01NUWCGRA0080U.M1

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Naval Undersea Warfare Center In-House Basic and
Applied Research Presented by Dick
Philips Research Manager Naval Undersea Warfare
Center Division Newport Building 990/5 (401)
832-2791 PhilipsRB_at_NPT.NUWC.NAVY.MIL
01-NUWC-GRA/0080U.M1
0321-TLW
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Outline

• A little about NUWC
• Who we are
• What we do
• Opportunities to work with us
• NUWC Basic and Applied Research

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President Secretary of Defense Secretary of the
Navy
Simplified Navy Organization Shore Side Operations
CNO Chief of Naval Operations
Admiral Landay Chief of Naval Research CNR
NAVAIR
NAVSEA
SPAWAR Space Naval Warfare
ONR Office of Naval Research
Surface Warfare
Undersea Warfare
Naval Research Lab
Division Newport
Division Keyport
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NUWC Division, Newport (abbreviated)
COMMANDER 00 CAPT Mike
Byman __________________________________
TECHNICAL DIRECTOR 01 Dr. Paul
Lefebvre
DEPUTY, TECHNICAL DIRECTOR Donald Aker
01A

• Business Codes
• Financial
• Safety
• Council
• Operations
• Etc.

DEPUTY, WARFARE CENTER TEST AND EVAL Robert
Connerney
01T
SPECIAL PROJECTS OFFICE Michael Maguire
01Y
CHIEF TOGY OFFICER Dr. Pierre Corriveau
01CTO
UNDERSEA WARFARE ANALYSIS DEPARTMENT Dave
Medeiros 60
TORPEDO SYSTEMS DEPARTMENT Phil Tabor
81 (Acting)
COMMUNICATION IMAGING SENSORS DEPT Gerry Exley
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SENSORS AND SONAR SYSTEM DEPARTMENT Joe Monti
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RANGES, ENGINEERING, AND ANALYSIS
DEPARTMENT Harriet Coleman70

AUTONOMOUS SYSTEMS AND TECHNOLOGY DEPARTMENT James
Griffin 82
COMBAT SYSTEMS DEPARTMENT
Ernie Correia 25
PLATFORM AND PAYLOAD INTEGRATION DEPT
John Conti 40

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NUWC Mission Statement
To operate the Navys full-spectrum research,
development, test and evaluation, engineering and
fleet support Center for submarines, autonomous
underwater systems, and offensive and defensive
weapon systems associated with undersea warfare.
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Submarine Contributions
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Surface Combatant Contributions
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Highly Skilled Technical Workforce (FY07)
Unique Capabilities
Technicians 624
Craftsman 141

• Acoustic Sensors, Transducers and Arrays
• Signal Processing
• Structural Acoustics
• Information Processing
• Weapon Systems Targeting and Control
• Torpedo UUV Propulsion and Signature Control
• Submarine Electromagnetics, Antennas,
  Electro-Optics and Communications
• Undersea Vehicle Guidance and Control
• Hydrodynamics
• Ocean Physics
• Undersea Range Technology
• Warfare Modeling, Simulation and Analysis
• Large Scale Numerical Modeling and Analysis
• System Engineering/Analysis of Assessment
• Undersea Materials Technology

Engineers/Scientists 2374
Admin Professional 700
Admin Support 51
Clerical 55

• 3945 Civilian Employees
• Over 957 Advanced Degrees
• 154 PhDs

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DIVNPT Science and Technology Profile FY07
Encumbered
Total FY07 Funding 932.4M
Science Technology Slice 57.8 M (6.2 of NUWC
Total ) 6.1 5.140M ( 9) 6.2
22.362M (39) 6.3 30.293M
(52)
Non ST 874.7M (93.8)
Science Technology funding by Sponsor FY07
Encumbered
Science Technology Funding by Sponsor FY07
Encumbered
57.8M
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We Operate as a Business (nonprofit)
Requirements

• We are not institutionally funded
• We need to attract program sponsors (customers)
• Quality
• Reasonable price
• Our viability depends on our budget provided by
  customers
• We sign a contract responsible / accountable to
  our customers for quality / timeliness of product
  / services

APPROPRIATED FUNDS

RESOURCESPONSORS
Headquarters, PEO Program Manager
PMDECISIONS
TASKING ELEMENT





Systems, Products, and Services
DoD
Other Federal Agencies
WARFARE CENTERS
We run an efficient, cost effectivebusiness
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Newport USW Technical Facilities
Propulsion Test Facility
Anechoic Chamber
Wind Tunnel
Periscope Test Facility
Submarine Combat Control System
Towed Array Complex
Advanced Launcher Test Facility
Submarine Radio Room
AUTEC
Our Facilities

• Stewarding National capabilities not commercially
  feasible
• Reduce cost, risk, and development time for USW
  system development
• Provide the ability to resolve Fleet issues while
  deployed
• Are available for industry and academia use to
  reduce Navy development cost

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Center of Excellence on Undersea Technology An
alliance between NUWCDIVNPT and The University of
Rhode Island

• Vision
• Preeminent national center focused on the
  education and training of the next generation of
  Navy technologists and on the research,
  development, test and evaluation of undersea
  technologies and associated products for national
  defense and security
• Mission
• Serve as a cooperative research, product
  development, technology transfer, and science and
  technology training and educational alliance
  between NUWC and the other center partners.
• Objectives
• To perform basic and applied research focused on
  the design, development, testing, and
  implementation of a wide variety of undersea
  technologies that support both military and
  civilian applications
• To provide research opportunities and training in
  support of graduate and undergraduate education
  for the next generation of ocean technologists.

