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G-equation modelling of thermo-acoustic oscillations of partially-premixed flames

Published version
Peer-reviewed

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Article

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Authors

Semlitsch, Bernhard  ORCID logo  https://orcid.org/0000-0001-7715-863X
Orchini, A 
Dowling, AP 
Juniper, MPJ 

Abstract

Numerical simulations aid combustor design to avoid and reduce thermo-acoustic oscillations. Non-linear heat release rate estimation and its modelling are essential for the prediction of saturation amplitudes of limit cycles. The heat release dynamics of flames can be approximated by a Flame Describing Function (FDF). To calculate an FDF, a wide range of forcing amplitudes and frequencies needs to be considered. For this reason, we present a computationally inexpensive level-set approach, which accounts for equivalence ratio perturbations on flames with arbitrarily-complex shapes. The influence of flame parameters and modelling approaches on flame describing functions and time delay coefficient distributions are discussed in detail. The numerically-obtained flame describing functions are compared with experimental data and used in an acoustic network model for limit cycle prediction. A reasonable agreement of the heat release gain and limit cycle frequency is achieved even with a simplistic, analytical velocity fluctuation model. However, the phase decay is over-predicted. For sophisticated flame shapes, only the realistic modelling of large-scale flow structures allows the correct phase decay predictions of the heat release rate response.

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Keywords

Thermoacoustic instability, non-linear combustion modelling, flame describing function, equivalence ratio perturbation

Journal Title

International Journal of Spray and Combustion Dynamics

Conference Name

Journal ISSN

1756-8277
1756-8285

Volume Title

9

Publisher

Sage
Sponsorship
European Commission (641453)
This work was conducted within the EU 7th Framework Project Joint Technology Initiatives - Clean Sky (AMEL- Advanced Methods for the Prediction of Lean-burn Combustor Unsteady Phenomena), project number: JTI-CS-2013-3-SAGE- 06-009 / 641453. This work was performed using the Darwin Supercomputer of the University of Cambridge High Performance Computing Service (http://www.hpc.cam.ac.uk/), provided by Dell Inc. using Strategic Research Infrastructure Funding from the Higher Education Funding Council for England and funding from the Science and Technology Facilities Council.