Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-18T21:51:33.911Z Has data issue: false hasContentIssue false
  • English
  • Français

On the performance of particle tracking

Published online by Cambridge University Press:  21 April 2006

Juan C. Agüí  and
J. Jiménez
Juan C. Agüí
Affiliation:
School of Aeronautics, Universidad Politécnica, 28040 Madrid, Spain
J. Jiménez
Affiliation:
IBM Scientific Centre, Paseo Castellana 4, 28046 Madrid, Spain and School of Aeronautics, Universidad Politécnica, 28040, Madrid, Spain
Get access Rights & Permissions [Opens in a new window]

Abstract

The sources of error associated with the use of particle-tracking techniques in the measurement of velocity and vorticity fields in moderately three-dimensional turbulent flows are analysed. The two dominant sources of error are the visualisation error, resulting from the limited resolution of the optical data acquisition system, and the sampling error, due to limited particle concentration. Their relative importance is discussed.

The performance of the interpolation methods used to translate the measurements from the positions of the particles to an arbitrary point is discussed, and a non-parametric algorithm is given to estimate the errors that arise, using only the available data. The smoothing of the results to produce flow maps of a given statistical significance is also discussed. Finally, the method is validated using simultaneous laser-Doppler velocity measurements.

The system is applied to measurements of the near wake of a circular cylinder. Velocity and vorticity maps are provided which throw light on the process by which the large eddies form and relax to their final equilibrium configurations.

Type
Research Article
Information
Journal of Fluid Mechanics , Volume 185 , December 1987 , pp. 447 - 468
Copyright
© 1987 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Agterberg, F. P. 1974 Geomathematics, pp. 352–356. Elsevier.
Cantwell, B. & Coles, D. 1983 An experimental study of entrainment and transport in the turbulent near wake of a circular cylinder. J. Fluid Mech. 136, 321–374.Google Scholar
Clayton, B. R. & Massey, B. S. 1967 Flow visualisation in water: a review of techniques. J. Sci. Instrum. 44, 2–11.Google Scholar
Davis, R. W. & Moore, E. F. 1982 A numerical study of vortex shedding from rectangles. J. Fluid Mech. 116, 475–506.Google Scholar
Diaconis, P. & Efron, B. 1983 Computer intensive methods in statistics. Sci. Am. 248 (5), 116–132.Google Scholar
Dimotakis, P. E., Debussy, F. D. & Koochesfahani, M. M. 1981 Particle streak velocity field measurements in a two dimensional mixing layer. Phys. Fluids 2, 995–999.Google Scholar
Efron, B. 1979a Bootstrap methods: another look at the Jacknife. Annls Statist. 7, 1–26.Google Scholar
Efron, B. 1979b Computers and the theory of statistics: thinking the unthinkable. SIAM Rev. 21, 460–480.Google Scholar
Efron, B. 1982 The Jacknife, the Bootstrap and other resampling schemes. CBMS-NSF Reg. Conf. Ser. in App. Math. vol. 38, pp. 29–36. SIAM.
Efron, B. 1983 Estimating the error rate of a prediction rule: improvement on cross-validation. J. Am. Statist. Assoc. 78, 316–331.Google Scholar
Emrich, R. J. 1981 Methods of Experimental Physics, vol. 18: Fluid Dynamics. Academic Press.
Freymuth, P., Bank, W. & Palmer, M. 1985 Further experimental evidence for vortex splitting. J. Fluid Mech. 152, 289–299.Google Scholar
Garabedian, P. R. 1964 Partial differential equations, pp. 485–492. Wiley.
Gerrard, J. H. 1966 The three-dimensional structure of the wake of a circular cylinder. J. Fluid Mech. 25, 143–164.Google Scholar
Hjelmfelt, A. T. & Mockros, L. F. 1966 Motion of discrete particles in a turbulent fluid. Appl. Sci. Res. 16, 149–161.Google Scholar
Hinze, J. O. 1959 Turbulence. McGraw-Hill.
Imaichi, K. & Ohmi, K. 1983 Numerical processing of flow-visualisation pictures: measurement of two-dimensional vortex flow. J. Fluid Mech. 129, 283–311.Google Scholar
Jian, L. & Schmitt, F. 1982 Water current determination by picture processing. In Proc. ICASSP 82. Paris, pp. 830–833. IEEE.
Jiménez, J. 1985 Some computational problems in computer-assisted flow visualisation. In Proc. Intl Symp. Compu. Fluid Dyn. Tokyo, pp. 145–156. Japan Soc. Comput. Fluid Dyn.
Jiménez, J. & Agüí, J. C. 1987 Approximate reconstruction of randomly sampled signals. Signal Proc. 12, 153–168.Google Scholar
Landau, L. D. & Lifshitz, E. M. 1959 Fluid Mechanics, p. 122. Pergamon.
Matheron, G. 1972 In Traite de Informatique Geologique (ed. P. Laffite), pp. 362–378. Masson.
Merzkirch, W. 1974 Flow Visualization. Academic.
Papailiou, D. D. & Lykoudis, P. S. 1974 Turbulent vortex streets and the entrainment mechanism of the turbulent wake. J. Fluid Mech. 62, 11–31.Google Scholar
Prandt, L. & Tietjens, O. 1934 Applied Hydro and Aerodynamics. Dover.
Schaefer, J. W. & Eskinazi, S. 1959 Analysis of the vortex street generated in a viscous fluid. J. Fluid Mech. 6, 241–260.Google Scholar
Sommerscales, E. F. C. 1980 Fluid velocity measurement by particle tracking. In Flow, its Measurement and Control in Science and Industry, vol. I (ed. R. E. Wendt), pp. 795–808. Instrum. Soc. Am.
Utami, T. & Ueno, T. 1984 Visualisation and picture processing of turbulent flow. Exp. Fluids 2, 25–32.Google Scholar
Utami, T. & Ueno, T. 1987 Experimental study of the coherent structure of turbulent open channel flow using visualization and picture processing. J. Fluid Mech. 174, 399–440.Google Scholar
Werlé, H. 1973 Hydrodynamic flow visualisation. Ann. Rev. Fluid Mech. 5, 361–382.Google Scholar