Startseite Technik Evaluation and Analysis of Curvature-Corrected Filter-based Turbulent Model
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Evaluation and Analysis of Curvature-Corrected Filter-based Turbulent Model

  • Rui Zhang EMAIL logo
Veröffentlicht/Copyright: 3. März 2016
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Abstract

Prediction of the characteristics of turbulent flow with streamline curvature is of great importance in engineering applications. In this paper, a curvature-corrected filter-based turbulent model is suggested by applying the Spalart-Shur correction term. This new version of the model (FBM-CC) has been tested and verified through two canonical benchmarks with strong streamline curvature: the flow in a two-dimensional U-duct and the free shear flow past NACA0012 airfoil with a round tip. Predictions of the FBM-CC model are compared with available experimental data and the corresponding results of the original FBM model. The numerical results show that the FBM-CC model significantly improves the sensitivity to the effect of streamline curvature and the numerical calculation accuracy, in relatively good agreement with the experimental data, which suggests that this proposed model may be employed to simulate the turbulent curved flow in engineering applications.

Funding statement: Funding: This work is supported by Natural Science Foundation of Jiangsu Province (No. BK20150808) and Fundamental Research Funds for the Central Universities (No. 2014B12314).

Nomenclature

C

chord length, m

Cp

pressure coefficient

cr1, cr2, cr3

empirical constants of the FBM-CC turbulent model

C3, C, C

turbulent model constants

Cμ

eddy-viscosity coefficient

Gk

production of turbulence kinetic energy

H

channel height, m

k

turbulence kinetic energy

Re

Reynolds number

s

streamwise distance, m

S

strain tensor magnitude

Sij

components of the mean strain tensor

u, v, w

Cartesian velocity components, m/s

U

inlet velocity, m/s

x, y, z

Cartesian coordinate directions

Y

coordinate normal to wall

μ

molecular viscosity

μt

turbulent viscosity

νt

turbulent kinematic viscosity

ε

dissipation rate of turbulent kinetic energy, m2/s3

ω

specific dissipation rate of turbulence, s–1

Ω

rotation-rate magnitude

Ωij

components of the vorticity tensor

Ωm

components of the system rotation vector

εimn

tensor of Levi–Civita

Δ

filter size

References

1. Xu JL, Ma HY, Huang YN. Nonlinear turbulence models for predicting strong curvature effects. Appl. Math Mech Eng Ed 2008;29:31–42.10.1007/s10483-008-0105-zSuche in Google Scholar

2. Patel VC, Sotiropoulos F. Longitudinal curvature effects in turbulent boundary layers. Prog Aerospace Sci 1997;33:1–70.10.1016/S0376-0421(96)00001-2Suche in Google Scholar

3. Bradshaw P. Effects of streamline curvature on turbulent flow. AGARDograph 1973;169.Suche in Google Scholar

4. Johnston JP, Halleen RM, Lezius DK. Effects of spanwise rotation on the structure of two-dimensional fully developed turbulent channel flow. J Fluid Mech 1972;56:533–57.10.1017/S0022112072002502Suche in Google Scholar

5. Launder BE, Priddin CH, Sharma BI. The calculation of turbulent boundary layers on spinning and curved surfaces. J Fluid Eng 1977;99:231–9.10.1115/1.3448528Suche in Google Scholar

6. Howard JHG, Patankar SV, Bordynuik RM. Flow prediction in rotating ducts using Coriolis-modified turbulence models. J Fluid Eng 1980;102:456–61.10.1115/1.3240725Suche in Google Scholar

7. Leschziner MA, Rodi W. Calculation of annular and twin parallel jets using various discretization schemes and turbulence-model variations. J Fluid Eng 1981;103:352–60.10.1115/1.3241745Suche in Google Scholar

8. Park SW, Chung MK. Curvature-dependent two-equation model for prediction of turbulent recirculating flows. AIAA J 1989;27:340–4.10.2514/3.10117Suche in Google Scholar

9. Rinaldi E, Raspopov RS, Colonna P, Pecnik R. Modeling curvature effects on turbulence transition for turbomachinery flows. Proceedings of ASME Turbo Expo 2014: Turbine Technical Conference and Exposition, 2014.10.1115/GT2014-26958Suche in Google Scholar

10. Cazalbou JB, Chassaing P, Dufour G, Carbonneau X. Two-equation modeling of turbulent rotating flows. Phys Fluids 2005;17:1441–57.10.1063/1.1920630Suche in Google Scholar

11. Dufour G, Cazalbou JB, Carbonneau X, Chassaing P. Assessing rotation/curvature corrections to eddy-viscosity models in the calculations of centrifugal-compressor flows. J Fluid Eng 2008;130:091401(1–10).10.1115/1.2953231Suche in Google Scholar

12. Hellsten A. Some improvements in menter’s k–ω SST turbulence model. AIAA paper 98–2554.Suche in Google Scholar

13. Mani M, Ladd JA, Bower WW. Rotation and curvature correction assessment for one-and two-equation turbulence models. J Aircraft 2004;41:268–73.10.2514/1.9321Suche in Google Scholar

14. Rumsey CL, Nishino T. Numerical study comparing RANS and LES approaches on a circulation control airfoil. Int J Heat Fluid Flow 2011;32:847–64.10.2514/6.2011-1179Suche in Google Scholar

