Applications of Frequency and Wavenumber Nonlinear Digital Signal Processing to Nonlinear Hydrodynamics Research

Abstract

This report summarizes recent progress in applying higher-order statistical techniques (such as higher-order spectra) and associated nonlinear system identification techniques to nonlinear hydrodynamic phenomena. In particular, we estimate, given, model-test data of wave excitation and vessel/ structure response, either frequency-domain or time-domain Volterra kernels. Knowledge of the Volterra Kernels is important because the nonlinear physics is imbedded in them. Also such experimental knowledge is necessary to compare with theory, and to quantify the nonlinear mechanisms whereby energy is extracted from the wave excitation and downconverted or up-converted in the response frequency spectrum. Of fundamental practical importance is the fact that the approach is valid for Gaussian as well as nonGaussian excitation. (JHD)

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Document Details

Document Type
Technical Report
Publication Date
Dec 18, 1989
Accession Number
ADA216259

Entities

People

  • Edward Powers
  • Richard W. Miksad

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Data Sets
  • Digital Signal Processing
  • Energy Transfer
  • Engineering
  • Filters
  • Frequency
  • Frequency Bands
  • Frequency Domain
  • Identification
  • Model Tests
  • Models
  • Nonlinear Systems
  • Physics
  • Ship Motion
  • Signal Processing
  • Time Domain
  • Waves

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Radio communications and signal processing.