Transmission Coefficient Measurement and Improved Sublayer Material Property Determination for Thick Underwater Acoustic Panels: A Generalization and Improvement of the ONION Method

Abstract

Modifications of the ONION panel-measurement method that allow for simultaneous analysis for transmitted- and reflected-wave data are described. The revised algorithm determines more reliable values for the sound speed and loss of the material of each panel sublayer than does the algorithm that is based exclusively upon analysis of the reflected wave. Included in the revised method is a Taylor series expansion of the sound-speed function of each layer about the steady-state driving angular frequency. This Taylor series is similar to that used for the loss function in the original ONION method, and is introduced here to more accurately accommodate the frequency variation of the phase speed than does the frequency-independent model used previously. Descriptions of successful applications of the revised ONION method to experimental data are provided. The version of the ONION method described in this report has recently been adopted as the standard panel measurement method at the Underwater Sound Reference Detachment of the Naval Research Laboratory (NRL-USRD) in Orlando, FL for tests conducted in the 1- to 20-kHz frequency interval. Panel measurements, Materials measurements methods, Reflection and scattering.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1992
Accession Number
ADA255475

Entities

People

  • Jean C. Piquette

Organizations

  • United States Naval Research Laboratory

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Availability
  • Classification
  • Curve Fitting
  • Experimental Data
  • Frequency
  • Intervals
  • Measurement
  • Military Research
  • Monitoring
  • Security
  • Statistical Analysis
  • Steady State
  • Underwater Sound
  • Waveforms
  • Waves

Readers

  • Computational Modeling and Simulation
  • Computer Networking
  • Electromagnetic Wave Scattering and Antenna Radiation Engineering

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference