Skip to main content
Log in

Turbulent kinetic energy estimate in the near wall region of smooth turbulent channel flows

  • Published:
Meccanica Aims and scope Submit manuscript

Abstract

Turbulent kinetic energy (TKE) equation based on the Reynolds averaging hypothesis was approximated in the near wall region of turbulent channel flows and an analytical solution for TKE was proposed by Absi for \(y^{ + } < 20\) (R. Absi, Analytical solutions for the modeled k equation, Trans. ASME: J. Appl. Mech. 75 (2008) 044,501). While, comparisons with DNS data show very good agreement, some of the model approximations employed previously require revision which is the main motivation of this work. We here present an alternate formulation for the smooth near wall TKE budget and propose an improved method of solution. Results are compared against wide range of friction Reynolds numbers, Reτ DNS datasets and found to be in good agreement. Interestingly the proposed improved method reveals that beyond Reτ, = 5200 TKE profiles collapse meaning that the TKE remains independent of Reτ that is consistent with high Reynolds number turbulent characteristics reported in the DNS (Hultmark et. al., Turbulent pipe flow at extreme Reynolds numbers, Phys. Rev. Lett., 108 (2012) 094,501). Although there exist two parameters in the paresent work to be determined empirically from DNS data it is reported that these parameters become empirically free at high turbulent Reynolds numbers, Reτ → ∞.The other interesting aspect of this work is that one of these parameters may be sensitized to other additional effects viz., wall roughness, pressure gradient, magnetic field, etc. One of the potential advantages of these near wall smooth turbulent channel flow analytical solutions is to obviate the need for solving the TKE equation near the smooth wall in the RANS, hybrid RANS/LES closures thus resulting in quicker and accurate engineering computations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Abbreviations

C G C ε :

Constant coefficients in turbulent production and dissipation terms.

C ν t :

Proportionality constant, Eq. (11)

G :

Turbulent energy production

h :

Dimensional flow scale

k :

Dimensional turbulent kinetic energy

k+(=k/u2):

Dimensional turbulent length scale

L :

Dimensional turbulent length scale

l+(=lu./v2):

Dimensionaless turbulent length scale

L :

Geometrical length scale

Re τ(=(u*L)v):

Reynold number based on friction velocity

u’ :

Dimensional fluctuating velocity

u(=(τ0/ρ)’1/2):

friction velocity

y :

Dimensionl wall normal coordinate

y + :

Dimensionless wall normal coordinate

ε :

Dimensional turbulent energy dissipation

ε+(=εv/u*4):

Dimensionaless turbulent energy dissipation

k:

VonKarman constant

v, :

Kinematic viscosity

v t :

Turbulent or eddy viscosity

ρ :

Fluid density

τo :

Wall shear stress

References

  1. Pope SB (2000) Turbulent Flows. Cambridge University Press, Cambridge, UK

    Book  Google Scholar 

  2. W. Rodi and M. Mulas (Ed.), Engineering Turbulence Modelling and Experiments, 6th Proc. ERCOFTAC Int. Symp. Engg. Turb Mod. Measurements; ETMM6, (2005) 23–25.

  3. Hanjalic K (2005) Will RANS survive LES? a view of perspectives. Trans ASME: J Fluids Eng 127(2005):831–840

    Google Scholar 

  4. G. Alfonsi, Reynolds-Averaged Navier–Stokes Equations for Turbulence Modeling, Trans. ASME: Appl. Mech. Rev. 62 (2009) 040802.