Center Director Malcolm L. Spaulding Ocean
Engineering University of Rhode
Islandhttp//www.coeut.org/ Tel
401-874-6666E-mail Spaulding_at_oce.uri.edu
NUWC POC George McNamaraChief Development
OfficerPhone  [phone]e-mail
mcnamaragc_at_npt.nuwc.navy.mil
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Center of Excellence on Undersea Technology
Partners (Partial listing)

• Academia
• UMASS Dartmouth
• UMASS Boston
• Providence College
• Brown
• WHOI
• URI
• Ocean Engineering
• GSO
• Engineering
• Computer Science
• Chemistry
• USC, Information Sciences Institute
• North Carolina A T
• Naval Post Graduate School
• MIT
• Industry
• EB

• Industry (continued)
• ASA
• SAIC
• Wetlands
• Farsounder
• Eminent
• Mikel
• Exploration Technologies
• Ocean Server
• OSTC
• ARA
• ASC
• Alion
• Rite Solutions
• Subchem
• UTC
• BTech

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Autonomous Smart Sensor Design for Distributed
Networked Sensing Dr. John Blottman -- Sensors
Sonar Systems Department
Objective Create a revolutionary distributed
sensing node composed of Electro-active polymer
material, with extremely low energy consumption/
energy scavenging for long life deployable from
UUVs, Swimmer Delivery or submarines exhibiting
beamforming to extend range and bearing for
autonomous operation

• Deliverables
• 1 paper 1 presentation (FY06)

• Milestones
• Feasibility study

• Accomplishments to Date
• Build team of essential expertise (PSU, URI,
  DRDC,NUWC,OSU)
• Invention Disclosure, Navy Case 96973, Nov. 2004

• Payoff to the Navy
• Self-contained deployable node for covert
  persistent distributed surveillance systems
• Operational life several orders of magnitude
  beyond a traditional Sonobuoy
• Covert detection using electroluminescence for
  optical communications
• Energy harvesting systems based on
  piezoelectrics and ocean currents

Co-sponsored by ONR 321MS (Program Officer J.F.
Lindberg)
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NUWC Student and Faculty Programs
Undergraduate and Graduate Programs
Graduate and Faculty Programs

• National Science Foundation (NNCS) partnership
• Student commits to working at NUWC upon
  completion of degree - Application deadline-
  early June
• http//www.nsf.gov/pubs/2005/nsf05582/nsf05582.jsp
  
• National Defense Science and Engineering Graduate
  (NDSEG) Fellowship
• Summer work at a DoD Lab - Application deadline
  January https//www.asee.org/ndseg/
• ONR University/Laboratory Initiative
• Degree work with National Naval Responsibilities
  http//www.onr.navy.mil/sci_tech/33/333/uli.asp
• Postdoctoral Fellowship Program
• Currently program under construction
• - POC Dick Philips
• ONR Summer Faculty Research Program and
  Sabbatical Leave Program (ASEE)
• Faculty work at NUWC during summer
• Application Deadline - early December
• http//www.asee.org/summer/
• ONR Young Investigator Program (YIP)
• Faculty apply to perform research at NUWC in
  specific areas - Application deadline early
  January
• http//www.onr.navy.mil/02/baa

• Naval Research Enterprise Internship Program
  (NREIP)
• 18-27 students at NUWC for 10 weeks in summer
• Application deadline mid-January
• http//www.asee.org/nreip/details.cfm
• Science, Mathematics and Research for
  Transformation (SMART) Scholarship
• Student commits to working at NUWC upon
  completion of degree receives scholarship from
  DoD
• Application deadline is mid-December
• http//www.asee.org/nreip/details.cfm
• NUWC Student Services Contract
• 10-15 students at NUWC during the year - 20 hours
  per week during academic year-40 hours during
  vacations
• Program is administered by URI, however, student
  from any institution can apply
• POC Linda Josefson [phone]
• http//www.nuwc.navy.mil/npt/

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Basic and Applied Research

• Basic
• In-house Laboratory Independent Research (ILIR)
• 1.5 to 2M/year from ONR
• Discretionary funding to do work the Warfare
  Center believes is important
• Applied
• In-house Applied Research
• 0.5 M/year from ONR
• Discretionary funding to do work the Warfare
  Center believes is important

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Beaked Whale and Other Species Bio-acoustic
Density Estimation and Distribution on Navy
Undersea Ranges PI N. DiMarzio (Code 71) , AI
J. Ward (Code 74)
Objectives

• In FY07 passive acoustic density estimation
  algorithms were
• successfully used to

• Generate a density estimate for beaked whales on
  the AUTEC range using average group size
• Estimate the actual number of beaked whales
  present in a group
• Design algorithms and methodology for passive
  acoustic densityestimation of beaked whales and
  other marine mammal species
• Apply algorithms to the wealth of beaked whale
  data collected at AUTEC and SCORE to obtain the
  most comprehensive baseline assessment of beaked
  whale density, vocalization behavior, and
  distribution available to date

