Causality Bubbles to the Surface: Investigating Acoustic Causality in Highly Dispersive Bubbly Liquids

Abstract

Causality in nearly all physical systems has been a recurrent subject, often causing apparent paradoxes since before the 20th century. Linear acoustic propagation through subsurface bubble clouds in the ocean offers an especially challenging physical system within which to investigate issues of causality, and in the past has had several competing fundamental theories. Signal travel times and absorption in such a system exhibit enormous variations depending on the acoustic signal frequency, bubble size distribution, void fraction, and other ambient physical parameters. We have found a correction to some contemporary theories of acoustic propagation in bubbly media that has brought these theories into compliance with the physical law of causality. In doing so we have created a self-consistent theory that also matches higher-frequency data taken in the NRL Salt Water Tank Facility, as well as historical data. We have experimentally investigated this new theory and have observed some additional features that have significant implications upon acoustic signal propagation and suggest that we have only begun to scratch the surface of providing a comprehensive description of the physical phenomena surrounding acoustic propagation in the highly dispersive environment of bubbly media.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2009
Accession Number
ADA525293

Entities

People

  • D. K. Dacol
  • G. J. Orris
  • M. Nicholas

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acoustic Propagation
  • Acoustic Signals
  • Acoustic Waves
  • Acoustics
  • Dispersions
  • Equations
  • Frequency
  • Group Velocity
  • Liquids
  • Phase Velocity
  • Resonance
  • Resonant Frequency
  • Salt Water
  • Surface Tension
  • Transducers
  • Water Tanks
  • Wave Propagation

Fields of Study

  • Physics

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Neural Network Machine Learning.
  • Theoretical Analysis.