The reduction of pollution and noise emissions of modern aero engines represents a key concept to meet the requirements of the future air traffic. This requires an improvement in the understanding of combustion noise and its sources, as well as the development of accurate predictive tools. This is the major goal of the current study where the LOTAN network solver and a hybrid CFD/CAA approach are applied on a generic pre-mixed and pressurized combustor to evaluate their capabilities for combustion noise predictions. LOTAN solves the linearized Euler equations (LEE) whereas the hybrid approach consists of RANS mean flow and frequency-domain simulations based on linearized Navier-Stokes equations (LNSE). Both solvers are fed in turn by three different combustion noise source terms which are obtained from the application of a statistical noise model on the RANS simulations and a postprocessing of an incompressible and compressible LES. In this way the influence of the source model and acoustic solver is identified. The numerical results are compared with experimental data. In general good agreement with the experiment is found for both the LOTAN and LNSE solvers. The LES source models deliver better results than the statistical noise model with respect to the amplitude and shape of the heat release spectrum. Beyond this it is demonstrated that the phase relation of the source term does not affect the noise spectrum. Finally, a second simulation based on the inhomogeneous Helmholtz equation indicates the minor importance of the aerodynamic mean flow on the broadband noise spectrum.
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ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition
June 26–30, 2017
Charlotte, North Carolina, USA
Conference Sponsors:
- International Gas Turbine Institute
ISBN:
978-0-7918-5085-5
PROCEEDINGS PAPER
Prediction of Combustion Noise in a Model Combustor Using a Network Model and a LNSE Approach
Wolfram C. Ullrich,
Wolfram C. Ullrich
Technische Universität München, Garching, Germany
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Christoph Hirsch,
Christoph Hirsch
Technische Universität München, Garching, Germany
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Thomas Sattelmayer,
Thomas Sattelmayer
Technische Universität München, Garching, Germany
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Yasser Mahmoudi,
Yasser Mahmoudi
University of Cambridge, Cambridge, UK
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Ann P. Dowling,
Ann P. Dowling
University of Cambridge, Cambridge, UK
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Nedunchezhian Swaminathan,
Nedunchezhian Swaminathan
University of Cambridge, Cambridge, UK
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Kilian Lackhove,
Kilian Lackhove
Technische Universität Darmstadt, Darmstadt, Germany
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Amsini Sadiki,
Amsini Sadiki
Technische Universität Darmstadt, Darmstadt, Germany
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André Fischer,
André Fischer
Rolls-Royce Deutschland Ltd & Co KG, Blankenfelde-Mahlow, Germany
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Max Staufer
Max Staufer
Rolls-Royce Deutschland Ltd & Co KG, Blankenfelde-Mahlow, Germany
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Wolfram C. Ullrich
Technische Universität München, Garching, Germany
Christoph Hirsch
Technische Universität München, Garching, Germany
Thomas Sattelmayer
Technische Universität München, Garching, Germany
Yasser Mahmoudi
University of Cambridge, Cambridge, UK
Ann P. Dowling
University of Cambridge, Cambridge, UK
Nedunchezhian Swaminathan
University of Cambridge, Cambridge, UK
Kilian Lackhove
Technische Universität Darmstadt, Darmstadt, Germany
Amsini Sadiki
Technische Universität Darmstadt, Darmstadt, Germany
André Fischer
Rolls-Royce Deutschland Ltd & Co KG, Blankenfelde-Mahlow, Germany
Max Staufer
Rolls-Royce Deutschland Ltd & Co KG, Blankenfelde-Mahlow, Germany
Paper No:
GT2017-64300, V04BT04A009; 13 pages
Published Online:
August 17, 2017
Citation
Ullrich, WC, Hirsch, C, Sattelmayer, T, Mahmoudi, Y, Dowling, AP, Swaminathan, N, Lackhove, K, Sadiki, A, Fischer, A, & Staufer, M. "Prediction of Combustion Noise in a Model Combustor Using a Network Model and a LNSE Approach." Proceedings of the ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition. Volume 4B: Combustion, Fuels and Emissions. Charlotte, North Carolina, USA. June 26–30, 2017. V04BT04A009. ASME. https://doi.org/10.1115/GT2017-64300
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