Photo Bahamas Marine Mammal Survey M3R Acoustic
Monitoring Verification Test AUTEC 24-30
September, 2005
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Beaked Whale and Other Species Bio-acoustic
Density Estimation and Distribution on Navy
Undersea Ranges

• Investigators N. DiMarzio, J. Ward
• Proposed Project Length FY07 FY09
• Collaborators L. Thomas I. Boyd, U. of St.
  Andrews P. Tyack M. Johnson, WHOI W. Zimmer,
  NURC D. Claridge, BMMRO J. Calambokidis,
  Cascadia Research J. Hildebrand, Scripps J.
  Barlow, SFSC D. Mellinger, Oregon State U. J.
  Mobley, U. of Hawaii, A. Read, Duke U., D.
  Nowacek, Florida State U., S. Martin, SPAWAR
• Transition Sponsors N45, AUTEC, SCORE, PMRF,
  USWTR
• Related ONR/ST Focus
• Sustain combat readiness by allowing continued
  access to training
• Reduce costs by avoiding time-consuming
  litigation over environmental compliance issues

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What is Density Estimation?
Density estimation is the estimation of the
number of animals per unit area. Density
estimates are used for the study of animal
populations.
And Why is Density Estimation Important?

• NMFS/NOAA requires the Navy to provide marine
  mammal density estimates as part of the
  environmental compliance process.
• Density estimation data are used as input to the
  Navys Protective Measures Assessment Protocol
  (PMAP) tool.
• The estimation of animal density on Navy ranges
  will be used to monitor marine mammal populations
  over time, which is a critical element for
  mitigation.

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Group Localization Technique
Concept
Using click count statistics, estimate the number
of groups on range within a measurement window
derived from the dive cycle and multiply by the
average group size. Determine number of animals
by averaging multiple window results, and
dividing this number by the range area to find
density.
Result
Using the group localization technique on 79.33
hours of data over 6 days from April to May, 2005

Average Beaked Whale Density for AUTEC Range
32.8 Animals/1000 km2
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Click Counting
Concept

• Use DTAG beaked whale vocalization data from
  tagged animal and knowledge of 4 animals in
  tagged animals group to determine average click
  rate for an individual and the average detection
  ratio for a 7-hydrophone array surrounding the
  animal (i.e. clicks detected on the array /
  clicks emitted by the group).
• Verify efficacy of click-counting assumptions
  using visual verification data with known group
  sizes from species verification tests. Determine
  the dive duration and hydrophone array associated
  with a given sighting, apply the click count
  statistics calculated from the DTAG to the total
  number of clicks detected on the array to
  estimate the number of animals present, and
  compare to the known number of animals in the
  group.
• Extend this application to individual dives for
  groups of animals localized over a time window on
  the range to determine a beaked whale density
  estimate for the range.

Projections
Next Step Combine Group Localization with Click
Counting for Best Density Estimate
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3 Year Plan
FY07

• Software Optimization/Data Preparation
• Density Estimation three methods for density
  estimation were developed and applied to beaked
  whales at AUTEC group localization, TDOA
  histograms, and click counting. A density
  estimate was derived for the AUTEC range.

FY08

• FY08 focus will be on beaked whales (Mesoplodon
  densirostris, Ziphius cavirostris, Berardius
  baiirdi), followed by sperm whales.
• Density Estimation algorithms developed in FY07
  will be further enhanced, automated and
  investigated.
• Complications with the SCORE range will be
  addressed, and the algorithms will be modified as
  necessary. Classification will be important.
• The algorithms will be applied to data collected
  at AUTEC SCORE to obtain the most comprehensive
  baseline density estimate available for beaked
  whales.

• Density Estimation methods will be expanded to
  include other odontocetes.
• Data analysis and application to towed arrays
  will be investigated.
• Extend algorithm for remote single sensor and
  sparse arrays

FY09
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Principal Investigator Dr. Kimberly M.
Cipolla, cipollakm_at_npt.nuwc.navy.mil Associate
PI Dr. William L. Keith, keithwl_at_npt.nuwc.navy.mi
lJoint Investigator (NSWC CD) Deborah Furey,
FureyDA_at_nswccd.navy.mil
Investigation of Boundary Layer Development on
Small Diameter Towed Arrays

• Use stereo particle image velocimetry (SPIV) to
  experimentally measure the boundary layer
  development on very small diameter towed arrays
  (d0.89 and 2.5 mm).
• First evaluation of the development of the
  axisymmetric boundary layer as a function of
  axial location along cylinders with large aspect
  ratios and high Reynolds numbers (Req gt 104)
  relevant to Navy applications.
• Provide data necessary for the development of
  affordable, low drag, ultra thin fiber optic
  towed arrays and multiline towed arrays. This
  technology will allow higher gain (longer and/or
  volumetric) arrays to be stored on submarines,
  UUVs and USVs.

