September 2012
Name: Huikwan Kim
Department: Department of Ocean Engineering
School: University of Rhode Island
Project: Design and testing of a shear measurement system
Research Advisor: Professor James H. Miller and Professor Gopu R. Potty
Huikwan obtained his Bachelor’s degree in Naval Architecture from the Naval Academy in the Republic of Korea. He was interested in underwater radiated noise from submerged structures in the ocean. As a Naval Shipbuilding Officer in the Korean Navy Headquarters, he was tasked with the measurement and analysis of noise and vibration in naval ships’ major compartments using Brüel & Kjær’s test equipment. He completed the Master’s degree in the Department of Ocean Engineering at the University of Rhode Island (URI) in 2006 and came back for their PhD program in 2009. Huikwan participated in the 9th International Autonomous Underwater Vehicle (AUV) competition held in San Diego, CA as a passive SONAR system circuit board designer. The URI AUV team placed 4th out of 21 teams at the competition.
Currently, Huikwan is working on his doctoral research in the area of structure borne noise radiation and propagation in shallow water environment. He is developing analytical tools to predict near field acoustic levels to use them in conjunction with a long range propagation model (Parabolic Equation model). Recently, he published and presented the results of his research in the 162nd and the 163rd Acoustical Society of America (ASA) meetings in San Diego, CA, and in Hong Kong and MTS/IEEE Oceans 2012 conference in Korea. At the Hong Kong ASA meeting, he won 1st prize in the student paper competition. In addition to his major research area mentioned above, he will participate in the URI effort on the estimation of shear speed on the ocean bottom using the URI shear measurement system as a partial requirement of entire PhD work. He will be involved with the integration of different sensors in the system and the subsequent engineering tests.
For his Link Foundation research project, Huikwan is designing and testing a shear measurement system. Shear properties in the ocean bottom are important to model acoustic propagation in shallow water. Propagation of sound in shallow water is greatly affected by the boundary condition at the surface and bottom because of multipath effect in shallow water. One of the most promising approaches to estimate shear speed is to invert for the shear speed profile using phase and group speed dispersion of seismo-acoustic interface (Scholte) waves that travel along the sediment - water boundary. The phase and group speed of Scholte wave at the water-sediment interface strongly depend on its shear speed profile in the sediment down to one - two wavelengths. This approach is easier and less expensive than in situ and laboratory techniques (sediment probes, cone penetrometer etc.) available to estimate the sediment shear speed. Experimental investigations of the shear measurement system using three-axis and vertical axis gimbaled geophones are proposed to be carried out in shallow water. The collected data will be analyzed to estimate the phase speeds of the interface waves. The shear speed profile in the sediment will then be estimated based on the interface wave data.
Name: Audrey Maertens
Department: Mechanical Engineering Department
School: Massachusetts Institute of Technology
Project: Underwater object detection and identification using distributed pressure sensors
Research Advisor: Professor Michael Triantafyllou
Audrey graduated from one of the most prestigious French universities for engineering, the Ecole Polytechnique in Paris. There she led the scuba diving student association, which reinforced her all-time interest in the underwater world. Upon finishing her Bachelor’s degree in Engineering, Simulation and Modeling, she joined the Mechanical Engineering Department at Massachusetts Institute of Technology (MIT). In MIT’s Center for Ocean Engineering, she got involved into a project that draws inspiration from fish’s sensing and maneuvering capabilities to develop tomorrow’s underwater vehicles. She recently obtained her MS degree and is now ready to embark on her PhD.
For her Link Research project she is developing underwater object detection and identification using distributed pressure sensors. Underwater vision is usually limited. Object detection and identification is therefore one of the main challenges of underwater navigation. A new sensing modality, specifically developed for underwater environments, would greatly increase the scope of underwater missions.
This project will develop computational tools for allowing underwater vehicles to use distributed pressure sensors to detect and identify obstacles. State-of-the-art computational fluid dynamics simulations will be used to build a simplified hydrodynamic model for pressure prediction. The model will then be used to provide guidelines in terms of appropriate sensor location, spacing and sensitivity. Finally, an algorithm to detect and identify obstacles in real-time using distributed pressure sensors will be developed.
Name: Christopher McFarland
Department: Department of Mechanical Engineering
School: Johns Hopkins University
Project: Facilitate Unmanned Underwater Vehicle (UUV) scientific deployments by enabling these systems to better utilize their capacity for dynamic motion
Research Advisor: Professor Louis Whitcomb
After growing up in Oklahoma, Christopher McFarland attended the University of Puget Sound in Tacoma, WA, where he earned his BA degree in Physics. He then attended Washington University in St. Louis and received a BS degree in Mechanical Engineering. During the five years required to finish both degrees, he was lucky enough to have internships with Anadarko Petroleum Corporation's World Wide Deep Water Operations Group and Idaho National Lab's Adaptive Robotics Group. Based on these experiences, both inside and outside the classroom, Christopher chose to pursue a PhD at Johns Hopkins University based on Professor Whitcomb's commitment to developing both advanced techniques to control underwater vehicles and advanced tools to facilitate scientific research.
Christopher's current objective is to facilitate Unmanned Underwater Vehicle (UUV) scientific deployments by enabling these systems to better utilize their capacity for dynamic motion. Recent advances in UUV capabilities have enabled climatologists, geologists, biologists and archaeologists to consider addressing research topics previously thought impractical or impossible. These types of missions require precisely and quickly maneuvering the vehicle. Thus full utilization of UUV capabilities requires accurate tracking in the vehicle's position and velocity. Currently, UUVs use linear controllers which suffer tracking performance errors because they do not compensate for non-linearities such as drag, buoyancy, inertia and hydrodynamic forces. Christopher and his advisor will develop Model Based Adaptive Controllers (MBAC) which model drag, buoyancy, inertia and hydrodynamic forces and “learn” the correct values of these parameters as part of the control process. They hypothesize MBAC will significantly improve UUV effectiveness for scientific research. To test this claim, the Johns Hopkins Hydrodynamic Test Facility will be used in full scale trials of both linear PD control and MBAC to evaluate vehicle tracking performance gains.