Understanding Nonlinear Coherent Structure Interactions in Boundary-Layer Transition using Adaptive Signal Analysis

Abstract

In an effort to understand the fundamental source and sustainment mechanisms of a turbulent boundary layer, the evolution of energy spectra within a transitional boundary layer are studied. To conduct this program, an adaptive modal decomposition technique, the multi-variate, multidimensional empirical mode decomposition, was developed. This approach permitted velocity fields of interest to be separated into modal components as defined by an adaptive, empirical basis. In addition to this method, a Riesz transform and log-Gabor filter method were introduced to isolate key flow scales of interest and characterize wavenumber component projections of multi-dimensional velocity fields. Experimental data of controlled H-type transition were acquired in a refractive index matched flume, and a POD analysis was conducted to obtain an initial understanding of the energetic flow structures associated with the transition process.

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Document Details

Document Type
Technical Report
Publication Date
Oct 19, 2021
Accession Number
AD1202747

Entities

People

  • Phillip J. Ansell

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Boundary Layer
  • Boundary Layer Flow
  • Boundary Layer Transition
  • Channel Flow
  • Coefficients
  • Computational Fluid Dynamics
  • Energy
  • Engineering
  • Flow Fields
  • Fluid Dynamics
  • Fluid Flow
  • Fluid Mechanics
  • Mechanics
  • Modal Analysis
  • Order Statistics
  • Reynolds Number
  • Signal Processing
  • Skin Friction
  • Stratified Fluids
  • Three Dimensional
  • Turbulence
  • Turbulent Flow
  • Two Dimensional

Fields of Study

  • Physics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Fluid Dynamics.