High Velocity Jet Noise Source Location and Reduction. Task 6. Supplement. Computer Programs: Engineering Correlation (M*S) Jet Noise Prediction Method and Unified Aeroacoustic Prediction Model (M*G*B) for Nozzles of Arbitary Shape.
Abstract
This General Supplement Report documents two Computerized Jet Noise Prediction Techniques: the Engineering Method and the Unified Aeroacoustic Prediction Model. A complete description of the computer programs is provided, including examples of input preparation and output cases, plus a listing of the FORTRAN computer code. The comprehensive, empirical, jet noise prediction method has been developed by correlating extensive data from this program and available data from other published sources. The data were correlated by means of basic engineering principles and physical parameters. The resulting prediction method includes unsuppressed conical nozzles; multitube and multichute single- and dual-flow suppressed nozzles; and multitube/multichute nozzles with hardwall and treated sectors. A unified aerodynamic/acoustic prediction technique has also been developed for assessing the noise characteristics of suppressor nozzles. The technique utilizes an extension of Reichardt's method so as to provide predictions of a jet plume flow field. The turbulent fluctuations in the mixing regions of the jet are assumed to be the primary source of noise generation, as in Classical Theories of Jet Noise. The alteration of the generated noise by the jet plume itself as it propagates through the jet to the farfield is modeled utilizing the high-frequency shielding theory based on Lilley's equation. These basic modeling elements have been coupled together in a discrete volume-element formulation. The individual volume elements are assumed to be uncorrelated with each other, so that the total contribution to the farfield is simply the sum of the individual volume element contributions.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 1979
- Accession Number
- ADA094298
Entities
People
- A. Sieckman
- P. R. Gliebe
- R. E. Motsinger
Organizations
- General Electric