Improved jet noise modeling using a new time-scale

M. Azarpeyvand*, R. H. Self

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

14 Citations (Scopus)

Abstract

To calculate the noise emanating from a turbulent flow using an acoustic analogy knowledge concerning the unsteady characteristics of the turbulence is required Specifically, the form of the turbulent correlation tensor together with various time and length-scales are needed. However, if a Reynolds Averaged Navier-Stores calculation is used as the starting point then one can only obtain steady characteristics of the flow and it is necessary to model the unsteady behavior in some way. While there has been considerable attention given to the correct way to model the form of the correlation tensor less attention has been given to the underlying physics that dictate the proper choice of time-scale. In this paper the authors recognize that there are several time dependent processes occurring within a turbulent flow and propose a new way of obtaining the time-scale. Isothermal single-stream flow jets with Mach numbers 0.75 and 0.90 have been chosen for the present study. The Mani-Gliebe-Balsa-Khavaran method has been used for prediction of noise at different angles, and there is good agreement between the noise predictions and observations. Furthermore, the new time-scale has an inherent frequency dependency that arises naturally from the underlying physics, thus avoiding supplementary mathematical enhancements needed in previous modeling. (C) 2009 Acoustical Society of America. [DOI: 10.1121/1.3192221]

Original languageEnglish
Pages (from-to)1015-1025
Number of pages11
JournalJournal of the Acoustical Society of America
Volume126
Issue number3
DOIs
Publication statusPublished - Sept 2009

Keywords

  • MIXING NOISE
  • ACOUSTIC ANALOGY
  • TURBULENCE
  • PREDICTION
  • PATTERN

Fingerprint

Dive into the research topics of 'Improved jet noise modeling using a new time-scale'. Together they form a unique fingerprint.

Cite this