15. Reif P, Durbin PA, Ooi A. Modeling rotational effects in eddy-viscosity closures. Int J Heat Fluid Flow 1999;20:563–73.10.1016/S0142-727X(99)00056-9Suche in Google Scholar

16. Durbin P. Review: adapting scalar turbulence closure models for rotation and curvature. J Fluid Eng 2011;133:439–46.10.1115/1.4004150Suche in Google Scholar

17. Arolla SK, Durbin PA. Modeling rotation and curvature effects within scalar eddy viscosity model framework. Int J Heat Fluid Flow 2013;39:78–89.10.1016/j.ijheatfluidflow.2012.11.006Suche in Google Scholar

18. Arolla S, Durbin P. A rotation/curvature correction for turbulence models for applied CFD. Prog Comput Fluid Dyn 2014;14:341–51.10.1504/PCFD.2014.065472Suche in Google Scholar

19. York WD, Walters DK, Leylek JH. A simple and robust linear eddy-viscosity formulation for curved and rotating flows. Int J Numer Methods Heat Fluid Flow 2009;19:745–76.10.1108/09615530910972995Suche in Google Scholar

20. Chitta V, Dhakal TP, Walters DK. Sensitization of a transition-sensitive linear eddy-viscosity model to rotation and curvature effects. J Fluid Eng 2015;137:031207(1–14).10.1115/1.4028627Suche in Google Scholar

21. Spalart PR, Shur M. On the sensitization of turbulence models to rotation and curvature. Aerosp Sci Technol 1997;1:297–302.10.1016/S1270-9638(97)90051-1Suche in Google Scholar

22. Shur ML, Strelets MK, Travin AK, Spalart PR. Turbulence modeling in rotating and curved channels: assessing the Spalart-Shur correction. AIAA J 2000;38:784–92.10.2514/2.1058Suche in Google Scholar

23. Smirnov PE, Menter FR. Sensitization of the SST turbulence model to rotation and curvature by applying the Spalart–Shur correction term. J Turbomach 2009;131:1–8.10.1115/GT2008-50480Suche in Google Scholar

24. Ahmad NN, Proctor FH, Perry RB. Numerical simulation of the aircraft wake vortex flow field. 5th AIAA Atmospheric and Space Environments Conference, 2013.10.2514/6.2013-2552Suche in Google Scholar

25. Jošt D, Skerlavaj A, Lipej A. Improvement of efficiency prediction for a Kaplan turbine with advanced turbulence models. Strojniski Vestnik-J Mech Eng 2014;60:124–34.10.5545/sv-jme.2013.1222Suche in Google Scholar

26. Tao R, Xiao RF, Yang W, Wang FJ. A comparative assessment of Spalart-Shur rotation/curvature correction in RANS simulations in a centrifugal pump impeller. Math Prob Eng 2014;342905:1–9.10.1155/2014/342905Suche in Google Scholar

27. Peng B, Yan H, Fang H, Wang M. Modification of k–ω turbulence model for predicting airfoil aerodynamic performance. J Therm Sci 2015;24:221–8.10.1007/s11630-015-0777-zSuche in Google Scholar

28. Johansen ST, Wu JY, Shyy W. Filter-based unsteady RANS computations. Int J Heat Fluid Flow 2004;25:10–21.10.1016/j.ijheatfluidflow.2003.10.005Suche in Google Scholar

29. Zhang R, Chen HX. Numerical simulation and flow diagnosis of axial-flow pump at part-load condition. Int J Turbo Jet Engines 2012;29:1–7.10.1515/tjj-2012-0007Suche in Google Scholar

30. Wang ZY, Huang B, Wang GY, Zhang MD, Wang FF. Experimental and numerical investigation of ventilated cavitating flow with special emphasis on gas leakage behavior and re-entrant jet dynamics. Ocean Eng 2015;108:191–201.10.1016/j.oceaneng.2015.07.063Suche in Google Scholar

31. Argyropoulos CD, Markatos NC. Recent advances on the numerical modelling of turbulent flows. Appl Math Model 2015;39:693–732.10.1016/j.apm.2014.07.001Suche in Google Scholar

32. Launder BE, Spalding DB. The numerical computation of turbulent flows. Comput Methods Appl Mech Eng 1974;3:269–89.10.1016/B978-0-08-030937-8.50016-7Suche in Google Scholar

33. Monson DJ, Seegmiller HL, Mcconnaughey PK. Comparison of experiment with calculations using curvature-corrected zero and two equation turbulence models for a two-dimensional U-duct. AIAA–90–1484.Suche in Google Scholar

34. Dacles-Mariani J, Zilliac GG, Chow JS, Bradshaw P. Numerical/experimental study of a wingtip vortex in the near field. AIAA J 1995;33:1561–8.10.2514/3.12826Suche in Google Scholar

35. Chow JS, Zilliac GG, Bradshaw P. Mean and turbulence measurements in the near field of a wingtip vortex. AIAA J 1997;35:1561–7.10.2514/2.1Suche in Google Scholar

Received: 2016-2-9
Accepted: 2016-2-17
Published Online: 2016-3-3
Published in Print: 2017-8-28

© 2017 Walter de Gruyter GmbH, Berlin/Boston

Heruntergeladen am 19.1.2026 von https://www.degruyterbrill.com/document/doi/10.1515/tjj-2016-0008/pdf
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