•3-d propagation effects •effects of tropical storm...
TRANSCRIPT
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SW06 Data Analysis – URI Efforts
•3-D Propagation Effects
•Effects of Tropical Storm Ernesto
•Geoacoustic Inversion
James H. Miller and Gopu R. Potty
University of Rhode Island
Narragansett, RI 02879
SW06 Workshop, Ft. Lauderdale, 12-14 February, 2008
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URI Participation in SW06James Miller and Gopu Potty
Gregor Langer (MS (2007)- currently employed in Germany)
Kristy Moore (MS 2007) – Just started at NUWC
Georges Dossot (MS 2007, Ph.D-ongoing)
Steve Crocker (Ph.D-ongoing) - NUWC
CollaboratorsCollaborators
James Lynch
Arthur Newhall
Preston Wilson
Scott Glenn
Glen Gawarkiewicz
Kyle Becker
Mohsen Badiey
et al.
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3-D propagation effects due to Frontal Reflection
• The critical grazing angle is
about 10 degrees.
• Above 10 degrees most of
the energy penetrates the
front and is lost.
• Below the critical angle,
direct and reflected modal direct and reflected modal
rays add with appreciable
amplitude.
• Up until ~11km the reflected rays are above the critical grazing angle
• At 11km the oscillations in the field start
• This pattern yields up to a 6 dB increase in field strength
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R/V Knorr track60 Km long
Experiment Description
IW
Track of R/V Knorr start(39 8.2632, 72 47.9730)
WHOI Shark Array(39 01.2516,73 02.9833)
Appox. Location of shelf break front~110 m water depth
J-15 Source (ARL- UT, David Knobles) tow parallel to Shelf Break front
From R/V Knorr with J-15 at 50 m depth, Freq- 93 Hz, SL – 165 -168 dBSep 05, 2006 from R/V Knorr
ReceiverSource
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Knorr
Endeavor
Shelf Break Front during the Experiment
J-15 Source at 50m depth
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Frequency – 93 HzSource depth ~ 50 mSource Level – 165 – 168 dBCollaborators: Lynch, Newhall
Experiment Results
R/V Endeavor turned stern
towards Shark
Endeavor
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Propagating Modes w/ New Jersey Bathymetry
Shelfbreak
front
Internal
wave packet
Modeling Results
28.2 km
30.2 km
34.7 km
3-D Kraken (Porter)
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~ 6 dB
Transmission Loss w/ New Jersey Bathymetry
Modeling Results
TL Fluctuation of
the order of 6 dB
TL fluctuations
due to multipath
~ 5.6 dB (Dyer, ~ 5.6 dB (Dyer,
1970)
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A
B
CA. Acoustic Signal in dB. 93 Hz transmission
starts just before 0.5 hrs. From 2.25 hrs
onwards the signal is lost in Endeavor noise.
B. Spatial Fourier Transform by a sliding window
of length 0.68 hrs. Y-axis shows the location
(UTC time) where the window is located.
C. Three slices at UTC times (0.8, 1.6 and 2 hrs)
shown in figure B by white lines.
B
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Future Work
• More refined wave number estimation (Auto-regressive technique)
• Use accurate ship position to grid complex envelope instead of the approximate envelope instead of the approximate estimate (based on speed)
• Detailed 3-D modeling with ship position
• Mode filter to resolve modes
• Search for 3-D effects such as mode splitting
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Observation of travel time variations of normal acoustic modes during the
Tropical Storm ErnestoTropical Storm Ernesto
Gregor Langer, James H. Miller, Gopu R. Potty (URI),James F. Lynch (WHOI)
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Acoustic Normal Modes Under a Rough Sea Surface
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J. H. Miller, J. F. Lynch, and C.-S. Chiu, "Estimation of sea surface spectra using acoustic tomography," J. Acoust. Soc. Am., 86(1), 326-345, (1989).
