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Developing an Empirical Model for Jet-Surface Interaction Noise
Author(s) -
Clifford A. Brown
Publication year - 2014
Publication title -
22nd aerospace sciences meeting
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2014-0878
Subject(s) - airframe , jet (fluid) , observer (physics) , jet noise , noise (video) , spectral line , jet engine , computation , scaling , mechanics , amplitude , computational physics , physics , acoustics , computer science , optics , algorithm , mathematics , engineering , aerospace engineering , geometry , artificial intelligence , quantum mechanics , astronomy , image (mathematics) , thermodynamics
The process of developing an empirical model for jet-surface interaction noise is described and the resulting model evaluated. Jet-surface interaction noise is generated when the high-speed engine exhaust from modern tightly integrated or conventional high-bypass ratio engine aircraft strikes or flows over the airframe surfaces. An empirical model based on an existing experimental database is developed for use in preliminary design system level studies where computation speed and range of configurations is valued over absolute accuracy to select the most promising (or eliminate the worst) possible designs. The model developed assumes that the jet-surface interaction noise spectra can be separated from the jet mixing noise and described as a parabolic function with three coefficients: peak amplitude, spectral width, and peak frequency. These coefficients are fit to functions of surface length and distance from the jet lipline to form a characteristic spectra which is then adjusted for changes in jet velocity and/or observer angle using scaling laws from published theoretical and experimental work. The resulting model is then evaluated for its ability to reproduce the characteristic spectra and then for reproducing spectra measured at other jet velocities and observer angles; successes and limitations are discussed considering the complexity of the jet-surface interaction noise versus the desire for a model that is simple to implement and quick to execute.

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