled regards the unphysical pressure fluctuations present because of the synthetic turbulence, due to non perfectly constant mass-flow rate imposed in stochastic methodologies. The new methodology also showed an increased flexibility as it has been tested in embedded DDES simulation, by using the blending function to activate/deactivate it, and again it showed improved performances when compared against standard SEM.
Supervisor: Revell, Alistair Sponsor: EDF
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Hybrid RANS/LES ; Synthetic turbulence