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dc.contributor.advisorHoushuo Jiang.en_US
dc.contributor.authorRapo, Mark Andrewen_US
dc.contributor.otherWoods Hole Oceanographic Institution.en_US
dc.date.accessioned2009-09-24T20:48:48Z
dc.date.available2009-09-24T20:48:48Z
dc.date.copyright2009en_US
dc.date.issued2009en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/46805
dc.descriptionThesis (Ph. D.)--Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2009.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionIncludes bibliographical references (leaves 264-277).en_US
dc.description.abstractThe lateral line system on fish has been found to aid in schooling behavior, courtship communication, active and passive hydrodynamic imaging, and prey detection. The most widely used artificial prey stimulus has been the vibrating sphere, which some fish are able to detect even when the signal velocities to its lateral line are orders of magnitude smaller than background current velocities. It is not clear how the fish are able to extract this signal. This thesis uses a series of computational fluid dynamic (CFD) simulations, matched with recent experiments, to quantify the effects of 3D fish body parts on the received dipole signals, and to determine signal detection abilities of the lateral line system in background flow conditions. An approximation is developed for the dipole induced, oscillatory, boundary layer velocity profile over the surface of a fish. An analytic solution is developed for the case when the surface is a wall, and is accurate at points of maximal surface tangential velocity. Results indicate that the flow outside a thin viscous layer remains potential in nature, and that body parts, such as fins, do not significantly affect the received dipole signal in still water conditions. In addition, the canal lateral line system of the sculpin is shown to be over 100 times more sensitive than the superficial lateral line system to high frequency dipole stimuli. Analytical models were developed for the Mottled Sculpin canal and superficial neuromast motions, in response to hydrodynamic signals. When the background flow was laminar, the neuromast motions induced by the stimulus signal at threshold had a spectral peak larger than spectral peaks resulting from the background flow induced motions.en_US
dc.description.abstract(cont.) When the turbulence level increased, the resulting induced neuromast motions had dominant low frequency oscillations. For fish using the signal encoding mechanisms of phase-locking or spike rate increasing, signal masking should occur.en_US
dc.description.statementofresponsibilityby Mark Andrew Rapo.en_US
dc.format.extent277 leavesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subject/Woods Hole Oceanographic Institution. Joint Program in Oceanography/Applied Ocean Science and Engineering.en_US
dc.subjectMechanical Engineering.en_US
dc.subjectWoods Hole Oceanographic Institution.en_US
dc.subject.lcshLateral line organsen_US
dc.subject.lcshSignal detectionen_US
dc.titleCFD study of hydrodynamic signal perception by fish using the lateral line systemen_US
dc.title.alternativeComputational fluid dynamic study of hydrodynamic signal perception by fish using the lateral line systemen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentJoint Program in Oceanography/Applied Ocean Science and Engineeringen_US
dc.contributor.departmentWoods Hole Oceanographic Institutionen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.identifier.oclc429908519en_US


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