Tomographic Particle Image Velocimetry Using Colored Shadow Imaging

Handle URI:
http://hdl.handle.net/10754/605159
Title:
Tomographic Particle Image Velocimetry Using Colored Shadow Imaging
Authors:
Alarfaj, Meshal K. ( 0000-0001-8813-0608 )
Abstract:
Tomographic Particle Image Velocimetry Using Colored Shadow Imaging by Meshal K Alarfaj, Master of Science King Abdullah University of Science & Technology, 2015 Tomographic Particle image velocimetry (PIV) is a recent PIV method capable of reconstructing the full 3D velocity field of complex flows, within a 3-D volume. For nearly the last decade, it has become the most powerful tool for study of turbulent velocity fields and promises great advancements in the study of fluid mechanics. Among the early published studies, a good number of researches have suggested enhancements and optimizations of different aspects of this technique to improve the effectiveness. One major aspect, which is the core of the present work, is related to reducing the cost of the Tomographic PIV setup. In this thesis, we attempt to reduce this cost by using an experimental setup exploiting 4 commercial digital still cameras in combination with low-cost Light emitting diodes (LEDs). We use two different colors to distinguish the two light pulses. By using colored shadows with red and green LEDs, we can identify the particle locations within the measurement volume, at the two different times, thereby allowing calculation of the velocities. The present work tests this technique on the flows patterns of a jet ejected from a tube in a water tank. Results from the images processing are presented and challenges discussed.
Advisors:
Thoroddsen, Sigurdur T ( 0000-0001-6997-4311 )
Committee Member:
Roberts, William L. ( 0000-0003-1999-2831 ) ; Li, Erqiang ( 0000-0002-5003-0756 )
KAUST Department:
Physical Sciences and Engineering (PSE) Division; Mechanical Engineering Program
Program:
Mechanical Engineering
Issue Date:
Feb-2016
Type:
Thesis
Appears in Collections:
Theses; Physical Sciences and Engineering (PSE) Division; Mechanical Engineering Program

Full metadata record

DC FieldValue Language
dc.contributor.advisorThoroddsen, Sigurdur Ten
dc.contributor.authorAlarfaj, Meshal K.en
dc.date.accessioned2016-04-13T07:56:58Zen
dc.date.available2016-04-13T07:56:58Zen
dc.date.issued2016-02en
dc.identifier.urihttp://hdl.handle.net/10754/605159en
dc.description.abstractTomographic Particle Image Velocimetry Using Colored Shadow Imaging by Meshal K Alarfaj, Master of Science King Abdullah University of Science & Technology, 2015 Tomographic Particle image velocimetry (PIV) is a recent PIV method capable of reconstructing the full 3D velocity field of complex flows, within a 3-D volume. For nearly the last decade, it has become the most powerful tool for study of turbulent velocity fields and promises great advancements in the study of fluid mechanics. Among the early published studies, a good number of researches have suggested enhancements and optimizations of different aspects of this technique to improve the effectiveness. One major aspect, which is the core of the present work, is related to reducing the cost of the Tomographic PIV setup. In this thesis, we attempt to reduce this cost by using an experimental setup exploiting 4 commercial digital still cameras in combination with low-cost Light emitting diodes (LEDs). We use two different colors to distinguish the two light pulses. By using colored shadows with red and green LEDs, we can identify the particle locations within the measurement volume, at the two different times, thereby allowing calculation of the velocities. The present work tests this technique on the flows patterns of a jet ejected from a tube in a water tank. Results from the images processing are presented and challenges discussed.en
dc.language.isoenen
dc.subjectTomographyen
dc.subjectParticle image velocimetry (PIV)en
dc.subject3D Verticity Fielden
dc.subjectLight emitting diodes (LEDs)en
dc.subjectColored shadow imagingen
dc.titleTomographic Particle Image Velocimetry Using Colored Shadow Imagingen
dc.typeThesisen
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Divisionen
dc.contributor.departmentMechanical Engineering Programen
thesis.degree.grantorKing Abdullah University of Science and Technologyen_GB
dc.contributor.committeememberRoberts, William L.en
dc.contributor.committeememberLi, Erqiangen
thesis.degree.disciplineMechanical Engineeringen
thesis.degree.nameMaster of Scienceen
dc.person.id128772en
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