Intensity-enhanced MART for tomographic PIV

Intensity-enhanced MART for tomographic PIV A novel technique to shrink the elongated particles and suppress the ghost particles in particle reconstruction of tomographic particle image velocimetry is presented. This method, named as intensity-enhanced multiplicative algebraic reconstruction technique (IntE-MART), utilizes an inverse diffusion function and an intensity suppressing factor to improve the quality of particle reconstruction and consequently the precision of velocimetry. A numerical assessment about vortex ring motion with and without image noise is performed to evaluate the new algorithm in terms of reconstruction, particle elongation and velocimetry. The simulation is performed at seven different seeding densities. The comparison of spatial filter MART and IntE-MART on the probability density function of particle peak intensity suggests that one of the local minima of the distribution can be used to separate the ghosts and actual particles. Thus, ghost removal based on IntE-MART is also introduced. To verify the application of IntE-MART, a real plate turbulent boundary layer experiment is performed. The result indicates that ghost reduction can increase the accuracy of RMS of velocity field. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Experiments in Fluids Springer Journals

Intensity-enhanced MART for tomographic PIV

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2016 by Springer-Verlag Berlin Heidelberg
Subject
Engineering; Engineering Fluid Dynamics; Fluid- and Aerodynamics; Engineering Thermodynamics, Heat and Mass Transfer
ISSN
0723-4864
eISSN
1432-1114
D.O.I.
10.1007/s00348-016-2176-y
Publisher site
See Article on Publisher Site

Abstract

A novel technique to shrink the elongated particles and suppress the ghost particles in particle reconstruction of tomographic particle image velocimetry is presented. This method, named as intensity-enhanced multiplicative algebraic reconstruction technique (IntE-MART), utilizes an inverse diffusion function and an intensity suppressing factor to improve the quality of particle reconstruction and consequently the precision of velocimetry. A numerical assessment about vortex ring motion with and without image noise is performed to evaluate the new algorithm in terms of reconstruction, particle elongation and velocimetry. The simulation is performed at seven different seeding densities. The comparison of spatial filter MART and IntE-MART on the probability density function of particle peak intensity suggests that one of the local minima of the distribution can be used to separate the ghosts and actual particles. Thus, ghost removal based on IntE-MART is also introduced. To verify the application of IntE-MART, a real plate turbulent boundary layer experiment is performed. The result indicates that ghost reduction can increase the accuracy of RMS of velocity field.

Journal

Experiments in FluidsSpringer Journals

Published: May 6, 2016

References

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