Research

Labs & Centers

The research activities in the Department of Ocean and Mechanical Engineering are primarily defined by faculty interests. The research is inherently integrated into the academic programs of the department. Faculty research allows the department to provide challenging research experiences for graduate and undergraduate students. Additionally, faculty members bring their research experience to the classroom generating a sense of excitement in the courses being taught.

Research in Ocean Engineering

Ocean engineering research is typically involved with determining innovative solutions to challenging problems in working in the ocean environment. Faculty are involved in a range of federal and state sponsored projects including studies of seawater corrosion and marine materials, underwater acoustics, and acoustic imaging and communication, flow noise, autonomous marine vehicles and control, hydrodynamics and propulsion of marine vehicles, physical oceanography, fabrication of nano-materials, ocean energy technologies and machine monitoring. A significant amount of the research is in the area of naval engineering. An important traditional aspect of the department research has been the development of ocean technologies, including autonomous underwater and surface vehicles, air-deployable buoys, sonar systems, acoustic modems, and a spar platform. SeaTech, The Institute for Ocean and Systems Engineering, serves as a means to promote the transition of ocean technologies to industry.

Research in Mechanical Engineering

Mechanical engineering research involves design, manufacture and operation of thermal and mechanical systems. Mechanical systems research includes controls, robotics, mechatronics, fluid power and motion control as well as the dynamics and kinematics of machinery. Faculty are involved in several research areas including, composite materials, helicopter dynamics, robotics, fluid mechanics and heat transfer, combustion, manufacturing, solar energy, structural engineering, and mechanical vibrations. The department has particular strengths in the areas of composite materials, stochastic processes, fuel cell technology and finite element analysis.

Department Labs, Centers and The Institute

• Advanced Marine Systems Lab
• BioRobotics Lab
• Center for Acoustics & Vibration
• Center for Hydrodynamics & Physical Oceanography
• Center for Marine Materials
• Corrosion Lab
• Nanocomposites and Structures Laboratory
• SeaTech The Institute for Ocean & Systems Engineering
• Research Vessel

CHARTERS AVAILABLE FOR SCIENTIFIC PURPOSES

Contact and Scheduling
Dr. Francisco Presuel-Moreno, Director of SeaTech
954.924.7236 or 954.924.7000
fpresuel@fau.edu

Center for Acoustics and Vibrations

Affiliated Faculty:
Pierre-Philippe Beaujean, Ph.D., Email:    pbeaujea@fau.edu
Isaac Elishakoff, Ph.D., Email:    elishako@fau.edu
Nurgun Erdol, Ph.D., Email:    erdol@fau.edu
George Frisk, Ph.D., Email:    gfrisk@fau.edu
Gopal Gaonkar, Ph.D., Email:    gaonkar@fau.edu
Hanqi Zhuang, Ph.D., Email:    zhuang@fau.edu

The Center for Acoustics and Vibrations at FAU specializes in the following areas of research:

• Underwater Acoustics
• Sonar Technology
• Structural Acoustics and Vibration
• Aeroacoustics and Hydroacoustics

Support for research in these areas is typically provided by the following agencies.

• National Science Foundation
• Office of Naval Research
• The Naval Surface Warfare Center
• Naval Underwater Systems Center
• Naval Research Laboratory and
• NASA.

The Center supports a number of graduate students and graduate degrees are offered at the Masters and Ph.D. level in ocean or mechanical engineering with specialization in acoustics and vibrations.

Research Areas Overview

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Underwater Acoustics and Structural Vibrations

The CAV has major programs in underwater acoustics with projects in the following areas:

1. sonar and signal processing
2. acoustic inversion
3. acoustic communications
4. structural vibrations applied in particular to subsea machine fatigue.

Hermes

Hermes is a high-frequency underwater acoustic modem capable of very high bit rates in challenging acoustic environments. This technology is now licensed to an industrial partner, Edgetech.

Collaboration with: MIT, University of Michigan, SPAWAR, BlueFin Robotics, Woods Hole Oceanograhic Institution of Oceanography, NSWC, Edgetech and HBOI.

Sponsored by: ONR, NSWC, Office of Explosive Ordinance Disposal, NSF, SERDC, the NATO Undersea Research Centre, Edgetech and SNMREC.

Rapidly Deployable, Recoverable, and Reusable (RDRR) Gateway Buoys

Freely drifting buoys equipped with hydrophones, GPS navigation, and radio telemetry are used to measure the acoustic characteristics of complex shallow-water environments. The data can be used for the determination of the acoustic properties of the seabed, which the Navy requires for reliable predictions of sound fields in shallow-water operations. The ultimate goal is to transition the experimental methodology and inversion techniques to the operational Navy using commercial-off-the-shelf sonobuoy receivers.

Collaboration with: Woods Hole Oceanographic Institution and the Applied Research Laboratory/Penn State University.
Sponsored by: U.S. Navy

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Stochastic Processes

The CAV performs research in stochastic processes, vibration, buckling and nanotechnology under the direction of Isaac Elishakoff, Ph.D., Distinguished Research Professor in the Department of Ocean and Mechanical Engineering.

Signal Processing of Dolphin and Whale Vocalizations

A set of algorithms has been developed for the analysis and classification of the vocalizations of bottlenose dolphins and right whale Atlantic whale's vocalizations. The algorithms introduce novelty into bioacoustics, a field in which automation of the study of animal calls has only recently been undertaken. In this research methods to classify dolphin whistles according to their types is researched. Successful classification may be used to understand the encoded messages. Image processing techniques on time-frequency spectrograms of vocalizations to generate feature vectors which are then input to classifiers are used. The efficacy of Temporal-Frequency parameters Fourier descriptors (FDs), Local Binary Patterns (LBP) and Gabor wavelets to supply feature vectors to the K-Nearest Neighbor (KNN), Support Vector Machine and Sparse Representation Classifiers is studied.

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