  5. Chaouat B (2017) The state of the art of hybrid RANS/LES modeling for the simulation of turbulent flows. Flow Turbulence Combust 99:279–327

    Article  Google Scholar 

  6. Hahn M, Drikakis D (2009) Implicit large-eddy simulation of swept wing flow using high-resolution methods. AIAA J 47:618–629

    Article  Google Scholar 

  7. Wolfstein M (1967) The velocity and temperature distribution of one-dimensional flow with turbulence augmentation and pressure gradient. Int J Heat Mass Transfer 12:301–318

    Article  Google Scholar 

  8. P.A. Durbin, Limiters and wall treatments in applied turbulence modeling, Fluid Dyn. Res. 41 (2009) 012203.

  9. Spalding DB (1967) Heat transfer from turbulent separated flows. J Fluid Mech 27:97–109

    Article  Google Scholar 

  10. Hanjalic K, Launder BE (1976) Contribution towards a Reynolds-stress closure for low Reynolds number turbulence. J Fluid Mech 74:593–610

    Article  Google Scholar 

  11. I. Nezu, H. Nakagawa, Turbulence in open channel flows, A.A. Balkema (Ed.), Rotterdam, The Netherlands, 1993.

  12. J.J..H Brouwers, (2007) Dissipation equals production in the log layer of wall-induced turbulence, Phys. Fluids 19 101702.

  13. R. Absi, Analytical solutions for the modeled k equation, Trans. ASME: J. Appl. Mech. 75 (2008) 044501.

  14. Absi R (2009) A simple eddy viscosity formulation for turbulent boundary layers near smooth walls. CR Mec 337:158–165

    Article  Google Scholar 

  15. El Gharbi N, Absi R, Benzaoui A (2012) Effect of different near-wall treatments on indoor airflow simulations. J Appl Fluid Mech 5:63–70

    Google Scholar 

  16. Qi M, Li J, Chen Q, Zhang Q (2018) Roughness effects on near-wall turbulence modelling for open-channel flows. J Hydraulic Research 56:648–661

    Article  Google Scholar 

  17. Absi R (2019) Eddy viscosity and velocity profiles in fully-developed turbulent channel flows. Fluid Dyn 54:137–147

    Article  Google Scholar 

  18. M. Heisel, G.G. Katul, M. Chamecki and M. Guala, Velocity asymmetry and turbulent transport closure in smooth- and rough-wall boundary layers, Phys. Rev. Fluids, 5 (2020), 104605.

  19. S. Hoyas, J. Jiménez, Scaling of the velocity fluctuations in turbulent channels up to Reτ =2003, Phys. Fluids 18 (2006) 011702.

  20. M. Vallikivi1, M. Hultmark1 and A. J. Smits, Turbulent boundary layer statistics at very high Reynolds number, J. Fluid Mech. 779 (2015), 371–389.

  21. Ji CN, Munjiza A, Avital E, Ma J, J.J.R. (2013) Williams, Direct numerical simulation of sediment entrainment in turbulent channel flow, Phy. Fluids 25:1883–1897

    Google Scholar 

  22. Statistics from DNS of turbulent channel flow in very large boxes, Reτ = 180–550–950–2000–5000, http://turbulence.oden.utexas.edu/

  23. Moser RD, Kim J, Mansour NN (1999) DNS of turbulent channel flow up to reτ =590. Phys Fluids 11:943–945

    Article  Google Scholar 

  24. del Alamo JC, Jimenez J (2003) Spectra of the very large anisotropic scales in turbulent channels. Phys Fluids 15:L41–L44

    Article  Google Scholar 

  25. J.C. del Alamo, J. Jimenez, (2001) Direct numerical simulation of the very large anisotropic scales in a turbulent channel, Center for Turbulence Research Annual Research Briefs. Stanford University, 329–341.

  26. del Alamo JC, Jimenez J, Zandonade P, Moser RD (2004) Scaling of the energy spectra of turbulent channels. J Fluid Mech 500:135–144

    Article  Google Scholar 

  27. Monty JP, Hutchins N, Ng HGH, Marusic I, Chong MS (2009) A comparison of turbulent pipe, channel and boundary layer flows. J Fluid Mech 632:431–442

    Article  Google Scholar 

  28. Hultmark M, Vallikivi M, Bailey SCC, Smits AJ (2012) Turbulent pipe flow at extreme Reynolds numbers. Phys. Rev. Lett. 108:094501

