Turbulence Analysis by use of the Fast Fourier Transform.

Abstract

The author has shown that the Fast Fourier Transform is a useful tool in turbulence analysis and the lack of canned programs of the Fourier transform of the autocorrelation function poses no serious problem. The user is cautioned, however, to be aware of the differences between the spectra produced by these two techniques. A data sample procured with the Gill anemometer recorded at one-second time intervals reflect agreement with the turbulence hypothesis. The FFT has the advantage that turbulence data can be readily exressed as a Fourier series. The amplitude relationship is expressed by equations while the phase angles are randomly distributed. Although a set of phase angles can be constructed from random generators in electronic data processing, a simple technique would be a substitution from a set of empirical turbulence data. The author has been an example of an analytically produced nonstationary set of data which could be superimposed on the stationary wind profile. These inferred data sets can be established where special tower measurement are not available such as for altitudes beyond tower measurements and/or for geographic locations without lower measurements. These composed sets of wind data are better suited than present techniques for the assessment of the turbulence impact upon effectiveness, instrumental or missile sensitivity, and field use of systems such as DAFFR, Assault Breaker, CSWS, etc. by combining the stationary and non-stationary effect into one data set.

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Document Details

Document Type
Technical Report
Publication Date
Jun 18, 1982
Accession Number
ADA117157

Entities

People

  • Oskar M. Essenwanger

Organizations

  • United States Army Aviation and Missile Command

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Amplitude
  • Anemometers
  • Autocorrelation
  • Data Processing
  • Data Sets
  • Fast Fourier Transforms
  • Fourier Series
  • Measurement
  • Power Spectra
  • Spectra
  • Test And Evaluation
  • Test Facilities
  • Test Methods
  • Time Intervals
  • Turbulence
  • White Noise
  • Wind

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Computational Modeling and Simulation
  • Fluid Dynamics.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Microelectronics