Tomographic Particle Image Velocimetry Using Colored Shadow Imaging
AuthorsAlarfaj, Meshal K.
AdvisorsThoroddsen, Sigurdur T
KAUST DepartmentPhysical Science and Engineering (PSE) Division
Embargo End Date2016-04-10
Permanent link to this recordhttp://hdl.handle.net/10754/605159
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Access RestrictionsAt the time of archiving, the student author of this thesis opted to temporarily restrict access to it. The full text of this thesis became available to the public after the expiration of the embargo on 2016-04-10.
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.
CitationAlarfaj, M. K. (2016). Tomographic Particle Image Velocimetry Using Colored Shadow Imaging. KAUST Research Repository. https://doi.org/10.25781/KAUST-8859C