Analysis of Turbulent Scalar Flux Models for a Discrete Hole Film Cooling Flow

Algebraic closures for the turbulent scalar fluxes were evaluated for a discrete hole film cooling geometry using the results from a high-fidelity Large Eddy Simulation (LES). Several models for the turbulent scalar fluxes exist, including the widely used Gradient Diffusion Hypothesis, the Generalized Gradient Diffusion Hypothesis, and the Higher Order Generalized Gradient Diffusion Hypothesis. By analyzing the results from the LES, it was possible to isolate the error due to these turbulent mixing models. Distributions of the turbulent diffusivity, turbulent viscosity, and turbulent Prandtl number were extracted from the LES results. It was shown that the turbulent Prandtl number varies significantly spatially, undermining the applicability of the Reynolds analogy for this flow. The LES velocity field and Reynolds stresses were fed into a RANS solver to calculate the fluid temperature distribution. This analysis revealed in which regions of the flow various modeling assumptions were invalid and what effect those assumptions had on the predicted temperature distribution.

[1]  T. Simon,et al.  Measurement of Eddy Diffusivity of Momentum in Film Cooling Flows With Streamwise Injection , 2000 .

[2]  Ken-ichi Abe,et al.  Towards the development of a Reynolds-averaged algebraic turbulent scalar-flux model , 2001 .

[3]  Gianluca Iaccarino,et al.  RANS modeling of turbulent mixing for a jet in supersonic cross flow: model evaluation and uncertainty quantification , 2012 .

[4]  Christopher J. Elkins,et al.  Turbulent transport in an inclined jet in crossflow , 2013 .

[5]  G. Iaccarino,et al.  Epistemic uncertainty quantification of RANS modeling for an underexpanded jet in a supersonic cross flow , 2011 .

[6]  S. Corrsin Limitations of Gradient Transport Models in Random Walks and in Turbulence , 1975 .

[7]  Julia Ling,et al.  Near Wall Modeling for Trailing Edge Slot Film Cooling , 2015 .

[8]  F. Bazdidi-Tehrani,et al.  Implicit algebraic model for predicting turbulent heat flux in film cooling flow , 2009 .

[9]  Cun-liang Liu,et al.  New development of the turbulent Prandtl number models for the computation of film cooling effectiveness , 2011 .

[10]  Hui-ren Zhu,et al.  Effect of turbulent Prandtl number on the computation of film-cooling effectiveness , 2008 .

[11]  Andrew T. Hsu,et al.  The effect of Schmidt number on turbulent scalar mixing in a jet-in-crossflow , 1999 .

[12]  J. K. Eaton,et al.  High-fidelity simulation of a turbulent inclined jet in a crossflow , 2013 .

[13]  Djamel Lakehal,et al.  Perspectives in Modeling Film Cooling of Turbine Blades by Transcending Conventional Two-Equation Turbulence Models , 2002 .

[14]  Francis H. Harlow,et al.  Transport Equations in Turbulence , 1970 .

[15]  Djamel Lakehal,et al.  Near-Wall Modeling of Turbulent Convective Heat Transport in Film Cooling of Turbine Blades With the Aid of Direct Numerical Simulation Data , 2002 .

[16]  A. D. Gosman,et al.  The Turbulent Jet in a Cross Stream at Low Injection Rates: a Three-Dimensional Numerical Treatment , 1978 .

[17]  Julia Ling,et al.  Experimentally informed optimization of turbulent diffusivity for a discrete hole film cooling geometry , 2013 .

[18]  David G. Bogard,et al.  Turbulent Transport in Film Cooling Flows , 2005 .

[19]  Jing Ren,et al.  Algebraic Anisotropic Turbulence Modeling of Compound Angled Film Cooling Validated by PIV and PSP Measurements , 2013 .