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Investigation of Boundary Layer Development on
Small Diameter Towed Arrays

• Full-scale tow tank testing using SPIV to measure
  three-dimensional mean and turbulent velocity
  profiles as a function of axial distance along
  very small diameter cylinders.
• Direct measurement of total mean drag to
  calculate tangential drag coefficients Cd and
  momentum thickness at the end of the lines ?(L)
  through control volume analysis.
• Evaluate details of the turbulent boundary layer
  profiles near the surface of the cylinders.

Tow Strut
Test Cylinder
High Resolution Cameras
Tow Point Fairing
Laser Probe
Seeding Particle Manifolds
Hydraulic Lift

• PAYOFFS
• Improved knowledge base for flow noise and drag
  load predictions.
• Increased sensitivity and gain without increasing
  storage volume.
• Application to Fishline Array, Fiber Optic
  Multiline Towed Array (FOMLTA) and TB-29A
  tracking through turns projects.

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Investigation of Boundary Layer Development on
Small Diameter Towed Arrays

• Experiments have focused on measuring the spatial
  growth of axisymmetric TBLs on long, thin
  cylinders and the relationship between momentum
  thickness q and the boundary layer thickness d
  for axisymmetric TBLs.
• SPIV and drag measurements have revealed a
  periodic relaxation of the boundary layer which
  has never before been experimentally observed.
• Mean and fluctuating velocity profiles have a
  similar form to flat plate TBL profiles.
  However, the boundary layers are very thick
  (d/agt100) and the distribution of turbulence is
  markedly different, which has important
  implications to flow noise.

radial distance (mm)
radial distance (mm)
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Axisymmetric Turbulent Boundary Layer
Measurements on a Full Scale Towed Array Module
Wall Pressure Measurement Results
Figure 2 Nondimensional Wavenumber-Frequency
Spectra Cut at Fixed Frequency wod / Uo 4.0
Figure 1 Dimensional Wall Pressure Autospectra
The wall pressure autospectra are shown in Figure
1, for the steady state and accelerating tows.
At frequencies below approximately 70 Hz, the
levels reflect flow induced vibration of the
array. At higher frequencies, the levels are
dominated by convective energy. The levels for
the accelerating tow have similar features to the
steady state cases, with slightly lower flow
induced energy. The accelerating case is
referenced to a value of Uo 11.4 m/s, and
collapses very well with this scaling. Figure 2
shows the distribution of energy with wavenumber
for a fixed nondimensional frequency, where the
convective ridge levels dominate the spectra.
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Axisymmetric Turbulent Boundary Layer
Measurements on a Full Scale Towed Array Module

• Summary
• The work constitutes a 6.1 effort complimentary
  to ongoing programs aimed at improvements in
  towed array reliability. Unique Navy assets
  including the instrumented towed array (ITA), the
  CDNSWC towing basin, and data processing
  capabilities are utilized in this collaborative
  effort between warfare centers and university
  faculty and students.
• The results to date show a high mean wall shear
  stress and high levels of flow induced vibration
  related to this geometry and range of Reynolds
  numbers investigated. The accelerating tow shows
  features similar to the steady state case, with
  lower flow induced vibration. Processing and
  analysis of the stereo particle image velocimetry
  data is currently underway.
• The results of this investigation to date will be
  presented at the Undersea Technology Conference
  (UDT) Glasgow, in June of 2008.

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Development of Nano/ Microstructured Electrodes
for Increased Performance of Electrochemical
Energy Sources
Christian Schumacher, MS (8231) Charles
Patrissi, Ph.D. (8231) Start Date September 30,
2006

• Navy Relevance
• Navys Grand Challenges
• Power Sources
• Future Naval Capabilites (FNCs)
• Autonomous Operation
• Specifically, Range and Duration of certain
  Missions are Power Source Limited
• Sea Based Sensors
• Undersea Distributed Network Systems
• Unmanned Undersea Vehicles

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ST Objectives
Increase electrode surface area for fuel cells
and batteries.
Increase mass transport in flowing electrolyte
fuel cells.
NUWC's patented carbon microfiber array fuel cell
electrode.

• Prepare nanofiber coated microfibers.
• Assemble into high surface area array.
• Investigate as fuel cell catalyst supports and
  Li-ion battery anodes.

Study effect of fiber density and fiber length
(surface roughness) on electrolyte mass
transport.
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Increased Mass Transport Approach Rotating Disk
Electrochemistry
? 2? f
Epoxy Sheath
immerse in electrolyte
Limiting Current mA
Flocked Fibers
Fluid Flow
Rotation rate1/2
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• Navy Payoff
• Longer mission time and increased capabilities
  for AUVs and systems.
• Power sources with increased energy density and
  power density.

• Accomplishments
• Selection of suitable model compound
• Electrochemistry on fibers, adhesive, RDE
• RDE electrodes have been fabricated
• Electrochemical and electron microscope
  characterization
• Preparation of flocked RDEs has begun.
• Preparation of nano- / microfiber composites has
  begun.

• Future Work
• FY08
• Continue investigation of fiber density fiber
  length on electrode mass transport coefficient,
  kM.
• Prepare very high fiber density electrode in
  collaboration with Prof. Yong Kim (UMass)
• Further investigate microforest if warranted
• FY09
• Prepare optimized CMA for channel fuel cell
  studies.
• Model System performance
• Construction of parametric model (fiber length
  versus fiber density) for application specific
  optimization of CMA.

