Skip to main content
SpringerLink
Log in

Comparison of RANS-based jet noise models and assessment of a ray tracing method

  • Technical Paper
  • Published:
Journal of the Brazilian Society of Mechanical Sciences and Engineering Aims and scope Submit manuscript

Abstract

Four models to predict jet mixing noise available in the literature are reviewed and compared. Two models are derived from the Lighthill Acoustic Analogy (LAA) and the other two use the Linearized Euler Equations (LEE) with added source terms. All models use input from a computational solution of the Reynolds-Averaged Navier–Stokes (RANS) equations and empirical functions to model turbulent correlations. The models are concerned with the sources of sound related to small turbulent structures. Results for an observer at 90\(^{\circ }\) to the jet axis are presented, where effects of sound-flow interaction are negligible and the small structures are considered to act as the dominant source. A range of subsonic jets issued from different nozzle geometries with different exit velocities and temperatures is considered. In addition, a ray tracing method to compute the effects of sound refraction is reviewed. The comparison of the numerical predictions with experimental data shows that using the LAA with an improved description of turbulence statistics results in a model as accurate as the ones based on the LEE that relies on less empirical coefficients and has a simpler mathematical derivation. The results corroborate the use of RANS along with LAA to model jet mixing noise.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Adapted from Pierce [25]

Fig. 3

Adapted from Pierce [25]

Fig. 4

From Rosa et al. [28]; reprinted by permission of the American Institute of Aeronautics and Astronautics, Inc.

Fig. 5

From Rosa et al. [28]; reprinted by permission of the American Institute of Aeronautics and Astronautics, Inc.

Fig. 6

From Rosa et al. [28]; reprinted by permission of the American Institute of Aeronautics and Astronautics, Inc.

Fig. 7

From Rosa et al. [28]; reprinted by permission of the American Institute of Aeronautics and Astronautics, Inc.

Fig. 8

From Rosa et al. [28]; reprinted by permission of the American Institute of Aeronautics and Astronautics, Inc.

Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Notes

  1. For a typical analysis of the whole jet plume by Ilário et al. [13], the jet shear layer is discretized in approximately \(10^3\) sources.

References

  1. Balsa TF, Gliebe PR (1977) Aerodynamics and noise of coaxial jets. AIAA J 15(11):1550–1558. doi:10.2514/3.60822

    Article  MATH  Google Scholar 

  2. Balsa TF, Gliebe PR, Kantola RA, Mani R, Stringas EJ, Wang JCF (1978) High velocity jet noise source location and reduction. Task 2. Theoretical developments and basic experiments. Technical Report. FAA-RD-76-II, Federal Aviation Administration

  3. Batchelor GK (1953) The theory of homogeneous turbulence. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  4. Blokhintzev D (1946) The propagation of sound in an inhomogeneous and moving medium I. J Acoust Soc Am 18(2):322–328. doi:10.1121/1.1916368

    Article  MathSciNet  Google Scholar 

  5. Bridges J, Brown CA (2004) Parametric testing of chevrons on single flow hot jets. In: 10th AIAA/CEAS Aeroacoustics Conference. doi:10.2514/6.2004-2824

  6. Durbin PA (1983) High frequency Green function for aerodynamic noise in moving media, part I: general theory. J Sound Vib 91(4):519–525. doi:10.1016/0022-460X(83)90830-1

    Article  MATH  Google Scholar 

  7. Durgin G, Patwari N, S RT (1997) An advanced 3D ray launching method for wireless propagation prediction. In: IEEE 47th vehicular technology conference. doi:10.1109/VETEC.1997.600436

  8. Engel RC, Ilário CRS, Deschamps CJ (2014) Application of RANS-based method to predict acoustic noise of chevron nozzles. Appl Acoust 79:153–163. doi:10.1016/j.apacoust.2013.12.019

    Article  Google Scholar 

  9. Freund JB (2001) Noise sources in a low-Reynolds-number turbulent jet at Mach 0.9. J Fluid Mech 438:277–305. doi:10.1017/S0022112001004414

    Article  MATH  Google Scholar 

  10. Freund JB, Fleischman TG (2002) Ray traces through unsteady jet turbulence. Int J Aeroacoust 1(1):83–96. doi:10.1260/1475472021502686

