There is an increasing interest in design methods and performance prediction for aircraft engine turbines operating at low Reynolds numbers. In this regime, boundary layer separation may be more likely to occur in the turbine flow passages. For accurate computational fluid dynamics (CFD) predictions of the flow, correct modeling of laminar-turbulent boundary layer transition is essential to capture the details of the flow. To investigate possible improvements in model fidelity, CFD models were created for the flow over two low pressure turbine blade designs. A new three-equation eddy-viscosity type turbulent transitional flow model, originally developed by Walters and Leylek (2004, “A New Model for Boundary Layer Transition Using a Single Point RANS Approach,” ASME J. Turbomach., 126(1), pp. 193–202), was employed for the current Reynolds averaged Navier–Stokes (RANS) CFD calculations. Previous studies demonstrated the ability of this model to accurately predict separation and boundary layer transition characteristics of low Reynolds number flows. The present research tested the capability of CFD with the Walters and Leylek turbulent transitional flow model to predict the boundary layer behavior and performance of two different turbine cascade configurations. Flows over low pressure turbine (LPT) blade airfoils with different blade loading characteristics were simulated over a Reynolds number range of 15,000–100,000 and predictions were compared with experimental cascade results. Part I of this paper discusses the prediction methodology that was developed and its validation using a lightly loaded LPT blade airfoil design. The turbulent transitional flow model sensitivity to turbulent flow parameters was investigated and showed a strong dependence on freestream turbulence intensity with a second-order effect of turbulent length scale. Focusing on the calculation of the total pressure loss coefficients to judge performance, the CFD simulation incorporating Walters and Leylek’s turbulent transitional flow model produced adequate prediction of the Reynolds number performance for the lightly loaded LPT blade cascade geometry. Significant improvements in performance were shown over predictions of conventional RANS turbulence models. Historically, these models cannot adequately predict boundary layer transition.
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July 2011
Research Papers
Predicting Separation and Transitional Flow in Turbine Blades at Low Reynolds Numbers—Part I: Development of Prediction Methodology
Darius D. Sanders,
Darius D. Sanders
Department of Mechanical Engineering,
Virginia Tech
, Blacksburg, VA 24061
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Walter F. O’Brien,
Walter F. O’Brien
J. Bernard Jones Professor
Department of Mechanical Engineering,
Virginia Tech
, Blacksburg, VA 24061
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Rolf Sondergaard,
Rolf Sondergaard
Air Force Research Lab, Propulsion Directorate,
Wright Patterson AFB
, OH 45433
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Marc D. Polanka,
Marc D. Polanka
Air Force Research Lab, Propulsion Directorate,
Wright Patterson AFB
, OH 45433
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Douglas C. Rabe
Douglas C. Rabe
Air Force Research Lab, Propulsion Directorate,
Wright Patterson AFB
, OH 45433
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Darius D. Sanders
Department of Mechanical Engineering,
Virginia Tech
, Blacksburg, VA 24061
Walter F. O’Brien
J. Bernard Jones Professor
Department of Mechanical Engineering,
Virginia Tech
, Blacksburg, VA 24061
Rolf Sondergaard
Air Force Research Lab, Propulsion Directorate,
Wright Patterson AFB
, OH 45433
Marc D. Polanka
Air Force Research Lab, Propulsion Directorate,
Wright Patterson AFB
, OH 45433
Douglas C. Rabe
Air Force Research Lab, Propulsion Directorate,
Wright Patterson AFB
, OH 45433J. Turbomach. Jul 2011, 133(3): 031011 (10 pages)
Published Online: November 15, 2010
Article history
Received:
August 13, 2009
Revised:
October 19, 2009
Online:
November 15, 2010
Published:
November 15, 2010
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Citation
Sanders, D. D., O’Brien, W. F., Sondergaard, R., Polanka, M. D., and Rabe, D. C. (November 15, 2010). "Predicting Separation and Transitional Flow in Turbine Blades at Low Reynolds Numbers—Part I: Development of Prediction Methodology." ASME. J. Turbomach. July 2011; 133(3): 031011. https://doi.org/10.1115/1.4001230
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