Abstract
The present contribution focuses on the behavior of two RANS Reynolds stress turbulence models in the prediction of flow reversal occurring in turbulent wakes subjected to strong adverse pressure gradients. RANS results are compared to a high-fidelity RANS-IDDES solution for an experimental set-up from Driver and Mateer. The tested models are the JHh-\(\varepsilon ^h\) v2 and the SSG/LRR-\(\omega \). Additionally, the comparison includes a modified version of the SSG/LRR-\(\omega \) model where the sensitivity to pressure gradients is enhanced by the \(S_{\varepsilon 4}\) term, which is already present in the JHh-\(\varepsilon ^h\) v2 model. None of these RANS approaches was able to capture the flow recirculation as shown by the IDDES. The analysis aims at characterizing the wake flow and identifying possible sources of the RANS shortcomings, such as departure from dynamic equilibrium and strong Reynolds stress anisotropy.
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References
Driver, D.M., Mateer, G.G.: Evolution of a planar wake in adverse pressure gradient. NASA/TM-2016-219068 (2016)
Tummers, M.J., Hanjalić, K., Passchier, D.M., Henkes, R.A.W.M.: Computations of a turbulent wake in a strong adverse pressure gradient. Int. J. Heat Fluid Flow 28, 418–428 (2007)
Shur, M.L., Spalart, P.R., Strelets, M.Kh., Travin, A.K.: A hybrid RANS-LES approach with delayed-DES and wall-modelled LES capabilities. Int. J. Heat Fluid Flow 29, 1638–1649 (2008)
Shur, M.L., Strelets, M.Kh., Travin, A.K., Radespiel, R., Scholz, P., Breitenstein, W., Knopp, T.: Experimental/numerical study of turbulent wake in adverse pressure gradient. In: Numerical Notes in Fluid Mechanics and Multidisciplinary Optimization, from the 7th Symposium on Hybrid RANS-LES Methods, Berlin, 17–19 September 2018
Shur, M.L., Strelets, M.Kh., Travin, A.K.: High-order implicit multi-block Navier-Stokes code: ten-years experience of application to RANS/DES/LES/DNS of turbulent flows (2004). https://cfd.spbstu.ru//agarbaruk/doc/NTS_code.pdf
Kroll, N., Rossow, C.-C., Schwamborn, D.: The MEGAFLOW project - numerical flow simulation for aircraft. In: Di Bucchianico, A., Mattheij, R., Peletier, M. (eds.) Progress in Industrial Mathematics at ECMI 2004. Springer, Heidelberg (2005)
Jakirlić, S., Hanjalić, K.: A new approach to modelling near-wall turbulence energy and stress dissipation. J. Fluid Mech. 459, 139–166 (2002)
Eisfeld, B., Rumsey, C., Togiti, V.: Verification and validation of a second-moment-closure model. AIAA J. 54(5), 1524–1541 (2016)
Probst, A., Radespiel, R.: Implementation and extension of a near-wall Reynolds-stress model for application to aerodynamic flows on unstructured meshes. In: AIAA-2008-770, 46th AIAA Aerospace Sciences Meeting and Exhibit, 7–10 January 2008
Cecora, R., Radespiel, R., Eisfeld, B., Probst, A.: Differential Reynolds-stress modeling for aeronautics. AIAA J. 53(3), 739–755 (2015)
Alber, I.E.: Turbulent wake of a thin, flat plate. AIAA J. 18(9), 1044–1051 (1980)
Maciel, Y., Wei, T., Gungor, A.G., Simens, M.: Outer scales and parameters of adverse-pressure-gradient turbulent boundary layers. J. Fluid Mech. 844, 5–35 (2018)
Pope, S.B.: Turbulent Flows. Cornell University, Cambridge University Press, Cambridge (2000)
Acknowledgements
The funding of the project by DFG and RBRF (Grants No. RA 595/26-1, 17-58-12002 and KN 888/3-1) is thankfully acknowledged.
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Burnazzi, M. et al. (2020). Prediction Capabilities of Two Reynolds Stress Turbulence Models for a Turbulent Wake Subjected to Adverse Pressure Gradient. In: Dillmann, A., Heller, G., Krämer, E., Wagner, C., Tropea, C., Jakirlić, S. (eds) New Results in Numerical and Experimental Fluid Mechanics XII. DGLR 2018. Notes on Numerical Fluid Mechanics and Multidisciplinary Design, vol 142. Springer, Cham. https://doi.org/10.1007/978-3-030-25253-3_54
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