Acceleration of Tomo-PIV by estimating the initial volume intensity distribution

Acceleration of Tomo-PIV by estimating the initial volume intensity distribution Tomographic particle image velocimetry (Tomo-PIV) is a promising new PIV technique. However, its high computational costs often make time-resolved measurements impractical. In this paper, a new preprocessing method is proposed to estimate the initial volume intensity distribution. This relatively inexpensive “first guess” procedure significantly reduces the computational costs, accelerates solution convergence, and can be used directly to obtain results up to 35 times faster than an iterative reconstruction algorithm (with only a slight accuracy penalty). Reconstruction accuracy is also assessed by examining the errors in recovering velocity fields from artificial data (rather than errors in the particle reconstructions themselves). http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Experiments in Fluids Springer Journals

Acceleration of Tomo-PIV by estimating the initial volume intensity distribution

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Publisher
Springer-Verlag
Copyright
Copyright © 2008 by Springer-Verlag
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/s00348-008-0504-6
Publisher site
See Article on Publisher Site

Abstract

Tomographic particle image velocimetry (Tomo-PIV) is a promising new PIV technique. However, its high computational costs often make time-resolved measurements impractical. In this paper, a new preprocessing method is proposed to estimate the initial volume intensity distribution. This relatively inexpensive “first guess” procedure significantly reduces the computational costs, accelerates solution convergence, and can be used directly to obtain results up to 35 times faster than an iterative reconstruction algorithm (with only a slight accuracy penalty). Reconstruction accuracy is also assessed by examining the errors in recovering velocity fields from artificial data (rather than errors in the particle reconstructions themselves).

Journal

Experiments in FluidsSpringer Journals

Published: Jun 8, 2008

References

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