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A Study of Shallow Water Ambient Noise Intensity
Fields Utilizing Vector Sensor Arrays

• 17 January 2008
• PI David M. Deveau (Code 74)

NUWCDETAUTEC 242-368-2188 x4025 david.deveau_at_aut
ec.navy.mil
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• 2 year Plan
• FY08
• Assemble System
• Deploy
• 8-12 Months Data Acquisition Period
• Matlab Processing Code Development
• FY09
• System recovery
• Processing Publication

Objective Acquire a long term non-isotropic
acoustic Noise Intensity data set and determine
how Vector Sensor performance is correlated to
variations in environmental conditions of shallow
water

• Investment Funding Support
• ONR has provided Investment funding in excess of
  100K for the data acquisition hardware,
  underwater housing and real time software
• ARL/PSU will provide processing support and
  mentoring throughout the project at no cost

• NUWC/Navy Relevance
• Intensity Field Measurement Potential
• Distributed Network System reduction in false
  alarms and better message discrimination
• Adaptive Sensing thru correlation with conditions
• Harbor Security Target Localization
• But
• Very limited knowledge on environment.
• Phase based models have limited actual data
• Limited knowledge on actual Sensing Gains

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Data Acquisition Systems
Shore Cable Interface
Nicolet Liberty System
Sensor Connectors
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Data Processing Analysis
To Gain An Understanding of

• Beamforming techniques (Cray, DSpain, Hawkes)
  and correlate with environmental conditions.
• Determine performance gain variations relative to
  modeled noise fields
• Determine stratification of acoustic intensity
• Utilize surface generated noise to identify known
  scatterers acoustic daylight application
• Cross-correlate surface direct path with bottom
  reflected paths to gauge bottom scattering
  characteristics
• Better understanding of vector sensor handling

• Develop MatLab code to analyze individual
  pressure and vector sensors and arrays.
• Localization of a sound source to baseline system
  performance.
• Intensity Field analysis relative to
  wave/weather.
• Cross-spectral analysis of Bottom Scattering
  utilizing wave generated noise.
• Determination of vessel signatures as they
  traverse local harbor.

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Summary

• Unique Long Term Noise Intensity Study
• Addresses Navy Challenge Areas
• Sensing
• Distributed Network System
• Harbor/Coastal Security
• Leverages Investment hardware in sensors and data
  acquisition hardware/software
• Professional Development
• PhD thesis in Acoustics from Penn State

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What Is Cathodic Delamination?
Corrosion reaction that occurs spontaneously
in seawater. Responsible for most
metal/polymer bonding failures on marine
hardware (Ms/year). Occurs on cathodically
polarized surfaces (usually metal, but not
always!). Produces a very high pH environment
at the interface between the cathodically
polarized surface and the material directly
above it. High pH conditions directly or
indirectly cause the overlying material to
delaminate from the cathodically polarized
substrate.
Typical anodic reaction Zn ? Zn2
2e- Cathodic reaction 2H2O O2 4e- ?
4OH-
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Problems with the Standard Theory For Cathodic
Delamination
The standard CD mechanism works well for thin
polymeric coatings with no exposed edges, like
paints
but many pieces of naval hardware have
thick, polymeric coatings with exposed edges,
such as this sonar transducer and this outboard
cable connector Reports from the Fleet, and
autopsies conducted at NUWC have indicated that
for pieces of hardware such as these,CD proceeds
from the exposed edge inward, often accompanied
by primer degradation/dissolution. DO WE
UNDERSTAND WHAT IS REALLY GOING ON? HOW CAN WE
IMPROVE LONG-TERM RELIABILITY?
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The Problem of Mechanism
THICK, FINITE COATING Has exposed
bond-lines Macroscopic thickness
THIN, INFINITE COATING No edges/exposed
bond-lines Microscopic thickness
QUESTIONS Is the cathodic delamination
mechanism the same for both
cases? If there are different
mechanisms, what are their
rates? Does hydroxide directly attack the
bondline? What primers/adhesive
are most resistant to hydroxide? IMPORTANCE The
degradation mechanism in operation dictates
the mitigation strategy!
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The Basis for Accelerated Life Testing
The Arrhenius Equation
K reaction rate constant A constant
represents the frequency at which atoms
and molecules collide in a way that leads to a
reaction e base of the natural logarithm
system E activation energy (energy required to
generate the reaction transition state k
Boltzmanns constant T absolute temperature
The Arrhenius equation is a mathematical expressio
n that describes the effect of temperature on
the velocity of a chemical reaction.
Svante Arrhenius (1859 - 1927)
Winner of the Nobel Prize for Chemistry in 1903
All existing USN Accelerated Life Testing (ALT)
experimental protocols utilize heat as the
accelerant. Are there better/faster ways to
conduct ALTs for cathodic delamination?
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Effect of Potential and DO Content on the rate of
the CD Reaction
The amount of dissolved oxygen (DO) available
limits the rate of the CD reaction. If the amount
of DO were to be increased, and the potential
manipulated, the initial CD reaction could
continue at higher rates (dashed line) allowing
an ALT to be run without the use of heat, and
with better knowledge of the acceleration factor.
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Distributed Target Tracking with Autonomous
Marine Sensor Networks
PI Dr. Donald P. Eickstedt, Code 2511

• NAVY CONOPS
• Control the battlespace from distributed,
  networked platforms
• Defend strategic coastal areas - ASW CONOPS for
  coastal threat prosecution
• Mobile sensors can dynamically optimize their
  position
• What is the optimal sensor motion for tracking
  both single and multiple targets with multiple
  sensor platforms?
• How do we incorporate this knowledge into an
  autonomy architecture for autonomous sensor
  platforms?

