International Journal of Rotating Machinery

International Journal of Rotating Machinery / 1995 / Article

Open Access

Volume 2 |Article ID 857591 | 8 pages | https://doi.org/10.1155/S1023621X95000200

Prediction of Heat Transfer For Turbulent Flow in Rotating Radial Duct

Received09 Aug 1995

Abstract

The objective of the current modeling effort is to validate the numerical model and improve upon the prediction of heat transfer in rotating systems. Low-Reynolds number turbulence model (without the wall function) has been employed for three-dimensional heat transfer predictions for radially outward flow in a square cooling duct rotating about an axis perpendicular to its length. Computations are also made using the standard and extended high-Reynolds number kturbulence models (in conjunction with the wall function) for the same flow configuration. The results from all these models are compared with experimental data for flows at different rotation numbers and Reynolds number equal to 25,000. The results show that the low-Reynolds number model predictions are not as good as the high-Re model predictions with the wall function. The wall function formulation predicts the right trend of heat transfer profile and the agreement with the data is within 30% or so for flows at high rotation number. Since the Navier-Stokes equations are integrated all the way to wall in the case of low-Re model, the computation time is relatively high and the convergence is rather slow, thus rendering the low-Re model as an unattractive choice for rotating flows at high Reynolds number.The extended k-ε turbulence model is also employed to compute heat transfer for rotating flows with uneven wall temperatures and uniform wall heat flux conditions. The comparison with the experimental data available in literature shows that the predictions on both the leading wall and the trailing wall are satisfactory and within 5-25% agreement.

Copyright © 1995 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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