Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-09T06:40:30.512Z Has data issue: false hasContentIssue false
  • English
  • Français

Non-equilibrium scaling laws in axisymmetric turbulent wakes

Published online by Cambridge University Press:  16 September 2015

T. Dairay ,
M. Obligado Open the ORCID record for M. Obligado [Opens in a new window]  and
J. C. Vassilicos
T. Dairay
Affiliation:
Turbulence, Mixing and Flow Control Group, Department of Aeronautics, Imperial College London, London SW7 2AZ, UK
M. Obligado
Affiliation:
Turbulence, Mixing and Flow Control Group, Department of Aeronautics, Imperial College London, London SW7 2AZ, UK
J. C. Vassilicos*
Affiliation:
Turbulence, Mixing and Flow Control Group, Department of Aeronautics, Imperial College London, London SW7 2AZ, UK
*
†Email address for correspondence: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

We present a combined direct numerical simulation and hot-wire anemometry study of an axisymmetric turbulent wake. The data lead to a revised theory of axisymmetric turbulent wakes which relies on the mean streamwise momentum and turbulent kinetic energy equations, self-similarity of the mean flow, turbulent kinetic energy, Reynolds shear stress and turbulent dissipation profiles, non-equilibrium dissipation scalings and an assumption of constant anisotropy. This theory is supported by the present data up to a distance of 100 times the wake generator’s size, which is as far as these data extend.

JFM classification

Turbulent Flows: Turbulence simulation Turbulent Flows: Turbulence theory Wakes/Jets: Wakes
Type
Papers
Information
Journal of Fluid Mechanics , Volume 781 , 25 October 2015 , pp. 166 - 195
Copyright
© 2015 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

Bevilaqua, P. M. & Lykoudis, P. S. 1978 Turbulence memory in self-preserving wakes. J. Fluid Mech. 89 (3), 589–606.CrossRefGoogle Scholar
Brown, G. L. & Roshko, A. 2012 Turbulent shear layers and wakes. J. Turbul. 13, N51.CrossRefGoogle Scholar
George, W. K. 1989 The self-preservation of turbulent flows and its relation to initial conditions and coherent structures. In Advances in Turbulence (ed. George, W. K. & Arndt, R.), Springer.Google Scholar
Goto, S. & Vassilicos, J. C. 2015 Energy dissipation and flux laws for unsteady turbulence. Phys. Lett. A 379, 1144–1148.CrossRefGoogle Scholar
Gourlay, M. J., Arendt, S. C., Fritts, D. C. & Werne, J. 2001 Numerical modeling of initially turbulent wakes with net momentum. Phys. Fluids 13 (12), 3783–3802.CrossRefGoogle Scholar
Johansson, P. B. V., George, W. K. & Gourlay, M. J. 2003 Equilibrium similarity, effects of initial conditions and local Reynolds number on the axisymmetric wake. Phys. Fluids 15 (3), 603–617.CrossRefGoogle Scholar
Kravchenko, A. G. & Moin, P. 1997 On the effect of numerical errors in large eddy simulation of turbulent flows. J. Comput. Phys. 131, 310–322.CrossRefGoogle Scholar
Laizet, S. & Lamballais, E. 2009 High-order compact schemes for incompressible flows: a simple and efficient method with quasi-spectral accuracy. J. Comput. Phys. 228, 5989–6015.CrossRefGoogle Scholar
Laizet, S., Lamballais, E. & Vassilicos, J. C. 2010 A numerical strategy to combine high-order schemes, complex geometry and parallel computing for high resolution DNS of fractal generated turbulence. Comput. Fluids 39 (3), 471–484.CrossRefGoogle Scholar
Laizet, S. & Li, N. 2011 Incompact3d: a powerful tool to tackle turbulence problems with up to $O(10^{5})$ computational cores. Intl J. Numer. Meth. Fluids 67 (11), 1735–1757.CrossRefGoogle Scholar
Laizet, S., Nedić, J. & Vassilicos, J. C. 2015 Influence of the spatial resolution on fine-scale features in DNS of turbulence generated by a single square grid. Intl J. Comput. Fluid Dyn. 29 (3–5), 286–302.CrossRefGoogle Scholar
Lamballais, E., Fortuné, V. & Laizet, S. 2011 Straightforward high-order numerical dissipation via the viscous term for direct and large eddy simulation. J. Comput. Phys. 230, 3270–3275.CrossRefGoogle Scholar
Lele, S. K. 1992 Compact finite difference schemes with spectral-like resolution. J. Comput. Phys. 103, 16–42.CrossRefGoogle Scholar
Nedic, J.2013 Fractal-generated wakes. PhD thesis, Imperial College London.Google Scholar
Nedić, J., Ganapathisubramani, B. & Vassilicos, J. C. 2013a Drag and near wake characteristics of flat plates normal to the flow with fractal edge geometries. Fluid Dyn. Res. 45 (6), 061406.CrossRefGoogle Scholar
Nedić, J., Vassilicos, J. C. & Ganapathisubramani, B. 2013b Axisymmetric turbulent wakes with new nonequilibrium similarity scalings. Phys. Rev. Lett. 111 (14), 144503.CrossRefGoogle ScholarPubMed
Parnaudeau, P., Carlier, J., Heitz, D. & Lamballais, E. 2008 Experimental and numerical studies of the flow over a circular cylinder at Reynolds number 3900. Phys. Fluids 20 (8), 085101.CrossRefGoogle Scholar
Pope, S. B. 2000 Turbulent Flows. Cambridge University Press.CrossRefGoogle Scholar
Redford, J. A., Castro, I. P. & Coleman, G. N. 2012 On the universality of turbulent axisymmetric wakes. J. Fluid Mech. 710, 419–452.CrossRefGoogle Scholar
de Stadler, M. B., Rapaka, N. R. & Sarkar, S. 2014 Large eddy simulation of the near to intermediate wake of a heated sphere at $\mathit{Re}=10\,000$ . Intl J. Heat Transfer Fluid Flow 49, 2–10.CrossRefGoogle Scholar
Tennekes, H. & Lumley, J. L. 1972 A First Course in Turbulence. MIT Press.CrossRefGoogle Scholar
Townsend, A. A. 1976 The Structure of Turbulent Shear Flow. Cambridge University Press.Google Scholar
Vassilicos, J. C. 2015 Dissipation in turbulent flows. Annu. Rev. Fluid Mech. 47, 95–114.CrossRefGoogle Scholar