Preparation of Noise Source Spheres for the Rotorcraft Noise Model

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Preparation of Noise Source Spheres for the
Rotorcraft Noise Model

• Kenneth J. Plotkin
• Juliet A. Page
• Micah Downing
• Wyle Laboratories
• Arlington, Virginia
• David A. Conner
• Aeroflightdynamics Directorate (AVRDEC) U.S. Army
  Aviation and Missile Command
• Langley Research Center

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Rotorcraft Noise Model (RNM)

• Atmospheric propagation model which performs an
  acoustic simulation of rotorcraft noise.
• Calculations begin with reference noise source
  characteristics defined on a sound source
  hemisphere.
• Sound Source Hemispheres contains broadband data
  for the following vehicles AH-1W, CH-146,
  CH-46E, CH-53E, MD-902, MV-22B, SH-60B, V-22A,
  XV-15, S-76. (Some data sets are restricted or
  proprietary.)

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Sound Hemisphere Content

• Directionality and Spectral content
• Broadband and narrowband data are considered.
• Broadband noise, obtained from measurement data,
  is defined in one-third octave bands.
• Narrow band amplitude and phase source
  hemispheres may also be generated.
• Sphere data can be from theory.

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ART2 Hemisphere creation from Measured Data

• Data Requirements
• Vehicle Tracking data
• Lateral Microphone Measurement Array
• Synchronized Acoustic data
• ART2 Model
• Acoustic Repropagation Technique 2
• Inverse propagation method
• Air absorption, ground effect, spherical
  spreading

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Hemisphere Depropagation Geometry

• Calculate times corresponding to ? at even
  increments
• ? follows from geometry of track, microphones

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Depropagation Physics

• Begin with original Level vs Time at each
  microphone
• Typically processed to ¼ or ½ second averages
• May be smoothed to eliminate turbulence artifacts
• Subtract spherical spreading
• Subtract air absorption current standard, at
  flight test conditions
• Subtract ground effect ground impedance
  methodology
• Obtain free-field, no-absorption spectrum at
  reference distance, at each ?, ?
• Interpolate onto sphere

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Normalized Data as Function of ?, ?
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Hemisphere Interpolation Method

• Normalized data at N values of ?, M values of ?
• N, ? controlled by user during analysis,
  correspond to those desired on sphere
• M is number of microphones, ? values are whatever
  they are
• Linearly interpolate between data at measured ?
  to get sphere points at desired regular ?
  intervals on sphere
• Force data at all ? values for ? 0o to be the
  same, and at ? 180o to be the same

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Final Sound Hemisphere

• Directly related to measured data
• Smoothing only at the original time-history
  recording level
• Simple interpolation onto sphere avoids artifacts
  of more sophisticated gridding methods
• NetCDF format for portability