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dc.contributor.advisorMichael S. Triantafyllou.en_US
dc.contributor.authorFernandez, Vicente Ien_US
dc.contributor.otherWoods Hole Oceanographic Institution.en_US
dc.date.accessioned2011-12-09T21:27:28Z
dc.date.available2011-12-09T21:27:28Z
dc.date.copyright2011en_US
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/67581
dc.descriptionThesis (Ph. D.)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2011.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 223-232).en_US
dc.description.abstractThe lateral line is a critical component of the fish sensory system, found to affect numerous aspects of behavior including maneuvering in complex fluid environments, schooling, prey tracking, and environment mapping. This sensory organ has no analog in modem ocean vehicles, despite its utility and ubiquity in nature, and could fill the gap left by sonar and vision systems in turbid cluttered environments. Yet, while the biological sensory system suggests the broad possibilities associated with such a sensor array, nearly nothing is known of the input processing and what information is available via the real lateral line. This thesis demonstrates and characterizes the ability of lateral-line-inspired linear pressure sensor arrays to perform two sensory tasks of relevance to biological and man-made underwater navigation systems, namely shape identification and vortex tracking. The ability of pressure sensor arrays to emulate the "touch at a distance" feature of the lateral line, corresponding to the latter's capability of identifying the shape of objects remotely, is examined with respect to moving cylinders of different cross sections. Using the pressure distribution on a small linear array, the position and size of a cylinder is tracked at various distances. The classification of cylinder shape is considered separately, using a large database of trials to identify two classification approaches: One based on differences in the mean flow, and one trained on a subset which utilizes information from the wake. The results indicate that it is in general possible to extract specific shape information from measurements on a linear pressure sensor array, and characterize the classes of shapes which are not distinguishable via this method. Identifying the vortices in a flow makes it possible to predict and optimize the performance of flapping foils, and to identify imminent stall in a control surface. Vortices in wakes also provide information about the object that generated the wake at distances much larger than the near-field pressure perturbations. Experimental studies in tracking a vortex pair and an individual vortex interacting with a flat plate demonstrate the ability to track vortices with a linear pressure sensor array from both small streamlined bodies and large flat bodies. Based on a theoretical analysis, the relationship between the necessary array parameters and the range of vortices of interest is established.en_US
dc.description.statementofresponsibilityby Vicente I. Fernandez.en_US
dc.format.extent232 p.en_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.subjectJoint Program in Applied Ocean Science and Engineering.en_US
dc.subjectMechanical Engineering.en_US
dc.subjectWoods Hole Oceanographic Institution.en_US
dc.subject.lcshSensor networksen_US
dc.subject.lcshUnderwater navigationen_US
dc.titlePerformance analysis for lateral-line-inspired sensor arraysen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentJoint Program in Applied Ocean Physics and Engineeringen_US
dc.contributor.departmentWoods Hole Oceanographic Institutionen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.identifier.oclc763256056en_US


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