    Article  Google Scholar 

  11. Goldstein ME (1982) High frequency sound emission from moving point multipole sources embedded in arbitrary transversely shear mean flows. J Sound Vib 80(4):499–522. doi:10.1016/0022-460X(82)90495-3

    Article  MATH  Google Scholar 

  12. Goldstein ME (2003) A generalized acoustic analogy. J Fluid Mech 488:315–333. doi:10.1017/S0022112003004890

    Article  MathSciNet  MATH  Google Scholar 

  13. Ilário CRS, Azarpeyvand M, Rosa V, Self RH, Meneghini JR (2017) Prediction of jet mixing noise with Lighthill's Acoustic Analogy and geometrical acoustics. J Acoust Soc Am 141(2):1203–1213. doi:10.1121/1.4976076

    Article  Google Scholar 

  14. Khavaran A, Bridges J (2012) An empirical temperature variance source model in heated jets. Technical Report. TM-2012-217743, NASA

  15. Khavaran A, Kenzakowski DC (2007) Noise prediction in hot jets. In: 13th AIAA/CEAS aeroacoustics conference. doi:10.2514/6.2007-3640

  16. Khavaran A, Krejsa EA (1993) Propagation of high frequency jet noise using geometric acoustics. In: 31st Aerospace sciences meeting and exhibit. doi:10.2514/6.1993-147

  17. Khavaran A, Krejsa EA (1999) Role of anisotropy in turbulent mixing noise. AIAA J 37:832–841. doi:10.2514/2.7531

    Article  Google Scholar 

  18. Khavaran A, Krejsa EA, Kim CM (1992) Computation of supersonic jet mixing noise for an axisymmetric CD nozzle using k-epsilon turbulence model. In: 30th Aerospace sciences meeting and exhibit. doi:10.2514/6.1992-500

  19. Lighthill MJ (1952) On sound generated aerodynamically. I. General theory. Proc R Soc A 211(1107):564–587. doi:10.1098/rspa.1952.0060

    Article  MathSciNet  MATH  Google Scholar 

  20. Lilley GM (1972) The generation and radiation of supersonic jet noise. Vol IV—Theory of turbulent generated jet noise, noise radiation from upstream sources, and combustion noise. Part II. Generation of sound in a mixing region. Technical report, Air Force Propulsion Laboratory

  21. Morris PJ, Boluriaan S (2004) The prediction of jet noise from CFD data. In: 10th AIAA/CEAS aeroacoustics conference. doi:10.2514/6.2004-2977

  22. Morris PJ, Farassat F (2002) Acoustic analogy and alternative theories for jet noise prediction. AIAA J 40(4):671–680. doi:10.2514/2.1699

    Article  Google Scholar 

  23. Morris PJ, Farassat F (2003) Reply by the authors to C. K. W. Tam. AIAA J 41(9):1845–1847. doi:10.2514/2.7309

    Article  Google Scholar 

  24. Peake N (2004) A note on “Computational aeroacoustics examples showing the failure of the acoustic analogy theory to identify the correct noise sources” by CKW Tam. J Comput Acoust 12(4):631–634. doi:10.1142/S0218396X04002420

    Article  Google Scholar 

  25. Pierce AD (1981) Acoustics: an introduction to its physical principles and applications. McGraw-Hill, New York

    Google Scholar 

  26. Press WH, Teukolsky SA, Vetterling WT, Flannery BP (1997) Numerical recipes in Fortran 77. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  27. Ribner HS (1969) Quadrupole correlations governing the pattern of jet noise. J Fluid Mech 38(1):1–24. doi:10.1017/S0022112069000012

    Article  MATH  Google Scholar 

  28. Rosa VHP, Deschamps CJ, Salazar JPLC, Ilário CRS (2013) Comparison of RANS-based methods for the prediction of noise emitted by subsonic turbulent jets. In: 19th AIAA/CEAS aeroacoustics conference. doi:10.2514/6.2013-2276

  29. Self RH (2004) Jet noise prediction using the Lighthill acoustic analogy. J Sound Vib 275(3–5):757–768. doi:10.1016/j.jsv.2003.06.020

