Fast and Accurate Acoustic Transmission Loss (TL)

164 Pages·2016·4.04 MB·English

by  Sean M. Reilly

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Sean M. Reilly
University of Rhode Island, [email protected]
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Reilly, Sean M., "WaveQ3D: Fast and Accurate Acoustic Transmission Loss (TL) Eigenrays, in Littoral
Environments" (2016). Open Access Dissertations. Paper 441.
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WAVEQ3D: FAST AND ACCURATE ACOUSTIC TRANSMISSION LOSS (TL)
EIGENRAYS, IN LITTORAL ENVIRONMENTS
BY
SEAN M. REILLY
A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE
REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
IN OCEAN ENGINEERING
UNIVERSITY OF RHODE ISLAND
2016
DOCTOR OF PHILOSOPHY DISSERTATION
OF
SEAN M. REILLY
APPROVED:
Dissertation Committee
Major Professor Gopu R. Potty
James H. Miller
Isaac Ginis
Nasser H. Zawia
DEAN OF THE GRADUATE SCHOOL
UNIVERSITY OF RHODE ISLAND
2016
Abstract
This study defines a new 3D Gaussian ray bundling acoustic transmission loss
model in geodetic coordinates: latitude, longitude, and altitude. This approach is de-
signed to lower the computation burden of computing accurate environmental effects
in sonar training application by eliminating the need to transform the ocean environ-
ment into a collection of Nx2D Cartesian radials. This approach also improves model
accuracy by incorporating real world 3D effects, like horizontal refraction, into the
model. This study starts with derivations for a 3D variant of Gaussian ray bundles
in this coordinate system. To verify the accuracy of this approach, acoustic prop-
agation predictions of transmission loss, time of arrival, and propagation direction
are compared to analytic solutions and other models. To validate the model’s ability
to predict real world phenomena, predictions of transmission loss and propagation
direction are compared to at-sea measurements, in an environment where strong hor-
izontal refraction effect have been observed. This model has been integrated into U.S.
Navy active sonar training system applications, where testing has demonstrated its
ability to improve transmission loss calculation speed without sacrificing accuracy.
Acknowledgments
The author would like to acknowledge all of the collaborators who have assisted in
this research over the years. In 1994, Dr. Roy Deavenport (Naval Undersea Warfare
Center Division Newport) first encouraged me to explore the development of a 3D
Gaussianbeamtheorytosupportthemodelingoftheenvironmentalimpulseresponse
foractivesonarapplications. Thetheoryforreflectionfroma3-Dslopewasdeveloped
by Dr. Michael Goodrich (Alion Science and Technology), who also made significant
contributions to the development of test cases as part of an internal research and
development effort funded by Alion Science and Technology in 2009. Efforts to test
and productize this model where funded from 2011-2015 by the High Frequency Ac-
tive Sonar Training (HiFAST) project at the U.S. Office of Naval Research (ONR),
where Mr. Michael Vaccaro led the charge to evolve this unproven concept into a
Navy training capability. Mr. David Thibaudeau provided testing support and Mr.
Ted Burns acted as our the lead system integrator during the HiFAST effort at Aegis
Technology Group. Thanks to Dr. Thomas Yudichak (Applied Research Laboratory
at the University of Texas in Austin), who provided years of Navy certification expe-
rience and keen insights during the his independent verification and validation effort.
Special thanks are due to Jonathan Glass, and his team at Naval Air Warfare Center
Training System Division, who suffered through the first integration of the this model
into a real Navy training system. Finally, the author would like to thank Dr. Gopu
iii
Potty and Dr. James Miller who brought their academic rigor and perspective to this
effort.
iv
Dedication
To my wife, Joan, my inspiration in all things.
v
Preface
Many underwater acoustic propagation models transform the three dimensional (3D)
environment into a collection of two dimensional (2D) radials, and then compute
transmission loss as a function of range and depth along each of those radials. This
approach, often called Nx2D, is used in tactical decision aids to compute millions of
range, depth, and bearing combinations in just a few minutes. Sonar training ap-
plications have an additional requirement that the results must be computed in real
time for presentation to the trainees. In littoral environments, the number of acoustic
contacts can be in the hundreds, and the Nx2D approach places a large computation
burden on the training system. The primary goal of this research is to develop a
transmission loss model that reduces the computational burden on training systems
without sacrificing accuracy. Improving the speed of this computation reduce acqui-
sition costs by reducing reliance on massively parallel computing systems. This study
alsoseekstoprovidetheacousticsresearchcommunitywithatoolthatcanpredict3D
effects in applications, like geophysical parameter inversion, where execution speed is
important.
This dissertation follows the University of Rhode Island Graduate School guide-
lines for the preparation of a dissertation in manuscript format. There are three
chapters that represent formally published papers:
• Manuscript 1 derives the theory behind the model, and provides key test results
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including: ray path refraction accuracy using a Munk profile, Gaussian beam
projectionintotheshadowzoneforann2 linearprofile, andhorizontalrefraction
from a 3D analytic wedge.
• Manuscript 2 compares model predictions to at-sea measurements of horizontal
refraction in a sloped environment.
• Manuscript3discussestheapplicationofthismodelindeployablesonartraining
systems.
• Manuscript 4 discusses the accuracy of this model in the deep sound channel.
Appendix A is an unpublished model accuracy test report, delivered to the High Fre-
quency Active Sonar Training (HiFAST) project at the U.S. Office of Naval Research
(ONR), in 2012.
vii
Table of Contents
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi
Table of Cotents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii
1 Computing Acoustic Transmission Loss Using 3D Gaussian Ray
Bundles in Geodetic Coordinates . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Derivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3.1 3-D ray propagation in spherical coordinates . . . . . . . . . . 5
1.3.2 3-D interface reflections . . . . . . . . . . . . . . . . . . . . . . 11
1.3.3 3-D eigenray path detection . . . . . . . . . . . . . . . . . . . . 15
1.3.4 3-D Gaussian ray bundles . . . . . . . . . . . . . . . . . . . . . 19
viii