PROJECT GOALS

• Develop a mathematical analysis of multi-sensor
  tracking with mobile sensors
• Transition this analysis into an autonomy
  architecture for mobile sensors
• Develop simulation tools for analysis and
  validation of concepts

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Distributed Target Tracking with Autonomous
Marine Sensor Networks

• Project began in FY07
• Collaboration partners
• Massachusetts Institute of Technology, Prof. H.
  Schmidt (PLUSNet)
• Co-funding
• ONR Code 322 (Tom Curtin) - 100K (2007)
• NUWC - 386K (includes 350K for UDNS testbed
  capital purchase) (2007)
• Other NUWC investigators
• M. Benjamin, Code 2501
• Core technical areas
• Distributed target tracking with mobile sensors
• Optimal sensor formation/motion
• Mobile sensor autonomy architecture
• Sensor platform behaviors
• Multi-objective optimization for autonomous
  sensor platform control

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Single-Sensor Autonomous TMA

• Typical TMA Approach
• Single sensor platform with a very high
  performance sensor, typically a submarine
• No or little use of information from off-board
  sensors or other submarines
• Focus RD on incremental sensor improvements
• Longer arrays
• More sensitive array elements
• Vector sensor arrays

• Disadvantages of Typical TMA Approach
• Cant overcome the basic observability problem
• Diminishing returns on sensor improvement
• Practical limits to array lengths
• Sensitivity eventually overcome by noise
• Coverage area is limited
• Ties up high-value assets for missions like
  harbor protection

Single-Sensor Track and Classify In-Water Field
Exercise Dec 4, 2005 - MIT Sailing Pavilion
Target Track
Classifier Orbit
Results
Sensor Orbit
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Distributed Sensor Autonomous TMA

• Distributed TMA Approach
• Low-cost distributed mobile sensors with lower
  performance, possibly heterogeneous sensors
• Networked communications with other mobile and
  fixed sensor nodes and surface craft
• Cooperation between mobile sensor platforms
• Persistent coverage of large areas

• Advantages to Distributed TMA Approach
• Relatively inexpensive sensor platforms
• Redundancy insures survivability
• Spatial diversity solves observability problem
  and creates additional sensor gain
• Networked integration with other fixed and mobile
  sensors insures maximum information availability
• Large area coverage possible without tying up
  high-value, mission-critical assets

Distributed Track and Trail In-Water Field
Exercise Dec 1, 2005 - MIT Sailing Pavilion
Target Track
Results
Sensor Orbit
Sensor Orbit
46
Technical Approach
Simulation
Optimization
In-Water Testing
47
Probabilistic Analysis of Distributed Sensor
Networks
PI Dr. Errol G. Rowe, code 2511

• NAVY NEED
• Distributed sensor networks are playing an
  increasing role in underwater surveillance and
  detection. However, due to sensor failure and
  drift, long-term network coverage can be
  unreliable. The goals of this theoretical
  analysis are to determine the coverage provided
  by a systems of distributed heterogene-ous
  sensors and to determine the long-term
  effectiveness of such systems.
• PROJECT GOAL
• Successful completion yields analytical tools
  to
• 1. Determine the coverage
  provided by a system of
• randomly
  distributed heterogeneous sensors.
• 2. Predict the
  coverage effectiveness of a network
• experiencing
  random sensor failure and/or
• degradation over
  time.
• 3. Develop algorithm to
  track target in randomly
• distributed
  sensor field.

48
Coverage Prediction Problem
Develop mathematical tools that accurately
predict the coverage of randomly distributed
sensor networks
Approximately 100 sensors randomly distributed
over a 100 by 100 square unit area
Actual coverage .247
Actual coverage .295
49
Design Guidance Learned fromSolution to Coverage
Problem
Homogeneous system all sensors have detection
range of 3 units
Heterogeneous system detection ranges (across
all sensors) follow a beta- type distribution
with mean of 3 units
Solution to coverage prediction problem enables
us to determine the number of randomly
distributed sensors needed to provide any
predetermined coverage rate.
50
Detection Capabilities of Randomly Distributed
Underwater Sensor Fields
Jill K. Nelson (George Mason U.), Errol G. Rowe
(NUWC), and G. Cliff Carter (NUWC)
VS.

• What is the cost-performance trade-off between
  many randomly distributed inexpensive sensors
  and a small set of expensive platforms (subs)?
  
• Can the same total detection area yield better
  detection/tracking results when smaller, cheaper
  sensors are employed?

