NDLI: Double-frame 3D-PTV using a tomographic predictor

Content Provider	Springer Nature Link
Author	Fuchs, Thomas Hain, Rainer Kähler, Christian J.
Copyright Year	2016
Abstract	Thanks to the technological progress, 3D velocimetry techniques are becoming more popular. In particular, the time-resolved flow analysis by means of particle tracking is very attractive. Compared to double-frame recordings, higher seeding concentrations are feasible, yielding high spatial resolution results without bias errors due to strong velocity gradients. However, hardware restrictions still limit time-resolved measurements to rather small flow velocities and low magnifications. In aerodynamics, especially, this is a drawback, since often higher flow velocities are of interest. To conduct reliable 3D-PTV measurements from double-frame recordings, the well-established techniques tomographic particle imaging and 3D-PTV are employed for a novel processing approach. In this combined approach, the tomographic reconstruction is used as a predictor for the sensor locations of the corresponding particle images of the reconstructed particles. Furthermore, the reconstruction helps to identify and reject non-corresponding sets of particle images, reducing the amount of ghost particles to a minimum. A probabilistic tracking algorithm is then applied to estimate the flow field.
Starting Page	1
Ending Page	5
Page Count	5
File Format	PDF
ISSN	07234864
Journal	Experiments in Fluids
Volume Number	57
Issue Number	11
e-ISSN	14321114
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2016-10-24
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Engineering Fluid Dynamics Fluid- and Aerodynamics Engineering Thermodynamics, Heat and Mass Transfer
Content Type	Text
Resource Type	Article
Subject	Fluid Flow and Transfer Processes Physics and Astronomy Mechanics of Materials Computational Mechanics

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