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Uncertainty analysis of a particle tracking algorithm developed for super-resolution particle image velocimetry

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dc.contributor.advisorBugg, James D.en_US
dc.contributor.committeeMemberHabibi, Saeid R.en_US
dc.contributor.committeeMemberEvitts, Richard W.en_US
dc.contributor.committeeMemberBurton, Richard T.en_US
dc.contributor.committeeMemberSumner, Daviden_US
dc.creatorJoseph, Sujithen_US
dc.date.accessioned2003-08-04T06:40:37Zen_US
dc.date.accessioned2013-01-04T04:50:55Z
dc.date.available2004-08-11T08:00:00Zen_US
dc.date.available2013-01-04T04:50:55Z
dc.date.created2003-05en_US
dc.date.issued2003-05-26en_US
dc.date.submittedMay 2003en_US
dc.description.abstractParticle Image Velocimetry (PIV) is a powerful technique to measure the velocity at many points in a flow simultaneously by performing correlation analysis on images of particles being transported by the flow. These images are acquired by illuminating the flow with two light pulses so that each particle appears once on each image. The spatial resolution is an important parameter of this measuring system since it determines its ability to resolve features of interest in the flow. The super-resolution technique maximises the spatial resolution by augmenting the PIV analysis with a second pass that identifies specific particles and measures the distance between them. The accuracy of the procedure depends on both the success with which the proper pairings are identified and the accuracy with which their centre-to-centre distance can be measured. This study presents an analysis of both the systematic uncertainty and random uncertainty associated with this process. The uncertainty is analysed as a function of several key parameters that define the quality of the image. The uncertainty analysis is performed by preparing 4000 member ensembles of simulated images with specific setpoints of each parameter. It is shown that the systematic uncertainty is negligible compared to the random uncertainty for all conditions tested. Also, the image contrast and the selection of a threshold for the particle search are the most critical parameters influencing both success rate and uncertainty. It is also shown that high image intensities still yield accurate results. The search radius used by the super-resolution algorithm is shown to be a critical parameter also. By increasing the search radius, the success rate can be increased although this is accompanied by an increase in random uncertainty.en_US
dc.identifier.urihttp://hdl.handle.net/10388/etd-08042003-064037en_US
dc.language.isoen_USen_US
dc.subjectHigh Resolution PIV. Simulated PIV images.en_US
dc.subjectLDVen_US
dc.subjectwhole field velocity measurementsen_US
dc.subjectError Measurements in PIVen_US
dc.subjectUncertainty analysis of PIV algorithmen_US
dc.subjectSuper-resolution particle image velocimetryen_US
dc.subjectPIVen_US
dc.subjectSPIVen_US
dc.subjecthot-wire measurementsen_US
dc.subjectParticle Image Velocimetryen_US
dc.titleUncertainty analysis of a particle tracking algorithm developed for super-resolution particle image velocimetryen_US
dc.type.genreThesisen_US
dc.type.materialtexten_US
thesis.degree.departmentMechanical Engineeringen_US
thesis.degree.disciplineMechanical Engineeringen_US
thesis.degree.grantorUniversity of Saskatchewanen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Science (M.Sc.)en_US

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