Initial results to be presented at ICASSP2008
51
Optimization of Sensor Distribution and
Placement for Distributed Sensor Networks
PI Mr. Russell Costa, Code 2511

• NAVY NEED
• The many existing concepts for distributed
  networked systems of sensors being designed
  and/or built for the Navy require analytical
  tools for answering difficult design questions,
  as well as tactical aids for deploying and
  maintaining these systems.
• Must build useful objectives with a corresponding
  Optimization framework for solving difficult
  design / deployment problems

• PROJECT GOAL
• Successful completion yields tools for optimal
  design
• Optimal Sensor Placement for multiple competing
  performance objectives which are inclusive of
  target dynamics as well as sensor
  characterization

52
Optimization of Sensor Distribution and
Placement for Distributed Sensor Networks

• Project began in FY07
• Co-sponsored by ONR 321MS
• Connections with ONR32SP (PLUS)
• Collaborating with
• Duke University, Prof. S. Ferrari
• Other NUWC investigators
• T. Wettergren, Code 2501
• Core technical areas
• Distributed sensor system design and maintenance
• Multi-objective optimization
• Evolutionary-based optimization

53
Optimization of Sensor Distribution and
Placement for Distributed Sensor Networks
Problem Deploy a pre-determined number of
sensors in a specified search region in an
optimal way (maximize probability of successful
search).
Sensor Parameters
Optimization
Selection
54
Optimization of Sensor Distribution and
Placement for Distributed Sensor Networks

• FY07 accomplishments
• Completed analytical form of Probability of
  Successful Search Objective
• Implemented efficient numerical evaluation of the
  objective for use in optimization
• Demonstrated the utility of the PSS Objective in
  finding Optimal Sensor Distributions for various
  target priors and track-before-detect parameters
• Formulated Information-Theoretic Approach to
  Sensor Placement from Optimal Sensor Distribution
• Documented Single Objective results for journal
  submission (Paper in review)

55
A Fracture Criterion for Piezocrystals D. Cox
Understand crack growth in PMN-PT single
crystals under navy relevant mechanical stresses
and electric fields using a combination of
experimental, analytical and numerical tools.
Develop a fracture criterion for these
piezocrystals that will quantify their fracture
toughness.
56
Importance of Piezocrystals

• Single crystals have an electromechanical
  coupling of 90, far in excess of traditional
  piezoceramics ( 70).
• Single crystals have a maximum strain level in
  excess of 1, while traditional piezoceramics
  have about 0.1.
• Dramatic increase in Transducer Bandwidth and
  Acoustic Source Level

Research Motivation
Single crystals appear to have a lower Fracture
Toughness or a greater propensity to propagate
cracks than traditional piezoceramics
57
A Fracture Criterion for Piezocrystals - Problems
with existing Criteria -

• Stress intensity factors
• ? Stresses and electric displacements are
  uncoupled, i.e. cannot account for the effect of
  the electric field .
• Total energy release rate
• ? Includes mechanical and electrical energies
  released as a crack propagates. Indicates that
  an electric field always impedes crack
  propagation

• Mechanical strain energy release rate
• ? The mechanical energy release rate may increase
  or decrease (crack propagation may be enhanced or
  retarded) depending on the direction of electric
  loading however, also indicates that an electric
  field alone cannot cause crack propagation in
  conflict with experimental observation.

58
A Fracture Criterion for Piezocrystals - Approach
for Objective Criterion -
Done

• Incorporate field driven domain switching into
  analytical predictions of strain energy density,
  and then, evaluate/extend the strain energy
  density criterion by comparison with experimental
  data.
• The strain energy density criterion
• a method of obtaining crack propagation
  information, such as direction, critical stress
  levels, etc., from a single scalar function, the
  energy density
• provides a means of assessing how much load -
  mechanical, electrical or combined - can be
  applied before cracking begins.

Comparison with limited experimental data
indicate good predictive capability
59
NUWCs FY07 ILIR and IAR External ST
Collaborations
UNIVERSITY
GOVERNMENT
INDUSTRY OTHER


Brown University Cornell University Duke
University Florida State University George Mason
University Georgia Tech MIT Naval Postgraduate
School New York University School of
Medicine Northwestern University Oregon State
University Penn State University Providence
College Rensselaer Polytechnic Institute Scripps
Oceanographic Institution Stevens Inst.
Tech University of California, Riverside Universit
y of Connecticut University of Hawaii University
of Nevada, Las Vegas University of Rhode
Island University of St. Andrews,
Scotland University of Texas, Arlington Vassar
College Virginia Polytechnic University Woods
Hole Oceanographic Institution
Bahamas Marine Mammal Research Organization CREEM
DoE/NETL NATO Undersea Research Centre Naval
Research Laboratory, Key West, FL Naval Research
Laboratory, Stennis MS NOAA Fisheries Office of
Science Technology NSWC Carderock, MD NSWC
Philadelphia, PA Southwest Fisheries Science
Center SPAWAR, San Diego
Arkema, Inc Cascadia Research Delphi Corporation
Innovatek Nanolabs, Inc Sierra Lobo United
Technologies Research Center Versa Power Systems
Wayne Pigment Co SWRI Vanu Corp


