A coupled LES/stochastic modeling approach to jet noise prediction

Joshua Blake, Adrian Sescu, David Thompson, Yuji Hattori

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper reports the progress on combining large eddy simulations (LES) with a stochastic model, aiming at resolving both the low and high frequency ranges in the acoustic spectrum associated with noise radiating from jets. Within this procedure, the source region is modeled using a combination of LES, modeling the large flow structures, and a stochastic model, accounting for the small flow scales. Sweeping of the stochastic scales by large LES scales is also considered. The farfield noise is predicted using a formulation of the linearized Euler equations (LEE), where the LES and the stochastic field are accounted for by a source term on the right hand side. A high-order numerical algorithm, involving dispersion relation preserving schemes for spatial discretization and low-dissipation and low-dispersion Runge-Kutta schemes for time marching, is applied for both LES and LEE solvers. The LEE numerical algorithm is validated using a 2D dipole test case. Then, preliminary results for the combined LES/stochastic model are reported for acoustic waves propagating from a Mach 0.9 jet. Results show promise in resolving higher frequency acoustic waves, although further investigation is needed to refine the method for predicting farfield acoustics.

Original languageEnglish
Title of host publicationAIAA Aerospace Sciences Meeting
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
Edition210059
ISBN (Print)9781624105241
DOIs
Publication statusPublished - 2018
EventAIAA Aerospace Sciences Meeting, 2018 - Kissimmee, United States
Duration: 2018 Jan 82018 Jan 12

Publication series

NameAIAA Aerospace Sciences Meeting, 2018
Number210059

Other

OtherAIAA Aerospace Sciences Meeting, 2018
CountryUnited States
CityKissimmee
Period18/1/818/1/12

ASJC Scopus subject areas

  • Aerospace Engineering

Fingerprint Dive into the research topics of 'A coupled LES/stochastic modeling approach to jet noise prediction'. Together they form a unique fingerprint.

  • Cite this

    Blake, J., Sescu, A., Thompson, D., & Hattori, Y. (2018). A coupled LES/stochastic modeling approach to jet noise prediction. In AIAA Aerospace Sciences Meeting (210059 ed.). (AIAA Aerospace Sciences Meeting, 2018; No. 210059). American Institute of Aeronautics and Astronautics Inc, AIAA. https://doi.org/10.2514/6.2018-1248