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Scale-resolving simulations of spatially evolving turbulence: Physically consistent inflow specification of unresolved velocity and length-scale profiles

Pedram Tazraei1,* and Sharath S. Girimaji1,2,3,†

  • 1Department of Mechanical Engineering, Texas A&M University, College Station, Texas 77843, USA
  • 2Department of Aerospace Engineering, Texas A&M University, College Station, Texas 77843, USA
  • 3Department of Ocean Engineering, Texas A&M University, College Station, Texas 77843, USA

  • *ptazraei@tamu.edu
  • †girimaji@tamu.edu
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Phys. Rev. Fluids 5, 124604 – Published 14 December, 2020

DOI: https://doi.org/10.1103/PhysRevFluids.5.124604

Abstract

Scale-resolving simulations (SRS) of spatially evolving turbulent flows require specification of physically meaningful inflow fields for optimal outcome. SRS methods that employ two-equation subgrid closures must ensure that the inflow unresolved-field velocity-scale (kinetic energy) and length-scale (dissipation or frequency) distributions are compatible with the inflow resolved fields. This work aims to develop accurate inflow turbulent boundary layer description by (i) adapting the recycling-rescaling technique for the resolved field and (ii) deriving unresolved flow-field statistics that are consistent with the resolved-flow profile using the equilibrium boundary layer analysis. The proposed scheme is employed to simulate a spatially evolving zero pressure gradient flat plate boundary layer over a computational domain of 650<Reθ<1434. The SRS results are evaluated in the following categories: wall coefficients, mean-flow profiles, second- and higher-order moments, and multipoint correlations. The agreement with established direct numerical simulation data is shown to be good. Equally importantly, it is demonstrated that the prescribed degree of flow resolution is maintained quite precisely. Overall, the results indicate that the proposed approach can improve the computational efficiency of two-equation SRS closure methods in a wide range of spatially developing turbulent flows.

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References (37)

