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Improved Turbulence Prediction in Turbomachinery Flows and the Effect on Three-Dimensional Boundary Layer Transition

1
Institute of Jet Propulsion and Turbomachinery, University of Braunschweig, 38108 Braunschweig, Germany
2
Institute of Turbomachinery and Fluid Dynamics, Leibniz University of Hannover, 30167 Hannover, Germany
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Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in Proceedings of the 17th International Symposium on Transport Phenomena and Dynamics of Rotating Machinery (ISROMAC 2017).
Int. J. Turbomach. Propuls. Power 2018, 3(3), 18; https://doi.org/10.3390/ijtpp3030018
Received: 22 January 2018 / Revised: 13 June 2018 / Accepted: 13 June 2018 / Published: 2 July 2018
For the numerical prediction of turbomachinery flows, a two-equation turbulence model in combination with a proper transition model to account for laminar boundary layers and their transition to turbulence is state of the art. This paper presents the ability of such a method (k-ω + γ-ReΘ) for turbulence prediction and the effect on three-dimensional boundary layer behavior. For this purpose, both applied models (turbulence and transition) are improved to better account for turbulence length scale effects and three-dimensional transition prediction (Bode et al., 2014 and 2016), since these are the main deficiencies in predicting such kinds of flows. The improved numerical method is validated and tested on existing turbine cascades with detailed experimental data for the viscous regions and additionally on a low-speed axial compressor rig where wake-induced transition takes place. View Full-Text
Keywords: computational fluid dynamics; turbulence and transition modeling; boundary layer transition computational fluid dynamics; turbulence and transition modeling; boundary layer transition
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Bode, C.; Friedrichs, J.; Frieling, D.; Herbst, F. Improved Turbulence Prediction in Turbomachinery Flows and the Effect on Three-Dimensional Boundary Layer Transition. Int. J. Turbomach. Propuls. Power 2018, 3, 18.

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