SourceReceivearray
Mode propagation direction
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Meteorological data of Ernesto
Windspeed Waveheight
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Travel-time Spectra
• WHOI 224 Hz tomography source
• WHOI VLA/HLA – single hydrophone at mid-water depth
• WHOI VLA/HLA – single hydrophone at mid-water depth
• Arrival dominated by mode 1 but possible interference from mode 2
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Pulse compressed acoustic signal and spectra of travel time fluctuations on September 3
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Summary and Future work
• The surface wave fluctuations due to Ernesto produces observable fluctuations in the acoustic modal travel times.
• The travel time spectra and has peak at a frequency equal to surface wave frequencyfrequency equal to surface wave frequency
• We plan to quantify the rms travel time fluctuations and relate that to surface wave heights.
• We will resolve the modes using the vertical array for possible inversions.
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Geoacoustic inversion using
combustive sound source
signals
Gopu Potty, James H. Miller University of Rhode Island, Narragansett, RI
Preston S. WilsonUniversity of Texas, Austin, TX
James F. Lynch & Arthur NewhallWoods Hole Oceanographic Institution, Woods Hole, MA
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Combustive Sound Source (CSS)
From: Wilson, P. S, Ellzey, J. L., and Muir, T. G., “Experimental Investigation of the Combustive Sound Source,” IEEE J. Oceanic. Eng., 20(4), 1995.
a.
b.
The chamber we used in SW06 was a cylinder with a hemispherical cap. The bubble motion is not the same for the cylinder and the cone, although the radiated acoustic pulse is similar.
Cross section of CSS combustion Chambera. Unburnt gaseous fuel/oxygen mixtureb. Gases expand during combustionc. Bubble assumes a toroidal shape upon
full expansion
A typical CSS pressure signature (produced by the combusion of 5.0 l stoichiometric hydrogen and oxygen and the power spectrum
b.
c.
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• ARL group (Preston Wilson and David Knobles) deployed 31 CSS shots from R/V Knorr
• Depth of CSS ~26 m
Combustive Sound Source (CSS) during SW-06
• Depth of CSS ~26 m
• There was a monitoring hydrophone
• Difficult to deploy especially in rough seas
CSS was used as a boot-strap measure to field an impulsive sound source during SW-06. At the time, CSS had been inactive for a decade, and had never been developed beyond the proof-of-concept stage. The device deployed during SW06 was designed for a laboratory engineering study and was not designed to be used at sea. ARL will be working on a more field-able version of CSS.
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SHRU-1 (Single Hydrophone Receive Unit) – deployed at 85 m; sampled @ 9765 Hz
CSS –Event 2 at Range - 15.2747 km
First two modes strong; higher modes comparatively weak
CSS Signal Received on a WHOI SHRU
SHRU 1; Rec # 28
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obtained by rotating or shearing the time
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the parameter d (u, ξ)
If d (u, ξ) is chosen based on the local
wave dispersion, then the resulting time-
frequency tiling will correspond to the
entire wave dispersion behavior.
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Time – Frequency Diagrams
Modes 1, 2 and 3 are strong in the CSS signal
Modes 4, 5 and 6 partially present
Wavelet scalogram – poor time Wavelet scalogram – poor time resolution at low frequencies
DSTFT performs well at the upper frequency band (compares well with wavelets)
At low frequencies DSTFT produces better time resolution.
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Iterative Scheme for estimating modal group speeds
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CSS # 20390 5.5174’-730 5.5816
SHRU # 2380 57.6715’-720 54.8139’
Deployed at
Bathymetry, Source and Receiver locations
Deployed at107 m
Bathymetry fromJohn Goff
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6
5
Range Depth Lengthsection (m) (km)
1 100-95 1.442 95-90 1.043 90-85 3.684 85-80 11.275 80-75 1.18
Geo-acoustic data
12
3
4
5 80-75 1.186 75-70 2.63
In situ probes
Short core- station 77
AHC – 800 Core
Grab samples
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Inversion Results
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Future Work
• Inverting for attenuation
• Looking at the spatial variation using • Looking at the spatial variation using multiple sources and receivers
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QuestionsQuestions