Reynolds averaged simulation of flow and heat transfer in ribbed ducts

The accuracy of modern eddy-viscosity type turbulence models in predicting turbulent flows and heat transfer in complex passages is investigated. The particular geometries of interest here are those related to turbine blade cooling systems. This paper presents numerical data from the calculation of the turbulent flow field and heat transfer in two-dimensional (2D) cavities and threedimensional (3D) ribbed ducts. It is found that heat transfer predictions obtained using the v 2 –f turbulence model for the 2D cavity are in good agreement with experimental data. However, there is only fair agreement with experimental data for the 3D ribbed duct. On the wall of the duct where ribs exist, predicted heat transfer agrees well with experimental data for all configurations (different streamwise rib spacing and the cavity depth) considered in this paper. But heat transfer predictions on the smooth-side wall do not concur with the experimental data. Evidence is provided that this is mainly due to the presence of strong secondary flow structures which might not be properly simulated with turbulence models based on eddy viscosity. 2002 Elsevier Science Inc. All rights reserved. Accurate evaluation of heat loads in the components of a gas-turbine engine is a key factor in the development of new, efficient engines. Common design techniques utilize experimental data correlations to quickly estimate the heat transfer coefficients (Webb et al., 1971). These methods do not reveal the underlying mechanism of turbulence and heat transfer for the device in question. They often are inaccurate. Owing to advances in available computer resources, elaborate numerical techniques, based on the solution of the full 3D Reynolds averaged Navier–Stokes (RANS) equations, are now being used to shed light on the flow phenomena and to provide guidelines to improve design methodology. In the RANS approach, the Navier– Stokes equations are averaged and the Reynolds stresses are computed with a turbulence model. The choice of turbulence model is crucial, as it directly affects the computational requirements and the accuracy of the

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