Numerical Simulation of Subsonic Jet Noise on Non-Conformal Mesh by Spectral Difference Method

  • Junhui Gao*
  • , Jiamin Zhao
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this study, the noise from a subsonic cold jet with acoustic Mach number 0.9 is simulated with a high order spectral difference solver on non-conformal mesh. To accurately simulate the thin turbulence boundary layer inside the nozzle, the jet plume, and the generated noise, which have vastly different scales, the meshes with different sizes are adopted in the nozzle boundary layer, jet shear-layer and the outside region. An interpolation method based on mortar is proposed for data communication at the interface where the non-conformal mesh is used. This method is validated by inviscid and viscous flow problems to demonstrate its accuracy on non-conformal mesh. The Large Eddy Simulation method is utilized to simulate the turbulence with the Vreman model to account for the unresolved dynamics on the solution. The mean flow results are presented and compared with the experimental data by Bridges et al. [1, 2]. The far field noise is obtained by the Ffowcs Williams-Hawkings integration method. The noise spectra at different observer angles are presented and compared with the experimental data, and a good agreement is obtained.

Original languageEnglish
Title of host publication30th AIAA/CEAS Aeroacoustics Conference, 2024
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624107207
DOIs
StatePublished - 2024
Event30th AIAA/CEAS Aeroacoustics Conference, 2024 - Rome, Italy
Duration: 4 Jun 20237 Jun 2023

Publication series

Name30th AIAA/CEAS Aeroacoustics Conference, 2024

Conference

Conference30th AIAA/CEAS Aeroacoustics Conference, 2024
Country/TerritoryItaly
CityRome
Period4/06/237/06/23

Fingerprint

Dive into the research topics of 'Numerical Simulation of Subsonic Jet Noise on Non-Conformal Mesh by Spectral Difference Method'. Together they form a unique fingerprint.

Cite this