Experiments in Fluids

, 45:847 | Cite as

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

  • N. A. Worth
  • T. B. Nickels
Research Article


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).


Particle Image Velocimetry Seeding Density Camera Angle Ghost Particle Tomographic Particle Image Velocimetry 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The first author wishes to acknowledge funding from the Engineering and Physical Sciences Research Council, through a Cambridge University Doctoral Training Award.


  1. Elsinga G, Scarano F, Wieneke B, van Oudheusden B (2006) Tomographic particle image velocimetry. Exp Fluids 41:933–947CrossRefGoogle Scholar
  2. Elsinga G, Kuik D, van Oudheusden B, Scarano F (2007) Investigation of the three-dimensional coherent structures in a turbulent boundary layer with Tomographic-PIV. In: 45th AIAA Aerospace Sciences Meeting and Exhibit, Reno, NevadaGoogle Scholar
  3. Herman G (1980) Image reconstruction from projections: the fundamentals of computerized tomography. Academic Press, LondonzbMATHGoogle Scholar
  4. Herman G, Lent A (1976) Iterative reconstruction algorithms. Comput Biol Med 6:273–294CrossRefGoogle Scholar
  5. Hinsch K (2002) Holographic particle image velocimetry. Meas Sci Technol 13:R61–R72CrossRefGoogle Scholar
  6. Hori T, Sakakibara J (2004) High-speed scanning stereoscopic PIV for 3D vorticity measurement in liquids. Meas Sci Technol 15:1067–1078CrossRefGoogle Scholar
  7. Maas H, Gruen A, Papantoniou D (2004) Particle tracking velocimetry in three-dimensional flows. Exp Fluids 15:133–146Google Scholar
  8. Natterer F (1999) Numerical methods in tomography. Acta Numer 8:107–142MathSciNetCrossRefGoogle Scholar
  9. Schröder A, Geisler R, Elsinga G, Scarano F, Dierksheide U (2006) Investigation of a turbulent spot using time-resolved tomographic PIV. In: 13th international symposium on applications of laser techniques to fluid mechanics, Lisbon, PortugalGoogle Scholar
  10. Wieneke B, Taylor S (2006) Fat-sheet PIV with computation of full 3D-strain tensor using tomographic reconstruction. In: 13th international symposium on applications of laser techniques to fluid mechanics, Lisbon, PortugalGoogle Scholar
  11. Willert CE, Gharib M (1992) Three-dimensional particle imaging with a single camera. Exp Fluids 12:353–358CrossRefGoogle Scholar
  12. Worth N, Nickels T (2007) A computational study of tomographic reconstruction accuracy and the effects of particle blocking. In: 5th joint ASME/JSME fluids engineering conference, San DiegoGoogle Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  1. 1.Department of EngineeringCambridge UniversityCambridgeUK

Personalised recommendations