A Physical Sediment Model for the Prediction of Seafloor Geoacoustic Properties

Abstract

A study was performed to adapt, implement, and test a version of the Biot/Stoll physical sediment model in a form which allows the prediction of those geoacoustic properties needed by current Navy acoustic or bottom loss calculation models. Particular attention was paid to the depth and frequency dependence of compressional wave speed and attentuation; two properties considered to be most important to acoustic modeling. Additionally, input sensitivity studies yielded insight into certain 'critical factors' important to accurate geoacoustic property predictions. Model predictions of seafloor geoacoustic properties were compared with speed and attenuation values measured directly or inferred from acoustic measurements for a deep water site near DSDP site 135, and a shallow water site near Panama City, Florida. The acoustic significance of observed differences in geoacoustic properties was assessed by comparing the outputs of a complex reflection coefficient model using inputs derived from physical sediment properties using the Biot/Stoll approach and inputs derived from acoustical measurements using the inversion technique developed for the Bottom Loss Upgrade (BLUG). The study yield positive evidence that the physical seidment approach is useful. The Biot/Stoll model is a potentially powerful tool for estimating or extrapolating geoacoustic parameters, particularly when a priori estimates are needed in geogrpahic areas or frequency regimes which have not been acoustically surveyed.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1982
Accession Number
ADA119445

Entities

People

  • Burlie A. Brunson
  • Eugene J. Molinelli

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Weapons Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Acoustic Measurement
  • Acoustic Propagation
  • Acoustic Properties
  • Acoustic Waves
  • Acoustics
  • Bulk Modulus
  • Elastic Properties
  • Fluid Flow
  • Geographic Regions
  • Geometry
  • Grain Size
  • Mechanical Properties
  • Modulus Of Elasticity
  • Physical Properties
  • Seabed
  • Shear Modulus

Readers

  • Acoustical Oceanography.
  • Computational Modeling and Simulation

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks