A Guide for Predicting the Aural Detectability of Aircraft

Abstract

The concepts which underlie the detection of aircraft by the human ear are described. A scheme is delineated for predicting the range at which a given aircraft will first be heard by an average listener; this scheme is also applicable to comparing the aural detectabilities of alternate aircraft configurations and to identifying those components of the noise of a given configuration which bear prime responsibility for the aircraft's detectability. Means are presented for predicting the noise due to all sources likely to be significant for light aircraft, the attenuation of acoustic signals propagating from an aircraft to a listener on the ground, and the ability of a listener to detect an acoustic signal in the presence of background noise. From a diffuse literature of acoustics, engineering mechanics and aeronautical engineering this report gathers knowledge and data on methods of predicting the source intensities, propagation and aural detection os sound radiated by military aircraft of the utility class. This report will be used for the design of quiet aircraft and discloses detailed methods used in evaluating such aircraft from the acoustical standpoint.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1972
Accession Number
AD0893335

Entities

People

  • Daniel L. Nelson
  • Eric E. Ungar
  • Istvan Ver
  • Joseph Smullin
  • Richard E. Hayden

Organizations

  • BBN Technologies

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acoustic Properties
  • Acoustics
  • Aircraft Equipment
  • Aircraft Noise
  • Aircrafts
  • Airframes
  • Boundary Layer
  • Engine Noise
  • Engineers
  • Gas Turbines
  • Geometry
  • Human Factors Engineering
  • Propulsion Systems
  • Scattering
  • Turbines
  • Turbojet Engines
  • Turboshaft Engines

Fields of Study

  • Physics

Readers

  • Acoustical Oceanography.
  • Speech Processing/Speech Recognition.
  • Systems Analysis and Design