Skip to main content
    • Aa
    • Aa
  • Get access
    Check if you have access via personal or institutional login
  • Cited by 95
  • Cited by
    This article has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Nieckele, A. O. Thompson, R. L. and Mompean, G. 2016. Anisotropic Reynolds stress tensor representation in shear flows using DNS and experimental data. Journal of Turbulence, Vol. 17, Issue. 6, p. 602.

    Wang, Limin Qiu, Xiaoping Zhang, Lin and Li, Jinghai 2016. Turbulence originating from the compromise-in-competition between viscosity and inertia. Chemical Engineering Journal, Vol. 300, p. 83.

    Yamamoto, Yoshinobu and Kunugi, Tomoaki 2016. MHD effects on turbulent dissipation process in channel flows with an imposed wall-normal magnetic field. Fusion Engineering and Design,

    van Reeuwijk, Maarten and Hadžiabdić, Muhamed 2015. Modelling high Schmidt number turbulent mass transfer. International Journal of Heat and Fluid Flow, Vol. 51, p. 42.

    Chattopadhyay, Kinnor and Guthrie, Roderick I.L. 2014. Treatise on Process Metallurgy.

    Karimpour, Farid and Venayagamoorthy, Subhas K. 2014. A revisit of the equilibrium assumption for predicting near-wall turbulence. Journal of Fluid Mechanics, Vol. 760, p. 304.

    El Gharbi, Najla Absi, Rafik and Benzaoui, Ahmed 2013. Numerical investigation toward improving heat-transfer predictions in a turbulent channel flow. International Journal of Thermal Sciences, Vol. 70, p. 10.

    Gatski, Thomas B. and Bonnet, Jean-Paul 2013. Compressibility, Turbulence and High Speed Flow.

    Kaiser, Bryan Poroseva, Svetlana Johnson, Erick L. and Hovsapian, Rob 2013. 31st AIAA Applied Aerodynamics Conference.

    Rastgou, H. and Saedodin, S. 2013. Numerical simulation of an axisymmetric separated and reattached flow over a longitudinal blunt circular cylinder. Journal of Fluids and Structures, Vol. 42, p. 13.

    Sookhak Lari, Kaveh van Reeuwijk, Maarten and Maksimović, Čedo 2013. The role of geometry in rough wall turbulent mass transfer. Heat and Mass Transfer, Vol. 49, Issue. 8, p. 1191.

    Wu, Xin Ju, Ping and Wu, Feng 2013. A mixed-time-scale low-Reynolds-number one-equation turbulence model. Journal of Turbulence, Vol. 14, Issue. 4, p. 55.

    2013. Compressibility, Turbulence and High Speed Flow.

    Billard, F. and Laurence, D. 2012. A robust k−ε−/k elliptic blending turbulence model applied to near-wall, separated and buoyant flows. International Journal of Heat and Fluid Flow, Vol. 33, Issue. 1, p. 45.

    Balabel, A. and El-Askary, W.A. 2011. On the performance of linear and nonlinear turbulence models in various jet flow applications. European Journal of Mechanics - B/Fluids, Vol. 30, Issue. 3, p. 325.

    Borello, Domenico and Orlandi, Paolo 2011. DNS Scrutiny of the ζ-f Elliptic-Relaxation Eddy-Viscosity Model in Channel Flows with a Moving Wall. Flow, Turbulence and Combustion, Vol. 86, Issue. 2, p. 295.

    Chattopadhyay, K. Isac, M. and Guthrie, R. I. L. 2010. Applications of Computational Fluid Dynamics (CFD) in iron- and steelmaking: Part 1. Ironmaking & Steelmaking, Vol. 37, Issue. 8, p. 554.

    Menter, F. R. and Egorov, Y. 2010. The Scale-Adaptive Simulation Method for Unsteady Turbulent Flow Predictions. Part 1: Theory and Model Description. Flow, Turbulence and Combustion, Vol. 85, Issue. 1, p. 113.

    FREWER, MICHAEL 2009. Proper invariant turbulence modelling within one-point statistics. Journal of Fluid Mechanics, Vol. 639, p. 37.

    Golovnya, B.P. 2009. Modeling of the fluctuating component in the form of the sum of an infinite number of random quantities. Part 1: k–ε Modeling. International Journal of Heat and Mass Transfer, Vol. 52, Issue. 21-22, p. 5218.

  • Journal of Fluid Mechanics, Volume 250
  • May 1993, pp. 509-529

Low Reynolds number k—ε modelling with the aid of direct simulation data

  • W. Rodi (a1) and N. N. Mansour (a2)
  • DOI:
  • Published online: 01 April 2006

The constant Cμ and the near-wall damping function fμ in the eddy-viscosity relation of the k–ε model are evaluated from direct numerical simulation (DNS) data for developed channel and boundary-layer flow, each at two Reynolds numbers. Various existing fμ model functions are compared with the DNS data, and a new function is fitted to the high-Reynolds-number channel flow data. The ε-budget is computed for the fully developed channel flow. The relative magnitude of the terms in the ε-equation is analysed with the aid of scaling arguments, and the parameter governing this magnitude is established. Models for the sum of all source and sink terms in the ε-equation are tested against the DNS data, and an improved model is proposed.

Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Journal of Fluid Mechanics
  • ISSN: 0022-1120
  • EISSN: 1469-7645
  • URL: /core/journals/journal-of-fluid-mechanics
Please enter your name
Please enter a valid email address
Who would you like to send this to? *