Transport Phenomena and Fluid Mechanics

Direct numerical simulation of the turbulent flow in a baffled tank driven by a Rushton turbine

  1. J. J. J. Gillissen*,
  2. H. E. A. Van den Akker

Article first published online: 12 MAR 2012

DOI: 10.1002/aic.13762

Issue

AIChE Journal

AIChE Journal

Volume 58, Issue 12, pages 3878–3890, December 2012

Additional Information

How to Cite

Gillissen, J. J. J. and Van den Akker, H. E. A. (2012), Direct numerical simulation of the turbulent flow in a baffled tank driven by a Rushton turbine. AIChE J., 58: 3878–3890. doi: 10.1002/aic.13762

Author Information

  1. Dept. of Chemical Engineering, Delft University of Technology, Leeghwaterstraat 39, 2628 CB Delft, the Netherlands

*Dept. of Chemical Engineering, Delft University of Technology, Leeghwaterstraat 39, 2628 CB Delft, the Netherlands

Publication History

  1. Issue published online: 8 NOV 2012
  2. Article first published online: 12 MAR 2012
  3. Accepted manuscript online: 25 JAN 2012 11:11AM EST
  4. Manuscript Revised: 29 DEC 2011
  5. Manuscript Received: 3 NOV 2011

Funded by

  • Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Netherlands Organization for Scientific Research, NWO)

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Keywords:

  • computational fluid dynamics;
  • fluid mechanics;
  • mathematical modeling;
  • mixing;
  • turbulence

Abstract

We present a direct numerical simulation (DNS) of the turbulent flow in a baffled tank driven by by a Rushton turbine. The DNS is compared to a Large Eddy Simulation (LES), a Reynolds Averaged Navier-Stokes (RANS) simulation, Laser Doppler Velocimetry data, and Particle Image Velocimetry data from the literature. By Reynolds averaging the DNS-data, we validate the turbulent viscosity hypothesis by demonstrating strong alignment between the Reynolds stress and the mean strain rate. Although the turbulent viscosity νT in the DNS is larger than in the RANS simulation, the turbulent viscosity parameter Cμ = νTϵ/k2, is an order of magnitude smaller than the standard 0.09 value of the k-ϵ model. By filtering the DNS-data, we show that the Smagorinsky constant CS is uniformly distributed over the tank with CS ≈ 0.1. Consequently, the dynamic Smagorisnky model does not improve the accuracy of the LES. © 2012 American Institute of Chemical Engineers AIChE J, 2012

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