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Advanced Acoustical Modeling Tools for ESME. Martin Siderius and Michael Porter Science Applications Int. Corp. 10260 Campus Point Dr., San Diego, CA sideriust@saic.com michael.b.porter@saic.com. Acoustic Modeling Goals.

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advanced acoustical modeling tools for esme

Advanced Acoustical Modeling Tools for ESME

Martin Siderius and Michael Porter

Science Applications Int. Corp.

10260 Campus Point Dr., San Diego, CA

sideriust@saic.com

michael.b.porter@saic.com

acoustic modeling goals
Acoustic Modeling Goals
  • Through modeling, try to duplicate sounds heard by marine mammals (e.g. SONAR, shipping)
  • Develop both high fidelity and very efficient simulation tools
acoustic modeling goals1

Difficult task for any single propagation code

Approach is to use PE, Rays and Normal Modes

Acoustic Modeling Goals
  • Accurate field predictions in 3 dimensions
  • Computational efficiency (i.e. fast run times)
  • Propagation ranges up to 200 km
  • R-D bathymetry/SSP/seabed with depths 0-5000 m
  • Frequency band 0-10 kHz (or higher)
  • Moving receiver platform
  • Arbitrary waveforms (broadband time-series)
  • Directional sources
model comparisons
Model Comparisons

Accuracy

Rays

NM and PE

Computation Time

Rays

NM and PE

Frequency

Frequency

fast coupled nm method
Fast Coupled NM Method
  • Range dependent environment is treated as series of range independent sectors
  • Each sector has a set of normal modes
  • Modes are projected between sectors allowing for transfer of energy between modes (matrix multiply)
  • Algorithm marches through sectors
  • Speeds up in flat bathymetry areas
  • Pre-calculation of modes allows for gains in run-time (important for 3D calculation)
  • Very fast at lower frequencies and shallow water
mammal risk mitigation map

5 dB more loss

5 dB less loss

Mammal Risk Mitigation Map

SD = 50 m

SL = 230 dB

Freq = 400 Hz

Lat = 49.0oN

Long = 61.0oW

shipping simulator
Shipping Simulator
  • Using the fast coupled normal-mode routine shipping noise can be simulated
  • This approach can rapidly produce snapshots of acoustic data (quasi-static approximation)
  • Self noise can also be simulated (i.e. on a towed array)
  • Together with a wind noise model this can predict the background ambient noise level
example simulated btr
Example: Simulated BTR
  • Input environment, array geometry (e.g. towed array hydrophone positions) and specify ship tracks (SL, ranges, bearings, time)
computing time series data for moving receiver
Computing Time-Series Data for Moving Receiver
  • How is the impulse response interpolated between grid points?
  • How are these responses “stitched” together?
1 interpolating the impulse response
1. Interpolating the Impulse Response
  • In most cases the broad band impulse response cannot be simply interpolated
  • For example, take responses from 2 points at slightly different ranges:
2 stitching the responses together
2. “Stitching” the Responses Together
  • Even if the impulse response is calculated on a fine grid, there can be glitches in the time-series data (due to discrete grid points)
  • For example, take the received time-series data at points 1 m apart:
solution interpolate in arrival space
Solution: Interpolate in Arrival Space
  • The arrival amplitudes and delays can be computed on a very course grid and since these are well behaved, they can be interpolated for positions in between.
  • Using the “exact” arrival amplitudes and delays at each point, the convolution with the source function is always smooth.
ray beam arrival interpolation

Endpoint #2

Interpolated

Endpoint #1

Advantage: very fast and broadband

Ray/Beam Arrival Interpolation
test case determine long time series over rd track
Test Case: Determine Long Time Series Over RD Track
  • Source frequency is 3500 Hz
  • Source depth is 7 m
  • Environment taken from ESME test case
  • Receiver depth is 7-100 m
  • Receiver is moving at 5 knots
computing tl variance
Computing TL Variance
  • Fast Coupled Mode approach allows for:
    • TL computations in 3D (rapid enough to compute for several environments)
    • Changing source/receiver geometry
  • Ray arrivals interpolation allows for Monte-Carlo simulations of TL over thousands of bottom types to arrive at TL variance
ray beam arrival interpolation1

Endpoint #2

Interpolated

Endpoint #1

Advantage: very fast and broadband

Ray/Beam Arrival Interpolation
does it work tl example
Does it work? TL example
  • 100-m shallow water test case:
    • Source depth 40-m
    • Receiver depth 40-m
    • Downward refracting sound speed profile
    • 350 Hz
  • 3 parameters with uncertainty:
    • Sediment sound speed 1525-1625 m/s
    • Sediment attenuation 0.2-0.7 dB/l
    • Water depth 99-101 m
does it work tl example1
Does it work? TL example
  • Interpolated (red) is about 100X faster than calculated (black)