{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/95396"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/95396","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Three-dimensional particle tracking velocimetry study of marine organism wake behavior","abstract":"Three-dimensional particle tracking velocimetry (3D-PTV) is a flow measurement technique that tracks Lagrangian trajectories of passive tracer particles using stereoscopic imaging. The technique allows for detailed analysis of the velocities along particle trajectories in unsteady flows. The implementation and optimization of the technique is involved however, requiring precise attention to the correct methods of system setup, camera calibration, and processing. This thesis aims to develop an optimal system setup for the use of 3D-PTV for studying flow behavior in the wakes of marine organisms. Previous studies have been limited by the restrictions of other flow measurement techniques, and have been largely confined to 2D analysis. This paper describes the methods by which 3D-PTV can be optimized for this purpose, including choice of calibration target, seeding particles, and PTV software parameters. The output data is analyzed and compared with existing 2D data as a demonstration of the technique.","abstract_html":"Three-dimensional particle tracking velocimetry (3D-PTV) is a flow measurement technique that tracks Lagrangian trajectories of passive tracer particles using stereoscopic imaging. The technique allows for detailed analysis of the velocities along particle trajectories in unsteady flows. The implementation and optimization of the technique is involved however, requiring precise attention to the correct methods of system setup, camera calibration, and processing. This thesis aims to develop an optimal system setup for the use of 3D-PTV for studying flow behavior in the wakes of marine organisms. Previous studies have been limited by the restrictions of other flow measurement techniques, and have been largely confined to 2D analysis. This paper describes the methods by which 3D-PTV can be optimized for this purpose, including choice of calibration target, seeding particles, and PTV software parameters. The output data is analyzed and compared with existing 2D data as a demonstration of the technique.","abstract_has_math":false,"creators":["Piper, Matthew J"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Theoretical & Applied Mechanics","degree_department":null,"school":null,"contributors":["Chamorro, Leonardo P."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-03-01T15:49:27Z","date_published":"2017-03-01T15:49:27Z","updated_at":"2026-07-22T22:26:37Z","subjects":["Jellyfish","Aurelia aurita","Particle Tracking Velocimetry"],"languages":["en"],"rights":["Copyright 2016 Matthew Piper"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/95396","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Chamorro, Leonardo P."]},{"key":"dc:creator","label":"Author","values":["Piper, Matthew J"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2017-03-01T15:49:27Z","2016-12-05","2016-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Theoretical & Applied Mechanics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Jellyfish","Aurelia aurita","Particle Tracking Velocimetry"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2016 Matthew Piper"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/95396"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Three-dimensional particle tracking velocimetry (3D-PTV) is a flow measurement technique that tracks Lagrangian trajectories of passive tracer particles using stereoscopic imaging. The technique allows for detailed analysis of the velocities along particle trajectories in unsteady flows. The implementation and optimization of the technique is involved however, requiring precise attention to the correct methods of system setup, camera calibration, and processing. This thesis aims to develop an optimal system setup for the use of 3D-PTV for studying flow behavior in the wakes of marine organisms. Previous studies have been limited by the restrictions of other flow measurement techniques, and have been largely confined to 2D analysis. This paper describes the methods by which 3D-PTV can be optimized for this purpose, including choice of calibration target, seeding particles, and PTV software parameters. The output data is analyzed and compared with existing 2D data as a demonstration of the technique.","Submission original under an indefinite embargo labeled 'Open Access'. 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The implementation and optimization of the technique is involved however, requiring precise attention to the correct methods of system setup, camera calibration, and processing. This thesis aims to develop an optimal system setup for the use of 3D-PTV for studying flow behavior in the wakes of marine organisms. Previous studies have been limited by the restrictions of other flow measurement techniques, and have been largely confined to 2D analysis. This paper describes the methods by which 3D-PTV can be optimized for this purpose, including choice of calibration target, seeding particles, and PTV software parameters. The output data is analyzed and compared with existing 2D data as a demonstration of the technique.","Submission original under an indefinite embargo labeled 'Open Access'. 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