    Article  Google Scholar 

  30. Self RH, Azarpeyvand M (2008) Utilization of turbulent energy transfer rate time-scale in aeroacoustics with application to heated jets. Int J Aeroacoust 7(2):83–102. doi:10.1260/147547208784649455

    Article  Google Scholar 

  31. Self RH, Azarpeyvand M (2009) Jet noise prediction using different turbulent scales. Acoust Phys 55(3):433–440. doi:10.1134/S106377100903021X

    Article  Google Scholar 

  32. Spalart PR (2007) Application of full and simplified acoustic analogies to an elementary problem. J Fluid Mech 578:113–118. doi:10.1017/S002211200700496X

    Article  MATH  Google Scholar 

  33. Spalart PR, Shur ML, Strelets MK (2007) Identification of sound sources in large-eddy simulations of jets. In: 13th AIAA/CEAS aeroacoustics conference. doi:10.2514/6.2007-3616

  34. Stone JT, Self RH, Howls CJ (2014) A complex ray-tracing tool for high-frequency mean field flow-interaction effects in jets. In: 20th AIAA/CEAS aeroacoustics conference. doi:10.2514/6.2014-2757

  35. Tam CKW (2002a) Computational aeroacoustics examples showing the failure of the acoustic analogy theory to identify the correct noise sources. J Comput Acoust 10(4):387–405. doi:10.1142/S0218396X02001607

    Article  MathSciNet  MATH  Google Scholar 

  36. Tam CKW (2002b) Further consideration of the limitations and validity of the acoustic analogy theory. In: 8th AIAA/CEAS aeroacoustics conference and exhibit. doi:10.2514/6.2002-2425

  37. Tam CKW (2003) Comment on “Acoustic analogy and alternative theories for jet noise prediction”. AIAA J 41(9):1844–1845. doi:10.2514/2.7308

    Article  Google Scholar 

  38. Tam CKW, Auriault L (1999) Jet mixing noise from fine-scale turbulence. AIAA J 37(2):145–153. doi:10.2514/2.691

    Article  Google Scholar 

  39. Tam CKW, Golebiowski M, Seiner JM (1996) On the two components of turbulent mixing noise from supersonic jets. In: 2nd AIAA/CEAS aeroacoustics conference. doi:10.2514/6.1996-1716

  40. Tam CKW, Pastouchenko NN, Viswanathan K (2005) Fine-scale turbulence noise from hot jets. AIAA J 43(8):1675–1683. doi:10.2514/1.8065

    Article  Google Scholar 

  41. Wundrow DW, Khavaran A (2004) On the applicability of high-frequency approximations to Lilley’s equation. J Sound Vib 272(3–5):793–830. doi:10.1016/S0022-460X(03)00420-6

    Article  Google Scholar 

Download references

Acknowledgements

The authors gratefully acknowledge support from EMBRAER and the Brazilian agencies CAPES and CNPq. This research has been conducted with data from the SYMPHONY project, which is part of the UK Technology Strategy Board contract TP11/HVM/6/I/AB201K. The data was made available by a partnership with ISVR, for which the authors are extremely thankful.

Author information

Authors and Affiliations

  1. POLO Laboratories, Federal University of Santa Catarina, Florianópolis, Brazil

    V. Rosa & C. J. Deschamps

  2. Aerospace Engineering, Federal University of Santa Catarina, Joinville, Brazil

    J. P. L. C. Salazar

  3. Embraer, São José dos Campos, Brazil

    C. R. S. Ilário

Authors
  1. V. Rosa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. C. J. Deschamps
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. J. P. L. C. Salazar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. C. R. S. Ilário
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to V. Rosa.

Additional information

Technical Editor: Joao Luiz F. Azevedo.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rosa, V., Deschamps, C.J., Salazar, J.P.L.C. et al. Comparison of RANS-based jet noise models and assessment of a ray tracing method. J Braz. Soc. Mech. Sci. Eng. 39, 1859–1872 (2017). https://doi.org/10.1007/s40430-017-0746-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40430-017-0746-4

Keywords

Search

Navigation