A number of University connections have more
than one association



60
QUESTIONS?
61
NUWC Sites
N.W. RANGE COMPLEX NANOOSE SITE DABOB BAY
SITE QUINAULT SITE
Division Keyport, WA
HEADQUARTERS Newport, RI
Division Newport, RI
Detachment Hawthorne, NV
Detachment San Diego, CA
Detachment Norfolk, VA
Detachments Atlantic Undersea Test Evaluation
Center (AUTEC) West Palm Beach, FL AUTEC
Ranges, Andros Island Bahamas
Detachment Hawaii
Our workforce is concentrated at 2 major
locations proximate to the Fleet We operate 2
major ranges AUTEC in the Bahamas and the
Northwest Range Complex
62
NUWCUndersea Warfare Science Technology
Undersea Distributed NetworkedSystems
Sensors Sonar
Imaging Electronic Warfare
USW CombatSystems

• Cognition DecisionSupport
• Interoperability
• Warfighter Performance

• Transducer Technology
• Signal Processing
• Hull Towed Arrays
• Fiber Optic Laser Sensor

• Signatures WakeReduction
• High Res. Imaging
• EW Sensing

• UnderwaterCommunications
• Adaptive Novel Antennas
• Comms at Speed Depth
• Info Assurance

• Planning and OperationsAnalysis/Research
• Multi-PhenomenologySensor Field
• Coatings Biofouling Anti-Corrosion

USW Solutions for the Warfighter
Core ST Areas
USW Weapons
Launchers
Platform Defense

• Decoy Deception
• Soft Kill technologies
• Countermeasures
• Performance Analysis

• External Launchers
• Undersea Launch Recovery
• Implosion

• Littoral Targeting
• Exploitation
• GC
• Design Analysis
• Propulsion

• Marine Mammal Behavior
• Automated Reconstruction Analysis
• Portable Ranges

• Autonomy
• Long Endurance Power Sys.
• Multi-Vehicle Collaboration
• Biomimetic Vehicles

63
Collaboration on a Global Basis
International Symposium and Conference
Basic Research, Fundamental Ideas, Scientific
Talent Pool Educational Partnership Agreements
Stable, Long Term Investments -Stewardships-
Office of Naval Research Etc.
NWC NWDC Fleet Fleet Reps
International ST Resources
Innovation
Academia
21 Educational Partnership Agreements
Service Laboratories/Centers
56 Cooperative RD Agreements
Demo/Validation, Production
High Risk, High Payoff RD

• Recent Alliances
• Sandia
• Electric Boat
• Raytheon
• Northrop Grumman

Foreign Military Sales Armament Cooperation
Programs Data Exchange Agreements Technical
Cooperation Programs Cooperative Research and
Development Agreements
CRADAs
SBIR
U. S. Allies
Industry IRAD
64
Challenge for the Future USW Distributed
Networked Systems (UDNS)

• Major DNS System Functions
• Sensing
• Transport
• Netting
• Information Fusion and Pattern Recognition
• Interpretation, Cognition and Decision
• Influence
• Technology Barriers
• Smart Sensors
• Data Fusion
• Detecting Range
• Communications
• Transport

Supporting USW in the joint environment with the
development of a scalable and flexible mix of
sensors, platforms, and systems for now and the
future
65
ST Requirements Flow-Down Process
Capability Driven Warfighting Requirements
W A R F A R E C E N T E R P R O G R A M

• Operational Maneuver From Sea
• CNO Guidance 03
• NWDC
• Sea Power 21
• Naval Transformation
• DoN Strategic Guidance
• CNO Strategic Studies Group
• USE ST Priorities
• Battle Force Cap. Assessment
• Force Structure Analysis (IWAR)
• CNO Program Analysis (CPAM)
• Mission Capabilities Package
• Fleet Battle Expmts.
• Naval Studies Board

• Revolution in Military Affairs
• Joint Vision 2020
• Transformation
• DoD ST Strategy
• JCS Planning Guidance
• QDR
• CONOPS
• Militarily Critical Technology
• Defense Technology Area Plan
• Joint Warfighting ST Plan
• Basic Research Plan
• Defense Technology Objectives
• Defense Science Board Reports
• MANTECH
• DARPA

• Grand Challenges
• Command Capability Issues
• Future Naval Capabilities
• Swampworks
• ST (ILIR) Guidance
• National Naval Responsibilities
• NFFTI (Tech Solutions)
• DoN ST Execution Process
• MANTECH
• SBIR
• ONR ST Focus Areas
• Naval ST Strategy

• Congressional Direction
• National Science Foundation
• National Academy of Sciences Studies
• US CodeTitle X
• National Military Strategy
• Homeland Security
• National Security ST Strategy
• SACLANT
• DoT (Coast Guard)

• NAVSEA
• ST Technical Area Plan
• Technology Roadmaps
• FORCENET
• SUBTECH Process
• External Scan
• NUWC Strategic Plan
• Technical Capabilities
• TD Grand Challenge
• UDNS

SEA Power
DoD Joint Forces
OPNAV Naval Forces
NAVSEA WFC
ONR Navy ST
National
Technology Push Internal Investments
66
Working Together to Deliver the Best Solutions
Quickly
Science
INNOVATION
Prototyping
Test Evaluation
Undersea Warfare Analysis
Operating Principles (1) Teamwork, (2)
Integrity, (3) Accountability, (4) Initiative,
(5) Respect
04-NUWC-GRA/0066U.M5
4210-BFL