Modeling the Effects of Transbasin Nonlinear Internal Waves Through the South China Sea Basin

Abstract

The objective of this research is to model and study the effects of transbasin internal waves on lowfrequency signal transmission through the South China Sea (SCS) basin. Specifically, the fluctuations in the multipath arrival structure of a 400-Hz acoustic pulse transmitted through a distance of 167-km in the SCS basin in the presence of an internal ocean soliton was modeled and examined. The modeling entailed the integration of a raytracing program with an eigenray search and arrival-structure calculation program, and the use of measured bathymetry and inferred bottom-loss characteristics from previous research. A range-dependent perturbation was added to a range-independent background sound-speed profile to model the varying sound-speed field as the nonlinear ocean internal soliton propagates along the transmission path. All cases studied, each simulating a soliton at a different location, had six distinct acoustic arrivals that suffered from large-amplitude fluctuations (~ 10 dB). The factors that affect the amplitude of the arrivals are changes: in the number of bottom interaction, in ray tube spreading, phase interference and in the number of eigenrays making up an arrival. The results also show that the closer the soliton to the receiver, the less impact the soliton has on the arrival structure.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2013
Accession Number
ADA583538

Entities

People

  • Joseph J. Ceschini

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acoustics
  • Amplitude
  • Bathymetry
  • Boltzmann Equation
  • Bottom Bounce
  • Bottom Loss
  • Internal Waves
  • Losses
  • Oceans
  • Pacific Ocean
  • Perturbations
  • Physics
  • Simulations
  • Sound Pressure
  • South China Sea
  • Travel Time
  • Waves

Readers

  • Acoustical Oceanography.
  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference