Prediction of supersonic jet noise using non-parallel flow asymptotics and LES data within Goldstein’s acoustic analogy

M. Z. Afsar, A. Sescu, V. Sassanis, A. Towne, G. A. Brès, S. K. Lele

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this study we show how accurate jet noise predictions can be achieved within Gold-stein’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. In this approach, mean flow non-parallelism enters the leading order dominant balance producing enhanced amplification at low frequencies, which we believe corresponds to the peak sound at small polar observation angles. We determine all relevant mean flow and turbulence quantities using Large Eddy Simulations of two axi-symmetric round jets at fixed jet Mach number and different nozzle temperature ratios. Certain empirical co-efficients that enter the turbulence length scales formula are tuned for good agreement with the far-field noise data. Our results indicate that excellent jet noise predictions are obtained using the asymptotic approach, remarkably, up to a Strouhal number of 0.5.
LanguageEnglish
Title of host publicationStudying Turbulence using Numerical Simulation Databases - XVI
Subtitle of host publicationProceedings of the 2016 Summer Program
Place of PublicationStanford, California
Number of pages10
Publication statusPublished - 31 Dec 2016

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Acoustics
Turbulence
Strouhal number
Large eddy simulation
Green's function
Mach number
Amplification
Nozzles
Gold
Acoustic waves
Temperature

Keywords

  • jet noise predictions
  • Gold-stein’s generalized acoustic analogy formulation
  • adjoint vector Green’s function
  • asymptotic approach
  • turbulence
  • mean flow

Cite this

Afsar, M. Z., Sescu, A., Sassanis, V., Towne, A., Brès, G. A., & Lele, S. K. (2016). Prediction of supersonic jet noise using non-parallel flow asymptotics and LES data within Goldstein’s acoustic analogy. In Studying Turbulence using Numerical Simulation Databases - XVI: Proceedings of the 2016 Summer Program Stanford, California.
Afsar, M. Z. ; Sescu, A. ; Sassanis, V. ; Towne, A. ; Brès, G. A. ; Lele, S. K. / Prediction of supersonic jet noise using non-parallel flow asymptotics and LES data within Goldstein’s acoustic analogy. Studying Turbulence using Numerical Simulation Databases - XVI: Proceedings of the 2016 Summer Program. Stanford, California, 2016.
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abstract = "In this study we show how accurate jet noise predictions can be achieved within Gold-stein’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. In this approach, mean flow non-parallelism enters the leading order dominant balance producing enhanced amplification at low frequencies, which we believe corresponds to the peak sound at small polar observation angles. We determine all relevant mean flow and turbulence quantities using Large Eddy Simulations of two axi-symmetric round jets at fixed jet Mach number and different nozzle temperature ratios. Certain empirical co-efficients that enter the turbulence length scales formula are tuned for good agreement with the far-field noise data. Our results indicate that excellent jet noise predictions are obtained using the asymptotic approach, remarkably, up to a Strouhal number of 0.5.",
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Afsar, MZ, Sescu, A, Sassanis, V, Towne, A, Brès, GA & Lele, SK 2016, Prediction of supersonic jet noise using non-parallel flow asymptotics and LES data within Goldstein’s acoustic analogy. in Studying Turbulence using Numerical Simulation Databases - XVI: Proceedings of the 2016 Summer Program. Stanford, California.

Prediction of supersonic jet noise using non-parallel flow asymptotics and LES data within Goldstein’s acoustic analogy. / Afsar, M. Z.; Sescu, A.; Sassanis, V.; Towne, A.; Brès, G. A.; Lele, S. K.

Studying Turbulence using Numerical Simulation Databases - XVI: Proceedings of the 2016 Summer Program. Stanford, California, 2016.

Research output: Chapter in Book/Report/Conference proceedingChapter

TY - CHAP

T1 - Prediction of supersonic jet noise using non-parallel flow asymptotics and LES data within Goldstein’s acoustic analogy

AU - Afsar, M. Z.

AU - Sescu, A.

AU - Sassanis, V.

AU - Towne, A.

AU - Brès, G. A.

AU - Lele, S. K.

PY - 2016/12/31

Y1 - 2016/12/31

N2 - In this study we show how accurate jet noise predictions can be achieved within Gold-stein’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. In this approach, mean flow non-parallelism enters the leading order dominant balance producing enhanced amplification at low frequencies, which we believe corresponds to the peak sound at small polar observation angles. We determine all relevant mean flow and turbulence quantities using Large Eddy Simulations of two axi-symmetric round jets at fixed jet Mach number and different nozzle temperature ratios. Certain empirical co-efficients that enter the turbulence length scales formula are tuned for good agreement with the far-field noise data. Our results indicate that excellent jet noise predictions are obtained using the asymptotic approach, remarkably, up to a Strouhal number of 0.5.

AB - In this study we show how accurate jet noise predictions can be achieved within Gold-stein’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. In this approach, mean flow non-parallelism enters the leading order dominant balance producing enhanced amplification at low frequencies, which we believe corresponds to the peak sound at small polar observation angles. We determine all relevant mean flow and turbulence quantities using Large Eddy Simulations of two axi-symmetric round jets at fixed jet Mach number and different nozzle temperature ratios. Certain empirical co-efficients that enter the turbulence length scales formula are tuned for good agreement with the far-field noise data. Our results indicate that excellent jet noise predictions are obtained using the asymptotic approach, remarkably, up to a Strouhal number of 0.5.

KW - jet noise predictions

KW - Gold-stein’s generalized acoustic analogy formulation

KW - adjoint vector Green’s function

KW - asymptotic approach

KW - turbulence

KW - mean flow

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UR - https://ctr.stanford.edu/proceedings-2016-summer-program

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M3 - Chapter

BT - Studying Turbulence using Numerical Simulation Databases - XVI

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Afsar MZ, Sescu A, Sassanis V, Towne A, Brès GA, Lele SK. Prediction of supersonic jet noise using non-parallel flow asymptotics and LES data within Goldstein’s acoustic analogy. In Studying Turbulence using Numerical Simulation Databases - XVI: Proceedings of the 2016 Summer Program. Stanford, California. 2016