    Article  Google Scholar 

  29. Superpipe Turbulence Data, Princeton University, https://smits.princeton.edu/superpipe-turbulence-data/

  30. Rahman MM, Siikonen T, T (2005) An eddy viscosity model with near-wall modifications. Int. J. Num. Meth. Fluids 49:975–997

    Article  MathSciNet  Google Scholar 

  31. Schlatter P, Örlu R (2010) Assessment of direct numerical simulation data of turbulent boundary layers. J Fluid Mech 659:116–126

    Article  Google Scholar 

  32. Patel VC, Rodi W, Scheuerer G (1985) Turbulence models for near-wall and low Reynolds numbers flows: a review. AIAA J 23:1308–1319

    Article  MathSciNet  Google Scholar 

  33. R. Absi, (2019) Discussion of “Roughness effects on near-wall turbulence modelling for open-channel flows By M. Qi, J. Li, Q. Chen and Q. Zhang”, J. Hydraulic Research, 57, 744–746.

Download references

Acknowledgements

We thank Drs John Kim, Parviz Moin, Nagi N. Mansour, A.J. Smits, S. Hoyas, J. Jimenez, R. D. Moser, J.-C. del Alamo, P. S. Zandonade, P. Schlatter and R Örlu for producing and publishing the DNS flow fields online.

Funding

No funding was received.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kannan Sundaravadivelu.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendix 1

Equation (13) can be rewritten as

$$\frac{\partial }{{\partial y^{ + } }}\left( {C_{{\nu t}} y^{ + } \left( {1 - e^{{ - \frac{{y^{ + } }}{{A_{3}^{ + } }}^{ + } }} } \right)^{2} \frac{{\partial k^{ + } }}{{\partial y^{ + } }}} \right) = \lambda C_{{\nu t}} y^{ + } \left( {1 - e^{{ - \frac{{y^{ + } }}{{A_{3}^{ + } }}^{ + } }} } \right)^{2} \left( {\frac{{\partial U^{ + } }}{{\partial y^{ + } }}} \right)^{2} e^{{\left( { - \frac{{y^{ + } }}{{2\text{Re} _{\tau }^{\alpha } }}} \right)}}$$
(A1)

Retaining only the leading order terms in Eq. (A1), we have

$$\frac{\partial }{{\partial y^{ + } }}\left( {y^{{ + 3}} \frac{{\partial k^{ + } }}{{\partial y^{ + } }}} \right) = \lambda y^{{ + 3}} \left( {\frac{{\partial U^{ + } }}{{\partial y^{ + } }}} \right)^{2} e^{{\left( { - \frac{{y^{ + } }}{{2\text{Re} _{\tau }^{\alpha } }}} \right)}}$$
(A2)

With \(U^{ + } = y^{ + }\) and \(A_{3}^{ + } = 2\text{Re} _{\tau }^{\alpha }\), Eq. (A2) is written as

$$\frac{\partial }{{\partial y^{ + } }}\left( {y^{{ + 3}} \frac{{\partial k^{ + } }}{{\partial y^{ + } }}} \right) = \lambda \sum\limits_{0}^{\infty } {\frac{{\left( { - 1} \right)^{n} \left( {A_{3} ^{{ + - 1}} } \right)^{3} }}{{n!}}} y^{{ + (n + 3)}}$$
(A3)

Integrating (A3) we get

$$y^{{ + 3}} \frac{{\partial k^{ + } }}{{\partial y^{ + } }} = \lambda \sum\limits_{0}^{\infty } {\frac{{\left( { - 1} \right)^{n} \left( {A_{3} ^{{ + - 1}} } \right)^{3} }}{{n!(n + 4)}}} y^{{ + (n + 4)}} + C1$$
(A4)

where the integration constant C1 = 0 because \(\frac{{dk^{ + } }}{{dy^{ + } }} = 0\) at y+ = 0. Integrating (A4) we get

$$k^{ + } = y^{{ + 2}} \sum\limits_{0}^{\infty } {\frac{\lambda }{{(n + 2)(n + 4)}}\frac{{\left( { - 1} \right)^{n} \left( {A_{3} ^{{ + - 1}} } \right)^{n} }}{{n!}}} y^{{ + n}} + C2$$
(A5)

