An empirical model of noise sources in subsonic jets

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KARBAN U., Bugeat B., Towne A., Lesshafft L., Agarwal A., Jordan P.

Journal of Fluid Mechanics, vol.965, 2023 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 965
  • Publication Date: 2023
  • Doi Number: 10.1017/jfm.2023.376
  • Journal Name: Journal of Fluid Mechanics
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Aerospace Database, Applied Science & Technology Source, Aquatic Science & Fisheries Abstracts (ASFA), Chimica, Communication Abstracts, Compendex, Computer & Applied Sciences, Geobase, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Keywords: aeroacoustics, jet noise, turbulence modelling
  • Middle East Technical University Affiliated: Yes


Modelling the noise emitted by turbulent jets is made difficult by their acoustic inefficiency: only a tiny fraction of the near-field turbulent kinetic energy is propagated to the far field as acoustic waves. As a result, jet-noise models must accurately capture this small, acoustically efficient component hidden among comparatively inefficient fluctuations. In this paper, we identify this acoustically efficient near-field source from large-eddy simulation data and use it to inform a predictive model. Our approach uses the resolvent framework, in which the source takes the form of nonlinear fluctuation terms that act as a forcing on the linearised Navier-Stokes equations. First, we identify the forcing that, when acted on by the resolvent operator, produces the leading spectral proper orthogonal decomposition modes in the acoustic field for a Mach 0.4 jet. Second, the radiating components of this forcing are isolated by retaining only portions with a supersonic phase speed. This component makes up less than 0.05Â % of the total forcing energy but generates most of the acoustic response, especially at peak (downstream) radiation angles. Finally, we propose an empirical model for the identified acoustically efficient forcing components. The model is tested at other Mach numbers and flight-stream conditions and predicts noise within 2Â dB accuracy for a range of frequencies, downstream angles and flight conditions.