Modeling supersonic heated jet noise at fixed jet Mach number using an asymptotic approach for the acoustic analogy Green’s function and an optimized turbulence model

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Afsar, Mohammed Z. and Sescu, Adrian and Minisci, Edmondo; (2019) Modeling supersonic heated jet noise at fixed jet Mach number using an asymptotic approach for the acoustic analogy Green’s function and an optimized turbulence model. In: 25th AIAA/CEAS Aeroacoustics Conference. AIAA, NLD. ISBN 9781624105883 (https://doi.org/10.2514/6.2019-2731)

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Abstract

In this study we show how accurate jet noise predictions can be achieved within Goldstein’s generalized acoustic analogy formulation for heated and un-heated supersonic jets using a previously developed asymptotic theory for the adjoint vector Green’s function and a turbulence model whose independent parameters are determined using an optimization algorithm . In this approach, mean flow non-parallelism enters the lowest order dominant balance producing enhanced amplification at low frequencies, which we believe corresponds to the peak sound at small polar observation angles. The novel aspect of this paper is that we exploit both mean flow and turbulence structure from existent Large Eddy Simulations database of two axi-symmetric round jets at fixed jet Mach number and different nozzle temperature ratios to show (broadly speaking) the efficacy of the asymptotic approach. The empirical parameters that enter via local turbulence length scales within the algebraic-exponential turbulence model are determined by optimizing against near field turbulence data post-processed from the LES calculation. Our results indicate that accurate jet noise predictions are obtained with this approach up to a Strouhal number of 0.5 for both jets without introducing significant empiricism.

ORCID iDs

Afsar, Mohammed Z. ORCID logoORCID: https://orcid.org/0000-0002-7417-2089, Sescu, Adrian and Minisci, Edmondo ORCID logoORCID: https://orcid.org/0000-0001-9951-8528;
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