where the integration constant C2 = 0 because \(k^{ + } = 0\) at y+ = 0. Since α appearing in \(A_{3}^{ + } = 2\text{Re} _{\tau }^{\alpha }\) is to be determined empirically from DNS, we may safely assume \(\frac{\lambda }{{(n + 2)(n + 4)}}\) to be a constant for simplicity which otherwise will lead to a higher order polynomial expression for k+. Even with a higher order polynomial solution for k+ the corresponding polynomial coefficients have to be fitted empirically through measurements that will simply make the computations laborious. Hence it is better to assume \(\frac{\lambda }{{(n + 2)(n + 4)}}\) to be a single constant.

Therefore Eq. (A5) finally takes the form.

$$k^{ + } = By^{{ + 2}} e^{{ - \left( {\frac{{y^{ + } }}{{A_{3} ^{ + } }}} \right)}}$$
(A6)

where B = \(\frac{\lambda }{{(n + 2)(n + 4)}}\) = 0.17 and \(\alpha (\text{Re} _{\tau } ) = 0.4147\text{Re} _{\tau } ^{{ - 0.11}}\).

Appendix 2

Equation (11a) is

$$i.e,\;\;\nu _{t}^{{}} = C_{{\nu t}} v^{'} {\text{ }}l$$
(A7)

Approximating \(v^{'} \sim \sqrt k\) and using normalised variables \({\text{ }}k^{ + } = k/u_{*}^{2}\), \({\text{ }}\nu _{{\text{t}}}^{ + } = \nu _{t} /\nu\),\({\text{ }}l^{ + } = lu_{*} /\nu\), Eq. (A7) can be rewritten as

$$\nu _{t}^{ + } = {\text{C}}_{{\nu {\text{t}}}} {\text{ }}\sqrt {k^{ + } } {\text{ }}l^{ + }$$
(A8)

Employing the near wall van driest damping function \(l^{ + } = \kappa y^{ + } \left( {1 - e^{{ - \frac{y}{{A_{d} ^{ + } }}^{ + } }} } \right)\)(Pope [1]), Eq. (A8) becomes

$$\nu _{t}^{ + } = {\text{C}}_{{\nu {\text{t}}}} {\text{ }}\kappa \sqrt {k^{ + } } {\text{ }}y^{ + } \left( {1 - e^{{ - \frac{y}{{A_{d} ^{ + } }}^{ + } }} } \right)$$
(A9)
$$i.e.,\;\;\;\nu _{t}^{ + } = {\text{C}}_{{\nu {\text{t}}}} {\text{ }}\kappa {\text{ }}(b^{ + } y^{ + } ){\text{ }}y^{ + } \left( {1 - e^{{ - \frac{{y^{ + } }}{{A_{d} ^{ + } }}}} } \right),$$
(A10)

\({\text{where }}\sqrt {{\text{k}}^{ + } } = b^{ + } y^{ + } {\text{,}}\) in the leading order near the wall, Pope [1].

\({\text{Writing, }}b^{ + } y^{ + } \sim \left( {1 - e^{{ - \frac{{y^{ + } }}{{A_{d} ^{ + } }}}} } \right){\text{ with }}b^{ + } = \frac{1}{{A_{d} ^{ + } }} < < 1,\) Eq. (A10) becomes

$$\nu _{t}^{ + } = {\text{C}}_{{\nu {\text{t}}}} {\text{ }}\kappa {\text{ }}y^{ + } \left( {1 - e^{{ - \frac{{y^{ + } }}{{A_{d} ^{ + } }}}} } \right)^{2}$$
(A11)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sundaravadivelu, K., Absi, R. Turbulent kinetic energy estimate in the near wall region of smooth turbulent channel flows. Meccanica 56, 2533–2545 (2021). https://doi.org/10.1007/s11012-021-01396-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11012-021-01396-2

Keywords

Navigation