A Self-Affine Multi-Fractal Wave/Turbulence Discrimination Method Using Data from Single Point Fast Response Sensors in a Nocturnal Atmospheric Boundary Layer

Abstract

We present D sub A, a self-affine, multi-fractal which may become the first routine wave/turbulence discriminant for time series data. Using nocturnal atmospheric data, we show the advantages of D sub A over self-similar fractals and standard turbulence measures such as FFTs, Richardson number, Brunt Vaisala frequency, buoyancy length scale, variances, turbulent kinetic energy, and phase averaging. D sub A also shows promise in resolving wave-break events. Since it uses local basis functions, D sub A may be ideal tool to detect intermittent turbulence, coherent structures, and discrete wave trains in general. D sub A may also be a measure of chaos in general.

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Document Details

Document Type
Technical Report
Publication Date
Apr 10, 1992
Accession Number
ADA250419

Entities

People

  • A. J. Decaria
  • R. F. Kamada

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Boundary Layer
  • Buoyancy
  • Computer Science
  • Differential Equations
  • Energy
  • Energy Transfer
  • Equations
  • Flow
  • Geometry
  • Kinetic Energy
  • Meteorology
  • Observatories
  • Richardson Number
  • Turbulence
  • Wind

Fields of Study

  • Physics

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Computer Vision.