  1. P. R. Spalart, Direct simulation of a turbulent boundary layer up to Reθ=1410, J. Fluid Mech. 187, 61 (1988).
  2. X. Wu and P. Moin, Direct numerical simulation of turbulence in a nominally zero-pressure-gradient flat-plate boundary layer, J. Fluid Mech. 630, 5 (2009).
  3. P. Schlatter and R. Örlü, Turbulent boundary layers at moderate reynolds numbers: Inflow length and tripping effects, J. Fluid Mech. 710, 5 (2012).
  4. T. S. Lund, X. Wu, and K. D. Squires, Generation of turbulent inflow data for spatially-developing boundary layer simulations, J. Comput. Phys. 140, 233 (1998).
  5. L. Di Mare, M. Klein, W. Jones, and J. Janicka, Synthetic turbulence inflow conditions for large-eddy simulation, Phys. Fluids 18, 025107 (2006).
  6. Z. Xie and I. P. Castro, Efficient generation of inflow conditions for large eddy simulation of street-scale flows, Flow, Turbul. Combust. 81, 449 (2008).
  7. J.-C. Golaz, J. D. Doyle, and S. Wang, One-way nested large-eddy simulation over the Askervein Hill, J. Adv. Model. Earth Syst. 1, 3 (2009).
  8. H. Nakayama, T. Takemi, and H. Nagai, Large-eddy simulation of urban boundary-layer flows by generating turbulent inflows from mesoscale meteorological simulations, Atmos. Sci. Lett. 13, 180 (2012).
  9. A. Ferrante and S. Elghobashi, A robust method for generating inflow conditions for direct simulations of spatially-developing turbulent boundary layers, J. Comput. Phys. 198, 372 (2004).
  10. X. Wu, Inflow turbulence generation methods, Annu. Rev. Fluid Mech. 49, 23 (2017).
  11. M. Inoue and D. Pullin, Large-eddy simulation of the zero-pressure-gradient turbulent boundary layer up to Reθ=O(1012), J. Fluid Mech. 686, 507 (2011).
  12. M. P. Simens, J. Jiménez, S. Hoyas, and Y. Mizuno, A high-resolution code for turbulent boundary layers, J. Comput. Phys. 228, 4218 (2009).
  13. F. S. Pereira, L. Eça, G. Vaz, and S. S. Girimaji, Challenges in scale-resolving simulations of turbulent wake flows with coherent structures, J. Comput. Phys. 363, 98 (2018).
  14. S. S. Girimaji, Partially-averaged Navier-Stokes Model for turbulence: A Reynolds-averaged Navier-Stokes to direct numerical simulation bridging method, J. Appl. Mech. 73, 413 (2006).
  15. S. S. Girimaji, E. Jeong, and R. Srinivasan, Partially-averaged Navier-Stokes method for turbulence: Fixed point analysis and comparison with unsteady partially-averaged Navier-Stokes, J. Appl. Mech. 73, 422 (2006).
  16. R. S. Barlow and J. P. Johnston, Structure of a turbulent boundary layer on a concave surface, J. Fluid Mech. 191, 137 (1988).
  17. H. Le, P. Moin, and J. Kim, Direct numerical simulation of turbulent flow over a backward-facing step, J. Fluid Mech. 330, 349 (1997).
  18. P. Schlatter, Q. Li, G. Brethouwer, A. V. Johansson, and D. S. Henningson, Simulations of spatially evolving turbulent boundary layers up to Reθ=4300, Int. J. Heat Fluid Flow 31, 251 (2010).
  19. S. S. Girimaji and S. Wallin, Closure modeling in bridging regions of variable-resolution (VR) turbulence computations, J. Turbul. 14, 72 (2013).
  20. P. Razi, P. Tazraei, and S. Girimaji, Partially-averaged Navier–Stokes (PANS) simulations of flow separation over smooth curved surfaces, Int. J. Heat Fluid Flow 66, 157 (2017).
  21. S. S. Girimaji and K. S. Abdol-Hamid, Partially-averaged Navier–Stokes model for turbulence: Implementation and validation, in 43rd AIAA Aerospace Sciences Meeting and Exhibit (AIAA, Reston, VA, 2005), p. 502.
  22. D. A. Reyes, J. M. Cooper, and S. S. Girimaji, Characterizing velocity fluctuations in partially resolved turbulence simulations, Phys. Fluids 26, 085106 (2014).
  23. S. Lakshmipathy and S. Girimaji, Partially-averaged Navier-Stokes method for turbulent flows: k−ω model implementation, in 44th AIAA Aerospace Sciences Meeting and Exhibit (AIAA. Reston, VA, 2006), p. 119.
  24. P. Tazraei and S. S. Girimaji, Scale-resolving simulations of turbulence: Equilibrium boundary layer analysis leading to near-wall closure modeling, Phys. Rev. Fluids 4, 104607 (2019).
  25. B. Basara, S. Krajnovic, S. Girimaji, and Z. Pavlovic, Near-wall formulation of the partially averaged Navier-Stokes turbulence model, AIAA J. 49, 2627 (2011).
  26. T. S. Lund and P. Moin, Large-eddy simulation of a concave wall boundary layer, Int. J. Heat Fluid Flow 17, 290 (1996).
  27. D. Spalding, A single formula for the ‘law of the wall', J. Appl. Mech. 28, 455 (1961).
  28. E. De Villiers, The potential of large eddy simulation for the modeling of wall bounded flows. Ph.D. thesis, Imperial College of Science, Technology and Medicine, London (UK), 2006.
  29. F. R. Menter, Two-equation eddy-viscosity turbulence models for engineering applications, AIAA J. 32, 1598 (1994).
  30. I. Orlanski, A simple boundary condition for unbounded hyperbolic flows, J. Comput. Phys. 21, 251 (1976).
  31. L. L. Pauley, P. Moin, and W. C. Reynolds, A numerical study of unsteady laminar boundary layer separation, Report No. TF-34. Thermosciences Division, Stanford University, Stanford CA 94305, USA, 1988.
  32. Y. Li, J. I. Choi, Y. Choic, and J. Kim, A simple and efficient outflow boundary condition for the incompressible Navier–Stokes equations, Eng. Appl. Comput. Fluid Mech. 11, 69 (2017).
  33. P. R. Spalart and C. L. Rumsey, Effective inflow conditions for turbulence models in aerodynamic calculations, AIAA J. 45, 2544 (2007).
  34. R. J. Adrian, Hairpin vortex organization in wall turbulence, Phys. Fluids 19, 041301 (2007).
  35. S. B. Pope, Turbulent Flows (Cambridge University Press, 2000).
  36. X. Wu, P. Moin, J. M. Wallace, J. Skarda, A. Lozano-Durán, and J.-P. Hickey, Transitional–turbulent spots and turbulent–turbulent spots in boundary layers, Proc. Natl. Acad. Sci. USA 114, E5292 (2017).
  37. C. Wenzel, B. Selent, M. Kloker, and U. Rist, DNS of compressible turbulent boundary layers and assessment of data/scaling-law quality, J. Fluid Mech. 842, 428 (2018).

Outline

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Phys. Rev. Fluids 5, 124604– Published 14 December, 2020
  • Received 4 July 2020
  • Accepted 13 November 2020
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